Paleocene Climate and Carbon Cycle: Insights Into an
Unstable Greenhouse from a Biomarker and Compound
Specific Carbon Isotope Approach
Kyle William Robert Taylor
A dissertation submitted to the University of Bristol in accordance with the
requirements of the degree of Doctor of Philosophy in the Faculty of Science
School of Chemistry
January 2012
Word Count: 66,250
Author’s Declaration
I declare that the work in this dissertation was carried out in accordance with the
Regulations of the University of Bristol. The work is original, except where indicated by
special reference in the text, and no part of the dissertation has been submitted for any
other academic award. Any views expressed in the dissertation are those of the author.
SIGNED: ......................................... DATE:..........................
i
Abstract
Climatic conditions throughout the Paleocene (55 – 65.5 Ma) are believed to have
remained relatively stable (Shackleton and Hall, 1984a,b; Zachos et al., 1994; Zachos et
al., 2001). The Paleocene is generally considered to be time of global warmth and reduced
latitudinal temperature gradients compared with the present day (e.g. Zachos et al. 1993,
1994), although generally experienced temperatures relatively lower than those of the late
Cretaceous and early-mid Eocene (Zachos et al., 2001; Pagani et al., 2005). It also
experienced elevated levels of atmospheric CO2 compared to the present day. Some
evidence however suggests that the Paleocene may not have been as stable as is generally
accepted; the devastation of marine biota at the Cretaceous/Tertiary boundary (K/Pg) may
have disrupted biogeochemical cycles for up to 1 - 3 My (D’Hondt et al., 1996a; 1998), as
evidenced by the sustained collapse or suppression of the benthic-planktic carbon isotope
gradient (Keller and Lindinger, 1989; Zachos et al., 1989; Zachos et al., 1992; D’Hondt et
al., 1998; Coxall et al., 2006). In the late Paleocene, a decrease in global benthic
temperatures (Zachos et al., 2001; Cramer et al., 2009) is recorded, coinciding with a
positive carbon isotope excursion in marine carbonates. The Paleocene may therefore
represent an epoch with a relatively dynamic carbon cycle and climate, and as such
provides an ideal period to study the relationship between carbon cycling and climate
change in a high-CO2 Earth system.
The central aim of this thesis was to determine whether significant climate and carbon
cycle instability occurred through the Paleocene using organic biomarker approaches,
including the TEX86 palaeothermometer and compound specific carbon isotope analysis of
algal and terrestrial biomarkers. Transient climate change and ecological disruption
occurred at the K/Pg in the southwest Pacific. Climate instability persisted for c. 1 – 1.2
My, and then proceeded to stabilise, with most climate and ecological parameters returning
to pre-K/Pg values; a notable exception is the algal biomarker distributions, which reflect a
restructured algal community, in keeping with the suggestion that algal community
restructuring, and thus the restructuring of tropic levels, was responsible for the long-term
term recovery of the benthic-planktic carbon isotope gradient.
Late Paleocene climate reconstructions indicate cooling coeval with
13
C-enrichment of
terrestrial and marine reservoirs in the Southern Ocean (SO), perhaps associated with
enhanced marine productivity and a drawdown of CO2, indicating that this period, referred
to as the Paleocene Carbon Isotope Maximum (PCIM) reflects a period of cooling
associated with carbon cycle changes. A tentatively dated low-latitude north Atlantic SST
ii
record does not indicate cooling. Assuming a correct age assignment, this could indicate
that SST cooling was a more regionally restricted phenomenon, and that the global benthic
carbonate
18
O-enrichment reflects Southern Ocean (SO) cooling and strengthening of SO
sourced bottom waters. Tentatively, drawdown of CO2 and Southern Ocean cooling could
have brought about early Antarctic glaciations and an associated drop in sea level.
Although such an inference is contentious and evidence presented here is circumstantial,
such an event provides a mechanism for the pronounced oceanographic changes, including
enhanced cooling and sedimentary anoxia, occurring at the neritic mid-Waipara River site
from 58.3 – 58 Ma. Furthermore, these findings suggest that the Paleocene SO climate may
have been more sensitive to carbon cycle dynamics than the classic ocean heat transport
models suggest; this is in agreement with Paleogene climate models which predict a
stronger influence of CO2 on Southern Ocean climate than the thermal isolation brought
about by circum-Antarctic circulation (Huber and Sloan, 2001; DeConto and Pollard,
2003a; 2003b; Huber and Nof, 2004; Huber et al., 2006; DeConto et al., 2008).
iii
Acknowledgements
There are many people without whom the completion of this thesis would not have been
possible, and I am forever indebted to. Although everyone acknowledges their family in
their thesis, I hope mine realise they are truly appreciated; my father Alan, mother Gail and
brother Ricky have been a constant inspiration and source of unwavering encouragement
throughout, and of course always have been, long before I moved to Bristol to undertake
this work. I also wish to thank Sioned in this same paragraph; while I have been in thesis
lock-down, she has kept me fed, watered, and prevented our home from falling into
disrepair. She has also reminded me to tear myself away from the manuscript to sleep once
in a while. She, together with my family, has believed in me at times when I gave up
believing in myself, and that has been enough to keep me going. I now also owe around
four months of cooking and cleaning.
I am also forever indebted to my supervisor, Prof. Richard D. Pancost. If you happen to
read any other thesis of a past student of his, you will see a similar theme; I do not believe
there could be a more understanding, enthusiastic and exciting person to work for. But I
hope it is alright to say I also consider him a friend. He has provided me with a job which
has kept me in financial comfort while I have been writing, and that is one less
unimaginable stress he removed, for which I am also truly grateful. It more than pays back
for the car battery. I also thank my main collaborator, who I really consider as a second
supervisor, Dr. Christopher Hollis of GNS Science NZ; his enthusiasm for the field has
often inspired me, and I am hopeful to continue to be a part of the Paleogene investigations
of NZ in my career. I thank Matt Huber, for his very large part in the discussions between
the four of us which led to my deeper investigations into the TEX86 palaeothermometer. I
have Prof Richard P. Evershed FRS to thank along these lines also; he reminded me not to
be a stamp collector, and to maintain an analytical approach. It has always stuck in my
mind since as some of the best advice to refer to.
I would like to thank the group at the Organic Geochemistry Unit for friendship,
interesting discussions and support. In particular I thank Preeti, our resident ‘woman in
science’; chats in the office with this colleague have kept me sane over the past few years.
Amy for the Oysterband, and the reassurance that everyone feels lost along the way
sometimes. Thanks also go to Dr Ian. D. Bull, not only for support with the analytical
equipment in the NERC Life Sciences Mass Spectrometry Facility, but also for the laughs.
Also James Williams for the technical support and haggis cooking instructions. George for
the crash pad when I locked myself out of my house. Tim, Marcus and Pete, for the always
interesting and sometimes brain-addling exchanges in the office. Lucija for the Slovenian
humour. Thanks to Charlotte O’B for showing me what an alkenone looks like. I should
thank Richard Evershed here too, for diagnosing my ‘alkenone envy’ condition, but
unfortunately there is no discernible cure other than alkenones in the Paleocene. Also a
mention to past members; Karl for the philosophical transactions and the Swedish
approach to life, Luke Handley for the hand-me-down samples and the introduction to
Bristol, and Alf for reminding me that if we were to have a fight, he would probably win.
Nicole Bale, for laying the ground work in the group that us Plymouthians aren’t as bad
our preceding reputation. Finals thanks to Dave Strong, for the Christmas sing-alongs, the
open-mic nights, beer festivals and malt whiskey.
iv
Table of Contents
Author’s Declaration ............................................................................................................i
Abstract .................................................................................................................................ii
Acknowledgements .............................................................................................................iv
Table of Contents ................................................................................................................. v
List of Figures ......................................................................................................................xi
List of Tables...................................................................................................................xviii
Glossary of Terms.............................................................................................................xix
Chapter 1: Introduction ..................................................................................................... 1
1.1. Geological Timescale ..................................................................................................5
1.2. The Paleocene ..............................................................................................................6
1.2.1. The Cretaceous / Paleogene Boundary and Subsequent Recovery ......................9
1.2.1.1. Climatic and Oceanographic Consequences of the K/Pg ........................................................ 9
1.2.1.2. The K/Pg Boundary : Recovery of Climate and Ecology......................................................11
1.2.1.3. The K/Pg and Recovery: Records from the South Pacific and NZ ....................................... 13
1.2.2. The Paleocene Carbon Isotope Maximum (PCIM)....................................................14
1.2.2.1. Causes of the PCIM and Associated Climate Change .......................................................... 15
1.2.2.2. Climate Records from the Southern Ocean ........................................................................... 16
1.2.3. Climate Instability in the Paleocene ...................................................................17
1.3. Thesis Aims and Hypotheses.....................................................................................18
1.4. Biomarkers ................................................................................................................20
1.4.1. Biomarkers as Tracers of Biological Inputs .......................................................20
1.4.1.1. Terrestrial Biomarkers .......................................................................................................... 21
1.4.1.2. Algal Biomarkers .................................................................................................................. 22
1.4.1.3. Prokaryote (Archaea and Bacteria) Biomarkers .................................................................... 25
1.4.1.3.1. Glycerol Dialkyl Glycerol Tetraethers( GDGTs).................................................26
1.4.1.3.2. Low Molecular Weight n-alkyl Compounds........................................................29
1.4.1.3.3. Hopanoids.............................................................................................................30
1.4.1. Biomarker proxies for SST .........................................................................................31
1.4.2.1. TEX86 : Relative Proportions of GDGTs as a Palaeothermometer. ...................................... 31
1.4.3. Biomarker Specific Isotopes in the Reconstruction of Ancient Carbon
Cycling .................................................................................................................................36
1.4.3.1. Controls on δ13C Values Higher Plant Biomass .................................................................... 36
v
1.4.3.2. Controls on d13C Values of Algal Biomass ......................................................................... 38
Chapter 2 : Experimental, Instrumental and Statistical Methods ................................39
2.1. Materials ....................................................................................................................40
2.2. Sample Processing .....................................................................................................40
2.2.1. Lipid Extraction Procedure: Soxhlet Extraction ................................................40
2.2.2. Total Lipid Extract Fractionation ......................................................................41
2.2.2.1. Aminopropyl Column Fractionation ..................................................................................... 41
2.2.2.2. Alumina Column Fractionation............................................................................................. 41
2.2.3. Preparation of Polar Fractions for Liquid Chromatography
– Mass Spectrometry Analysis ......................................................................................42
2.2.4. Derivatisation .....................................................................................................42
2.3. Analytical techniques ................................................................................................43
2.3.1. Elemental analysis ..............................................................................................43
2.3.1. Gas Chromatography..........................................................................................44
2.3.3. Gas Chromatography-Mass Spectrometry .........................................................44
2.3.4. Gas Chromatography-Combustion-Isotope Ratio Mass Spectrometry ..............44
2.3.5. Liquid Chromatography-Mass Spectrometry .....................................................45
2.4. Quantification ............................................................................................................46
2.4.1. GC and GC-MS Internal standards ....................................................................46
2.4.2. Glycerol Dialkyl Glycerol Tetraether Internal Standard ...................................47
2.4.3. Compound Identification ....................................................................................48
2.5 .Errors and Statistical Treatment ................................................................................48
2.5.1. Overview of Types of Data..................................................................................48
2.5.2. Estimation of Precision: Error Handling ...........................................................49
2.5.3 .Statistical Cluster Analysis of Compound Distribution ......................................51
Chapter 3 : Terrestrial and Marine Climate across the K/Pg Boundary at midWaipara River, New Zealand ...........................................................................................52
3.1. Introduction ...............................................................................................................53
3.2. Site Description and Stratigraphy..............................................................................57
3.2.1. Palynology ..........................................................................................................60
3.2.2. Age Model ...........................................................................................................61
3.3. Methods .....................................................................................................................63
vi
3.3.1. Biomarker Analyses. ...........................................................................................63
3.3.2. GDGT Quantification .........................................................................................63
3.3.3. Statistical Analysis of GDGT Distributions ........................................................64
3.4. Results .......................................................................................................................64
3.4.1. Elemental Analysis ..............................................................................................64
3.4.2. Glycerol Dialkyl Glycerol Tetraether Distributions and Concentrations ..........65
3.4.2.1. GDGT Concentrations .......................................................................................................... 65
3.4.2.2. GDGT Distributions .............................................................................................................. 69
3.4.2.2.1. Relative Proportions of Individual GDGTs used in SST reconstruction ....................... 69
3.4.2.2.2. Crenarchaeol and GDGT-0 ........................................................................................... 74
3.4.2.2.3. Degree of GDGT Cyclisation ........................................................................................ 75
3.4.2.3. GDGT Proxies ...................................................................................................................... 77
3.4.2.3.1. TEX86 and SST reconstruction ...................................................................................... 77
3.4.2.3.2. BIT Index ....................................................................................................................... 79
3.5. Discussion .................................................................................................................81
3.5.1. GDGT Concentrations ........................................................................................83
3.5.2. GDGT-derived Sea Surface Temperature Reconstructions ................................83
3.5.2.1. What is causing the unusual differences in reconstructed SSTs? .......................................... 85
3.5.2.1.1. Contribution of GDGTs from Sedimentary Inputs ........................................................ 85
3.5.2.1.2. Interrogation of modern GDGT distributions ................................................................ 88
3.5.2.1.3. Revised approach in the application of TEX86 based on GDGT-2/GDGT-3 ratios. ...... 93
3.5.3. Climate Succession at mid-Waipara River K/Pg Boundary Section ..................94
3.5.3.1. Maastrichtian and earliest Danian climate ............................................................................ 94
3.5.3.2.Danian climate and post-K/Pg recovery................................................................................. 99
3.6. Conculsions .............................................................................................................104
Chapter 4 : Ecological and Carbon Cycle Perturbation across the K/Pg Boundary at
mid-Waipara River, New Zealand..................................................................................106
4.1. Introduction .............................................................................................................107
4.2. Site Description .......................................................................................................109
4.3. Materials and Methods ............................................................................................110
4.3.1. Biomarker Analyses. .........................................................................................110
4.4. Results .....................................................................................................................110
4.4.1. Bulk Analysis.....................................................................................................110
4.4.2. Biomarker Sources, Concentrations and Distributions ....................................112
4.4.2.1. n-Alkanes and n-Alkanoic Acids ........................................................................................ 117
vii
4.4.2.1.1. Distribution of High Molecular Weight n-Alkanoic Acids and n-Alkanes ................. 118
4.4.2.1.2. Distribution of Low Molecular Weight n-alkanoic Acids ........................................... 125
4.4.2.2.Algal Biomarkers: Sterols, Pristane and Phytane.................................................................128
4.4.2.3. Taraxer-14-ene .................................................................................................................... 130
4.4.2.4. Soil Derived Branched GDGTs and BIT Index .................................................................. 130
4.4.3. Compound specific isotope analysis .................................................................131
4.4.3.2. High Molecular Weight n-alkanoic acids............................................................................ 132
4.4.3.1. Low Molecular weight n-alkanoic acids ............................................................................. 134
4.5. Discussion ...............................................................................................................136
4.5.1. Sources of Organic Matter ...............................................................................136
4.5.2. Changes in Sources of Organic Matter Through the Mid-Waipara ......................
River Section ...............................................................................................................137
4.5.2.1. Changes in the Terrestrial Plant Community ...................................................................... 139
4.5.2.2. Changes in Marine Algal Abundances and Assemblages ................................................... 141
4.5.2.3. Overview of Ecological Changes at Mid-Waipara River .................................................... 143
4.5.3. Carbon isotopic records ...................................................................................146
4.5.3.1. Terrestrial Response to Carbon Cycle Perturbations Across the K/Pg and Subsequent
Recovery .......................................................................................................................................... 146
4.5.3.2. Perturbations in the Marine Carbon Cycle across the K/Pg ................................................ 150
4.5.3.3. Overview of Carbon Isotope Records at Mid-Waipara ....................................................... 152
4.6. Conclusions .............................................................................................................154
Chapter 5 : The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the
Southern Ocean ................................................................................................................158
5.1. Introduction .............................................................................................................159
5.2. Site Descriptions......................................................................................................161
5.2.1. Mid-Waipara River Column 2 ..........................................................................161
5.2.2. Ocean Drilling Program Leg 181, Site 1121. ...................................................164
5.3. Methods ...................................................................................................................165
5.3.1. Biomarker Analyses. .........................................................................................165
5.3.2. Statistical Cluster Analysis of n-Alkanoic Acid δ13C ........................................166
5.4. Results .....................................................................................................................166
5.4.1. Bulk Organic Geochemical Analysis ................................................................166
5.4.2. Biomarker Concentrations and Distributions at mid-Waipara River ..............171
5.4.2.1. n-Alkanes and n-Alkanoic Acids ........................................................................................ 173
5.4.2.2. Sterols ................................................................................................................................. 176
viii
5.4.2.3. Archaeal Lipids ................................................................................................................... 179
5.4.3. Compound Specific Isotope Analysis ................................................................183
5.4.3.1. High-Molecular Weight n-Alkanoic Acids ......................................................................... 183
5.4.3.2. Mid-Molecular Weight n-Alkanoic Acids .......................................................................... 184
5.4.3.3. Low-Molecular Weight n-Alkanoic Acids .......................................................................... 186
5.4.3.4. Cluster Analysis of n-Alkanoic Acid Carbon Isotopic CompositionsError! Bookmark not
defined.188
5.4.3.5. Hopanoic Acids ................................................................................................................... 189
5.4.4. Glycerol Dialkyl Glycerol Tetraether Distributions .......................................................... 190
5.4.4.1. mid-Waipara River GDGT Distributions ............................................................................ 193
5.4.4.2. ODP Site 1121 GDGT Distributions ................................................................................... 196
5.4.4.3. ODP Site 1172 (Evaluation of Published Data) .................................................................. 199
5.5. Discussion ...............................................................................................................202
5.5.1. Environmental Change at mid-Waipara River Column 2 ................................202
5.5.1.1. Changes in Sources of Organic Matter ............................................................................... 204
5.5.1.2. Mid-Molecular Weight n-Alkanoic Acids: Evidence for a third source of OM? ................ 205
5.5.1.3. Changes in Sedimentary Redox Conditions.........................................................................208
5.5.2. Paleocene SST in the Southwest Pacific ...........................................................209
5.5.2.1. Assessment of the TEX86 Palaeothermometer at the Study Sites ........................................ 212
5.5.3. Carbon Cycle Dynamics Inferred From Carbon Isotopic Records ..................215
5.5.3.1. A Decline in pCO2 during the Late Paleocene .................................................................... 218
5.5.3.2. Strong 13C-Enrichment at Mid-Waipara River .................................................................. 221
5.6. Conclusions .............................................................................................................226
Chapter 6 : Overview and Integration of Preliminary and Global Data ....................229
6.1. Introduction..............................................................................................................230
6.2. The Paleocene Carbon Isotope Maximum ..............................................................230
6.2.1. Bass River Site Description, Materials and Methods (Supplementary
Preliminary Study) ......................................................................................................231
6.2.2. Bass River GDGT and TEX86 Results and Discussion .....................................234
6.2.3. Summary of Paleocene Climate and Carbon Cycle at the PCIM .....................237
6.6.4 Recommendation for Future Work: Further Characterisation of Climate and
Oceanographic Change Through the PCIM ...............................................................242
6.3. Summary of K/Pg Climate and Carbon Perturbation at mid-Waipara River ..........243
6.3.1 Recommendations for Future Work ...................................................................247
6.3.1.1. Hydrology Across the K/Pg Boundary Into the Early Danian ............................................ 247
6.3.1.2 Other K/Pg Boundary Sites in New Zealand ....................................................................... 247
ix
6.4. Overview of Compiled GDGT and TEX86 Data : Implications for the Continued
Application of the TEX86 Palaeothermometer ................................................................248
6.6.1.
Recommendation
for
Future
Work:
Development
of
the
TEX86
Palaeothermometer .....................................................................................................250
6.5. Paleocene : Climate Instability ................................................................................251
6.6.5. Recommendation for Future Work: Further Interrogation of Marine Carbon
Cycling Through the Paleocene..................................................................................252
6.6. A Synthesis of Southwest Pacific Early Paleogene Climate ...................................253
References.........................................................................................................................259
Appendix...........................................................................................................................308
Appendix I: GDGT Structures...............................................................................309
Appendix II: Bass River Geochemical and Statistical Data.................................310
Appendix III: Mid-Waipara River K/Pg Boundary Section: Geochemical and
Statistical Information............................................................................................316
Appendix IV: Mid-Waipara River Column 2 (Paleocene): Geochemical and
Statistical Information............................................................................................351
Appendix V: ODP Site 1121 (Paleocene): Geochemical and Statistical
Information.............................................................................................................370
Appendix VI: Geological, Lithological and Extended Sample Information........374
x
List of Figures
Number
Title
Page
Figure 1.1
GTS2004 Timescale
5
Figure 1.2
Estimates of atmospheric carbon dioxide concentrations from the past 7
60 myr
Figure 1.3
Simplified schematic of the benthic and planktic carbon isotope record 10
of the North Pacific K/Pg
Figure 1.4
Palaeomap reconstruction for the location of NZ at the time of the
13
K/Pg, 65.5 Ma.
Figure 1.5
Global compilation of oxygen and carbon benthic foraminiferal 14
isotopes (Cramer et al., 2009).
Figure 1.6
Examples of high-molecular weight n-alkyl compounds.
21
Figure 1.7
Phytol, and its degradation products pristane and phytane
22
Figure 1.8
Cholesterol, cholestanol and cholesterane structures.
23
Figure 1.9
Example sterol structures.
25
Figure 1.10
Glycerol dialkyl glycerol tetraether structures, as used for
SST 27
reconstructions.
Figure 1.11
Structure of 2,3-di-O-phytanyl-sn-glycerol (archaeol)
28
Figure 1.12
Example branched GDGT structures (as used in the BIT index).
28
Figure 1.13
Example biohopanoid (bacteriohopanetetrol) with example
30
diagenetic hopanoid compounds.
Figure 1.14
and
plotted as SST against the raw indices
34
xi
Figure 2.1
Derivatization reaction schemes for silylation of hydroxyl function 42
groups with BSFTA and pyridine, and methylation of carboxylic acids
using BF3/MeOH
Figure 2.2
Internal standards used for quantification of biomarkers analysed by 46
GC
and GC-MS; 5α-androstane, hexadecan-2-ol and n-nonadecane
Figure 2.3
Structure of C46 GDGT internal standard.
47
Figure 3.1
Geographical and palaeogeographical locations of the mid-Waipara 57
River Section, New Zealand.
Figure 3.2
Location of the K/Pg boundary at the mid-Waipara River section
58
Figure 3.3
Lithology, sample locations, biozonation and age model of the mid- 59
Waipara river K/Pg boundary sequence.
Figure 3.4
TOC content throughout the mid-Waipara River section
64
Figure 3.5
LC-MS chromatogram of isoprenoidal GDGTs for sample f561
65
Figure 3.6
Concentrations of GDGTs throughout the mid-Waipara River section, 67
normalised to dry weight of sediment
Figure 3.7
Concentrations of GDGTs throughout the mid-Waipara River section, 68
normalised to TOC
Figure 3.8
Relative proportions of GDGTs expressed as fractional percentage.
70
Figure 3.9
Agglomerative hierarchal cluster analysis of isoprenoidal GDGT
72
distributions
Figure 3.10
Average GDGT distributions for GDGT ‘Zones’, expressed as a bar 73
chart of fractional abundances, with representative LC-MS GDGT
chromatograms for each Zone
Figure 3.11
Relative proportions of GDGT-0 and crenarchaeol, expressed as 74
fractional percentage.
xii
Figure 3.12
Weighted average number of cyclopentyl rings in isoprenoidal GDGT
76
biphytanyl moieties through the mid-Waipara River section
Figure 3.13
TEX86 reconstructions at the Mid-Waipara River K/Pg section
78
Figure 3.14
BIT index, and concentrations of crenarchaeol and bGDGT-I
80
normalised to TOC
Figure 3.15
Compiled GDGT ratios, and offset between
87
and
derived SST reconstructions.
Figure 3.16
Ratio of GDGT-2/GDGT-3 measured in suspended particulate matter 89
(SPM) through the water column at a range of localities. Adapted from
Turich et al., (2007).
Figure 3.17
Concept schematic diagram of GDGT export and the effect of the 90
changes in GDGT distributions (ratio of GDGT-2/GDGT-3) on the
offset between
Figure 3.18
Crossplots
and
of
and
reconstructed SST.
GDGT-2/GDGT-3 ratio against offset
between 91
reconstructed SSTs for mid-Waipara and modern
coretop calibration dataset
Figure 3.19
Compiled climate indicators and palynological features of the mid- 96
Waipara River section
Figure 3.20
Time scaled comparison of bulk carbonate δ18O from ODP Site 1262 103
and mid-Waipara River TEX86 SST reconstructions
Figure 4.1
TOC content throughout the mid-Waipara River section
111
Figure 4.2
Carbon isotopic composition of bulk organic carbon (δ13C)
112
Figure 4.3
GC-MS chromatogram of Apolar fraction of sample f539 (7.84 m).
113
Figure 4.4
GC-MS chromatogram of methylated acid fraction of sample f172 (-27 115
cm).
xiii
Figure 4.5
Concentrations of Total, HMW and LMW n-alkanes and n-alkanoic 116
acids normalised to dry weight of sediment
Figure 4.6
Ratios of HMW/LMW n-alkanes and n-alkanoic acids, and 118
terrigenous/aquatic ratios (TARs)
Figure 4.7
HMW n-alkane and n-alkanoic acid distributions
120
Figure 4.8
Relative distributions of n-alkanes and n-alkanoic acids of selected 121
samples through each Zone
Figure 4.9
Indicators of terrestrial plant communities through the mid-Waipara 123
River section
Figure 4.10
molecular weight n-alkane and n-alkanoic acid distributions through the 127
mid-Waipara River section
Figure 4.11
Concentrations of algal biomarkers throughout the mid-Waipara River 129
section
Figure 4.12
BIT index, and concentrations of crenarchaeol and branched
131
GDGT I normalised to TOC through the mid-Waipara River Section
Figure 4.13
Compound specific carbon isotope analysis of HMW n-alkanoic acids
133
Figure 4.14
Compound specific carbon isotope analysis of LMW n-alkanoic acids
135
Figure 4.15
Long-term composite of δ13C measurements from late Maastrichtian to 145
early Danian
Figure 4.16
High resolution composite of carbon isotope (δ13C) analyses across the 148
K/Pg.
Figure 5.1
Palaeolocations for mid-Waipara River (MW), ODP Site 1121 and 161
ODP Site 1172.
Figure 5.2
Location of mid-Waipara River Column 2
162
xiv
Figure 5.3
Age model for mid-Waipara Column 2
163
Figure 5.4
Age model for ODP Site 1121
164
Figure 5.5
Bulk organic geochemical analysis of samples from mid-Waipara River 166
Column 2: TOC content and carbon isotopic composition of organic
carbon.
Figure 5.6
Bulk organic geochemical analyses from ODP Site 1121: δ13CTOC 168
δ13Ccarb , Δ13C(carb-TOC)
Figure 5.7
Total ion current chromatogram of polar fraction of MW58 (64.81 m),
172
with identification of sterols indicated.
Figure 5.8
Total Ion Chromatogram of MW35 methylated acid fraction. Numbers 173
above coloured circles represent carbon-number.
Figure 5.9
Relative proportions of n-alkane and n-alkanoic acids at mid-Waipara 174
River Column 2:
Figure 5.10
Trends in n-alkane and n-alkanoic acid distributions
175
Figure 5.11
Algal biomarkers at mid-Waipara River Column 2
177
Figure 5.12
GC-MS Total ion current (TIC) chromatogram of MW40 (128.38 m) 180
polar fraction, indicating archaeol peak with associated mass spectrum.
Figure 5.13
Concentrations of archaeol and biphytanoic diacid
181
Figure 5.14
Total ion current (TIC) chromatogram of MW40 methylated acid 182
fraction, with n-alkanoic acids, hopanoic acids acyclic C40 biphytanoic
diacid identified. Corresponding mass spectrum and characteristic
fragment ions of acyclic C40 biphytanoic diacid is given together with a
reference spectrum for comparison.
Figure 5.15
Compound specific carbon isotope analysis of HMW n-alkanoic acids
184
Figure 5.16
Compound specific carbon isotope analysis of MMW n-alkanoic acids
185
xv
Figure 5.17
Compound specific carbon isotope analysis of LMW n-alkanoic acids
186
Figure 5.18
Agglomerative hierarchal cluster analysis of δ13C of n-alkanoic acids,
188
Figure 5.19
Compound specific carbon isotope analysis of hopanoic acids
190
Figure 5.20
Example GDGT distributions at mid-Waipara River Column 2, plotted 191
with % TOC and δ13CTOC, including: MW43 (129.53 m) in the highTOC / low δ13CTOC interval, and MW56 (79.66 m) in the lower Waipara
Greensand formation.
Figure 5.21
Relative proportions of GDGTs expressed as fractional
192
Percentage at mid-Waipara Column 2
Figure 5.22
TEX86 reconstructions at Mid-Waipara River Column 2
194
Figure 5.23
BIT index through mid-Waipara Column 2.
195
Figure 5.24
Example LC-MS chromatograms of GDGTs at ODP Site 1121, 196
including: CP12 (56.97 m), CP21 (69.57 m), CP26 (76.04 m) and CP36
(94.05 m).
Figure 5.25
Relative proportions of GDGTs expressed as fractional
197
Percentage at ODP Site 1121
Figure 5.26
TEX86 reconstructions at ODP Site 1121
198
Figure 5.27
Relative proportions of GDGTs expressed as fractional
200
Percentage at ODP Site 1172
Figure 5.28
TEX86 reconstructions at ODP Site 1172
201
Figure 5.29
Compilation of environmental and ecological indicators at mid-Waipara 203
River Column 2
Figure 5.30
Compiled SST records for studied sites in the southwest Pacific
210
xvi
Figure 5.31
Compiled GDGT ratios, distributions and offset between
and 213
derived SST reconstructions.
Figure 5.32
Crossplots of GDGT-2/GDGT-3 ratio against offset between
and
214
reconstructed SSTs for SW Pacific sites,
and the modern core-top calibration data set
Figure 5.33
Compilation of carbon cycle indicators in the SW Pacific
217
Figure 5.34
Climate and carbon cycle compilation for the SW Pacific
219
Figure 5.35
Compiled compound specific carbon isotope analysis of LMW, HMW, 222
MMW n-alkanoic acids and hopanoic acids at mid-Waipara Column 2
Figure 6.1
Palaeomap of New Jersey ODP SITE 174X drill sites
231
Figure 6.2
Age model for Bass River
232
Figure 6.3
Example LC-MS chromatograms of GDGTs at Bass River
233
Figure 6.4
Bass River relative GDGT distributions expressed as fractional
235
percentage
Figure 6.5
TEX86 reconstructions at Bass River
236
Figure 6.6
Compilation of marine climate records for the (late) Paleocene
238
Figure 6.7
Compilation of carbon isotope record for the (late) Paleocene
239
Figure 6.8
Crossplots of compiled GDGT-2/GDGT-3 ratio against offset between 249
and
reconstructed SSTs for all generated and compiled
GDGT data sets in this study, and the modern core-top calibration data
set
Figure 6.9
Synthesis of early Paleogene TEX86-derived sea surface temperature 254
estimates for the Southwest Pacific.
Figure 6.10
Southwest Pacific Paleogene proxy/model comparison.
256
xvii
List of Tables
Number
Title
Page
Table 2.1
[M+H]+ m/z of isoprenoidal and branched GDGTs analysed for by 45
HPLC/APCI-MS in SIM mode
Table 2.2
Pooled standard deviations for types of data generated. Dataset 1 = 51
mid-Waipara K/Pg boundary (Appendix III) , 2 =
mid-Waipara
Column 2 (Appendix, IV) 3 = Bass River Paleocene (Appendix II), 4
= ODP Site 1121 (Appendix V) Paleocene. n = total number of
replicate analyses forming each dataset.
Table 5.1
Compiled carbon isotope data from ODP Site 1121 : bulk pelagic 169/170
carbonate (δ13Ccarb) and organic carbon (δ13Corg), and Δδ13C(carb-org)
xviii
Glossary of Terms
ACL
Average chain length
AOM
Anaerobic oxidation of methane
APCI
Atmospheric pressure chemical ionisation
ABW
Antarctic Bottom Water
bGDGT
Branched glycerol dialkyl glycerol tetraether
BHP
Bacteriohopanepolyol
BIT
Branched vs Isoprenoidal Tetraether (index)
BSTFA
N,O-bis( trimethylsilyl)trifluoroacetamide
δ13C
Ratio of 13C to 12C relative to the Vienna Pee Dee Belemnite standard
CBT
cyclisation of branched tetraethers (ratio)
CIE
carbon isotope excursion
CPI
Carbon preference index
CP
Campbell Plateau (ODP Site 1121)
DCM
Dichloromethane
DIC
Dissolved inorganic carbon
DSDP
Deep Sea Drilling Project
DST
Deep-sea temperature
DW
Dry weight
Isotopic discrimination (fractionation)
EOP
Even-over-odd predominance
FAME
Fatty acid methyl ester
GC
Gas chromatograph
GC-MS
Gas chromatograph – mass spectrometer
GC-C-IRMS Gas chromatograph – combustion – isotope ratio mass spectrometer
GDGT
Glycerol dialkyl glycerol tetraether
GNS
Geological and Nuclear Sciences (NZ)
HPLC
High performance (or pressure) liquid chromatograph
HMW
High molecular weight
IC
Inorganic carbon
IPL
Intact polar lipid
IODP
Integrated Ocean Drilling Program
iPA
Isopropyl alcohol (2-propanol)
K/Pg
Cretaceous/Paleogene (boundary)
Ka
Kilo annum: thousand years before present
xix
LC-MS
Liquid chromatograph – mass spectrometer
LMW
Low molecular weight
Ma
Mega annum : Million years before present
MAAT
Mean annual air temperature
MBT
methylation of branched tetraethers (ratio)
MeOH
Methanol
MI
Methane index
MMW
Mid molecular weight
MW
Mid-Waipara, NZ
NJ
New Jersey, USA
NZ
New Zealand
NZSSO
New Zealand sector of the Southern Ocean
ODP
Ocean Drilling Program
OC
Organic carbon
OM
Organic matter
OEP
Odd-over-even predominance
PCIM
Paleocene carbon isotope maximum
PETM
Paleocene/Eocene thermal maximum
PTFE
Polytetrafluoroethylene
Ph
Phytane
PCA
Principle component analysis
Pr
Pristane
RuBisCO
Ribulose-1,5-bisphosphate carboxylase oxygenase
SBB
Santa Barbara Basin
SO
Southern Ocean
SPE
Solid phase extraction
SPM
Suspended particulate matter
SST
Sea surface temperature
SW
Southwest
TAR
Terrigenous to aquatic ratio
TEX86
Tetraether index of tetraethers containing 86 carbon atoms
TLE
Total lipid extract
TOC
Total organic carbon
C37 alkenone unsaturation index
VPDB
Vienna Pee Dee Belemnite (carbon isotope standard)
xx
Chapter 1
Introduction
1
Chapter 1
Introduction
A key aspect in the determination of climate sensitivities and the dynamics behind climate
change is in the study of Earth’s history as recorded in sediments. Geological records
contain information on the climate at the time of deposition, and can be interrogated to
determine climate, environment and ecology at the time of deposition. Schott (1935;
translated 2002) documents one of the first instances of using the stratigraphic record of
foraminiferal communities to infer climate (and stratigraphic deposition of recent
sediments), determining the cooling of surface waters in an equatorial Atlantic sediment
from the last ice age, based on the planktic foraminiferal assemblage; i.e. the identification
of cool-dwelling species. In 1986, Brassell et al. introduced the use of molecular
stratigraphy, i.e. the use of organic biomarkers, fossilised in the sedimentary record, to
reconstruct palaeoenviroments and palaeoclimates. Since then molecular stratigraphy has
become a key tool in determining climate and ecology of the Earth’s history (Eglinton and
Pancost, 2004), addressing many key and diverse questions in the geological record, from
determining marine and sedimentary redox conditions during Cretaceous anoxic ocean
events (Pancost et al., 2004), to changes in climate and hydrology over the past 220 years
(Xie et al., 2004), to tracing the origins of photosynthesis 2.5 – 2.7 billion years ago (Ga),
predating the oldest known morphological fossils of eukaryotes by c. 900 My (Brocks et
al., 2005).
One of the main motivations of palaeoclimate reconstructions is to further the scientific
understanding of the Earth’s climate system. In particular there is much focus on predicting
the climate effects of contemporary anthropogenic carbon dioxide emissions into the
atmosphere from the burning of fossil fuels since the industrial revolution of the 18th
century (IPCC, 2007).
Our understanding of future climate change is largely informed by complex oceanatmosphere coupled General Circulation Models. However, climate models constrained by
palaeodata may be more helpful in predicting future climate, especially for climate states
distinct from that of the modern (Barron and Peterson, 1991; Huber and Sloan, 2001;
Huber et al., 2003, 2004; Huber and Nof, 2006; Hollis et al., 2009). As such, Sea Surface
Temperature (SST) and carbon cycle reconstructions are particularly important as these are
primary factors in modelling climate.
The classical method for SST reconstruction has been the measurement of planktic
foraminiferal calcite oxygen isotopic composition (δ18O) (Craig and Gordon, 1965;
Shackleton, 1967, 1986, 1987a,b) and these have revealed constantly evolving SSTs, as
well as indicating the timings of permanent polar ice formation, throughout Earth history;
2
Chapter 1
Introduction
In general, calcite δ18O increases as temperature decreases (0.25‰ / °C), or as the mass of
continental ice increases (0.1 ‰ / 10 m sea-level change) (Shackleton, 1987a). The oxygen
isotopic composition of benthic foraminifera provides complementary information on seafloor temperatures, although by extension of ocean circulation, these records are generally
accepted as being essentially determined by SSTs of high-latitude cold-water production
water masses (Zachos et al., 2001). More recently, the effects of foraminiferal calcite
preservation on the reconstruction of SSTs has been rigorously interrogated (Sexton et al.,
2006), owing to the discovery of excellently preserved (‘glassy’) planktonic foraminifera
from drill-cores in Tanzania from the Tanzanian Drilling Project (Pearson et al., 2007).
The oxygen isotopic composition of these ‘pristine’ foraminifera led to the reconstruction
of warmer tropical Eocene SSTs than previous reconstructions had suggested (Pearson et
al., 2007). Furthermore, the utility of foraminiferal calcite Mg/Ca ratios (e.g. Lear et al.,
2000; Tripati et al., 2003; Hollis et al., 2009) is considered to be an SST indicator that is
independent of ice-volume, and as such can be used to develop records complementary to
δ18O values (indeed the same calcite can be used for both analyses), in deciphering icevolume and temperature effects. Organic geochemical proxies can also provide
complementary information, often in settings where the use of inorganic proxies is
compromised.
Several organic SST proxies have now been developed. The unicellular coccolithophorid
Emiliania huxleyi (a Haptophyte algae which is ubiquitous in modern settings) contains
long chain (C37-C39) di-, tri-, and tetra-unsaturated methyl and ethyl ketones (alkenones)
(Volkman et al., 1980a; Marlowe et al., 1984). The degree of alkenones unsaturation is
dependent on growth temperature (Marlowe et al., 1984; Brassell et al., 1986); i.e., a
higher degree of saturation relates to a lower SST. The unsaturation index is usually
calculated using the di- and tri- unsaturated C37 alkenones, as these are generally the most
abundant in sediments (Brassell et al, 1986). Hence, the C37 alkenone unsaturation index
is determined as:
=
(1.1)
3
Chapter 1
Introduction
More recently, a palaeothermometer based on the glycerol dialkyl glycerol tetraethers
(GDGTs) deriving from pelagic thaumarchaeota, the tetraether index of tetraethers
containing 86 carbon atoms (TEX86; Schouten et al., 2002) has been developed (and is
discussed in Section 1.3.1). This is particularly useful in the reconstruction of SSTs from
sediments which do not contain abundant alkenones; despite the presence of long-chain
unsaturated ketone compounds related to the C37 alkenones in sediments as old as the
Aptian (c. 120 Ma; Farrimond et al., 1986; Brassell et al., 2004), the application of
has
generally been limited to studies of periods no older than the Pleistocene (c. 2.59 Ma)
(Schnieder et al., 2001), although there have been
derived SST reconstructions
performed in the Pliocene (c. 2.8 – 5.33 Ma; Rommerskirchen et al., 2011, c. 2.58 – 5 Ma;
Ravelo et al., 2006), Miocene (5.33 – 13.9 Ma; Rommerskirchen et al., 2011, c. 6.5 Ma;
Herbert and Schuffert. 1998), and Oligocene through to early Eocene (c. 26 – 40 Ma; Liu
et al., 2009). There are, however, no existing accounts of
reconstructions from
sediments older than the Eocene, and as such the TEX86 has provided an organic
geochemical tool to reconstruct older climates, such as in the Paleocene (Bijl et al., 2009)
and Cretaceous (Schouten et al., 2003b; Littler et al., 2011).
Changes in carbon cycling and their impact on the climates of the Paleocene (65.5 Ma –
55.8 Ma) are investigated in this thesis, as it is thought to represent a period in Earth’s
history characterised by high CO2 compared to the modern Earth, but temperatures
relatively lower than the late Cretaceous and early-mid Eocene (Zachos et al., 2001;
Pagani et al., 2005). In particular, events at the Cretaceous/Paleogene boundary (K/Pg) are
investigated, as it is a period in Earth’s history which represents a catastrophic perturbation
to the Earth system, with likely long term effects on the global biogeochemical cycle (e.g.
Hsü et al., 1982; D’Hondt et al., 1996a; Coxall et al., 2006), and the recovery of
ecosystems and climate following the event. A long term trend through the Paleocene
characterised by an increase in the δ13C values of global benthic foraminiferal calcite and
inferred cooling of the oceans is also interrogated. Evaluation of the long term climate
effects and influences related to the transient events, as well as assessment of the
relationship between carbon cycle dynamics and climate in a greenhouse system, will be
undertaken; this remains relatively poorly characterised for the Paleogene (Pagani et al.,
2005).
4
Chapter 1
Introduction
1.1. Geological Timescale
The geological timescale provides a reference for dating geological sediments. The
timescale is based on discreet recognised units that can be chronostratigraphic,
lithostratigraphic, biostratigraphic or magnetostratigraphic. As techniques for dating the
geological record become more sophisticated, the timescale requires updating.
Figure 1.1. GTS2004 Timescale for the Paleocene and Eocene (Gradstein et al., 2004),
based on biostratigraphic (e.g. planktonic foraminiferal and calcareous nannoplankton
biozones, which are based on first and last occurrences of age-diagnostic species) and
magnetostratigraphic (based on magnetic reversals which are globally observed) age
constraints.
5
Chapter 1
Introduction
The International Commission on Stratigraphy (ICS) is the largest scientific body within
the International Union of Geological Sciences (IUGS) and is responsible for keeping the
timescale up-to-date. Recent developments include the use of astronomically tuned age
models, paced to the changes in the Earth’s orbit as expressed in the sedimentary record
(e.g. Laskar et al., 2004; Westerhold et al., 2007). The most recent timescale update (Ogg
et al., 2008) utilises such orbitally tuned models; although the orbital solutions for the
Paleocene have not as yet been incorporated, they have been developed and implemented
in some studies (e.g. Westerhold et al., 2007, 2011). As such, the most recent timescale
(Ogg et al., 2008) does not differ in the age reconstruction of the Paleocene, and as such
data is presented in terms of the GTS2004 timescale (Gradstein et al., 2004; Fig. 1.1).
Where possible, data collected from other publications has also been scaled to this age
model, based on linear interpolation of durations of timescale units (e.g. interpolating
magnetochron reversals).
1.2. The Paleocene
Climatic conditions throughout the Paleocene are believed to have remained relatively
stable (Shackleton and Hall, 1984a,b; Zachos et al., 1994; Zachos et al., 2001). The
Paleocene is considered to be time of global warmth and reduced latitudinal temperature
gradients compared with the present day (e.g. Zachos et al., 1993, 1994), although
generally experienced temperatures which were relatively lower than those of the late
Cretaceous and early-mid Eocene (Zachos et al., 2001; Pagani et al., 2005). It also
experienced elevated levels of atmospheric CO2 (compared to the present day; Fig. 1.2)
that may have been at least partly responsible for its high global temperatures (Berner
1990; Arthur et al., 1991; Freeman & Hayes, 1992; Pearson and Palmer, 2000; Pagani et
al., 2005; Tipple et al., 2010). The Late Paleocene is an interval of climatic uncertainty;
ephemeral or more persistent continental ice sheets may have existed on Antarctica
(Speijer and Wagner, 2002).
6
Chapter 1
Introduction
Figure 1.2. Estimates of past atmospheric carbon dioxide concentrations. (A) pCO2
reconstruction for the past 60 My derived from sea surface water pH records reconstructed
from planktonic foraminifer boron-isotope ratios (reproduced from Pearson and Palmer,
(2000); P = Pleistocene, Pli = Pliocene, Pal = Paleocene) (B): pCO2 reconstruction for the
past 50 My derived from the carbon isotopic composition of di-unsaturated alkenones from
Haptophyte algae (reproduced from Pagani et al., 2005); solid grey curve, maximum to
intermediate values; dashed line, minimum values.
The initiation and termination of the Paleocene were characterised by catastrophic and
transient events which have been the focus of much study; the catastrophic biotic
disruption of the K/Pg boundary is contested to have been the result of a bolide impact
(Schulte et al., 2010a,b; but see Archibald et al., 2010; Courtillot and Fluteau, 2010), and
also famously marks the demise of the dinosaurs (Fastovsky and Weishampel, 1996).
A particularly notable feature of the K/Pg, however, is the homogenization of the marine
surface-to-deep water carbon isotope gradient immediately following the K/Pg boundary
event (Arthur et al., 1979; Boersma and Shackleton, 1981; Shackleton and Hall, 1984;
Zachos and Arthur, 1986; Zachos et al., 1989; Kump, 1991; Coxall et al., 2006; see Fig.
1.3), classically attributed to cessation of primary productivity in the surface ocean (Hsü et
al., 1982; Hsü and McKenzie, 1985). The Paleocene-Eocene thermal maximum (PETM)
marks the end of the Paleocene; bottom water warming of 4 to 6°C has been documented
in many locations including Antarctica (Kennett and Stott, 1991), the mid-Pacific
(Bralower et al., 1995), the tropical north Pacific and subtropical south Atlantic (Tripati
and Elderfield, 2005).
7
Chapter 1
Introduction
PETM TEX86 reconstructions indicate a SST rise of up to 8°C in the northwest Atlantic
(Zachos et al., 2006; Sluijs et al., 2007) and at least 5°C in the Arctic (Sluijs et al., 2006).
As such, it records one of the most extreme and transient warming events in the geological
record. It is also characterised by a negative excursion in the carbon isotope values (δ13C)
of inorganic and organic carbon (e.g. Kennett and Stott, 1991; Schmitz and Pujalte, 2003;
Zachos et al., 2005), and by major biotic events including extinctions and species
diversification in the terrestrial and marine realm (e.g. Kennett and Stott, 1991; Kelly et
al., 1996; Clyde and Gingerich, 1998; Crouch et al., 2001; Kelly, 2002; Smith et al., 2007;
Wang et al., 2007).
The Paleocene epoch itself has received relatively little attention compared to the initial
and terminal events described. This may be partly due to the generally inaccessible nature
of much Paleocene material; sediments of this age are too young to be widely exposed in
mountain belts, yet too old to have been easily accessible to shallow drilling technology
(Bralower et al., 1995). This has in part been remedied by the advancements in drilling
technology (e.g. ODP Leg 208; Zachos et al., 2004). Evidence exists to suggest that the
Paleocene may not have been as stable as is generally accepted; the devastation of marine
biota at the K/Pg is suggested to have disrupted biogeochemical cycles for up to 1 - 3 My
(D’Hondt et al., 1996a, 1998), as evidenced by the sustained collapse or suppression of the
benthic-planktic carbon isotope gradient (Keller and Lindinger, 1989; Zachos et al., 1989;
Zachos et al., 1992; D’Hondt et al., 1998; Coxall et al., 2006). The climate of the early
Danian is relatively poorly constrained due to conflicting records of climate change across
the K/Pg, and a tendency for climate reconstructions to focus on the immediate pre- and
post-K/Pg climate (e.g. Perch-Nielsen et al., 1982; Zachos and Arthur, 1986; Margolis,
1987; Keller and Benjamini, 1991; Magaritz et al., 1993). In the late Paleocene, a decrease
in global benthic temperatures (Zachos et al., 2001; Cramer et al., 2009) is recorded,
coinciding with a positive carbon isotope excursion in marine carbonates. δ13C values as
high as 4‰ are recorded in sections from the central equatorial Pacific (Shackleton et al.,
1985; Corfield and Cartlidge, 1992; Bralower et al., 1995), the North (Faul et al., 2003)
and South Atlantic (Corfield and Cartlidge, 1992), the Tethys (Schmitz et al., 1997) and
New Zealand (Hollis et al., 2005). This interval is often referred to as the Paleocene
Carbon Isotope Maximum (PCIM). The Paleocene may therefore represent an epoch with a
relatively dynamic carbon cycle and climate, and as such provides an ideal period to study
the relationship between carbon cycling and climate change in a high-CO2 Earth system.
8
Chapter 1
Introduction
1.2.1. The Cretaceous / Paleogene Boundary and Subsequent Recovery
The Cretaceous/Paleogene boundary is associated with one of the five largest mass
extinction events to occur in Earth history and major changes in the global environment.
The extent of mass extinction and ecological perturbation at the K/Pg boundary has been
extensively studied and is generally attributed to a bolide impact (Alvarez et al., 1980;
Shulte et al., 2010a), although debate persists (Archibald et al., 2010; Courtillot and
Fluteau, 2010; Keller et al., 2010; Schulte et al., 2010b). Global effects associated with the
putative K/Pg bolide could include global darkness, cooling and subsequent warming,
wildfires, SOx and/or NOx poisoning, dust and acid rain (Alvarez et al., 1980; O’ Keefe
and Ahrens, 1982; Brett 1992; Pope et al., 1994; Toon et al., 1997; Arinobu et al., 1999;
Smit, 1999; Premovic et al., 2000; Kieseling and Claeys, 2001). All, or a combination, of
these effects could have been responsible for the severe marine extinctions (Thierstein,
1982; D’Hondt et al., 1996; Bown, 2004) and terrestrial devastation (e.g. Tschudy et al.,
1984; Wolfe and Upchurch, 1986; Johnson 1992; Sweet et al., 1999; Sweet and Braman,
2001) observed at the K/Pg boundary. Such perturbations of the Earth systems are also
likely to have caused oceanographic and climatic change, along with severe disruption to
global biogeochemical cycles (D’Hondt et al., 1996a).
1.2.1.1. Climatic and Oceanographic Consequences of the K/Pg
Numerical models simulating the effects of a K/Pg boundary impact predict a brief (10 –
2000 yr) period of global cooling induced by the sulfate aerosols blocking the sun – the socalled ‘impact winter’ (Siggurdsson et al., 1992; Pope et al., 1997; Pierasso et al., 2003) –
followed by a period of more gradual warming caused by CO2 released by the impact
(Kring, 2007). Thus, the climate preceding and especially following the K/Pg boundary has
also been the subject of much scrutiny, in order to understand the context of the global
extinction and its longer-term consequences on the Earth system and biogeochemical
cycling.
Extinctions in the marine realm were extreme (e.g. up to 90% for foraminiferal species)
(Thierstein, 1982; D’Hondt et al., 1996; Bown, 2004), and homogenization of the marine
surface-to-deep water carbon isotope gradient immediately following the K/Pg boundary
event (Arthur et al., 1979; Boersma and Shakleton, 1981; Shakleton and Hall, 1984;
Zachos and Arthur, 1986; Zachos et al., 1989; Kump, 1991; Coxall et al., 2006) has been
attributed to cessation of primary productivity in the surface ocean, the so-called
9
Chapter 1
Introduction
‘‘Strangelove Ocean’’ (Fig. 1.3) (Hsü et al., 1982; Hsü and McKenzie, 1985; Keller and
Lindinger, 1989; Stott and Kennett, 1989; Zachos et al., 1992). A shutdown or reduction in
the uptake of
12
C by photosynthetic phytoplankton, and increased biomass burning
(Wolbach et al., 1988; Ivany & Salawitch, 1993), could together have lead to an
accumulation of 12CO2 in the ocean-atmosphere reservoir.
Figure 1.3. Simplified schematic of the benthic and planktic carbon isotope record of the
North Pacific K/Pg (Zachos et al., 1989) depicting the homogenisation of the benthicplanktic carbon isotope gradient. Figure adapted from Kump (1991).
One of the primary potential drivers of such widespread biotic change could have been the
‘impact winter’ (Siggurdsson et al., 1992; Pope et al., 1997; Pierasso et al., 2003), and
several studies have directly attributed observed marine biotic change following the K/Pg
to colder temperatures. Benthic planktonic and dinoflagellate records at El Kef, Tunisia
testify to the expansion of the Boreal (north Atlantic) province into the western Tethys
following the K/Pg, indicating a profound cooling lasting only c. 2 kyr (Galleoti et al.
2004). Similar dinoflagellate migrations reflecting transient cooling are recorded in Spain
and Denmark (Brinkhuis et al., 1998). Fossil leaf morphology (Wolfe, 1991) and terrestrial
flora survivorship patterns (Wolfe and Upchurch, 1987) provide evidence for freezing
conditions in the immediate aftermath of the K/Pg in the western interior of North
America. Together, the geographic ranges of these lines of evidence suggest a globally
pervasive cooling.
10
Chapter 1
Introduction
Unfortunately, palaeotemperature determinations from measurement of calcite δ18O values
across the K/Pg boundary transition itself and into the early Danian are hampered by poor
preservation, CaCO3 dissolution, low sampling resolution and extinction of planktic
calcifying organisms at the K/Pg (Zachos and Arthur, 1986; Keller and Benjamini, 1991;
Magaritz et al., 1993). As such, many existing records are either based on bulk carbonate
isotope analysis (e.g. Margolis, 1987; Perch-Nielsen, 1982; Smit 1990; Kroon et al.,2007),
the use of mixed species assemblages across the K/Pg (e.g. Douglas and Savin, 1971 ), or
the use of different species before and after the K/Pg (e.g. Boersma and Shakleton, 1981).
Despite the associated problems, attempts to reconstruct post-K/Pg marine temperatures
have been made, with often conflicting and widely ranging results. Sea surface and/or deep
sea cooling (Boersma and Shackleton, 1977, 1979; Boersma and Shackleton, 1981; Keller
and Lindinger, 1989) and warming (Douglas and Savin, 1971; Oberhänsli, 1986; Barrera
and Keller, 1990; Smit, 1990; Stott and Kennett, 1990; Schmitz et al., 1992; Barrera and
Keller, 1994) of varying extents have been reconstructed, or indeed a scenario of no
significant change at all has also been suggested (Zachos and Arthur, 1986). Disagreement
as to the direction of climate change is documented in sediments from the same ocean
basins (Zachos et al., 1986), and even between relatively proximal sites (Boersma and
Shackleton, 1977; 1979).
1.2.1.2. The K/Pg Boundary: Recovery of Climate and Ecology
Although plankton productivity apparently recovered quickly from K/Pg boundary
mortality, initial recovery of the surface-to-deep water carbon isotope gradient occurred
over approximately 500,000 years, indicating that complete marine recovery (AlcaláHerrera et al., 1992; Hollander et al., 1993; D’Hondt et al., 1998) and reestablishment of
mechanisms that transport reduced carbon into the deep ocean (i.e. the biological pump)
may not have occurred for up to 1–3 Ma (Keller and Lindinger, 1989; Zachos et al., 1989;
Zachos et al., 1992; D’Hondt et al., 1998; Coxall et al., 2006). This extended period of a
low surface-to-deep water carbon isotope gradient has been interpreted as a symptom of an
unusually low flux of organic carbon to the deep sea in an ecologically altered normal
productivity ocean, termed the ‘‘Living Ocean’’ model (D’Hondt et al., 1998). Inferred to
be superimposed on this long term recovery are periodic episodes of enhanced
monospecific calcareous nannoplankton productivity which may reflect the inherent
instability and unusual ecology of the early Danian marine system (Perch-Neilson et al.,
1982; Hollander, 1993).
11
Chapter 1
Introduction
In contrast, terrestrial ecosystems are believed to have recovered from the events of the
K/Pg boundary faster than counterpart marine ecosystems (Beerling et al., 2001). The most
severe extinctions in terrestrial palynoflora are generally localised to southern North
America (Tschudy et al., 1984; Wolfe and Upchurch, 1986; Johnson 1992; Sweet et al.,
1999; Sweet and Braman, 2001). Orth et al. (1981) first documented an abrupt replacement
of diverse flora with fern spores at the K/Pg boundary in New Mexico, interpreted as rapid
colonisation by opportunistic fern species following widespread deforestation. Extinctions
outside North America were apparently less severe (Beerling et al., 2001, Vajda and
McLoughlin, 2009), although dramatic short term changes in relative abundances of plant
groups reflect the global nature of the perturbation and widespread mass-kill of vegetation,
with associated colonisation by opportunistic species. (Vajda and McLoughlin, 2009). The
proceeding gradual succession of pioneer-type terrestrial flora to more diverse flora is
termed a ‘quasi-succession’, owing to the long-term (up to 1.5 My) assemblage changes
above the K/Pg boundary mimicking a short-term (hundreds of years) ecological
succession (Wolfe and Upchurch, 1986, 1987), such as that recorded after the local
terrestrial mass-kill associated with the 1883 eruption of Krakatau (Richards, 1952). In
summary, recovery of early Paleocene terrestrial diversity is argued to proceed over an
evolutionary, rather than ecological timescale (Wolfe and Upchurch, 1987).
A global understanding of the K/Pg boundary events requires the reconstruction of climate
across a wide variety of locations. In particular, the study of settings which are distal to the
site of the proposed K/Pg bolide impact (the Yucatan Peninsula, Chicxulub, New Mexico;
Hildebrand et al., 1991) can provide insight into the global effects of the putative impact
and the recovery of climate and biogeochemical cycles. The high latitude Southern Ocean,
in particular the southwest Pacific, provides such a location.
12
Chapter 1
Introduction
1.2.1.3. The K/Pg and Recovery: Records from the South Pacific and NZ
Figure 1.4. Palaeomap reconstruction for the location of NZ at the time of the K/Pg, 65.5
Ma. The map was plotted using the ODSN (Ocean Drilling Stratigraphic Network) online
service. Plate Tectonic Reconstruction Service after Hay et al. (1999). The reconstruction
was performed using the palaeomagnetic reference frame for North America (Harrison and
Lindh, 1982) and plotted as an equidistant cylindrical projection.
However, K/Pg boundary sections are rare in Southern high latitude settings (Nøhr-Hansen
and Dam, 1997); New Zealand (NZ; Fig. 1.4) contains the only South Pacific records of
the K/Pg. Further geochemical investigations of the K/Pg boundary at NZ are required to
directly determine the climate succession and recovery associated with the events of the
K/Pg. Analysis of marine and terrestrially derived carbon isotope records are required to
determine the immediate and long-term perturbations to the carbon cycle, as likely results
of the disruptions to the biogeochemical cycles. Existing global records of the ecology and
climate should be integrated with records from the southwest Pacific to determine the
scope and impact of marine and terrestrial reorganisation and climate change in a global
context.
13
Chapter 1
Introduction
1.2.2. The Paleocene Carbon Isotope Maximum (PCIM)
Following the biotic and oceanographic recovery from the K/Pg, the latter of which
appears to have been complete sometime between 64 and 62 Ma, the Paleocene is
generally thought to have been characterised by relatively stable climate. However,
evidence exists for a more dynamic climate in the mid to late Paleocene. Specifically, the
“Paleocene carbon isotope maximum” PCIM (Fig. 1.5), first reported in the calcite of
foraminifera from Deep Sea Drilling Project cores from Legs 74 (Shackleton et al., 1985)
and 84 (Shackleton et al., 1987b), is the most prominent feature of the Cenozoic benthic
carbon isotope record (Zachos et al., 2001; Cramer et al., 2009). The PCIM was initiated
around 2.5 My after the K-Pg boundary event, maximised in the middle Paleocene (mid
C26r to mid C25r; 58.7 – 56.4 Ma), and waned through the latest Paleocene and into the
early Eocene. Bulk calcium carbonate δ13C values reach up to 4 ‰ (a total enrichment
relative to pre-PCIM δ13C values of c. 2 ‰) at c. 57 Ma, persisting for around 2 – 4 My.
The negative carbon isotope excursion of the Paleocene Eocene Thermal Maximum
(Bralower et al., 1995; Corfield and Cartlidge, 1992; Shackleton, 1987b; Shackleton and
Hall, 1984a,b) is superimposed upon the waning stage of the PCIM.
Figure 1.5. Global compilations of oxygen and carbon benthic foraminiferal isotopes
(Cramer et al., 2009). Blue band represents interval of δ13C-enrichment, the Paleocene
carbon isotope maximum (PCIM).
14
Chapter 1
Introduction
1.2.2.1. Causes of the PCIM and Associated Climate Change
On the basis of sedimentary barium concentrations, there is evidence for a large increase in
marine organic carbon burial (6-fold) in oligotrophic regions of the oceans, and a much
smaller increase (1.6-fold) in highly productive regions (Thompson and Schmidtz, 1997).
An organic rich facies with relatively high δ13C values deposited in the late Paleocene in
East Coast and Great South Basins of New Zealand (the Waipawa ‘black shale’ Formation;
Killops et al., 2000) also suggests a widespread marine carbon burial event. Although there
is generally a lack of globally pervasive organic rich black-shales, such as those described
by Arthur et al. (1988) for positive carbon isotope events associated with anoxia in the
Cretaceous, some examples of Paleocene organic carbon rich marine sediments do exist.
For example, black clays which are abundant in mid-Cretaceous sediments of the western
North Atlantic at DSDP Leg 43 reappear at some sites in mid-Paleocene sediments
(Tucholke and Vogt, 1979). These abyssal sediments contain up to 1.3% organic carbon
and are interpreted to reflect poorly ventilated deep waters (Tucholke and Vogt, 1979).
However, it is argued that an increase in marine photosynthesis is insufficient to account
for the observed
13
C enrichment, and it has been suggested instead that high-latitude
terrestrial vegetation extended to lower latitudes, resulting in increased production of
terrestrial organic carbon (Oberhänsli and Perch-Nielsen, 1990). Kurtz et al. (2003)
modelled the relationship between buried organic carbon (Corg) and pyrite sulfur (Spy)
based on reconstructed sea water isotope curves for carbon and sulfur derived from
measurements performed on sedimentary calcite and barite from Atlantic and Pacific
DSDP/ODP core samples of Cenozoic age. They observed a greatly elevated Corg/Spy
burial ratio around the time of the PCIM, and thus invoked a terrestrial locus for organic
carbon burial. The authors concede that their findings could also be consistent with a net
shift of organic carbon sedimentation to pyrite-lean pelagic settings. Late Paleocene coal
deposits are amongst the thickest in the entire geological record (Shearer et al., 1995;
Ziegler et al., 2003; Kalkreuth, 2004). The late Paleocene Fort Union Formation, located in
the Montana-Wyoming Powder River Basin contains some of the most significant postPalaeozoic coals in North America (Ellis et al., 1999). The Wyodak-Anderson member
alone contains an estimated 550 Gt economically recoverable coal in beds as much as 60 m
thick (Ellis et al., 1999). Modelling by Kurtz et al. (2003) suggest it is reasonable to
assume that the total carbon sequestered terrestrially in the late Paleocene could account
for the global positive carbon isotope excursion and inferred OM burial.
15
Chapter 1
Introduction
If the PCIM was caused by carbon burial in either the marine or terrestrial realm, it could
have been associated with a decrease in pCO2. Such a scenario would require a 4-fold
increase in global open-ocean carbon burial to offset a calculated 50% decrease in shelf
carbon burial whilst maintaining a 20-30% net increase in global Corg burial (Kurtz et al.,
2003). This could be consistent with the evidence suggestive of increased productivity in
the oligotrophic oceans (Thompson and Schmidtz, 1997). A decrease in pCO2 could
provide a mechanism for cooling, i.e. a decreased greenhouse forcing. Indeed, the PCIM
appears to be coincident with isotopic evidence for cooling in the globally compiled
benthic carbonate δ18O record (Cramer et al., 2009). However, it is generally accepted that
the δ18O value of benthic foraminifera is essentially determined by SSTs of high-latitude
cold-water production water masses, whereas the δ13C values of open ocean calcite are
more likely to represent a global average value of benthic δ13C, as carbon cycles through
reservoirs quickly relative to the incorporation of
13
C in benthic foraminiferal tests
(Shackleton, 1987a). The oxygen isotope records associated with bottom water cooling
also indicate an increased importance of the Southern Ocean (SO) as a bottom water source
(Corfield and Norris, 1996). As such, the SO may be a pertinent setting to interrogate the
events of the PCIM, to determine whether oceanographic and climate change in the SO
may have effected global change as reflected in the global compilation of benthic
carbonate δ13C and δ18O values.
1.2.2.2. Climate Records from the Southern Ocean
Climate records of the Southern Ocean are essential in reconstructing the global climate
and oceanographic response to the PCIM, particularly as the influence of ocean heat
transport in cooling Southern Ocean is likely to be relatively minimised due to the lack of
fully opened ocean gateways; during the Paleocene, both the Tasman Gateway (between
South Tasman Rise and Antarctica) and Drake Passage (between South America and
Antarctica) seaways were closed (Wise et al. 1991; Abreu & Anderson 1998; Lawver, and
Gahagan, 1992). The SW Pacific region of the Southern Ocean is considered to be
influenced predominantly by undifferentiated subtropical surface waters circulating from
(north)west to east through the region as part of a large South Pacific warm-water gyre
(Barron and Peterson 1991). New Zealand contains several exposed and ‘pristine’
Paleocene sections deposited during a phase of thermal relaxation & passive margin
subsidence between prolonged episodes of active tectonism and uplift (Hollis et al., 2002;
2005 Killops et al., 2000; Morgans et al., 2005), and such provides an ideal setting to
examine the expression of the PCIM in the Southern Ocean.
16
Chapter 1
Introduction
However, on-land sediment records of New Zealand are either carbonate-lean or the
carbonate has frequently undergone significant diagenesis (Field and Browne, 1989;
McMillan and Wilson, 1997; Hollis and Manzano-Kareah, 2005; Hollis et al., 2005).
Diagenesis has not affected the carbon isotope record significantly, but interaction with
meteoric waters has produced strongly negative δ18O values (Hollis et al., 2005). As such,
SST reconstructions for these settings using carbonate oxygen isotope analysis are severely
hampered. Thus, the regional impact of the PCIM upon climate is generally
uncharacterised, yet the Southern Ocean response to the inferred changes in carbon cycling
is crucial in determining the global implications of the PCIM in terms of ecological and
climate change. If cooling in the Southern Ocean is a feature of carbon burial, this may
suggest that changes in the carbon cycle, and possibly pCO2, has a greater effect upon the
climate of the Southern Ocean (specifically on inducing cooling) than classically predicted
by the ocean heat transport models; indeed, this would agree with recent models which
indicate that CO2 exerts more of an influence on Southern Ocean Climate than ocean heat
transport (DeConto and Pollard, 2003a,b; DeConto et al., 2008).
1.2.3. Climate Instability in the Paleocene
The Paleocene may reflect a period of more dynamic climate and changes in the carbon
cycle than is generally thought. The impact of the K/Pg upon climate is poorly understood,
and the long-term effects of the disruption to the early Paleocene climate systems are
similarly poorly characterised. The cause of the PCIM remains unknown in terms of a
marine or terrestrial carbon burial, and the global extent of climate change associated with
the apparently dramatic and prolonged shift in carbon cycling also requires interrogation.
Southern Ocean, particularly southwest Pacific, settings are particularly rare, yet provide a
pertinent setting for the investigation of climate and biotic change as a response to changes
in the carbon cycle.
1.3. Thesis Aims and Hypotheses
The central aim of this thesis is to determine the extent of climate change and ecological
responses to perturbations or changes in the carbon cycle through the Paleocene. A central
hypothesis of this thesis therefore is that the climate of the late Cretaceous and through the
Paleocene was primarily driven by changes in pCO2, rather than other factors which have
been attributed to possibly driving climate change (e.g. ocean heat transport); as such this
17
Chapter 1
Introduction
hypothesis suggests that the carbon cycle and associated biogeochemical cycling regulated
climate change throughout the aforementioned time period. In order to test this hypothesis,
sea surface temperatures (SSTs) will be reconstructed for events characterised by dynamic
changes or disruptions to the carbon cycle, at a location which is unlikely to be affected by
changes in ocean heat transport.
There is significant existing evidence for long-term (up to 1.2 My) disrupted
biogeochemical cycles as a result of the K/Pg boundary event, but the impacts on global
climate are not well characterised. The hypothesis addressed in this thesis with regards to
the K/Pg boundary event therefore is that climate instability persisted in tandem with the
disruption to biogeochemical cycles, until a stable ecosystem was re-established; i.e. that
both climate and biogeochemical cycling was disrupted at the K/Pg boundary, and
remained unstable for at least 1.2 My. In order to address this hypothesis, the biomarker
approach will be applied to elucidate the K/Pg climate and ecology at mid-Waipara River,
NZ. The TEX86 palaeothermometer will be utilised to reconstruct SSTs at this site across
the K/Pg boundary and into the early Paleocene, and will be presented alongside other
local and global indicators of climate in Chapter 3. This organic geochemical based
reconstruction is particularly novel, as the use of inorganic SST proxies is compromised at
the chosen study site, as well as being generally problematic globally, due to diagenetic
alteration and extinctions of calcite-bearing fossils.
In Chapter 4, changes in sources of organic matter across the K/Pg boundary at midWaipara River will also be explored, as documented by exceptionally preserved terrestrial
and marine derived biomarkers. The carbon isotopic composition of higher plant and algal
biomarkers will be determined in order to evaluate both the relationships between
terrestrial and marine carbon cycling, and the extent to which the carbon cycle was
perturbed and subsequently recovered in both systems across the K/Pg boundary and into
the early Danian. Chapters 3 and 4 will together represent an integrated interrogation of the
impact of the K/Pg boundary events upon biogeochemical cycling, marine and terrestrial
perturbation and recovery, and the climate changes associated with the early Paleocene.
The global context of these climate and carbon isotope records will be established by
comparison with other available published records of carbon isotopes, SSTs and deep sea
temperatures (DSTs).
A significant and long-term
13
C-enrichment is recorded in the global benthic carbonate
carbon isotope record of the late Paleocene, the Palaeocene carbon isotope maximum
(PCIM), which may be related to an extended period of carbon burial. However, the locus
18
Chapter 1
Introduction
of burial is unknown, and the possible effect the carbon cycle disruption had on climate is
poorly constrained. The hypothesis addressed in this thesis is that the PCIM reflects a
global cooling event and a significant carbon sequestration. Furthermore, records of
Paleocene climate, ecology and carbon cycling are also particularly exiguous in the
Southern Ocean (SW Pacific). This setting is key to determining the global context of
climate changes through the Paleocene; both the Tasman Gateway and Drake’s Passage
were closed at this time (Kennett et al., 1972), precluding a strong influence of ocean heat
transport in the SW Pacific region of the Southern Ocean, due to the lack of a strong
circum-polar current (Nelson and Cooke, 2001). Moreover, a deep-water cooling and
increased importance of the Southern Ocean as source of deep-waters has been inferred for
the PCIM (Corfield and Cartilidge, 1996), and tentatively correlated deposition of organicrich sediments have been identified in New Zealand. Together these observations form the
basis for the hypothesis that cooling is reflected locally in the SW Pacific of the Southern
Ocean, associated with enhanced productivity and deposition of organic-rich sediments. A
corollary hypothesis is that the Southern Ocean is an important locus for carbon burial at
the PCIM, and that the mechanism of local carbon sequestration was stimulation of
primary productivity via upwelling. Overall, this setting may provide information to
support or refute climate models which predict a greater sensitivity of regional Southern
Ocean climate to changes in the carbon cycle than is generally attributed (Huber and Sloan,
2001; DeConto and Pollard 2003a,b; Huber et al., 2004; Huber and Nof, 2006; DeConto et
al., 2008). Essentially, pCO2 is hypothesised to be the primary driving force of local
Southern Ocean climate in the Paleocene, as typified by the relationship between climate
and the carbon cycle in a setting lacking influence of circum-polar current.
Late Paleocene climate and carbon cycling in the Southern Ocean will be assessed in
Chapter 5, with a particular focus at mid-Waipara. A central aim of this chapter is to
determine whether there was significant climate and oceanographic change associated with
evidence for
13
C-depletion in the ocean-atmosphere reservoir. Compound-specific isotope
analysis of terrestrial and algal biomarkers will be used to determine the carbon cycle
changes recorded for each reservoir, and changes in biomarker distributions will be
interrogated to assess ecological and climate/environmental changes associated with trends
in the carbon isotope records. The TEX86 palaeothermometer will be employed to
determine SSTs through the interval; inorganic proxies are again compromised in this
setting. Previously published records of pelagic carbonate δ13C from ODP Site 1121 will
be compiled and integrated with δ13C records of organic carbon generated for this study,
and pCO2 will be qualitatively estimated. Another principle aim is to determine whether the
19
Chapter 1
Introduction
Southern Ocean may have been a locus for the burial of organic matter, based on estimates
of productivity based on algal biomarker and isotope records. The Southern Ocean records
will be considered in a global context and compared with preliminary TEX86 SST data
generated for a low-latitude northern Hemisphere site (Bass River, NJ, USA), as well as
comparing to other global records in Chapter 6, which will serve as an overview of the
achievements of the project and place the climate records generated in a long-term context.
1.4. Biomarkers
Biomarkers, organic molecules preserved in the geological record, are now widely used in
the reconstruction of ancient biological and climatic change (e.g. Hollis et al., 2009;
Sepúlveda et al., 2009; Yamamoto et al., 2010; Handley et al., 2011; Zhu et al., 2011)..
Their utility arises from the presence of features that are diagnostic for precursor
organisms and/or environmental conditions at the time of lipid production. Such features
include their chemical structure, isomeric configurations, relative distributions and stable
isotope compositions. Since the inception of molecular stratigraphy (Brassell et al., 1986),
the application of biomarker proxies has become widespread in palaeoclimate studies, and
novel proxies are continually being discovered and developed. Recent developments in
biomarker proxies are particularly relevant to resolving the aforementioned questions with
respect to changes in Paleocene biology, carbon cycling and climate. Their application to
these challenges, exploiting their exceptional preservation in sediments of NZ, will be the
focus of this thesis.
1.4.1. Biomarkers as Tracers of Biological Inputs
Many bio-molecules are bio-synthesised by exclusive classes or species of organisms.
Thus, the presence of such molecules, or their recognisable degradation products, in the
sedimentary record provides evidence for the existence of said organisms at the time of
burial and can provide insight into environmental conditions. Discussed below are
biomarkers which may have particular utility in resolving questions raised in terms of
Paleocene ecology; e.g. the extent of marine and terrestrial disruption across the K/Pg
boundary and the subsequent recovery, and algal responses to changes in oceanography
through the PCIM.
20
Chapter 1
Introduction
1.4.1.1. Terrestrial Biomarkers
High-molecular weight (HMW) n-alkyl compounds (Fig. 1.6) are straight chain lipids,
including n-alkanes, n-alkanols and n-alkanoic acids derived from plant waxes and tissues
(Eglinton and Hamilton, 1967). Leaf waxes of terrestrial higher plants contain
predominantly odd-numbered n-alkanes and even-numbered n-alkanoic acids and nalcohols (Eglinton and Hamilton, 1963; Kolattukudy, 1980; Mazurek and Simoneit, 1984;
Tulloch, 1976).
Figure 1.6. Examples of high-molecular weight n-alkyl compounds.
These compounds are relatively resistant to degradation, which makes them suitable for
use as higher plant biomarkers (Cranwell, 1981). As such, they may be used as indicators
of continental material inputs into the marine environments, either by fluvial discharges
(Prahl et al., 1994; Pelejero et al., 1999b) or aeolian transport (Calvo et al., 2001b;
Gagosian & Peltzer, 1986; Ohkouchi et al., 1997; Poynter et al., 1989). The abundance of
terrestrial derived organic biomarkers and their relative distributions compared to those of
other sources can be used in coastal marine sections to assess relative changes in the
terrigenous supply of organic matter to the sediment.
The predominance of odd-numbered n-alkanes and even-numbered n-alkanoic acids and nalcohols in the HMW range characteristic for higher terrestrial plants (Eglinton and
Hamilton, 1963; Kolattukudy, 1980; Mazurek and Simoneit, 1984; Tulloch, 1976) can be
expressed as a number of ratios, such as the carbon preference index (CPI; Bray and
Evans, 1961) and the odd-to-even predominance (OEP; Scalan and Smith, 1970) and can
similarly provide insight into changes in higher plant contribution to the HMW n-alkyl
21
Chapter 1
Introduction
range and thus potential changes in terrigenous input. Chain-length distributions are also
sensitive to changes in the composition of their source vegetation or the environment, such
as temperature and aridity, with longer chain lengths generally indicating warmer and/or
drier condition (Hall and Jones, 1961; Gagosian and Peltzer, 1986; Poynter et al., 1989;
Rommerskirchen et al., 2003; Schefuβ et al., 2003; Sachse et al., 2006; van Dongen et al.,
2008). However, the ratio of C31 / (C29 + C31) is considered to be more closely related to
aridity than temperature, based on n-alkane distributions in dust samples collected from
equatorial Africa; the C29 homologue was found to dominate in samples collected from the
rain forest regions (Schefuβ et al., 2003).
1.4.1.2. Algal Biomarkers
Chlorophyll a is found in the chloroplasts of organisms which utilise photosynthetic
pathways; this includes higher plants, green algae, and species of cyanobacteria and
archaea (Rowland, 1990). Phytol is cleaved from the phytyl side chain, and depending
partly upon the redox conditions or thermal maturity will yield either pristane (Pr) or
phytane (Ph) (Didyk et al, 1978; Ten Haven et al., 1987) (Fig. 1.7). Pr is formed under
oxic conditions, whereas anoxic conditions yield Ph. Pristane and phytane are therefore
typically inferred to derive from the phytyl side chain of chlorophyll a in photoautotrophic
organisms and bacteriochlorophyll a and b in purple sulfur bacteria (Brooks et al., 1969;
Powell and McKirdy, 1973; Rowland, 1990; Rontani and Volkman, 2003), though other
sources have been recognised, such as archaea (Chappe et al., 1982; Goossens et al.,
1984). Furthermore, a terrigenous source for phytol and its degradation products has also
been observed in sediments (e.g. Pagani et al., 2000).
Figure 1.7. Phytol, and its degradation products pristane and phytane.
22
Chapter 1
Introduction
Low-molecular weight (LMW) n-alkyl compounds can derive from a variety of sources,
but odd-numbered n-alkanes in the range of C15-C21 are usually attributed to macro and
micro algal sources (Broman et al., 1987; Colombo et al., 1989). The even-numbered nalkanoic acid and n-alcohol homologues are also generally assigned a marine algal source
(Harrington et al., 1970; Patterson, 1970; Kenyon et al., 1972; Volkman et al., 1980; 1981;
Gagosian, 1986; Clauster et al., 1989; Carrie et al., 1998). Some n-alkanoic acids, such as
palmitic acid (16:0), are present in virtually all marine organisms (Carrie et al., 1998;
Mudge et al., 1998; Ali and Mudge, 2006) and have therefore been used as a measure of
total community biomass (Parkes, 1987). LMW n-alkanoic acids can, however, also derive
from terrestrial higher plants (Kollatukudy, 1976). As such, estimation of marine
contribution to sediments relative to terrestrial contribution should not be based on LMW
n-alkanoic acid concentrations and distributions.
Figure 1.8. Cholesterol (cholest-5-en-3β-ol), cholestan-3β-ol and cholestane structures.
Sterols are tetracyclic triterpenoids found in all eukaryote cell membranes (Mackenzie et
al., 1982; de Leeuw et al., 1989), which degrade diagenetically to produce unsaturated
sterenes and fully saturated steranes in sediments. Although sterols and their associated
diagenetic products have a wide range of sources, in a marine depositional environment
they are likely to have a predominantly algal source. Furthermore, the relative distributions
of steroids within a sediment can be used to distinguish shifts in biotic input to sediments
(Huang and Meinschein, 1978; 1979) as different classes of organisms synthesise different
carbon number compounds preferentially.
23
Chapter 1
Introduction
Cholest-5-en-3β-ol (cholesterol; Fig. 1.8) is known to derive from zooplankton (Huang and
Meinschein, 1976; Gagosian and Nigrelli, 1976), either directly or through dietary
alteration of phytosterols (Gagosian and Heinzer, 1979; Volkman et al., 1987; Grice et al.,
1998). Cholesterol has also been identified in microalgae such as dinoflagellates (Alam et
al., 1979; Volkman et al., 2003; Serrazanetti et al., 2006), eustigmatophytes (Volkman et
al., 1992; Patterson et al., 1994), diatoms, and haptophytes (Volkman, 1986; 1998; 2003),
and is present in relatively minor amounts in terrestrial (Itoh et al., 1977; Nishimura and
Koyama, 1977) and aquatic (Johns et al.,1980; Volkman et al., 1980b; 2008) plants. The
C28 24-methylcholest-5-en-3β-ol is much less widely distributed than cholesterol, and only
rarely is it the main sterol in algae; significant concentrations are found in a few diatoms
and dinoflagellates. Furthermore, 24-methylcholest-5-en-3β-ol may also be a very minor
constituent of some cyanobacteria (Volkman et al., 1986; 1998; 2003). Other C28 sterols,
such as 24-methylcholesta-5,22E-dien-3β-ol are major constituents of microalgae,
abundant in diatoms (Rubinstein and Goad 1974), haptophytes and cryptophytes (Goad et
al. 1983; Volkman 1986). In higher plants, both 24-methylcholesta-5,22E-dien-3β-ol and
its C-24 epimer brassicasterol can be found.
24-ethylcholest-5-en-3β-ol (β-sitosterol; Fig. 1.9) is one of the major sterols found in
terrestrial higher plants (Goad and Goodwin, 1972; Huang and Meinschen, 1976), as well
as in seagrasses and aquatic plants (Johns et al., 1980; Volkman et al., 1980b, 2008). The
occurrence of β-sitosterol in highly productive oceanic settings, however, is often
attributed to a contribution by non-specific planktonic sources (Lee et al., 1980; Volkman
et al., 1981; Walters and Cassa, 1985; Volkman, 1986, 2003; Pearson et al., 2000). The
compound has been found to dominate the sterol distributions in brown algae (Patterson,
1977), and has been reported from diatoms, green algae and cyanobacteria (Barrett et al.,
1995; Volkman, 1986, 1994). Thus, it is not necessarily indicative of terrestrial lipid input.
4α-methyl sterols, particularly 4α,23,24-trimethylcholest-22-en-3β-ol (dinosterol; Fig. 1.9),
are most widely produced by dinoflagellates (Withers et al., 1978; Boon et al., 1979;
Robinson et al., 1984; Volkman, 1998; 2003; Serrazanetti et al., 2006), although some
dinoflagellate species do not contain this sterol (Goad and Withers, 1982; Leblond and
Chapman, 2002). Relatively minor concentrations of 4-methyl sterols are also
biosynthesised by some diatoms (Volkman et al., 1993) and haptophytes (Volkman et al.,
1990, 1997), although the major C30 4-methyl sterol is 4α-methyl-24-ethyl-5α-cholest-22Een-3β-ol, which has a conventional C-24 alkylated side-chain rather than a 23,24- dimethyl
structure.
24
Chapter 1
Introduction
Figure 1.9. Example sterol structures.
1.4.1.3. Prokaryote (Archaea and Bacteria) Biomarkers
Bacteria and archaea may also contribute to organic matter in sediments. Biomarkers from
eukaryotes can also provide insights into the sedimentary conditions or thermal history of
the sediment.
25
Chapter 1
Introduction
The lipids of archaea are similar, but have diagnostic differences, to the lipids of other
prokaryotes (De Rosa et al., 1986; Koga and Morii, 2007). Archaea are partly
distinguished from the bacteria and eukarya because of the unique sn-2,3 rather than sn-1,2
stereochemistry of the glycerol moieties (Koga et al., 1998a; 1998b) and because they
contain ether-bound membrane lipids with isoprenoidal carbon skeletons rather than esterlinked alkyl lipids (De Rosa and Gambacorta, 1988). Archaeal lipids are based upon the
isoprenoid alcohol side chains. Only the archaea incorporate these compounds into their
cellular lipids, frequently as C20 (four monomers), C25 (5 monomers) or C40 (eight
monomers) side chains (De Rosa et al., 1977; 1980; 1986; Gliozzi et al., 1982; Koga and
Morii, 2007). In some archaea, the C40 isoprenoid side chain is long enough to span the
membrane, forming a monolayer for a cell membrane with glycerol phosphate moieties on
both ends. The unusual nature of this adaptation is reflected in the observation that it is
most common in extremely thermophilic archaea (De Rosa et al., 1977). As such, archaea
were initially thought to exist only in extreme conditions, such as high temperatures
(>60°C) or acidic conditions; the specific structures of their membrane lipids were
considered to be an evolutionary adaptation to these extreme conditions (De Rosa and
Gambacorta, 1988).
1.4.1.3.1. Glycerol Dialkyl Glycerol Tetraethers (GDGTs)
Glycerol Dialkyl Glycerol Tetraethers (GDGTs) are a principle component of archaeal
membranes (Fig. 1.10). Their structures were first characterised over 30 years ago (De
Rosa et al., 1977; 1980; Gliozzi et al., 1982). Despite apparent adaptations for an
extremophilic niche, more recent studies have demonstrated that GDGTs (Fig. 1.10) also
commonly occur in lower temperature environments (<20°C) (Sinninghe Damsté et al.,
2002). Crenarchaeol (Fig. 1.11) was originally considered to be a diagnostic biomarker
(Schouten et al., 2000) for marine Thaumarchaeota (formerly Crenarchaeota Group I;
Brochier-Armanet et al., 2008; Spang et al., 2010; Pester, 2011), however low abundances
of crenarchaeol have also been found in isolates and samples from terrestrial environments
such as soils and peats (Leininger et al., 2006; Weijers et al., 2006b; Walsh et al., 2008), as
well as in hot springs (Pearson et al., 2004; De La Torre et al., 2008; Pitcher et al., 2009),
and rivers (Herfort et al., 2006; Kim et al., 2007), indicating that the producing organisms
are more widespread than initially thought.
26
Chapter 1
Introduction
Figure 1.10. Glycerol dialkyl glycerol tetraether structures, as used for
SST
+
reconstructions. The m/z = [M+H] , i.e. the ion scanned in SIM mode to detect the
compound.
GDGTs, or their degradation products, have been found in hypersaline environments
(Teixidor et al., 1993), anoxic swamp sediments (Pauly and van Fleet, 1986; Pancost et al.,
2000b), and diverse pelagic settings (Hoefs et al., 1997; DeLong et al., 1998; King et al.,
1998; Schouten et al., 1998). Archaeol (Fig. 1.11) has been identified in halophiles,
thermophiles, and methanogens and is the most common of the archaeal diethers (Koga et
al., 1998a, b). The presence of archaeol in sediments is usually associated with the
anaerobic oxidation of methane in active seep settings (Thiel et al., 1999; 2001; Pancost et
al., 2000a, 2001) and has also been identified in settings which exhibit a diffusive methane
flux (Aquilina et al., 2010).
27
Chapter 1
Introduction
Figure 1.11. Structure of 2,3-di-O-phytanyl-sn-glycerol (archaeol).
Branched GDGTs (bGDGTs, Fig. 1.12) were first identified in soils and peat bogs, and
present branched alkyl chains. By analogy with the structures of bacterial lipids, bGDGT
source organisms were postulated to be soil bacteria, but so far their exact provenance has
not been conclusively ascertained (Weijers et al., 2006a,b, 2009).
Figure 1.12. Example branched GDGT structures (as used in the BIT index). The m/z =
[M+H]+, i.e. the ion scanned in SIM mode to detect the compound.
Acidobacteria has been proposed as a likely source (Weijers et al., 2009), and branched
GDGTs were indeed recently identified in two acidobacteria cultures (Sinninghe Damsté et
al., 2011). Marine bacteria do not appear to synthesize branched GDGTs because those
lipids have not been detected or are present only in low abundances in open ocean
sediment samples (Hopmans et al., 2004).
28
Chapter 1
Introduction
The Branched versus Isoprenoidal Ratio (BIT index) describes the ratio between the
branched and the isoprenoid tetraether crenarchaeol (Hopmans et al., 2004):
(1.2)
The BIT index was proposed as a proxy for the relative input of soil organic matter to
coastal marine sediments (Hopmans et al., 2004). Indeed, BIT indices have been shown to
track a plume from the mouth of the Congo River into the open ocean (Hopmans et al.,
2004), the fluvial input of terrestrial matter into the North Sea (Hopmans et al., 2004;
Herfort et al., 2006), as well as storm-flood events in a river dominated continental margin
(Kim et al., 2007, 2009). The BIT index is also increasingly used as a proxy to estimate
modern and ancient changes in terrestrial organic matter (or soil organic matter) input (e.g.
Ménot et al., 2006; Sluijs et al., 2006; Huguet et al. 2007; Donders et al., 2009; Weijers et
al., 2006a)
Recently, however, in situ production of branched GDGTs in marine and lacustrine
sediments has been suggested since core branched GDGTs were found at sites with low
direct run-off or fluvial inputs, and because their distributions did not match those in
nearby soils (Peterse et al., 2009; Sinninghe Damsté et al., 2009; Tierney et al., 2010).
This could complicate the interpretation of BIT indices in marine sediments; in situ
contribution of branched GDGTs would result in anomalously high BIT indices.
1.4.1.3.2. Low Molecular Weight n-alkyl Compounds
Odd-carbon-number n-alkanoic acids can also derive from multiple sources but are
typically attributed to bacteria (Parkes, 1987; Wakeham and Beier, 1991; Harvey, 1994),
with C15 and C17 largely synthesised by marine heterotrophic bacteria known to be
abundant in sediments (Volkman et al., 1980a; 1998). Alternatively, input of diagenetically
altered material can contribute to even-carbon-number n-alkanes and odd-numbered nalkanoic acids (Shimoyama and Johns, 1972; Tissot and Welte, 1984; Meyers and Eadie,
1993; Hedges and Oades, 1997).
29
Chapter 1
Introduction
1.4.1.3.3. Hopanoids
Prokaryotes do not produce sterols. Many (but not all) bacteria instead produce hopanoids
(Fig.
1.13;
Ourisson
et
al.,
1979,
1987;
Ourisson
and
Rohmer,
1982).
Bacteriohopanepolyols (BHPs) are believed to perform the role in cell membrane stability
analogous to that of sterols in eukaryotes (Sahm et al., 1993). BHPs are one of the most
abundant lipid classes in bacteria and the precursors to a wide range of hopanoids in the
sedimentary record, including hopanes, hopanoic acids and hopanones (Fig. 1.13: e.g.
Rohmer et al., 1984; Sahm et al., 1993; Farrimond et al., 2000). Hopanoic acids and
hopanones are generally considered to be early diagenetic products of biohopanoids (Quirk
et al., 1984; Barakat et al., 1990; Buchholz et al., 1993; Innes et al., 1997, 1998; Watson
and Farrimond, 2000). Hopanoids occur in a wide variety of structural and
unfunctionalised forms, which can be diagnostic of precursor organism class (e.g. Talbot
and Farrimond, 2007). They are also synthesised in specific isomeric configurations and
therefore post-depositional isomerisation can yield further insight into sedimentary burial
conditions (e.g. Seifert and Moldowan, 1980; Peters and Moldowan, 1991).
Figure 1.13. Example biohopanoid (bacteriohopanetetrol), with example diagenetic
hopanoid compounds.
30
Chapter 1
Introduction
1.4.2. Biomarker Proxies for Sea Surface Temperature
As described previously, SSTs can be estimated using the
on the
SST proxy, which is based
dependence of the degree of alkenone unsaturation on growth temperature
(Marlowe et al., 1984; Brassell et al., 1986); however, despite the presence of long-chain
unsaturated ketone compounds related to the C37 alkenones in sediments as old as the
Aptian (c. 120 Ma; Farrimond et al., 1986; Brassell et al., 2004), there are no existing
accounts of
reconstructions from sediments older than the Eocene;. i.e., alkenones
appropriate for the reconstruction of SSTs have not yet been discovered in Paleocene
sediments.
In contrast, GDGTs have been used to reconstruct SSTs in more ancient climates,
including the Paleocene (Bijl et al., 2009) and the Cretaceous (Schouten et al., 2003b;
Littler et al., 2011). The degree of cyclisation of GDGTs (e.g. Uda et al., 2001; Schouten
et al., 2002), described by the weighted average number of cyclopentyl moieties within
isoprenoidal GDGT biphytanyl chains, is considered a general measure of relative growth
temperature of archaeal communities producing the compounds (e.g. Shimada et al., 2002,
Schouten et al., 2007, Pearson et al., 2008). This is based on the physiological principle
that the degree of cyclisation of GDGTs increases as a response to growth temperature (De
Rosa et al., 1980; Gliozzi et al., 1983; De Rosa and Gambacorta, 1988; Uda et al., 2001),
initially identified for hyperthermophiles before the ubiquity of pelagic Thaumarchaeota
was recognised (Karner et al., 2001) and the original calibration of isoprenoidal GDGTs to
SST was determined (Schouten et al., 2002). The observation is based on a fundamental
understanding of membrane lipid homeoviscous adaptation (De Rosa et al., 1994, Gabriel
and Chong, 2000): a higher degree of membrane lipid cyclisation creates a higher thermal
transition point for the membrane, consistent with adaption to warmer temperatures (Gliozi
et al., 1983).
1.4.2.1. TEX86: Distributions of GDGTs as a Palaeothermometer.
The original tetraether index of tetraethers containing 86 carbon atoms (TEX86; Schouten et
al., 2002) was based upon the analysis of GDGT distributions in 40 core-top sediments
from 15 global locations. The index was derived to quantitatively express the GDGT
distribution, in order to determine the relationship between changes in the sedimentary
GDGT distributions to SST (Eq. 1.3):
31
Chapter 1
Introduction
=
(1.3)
GDGT-0 and crenarchaeol are excluded from the index for different reasons. Although
GDGT-0 in the core-top sediments analysed does exhibit an inverse relationship with SST
(e.g. Schouten et al., 2002, Kim et al., 2010), it is excluded from the calibration as it is
synthesised not only by the Thaumarchaeota, but also a wide range of other archaea, e.g.
methanogenic archaea (Koga et al., 1993; Schouten et al., 2000; 2002; Blaga et al., 2009)
and thermoacidophilic archaea (Shimada et al., 2002). Crenarchaeol is omitted as it is often
an order of magnitude (at least) more abundant than the other GDGTs in Eq. 1.1 and, as
such, would dominate the index if included. Although subsequent calibrations updated the
relationship of the index to SST, they generally maintained the same index of GDGTs.
Two examples of calibrations of this index to SST which will be presented in this study are
the most recent linear calibration (Eq. 1.4; Kim et al., 2008; n=223):
(1.4)
And a calibration which uses the reciprocal of TEX86 (Eq. 1.5; Liu et al., 2009; n=287):
(1.5)
Eq. 1.4 is associated with a 1.7°C calibration error, whereas Eq. 1.5 has a larger error of
5.4°C. This difference in calibration error is largely due to the exclusion of c. 22 % of the
total data in the calibration of Eq. 1.4; all polar data (and as such all SST < 7°C), the Red
Sea data (due to unusually high abundances of the region isomer GDGT-4’), and any data
which plotted outside a range of 1.5σ from a related regression. Eq. 1.5 was constructed
using the entire data set, and thus exhibits a greater degree of scatter.
32
Chapter 1
Introduction
However, the most recent update to the calibration has suggested two separate indices and
calibrations (Kim et al., 2010). The first index is the logarithmic function of TEX86,
denoted by the authors as GDGT index-2 (Eq. 1.6) and is related to SST by Eq. 1.7:
(1.6)
(1.7)
The second index (GDGT index-1) uses a different ratio of GDGTs (Eq. 1.6) and is related
to SST by Eq. 1.7
(1.8)
(1.9)
The authors refer to Eq. 1.6 as the
calibration, and Eq. 1.8 as the
calibration.
However, for simplicity and to avoid confusion, both index and calibration will be referred
to herein using the
and
nomenclature. GDGT-1 and GDGT-2 will be
reserved for discussing the GDGT structures, and do not relate to GDGT index-1 or GDGT
index-2 of Kim et al. (2010).
The separation of TEX86 into two indices is based on the sample set used;
was
constructed using the entire available coretop calibration dataset, except for those of
sediments from the Red Sea (n=395). This reconstructs SSTs with a calibration error
(inferred to be related to scatter in the dataset) of 4.5°C. As this calibration includes data
from polar and sub-polar locations, the authors term it
, where ‘L’ denotes ‘low’, to
express that it includes calibration to the low temperature polar data. In turn,
denotes
33
Chapter 1
Introduction
“high”, as this calibration excludes polar and sub-polar data (n=255), and as such
essentially calibrates GDGT distributions from sediments located in warmer climates. The
calibration error is reduced to 2.5°C. The plot of SST against the
and
indices
(Fig. 1.14) shows the different relationship of each index to SST throughout the calibration
core-top dataset. Scatter is generally reduced in the samples which exhibit colder (<10°C)
SSTs when plotting
against SST, but
reduces the scatter for samples which
fall in the c. 10°C - 30°C SST range.
It is therefore inferred that
and
should be used when all SSTs are reconstructed <15°C,
should be used if any SSTs within a record are reconstructed >15°C (Kim et al.,
2010). The argument for this methodology is that
and
reconstructed SSTs
within the modern core-top calibration dataset are generally similar above 15°C, but
is associated with a greater calibration error. However,
SSTs more accurately below 15°C. Indeed,
and thus
is argued to reconstruct
is not even calibrated below c. 10°C,
would be extrapolating when reconstructing colder SSTs. It is also
pertinent to note that as
and
are based on different indices, they are not
strictly different ‘calibrations’: rather, they are essentially distinct proxies. The continued
use of the term ‘calibration’ for
and
is however used throughout for
simplicity.
Figure 1.14. (A)
and (B)
plotted as SST against the raw indices (Eq.1.4 and
Eq1.6, respectively). High Latitude denotes >45° latitude.
34
Chapter 1
Introduction
A further point to note is that the basis of the
top
proxy is the assumption that the core-
values are truly defined by SSTs (e.g. Schouten et al., 2002; Kim et al., 2008,
2010). Although the calibrations are derived based on this assumption, there is increasing
evidence that in some settings,
values may reflect thermocline temperatures (e.g.
Lee et al., 2008; Huguet et al., 2007; Lopes dos Santos et al., 2010; Ho et al., 2011),
consistent with the fact that the GDGT-producing thaumarchaeota live throughout the
water column (Karner et al., 2001). As such, sedimentary GDGT distributions will reflect
the depth from which GDGTs were exported. Crucially, the impact of this effect on the
temperature calibration has yet to be explored; however, the fact that tropical
oceans are generally stratified (i.e. with potential GDGT export from the thermocline
rather than the sea surface) and represent the high temperature end of the Kim et al. (2010)
calibration suggests that
could overestimate temperatures at the upper limits of the
calibration. An additional factor to consider is the impact of seasonality. Previous work
has shown that seasonal biases in GDGT export can also affect the temperatures that are
recorded in underlying sediments (Herford 2006; Huguet 2006; Castañeda et al. 2010;
Leider et al. 2010).
Investigation into the effect of redox conditions on preservation of GDGTs (Schouten et
al., 2004) indicated no evidence for preferential degradation of any particular GDGT
across a range of bottom water redox conditions and GDGT accumulation rates. However,
more recent studies revealed evidence for preferential degradation of some GDGTs under
long term oxic conditions. GDGTs were analysed from different sections of turbidites at
the Madeira Abyssal Plain that had experienced different degrees of oxygen exposure
(Huguet et al., 2008, 2009). Differential degradation of GDGTs caused over-estimations,
underestimations, or no change in TEX86 SST reconstructions (Huguet et al., 2008, 2009).
This apparent variability was attributed to the preferential preservation of soil derived
GDGTs, perhaps as a result of matrix protection (Huguet et al., 2008, 2009). As
isoprenoidal GDGTs can also be present in soils as well as branched GDGTs (Weijers et
al., 2006), it is suggested that this mechanism of degradation leads to preferential
expression of terrestrially derived isoprenoidal GDGT distributions over the marine
derived signal. This also leads to an increase in the BIT index, as soil derived branched
GDGTs are preferentially preserved over marine derived crenarchaeol. Caution should
therefore be exercised when interpreting TEX86 values from sediments which have been
exposed (long term) to oxic conditions, particularly when high or increasing BIT indices
are also reconstructed in absence of other evidence for enhanced terrestrial input to the
sediment.
35
Chapter 1
Introduction
1.4.3. Biomarker Specific Isotopes in the Reconstruction of Ancient Carbon Cycling
Biomarker δ13C values facilitate the interrogation of how different organisms are
responding to changes in the carbon cycle, and thus documents changes in different
reservoirs. For example, n-alkanes from plants record changes in δ13C of the atmosphere
(e.g. Arens et al., 2000; Pancost and Boot, 2004; Smith et al., 2007)
Algal lipid δ13C
values reflect the δ13C of the surface waters, thus reflecting the global reservoir but also
changes in algal growth rate, cell size or even [CO2(aq)] and, by extension, pCO2 (Pancost
and Pagani, 2006).
1.4.3.1. Controls on δ13C Values Higher Plant Biomass
The carbon component of most naturally occurring carbon-containing materials contains
about 1.1% 13C and 98.9 % 12C. Carbon isotopic compositions are expressed as ratios, with
the lighter isotope in the denominator, i.e. 13C/12C. The ratio is reported as a δ13C value, in
units of per mil (‰), relative to the Vienna Pee Dee Belemnite (VPDB) standard:
Where R = 13C/12C
(1.10)
Higher plant biomass, including specific biomarkers, is common in marine sediments. Like
those of algal biomass, higher plant δ13C values are governed by the isotopic composition
of substrate carbon, fractionation during carbon assimilation ( ) and environmental
conditions that influence
values (e.g. Hayes, 1993). Plants discriminate against
13
C
during photosynthesis, and the magnitude of this fractionation reflects both the plant’s
metabolism and the growth environment. In addition, higher plant physiology, specifically
the differences between C3, C4 and CAM photosynthetic pathways, exerts an important
control on their carbon isotopic compositions. The majority of extant and fossil vascular
plants are characterized by C3 physiology, and various studies have established that
photosynthetic fixation of atmospheric CO2 by plants is accompanied by significant
discrimination against
13
C (O’ Leary, 1981). The primary cause of photosynthetic carbon
isotope fractionation during C3 plant photosynthesis is the discrimination against
13
C by
RuBisCO during carboxylation of ribulose-1,5-bisphosphate. The majority of higher plant
lipids found in marine or lacustrine sediments are thought to derive from sub-aerial land
36
Chapter 1
Introduction
plants rather than submerged plants. Thus, atmospheric carbon dioxide is their sole carbon
source and controls on the δ13C values of atmospheric CO2 represent a major control on the
carbon isotopic compositions of higher plants. The carbon isotopic composition (δ13C) of
C3 plants is related to that of atmospheric CO2 by the following relationship (Farquhar et
al., 1982):
(1.11)
where δ13Cair is the δ13C value of ambient CO2;
is the ratio of CO2 concentration in
the intercellular space of leaves ( ) to that in the atmosphere (
); a is the fractionation
associated with diffusion of CO2 from the atmosphere into the intercellular space of the
leaves (4.4 ‰) and b is the fractionation of CO2 during carboxylation mediated by
RuBisCO (ca. 30 ‰). Critically, the relationship established by Farquhar et al. (1982)
indicates that if the δ13Cair value increases or the
ratio decreases, the δ13C value of
plant tissues increases. Thus, the important controls on vascular plant δ13C values are the
isotopic composition of the atmosphere (Arens et al., 2000; Beerling and Royer, 2002) and
those environmental and physiological variables that influence
ratios, such as
photosynthetic rate, gas exchange rates and water use efficiency (Condon et al., 1987;
Cowan and Farquhar, 1977; Ehleringer et al., 1993; Ehleringer and Cerling, 1995;
Farquhar and Richards, 1984; Virgona et al., 1990). On geological timescales, variations in
atmospheric CO2 δ13C values are considered to be the most important control on δ13Cplant
(Arens et al., 2000).
On geological time scales, perhaps the most important control on
atmospheric pCO2 (Popp et al., 1989); lower can result in low
13
ratios is the
ratios and higher
13
plant δ C values. However, δ C values of higher plant material are less useful as a pCO2
palaeobarometer than δ13C values of algal-derived organic matter, because the latter
organisms are effectively more carbon-limited (Laws et al., 1995; Bidigare et al., 1997,
1999). In addition, plants apparently utilise a variety of strategies for maintaining constant
ratios (Beerling and Woodward, 1995), decreasing their apparent isotopic
sensitivity to pCO2 change. Other environmental factors can affect the
ratios; e.g.
decreases if stomatal conductance in the plant leaf is reduced, which can occur at
low humidity to minimise loss of water via evapotranspiration (Farquhar et al., 1982;
37
Chapter 1
Introduction
Madhavan et al., 1991). Imposed on these environmental controls, there appears to be
significant ecosystem and interspecies variations in δ13C values among C3 plants
(Chikaraishi and Naraoka, 2003), as well as some degree of intraspecific variation, i.e.
variation between plants of the same species at the same locality (up to 2 ‰) (Bocherens et
al., 1994; Marshall et al., 2008). Furthermore, it has been demonstrated that the
13
C-
depletion in lipids relative to biomass is due to isotopic fractionation during the oxidation
of pyruvate to acetyl coenzyme-A (O’ Leary, 1976; DeNiro and Epstein, 1977; Monson
and Hayes, 1982) Monson and Hayes (1982) also demonstrated that a secondary point for
isotopic fractionation exists in lipid biosynthesis; the hydrolysis of the thioester bond
attaching the acyl chain to the carrier protein during chain elongation allows fatty acids
with
13
C-depleted carboxyl groups to be incorporated more rapidly into complex lipids..
The measurement of leaf lipid (e.g. n-alkyl compound) δ13C can therefore be used to
interrogate ancient δ13C of CO2, and possibly long-term changes over geological time in
pCO2. However, the differences in
between plant types (e.g. Collister et al., 1994), and
the various environmental controls on plant tissue and, by extension, plant lipid
(Bocherens et al., 1994; Chikaraishi and Naraoka, 2003; Gröcke et al., 1999; Gröcke,
2002; Marshall et al., 2008) suggests that caution must be exercised when interpreting
plant lipid carbon isotope records.
1.4.3.2. Controls on δ13C Values of Algal Biomass
The δ13C of algal derived lipids records the
of photoautotrophic algae, i.e. the
magnitude of total carbon isotope discrimination
during photosynthesis (e.g. Arthur et
al., 1988), is a function of the isotope fractionations associated with carbon transport and
fixation. For modern photoautotrophs assimilating CO2(aq) and using diffusional transport
(Popp et al., 1998), there is a negative and linear correlation between [CO2(aq)]-1 and
,
with the slope of that relationship dependant on physiological variables such as cell
geometry and the permeability of the cell membrane (Popp et al., 1998; Riebesell et al.,
2000). As such,
largely reflects pCO2, and the δ13C of algal derived lipids may be used
to determine change in carbon cycling in marine systems. Furthermore, algae are more
sensitive to changes in pCO2 than higher plants, as the former are essentially limited by
diffusion. However, changes in δ13C of algal lipids may also be caused by a change in the
13C value of dissolved inorganic carbon; as such, more reliable reconstruction of
may
be undertaken if the lipid δ13C is compared with contemporaneous marine carbonate δ13C,
which reflects the δ13C of DIC (e.g. Arthur et al., 1988).
38
Chapter 2
Experimental, Instrumental and Statistical
Methods
39
Chapter 2
Experimental, Instrumental and Statistical Methods
2.1. Materials
Detailed site descriptions and age models for the sediments analysed in this study are given
in detail in each chapter. The following is an overview of the sediments processed: 25
samples from the mid-Waipara K/Pg section (Chapters 3 and 4) and 24 samples from midWaipara River Column 2 (Paleocene) were analysed (Chapter 5); these were New Zealand
outcrop sediments collected by GNS (NZ) scientists (Morgans et al., 2005). Chapter 5 also
includes results from the analysis of 44 samples from ODP Site 1121 (Campbell Plateau,
southeast of NZ), and Chapter 6 includes preliminary data from the analysis of 30 samples
from ODP Leg 174X (Bass River Core, New Jersey, USA). Details of sample processing
are outlined below.
2.2. Sample Processing
Prior to extraction, outcrop and borehole sediment samples (Waipara River section and
Bass River section) were gently washed with methanol (MeOH) and scraped to remove
any surface contamination. These sediments were then left to air-dry in a fume hood prior
to crushing. Ocean core sediments (ODP Site 1121) were freeze-dried to remove residual
water. Samples were then crushed, either by hand with a pestle and mortar, or with a
Retsch PM100 Ball Mill, resulting in homogenous fine powdered samples.
2.2.1. Lipid Extraction Procedure: Soxhlet Extraction
Pre-weighed powdered samples were placed in pre-extracted cellulose thimbles and
extracted under reflux using a Soxhlet apparatus for 24 h with dichloromethane/methanol
(DCM/MeOH; 2:1 v/v) as the organic solvent. After extraction, the solvent was removed
from each extract using a rotary evaporator. The resulting total lipid extracts (TLEs) were
transferred to pre-weighed vials (using DCM/MeOH, 2:1 v/v) and dried under a stream of
nitrogen (N2) assisted by gentle heating (40°C). TLEs were either split for archiving or
carried through the remaining procedure in their entirety, depending on extract yields
(yields of ≥100 mg were split by at least 50 %). The extracted residues were air-dried and
archived.
40
Chapter 2
Experimental, Instrumental and Statistical Methods
2.2.2. Total Lipid Extract Fractionation
Solid phase extraction (SPE) was used to separate neutral lipid and acid fractions, followed
by the application of alumina ‘flash’ column chromatography to split the neutral lipid
fractions into apolar and polar fractions.
2.2.2.1. Aminopropyl Column Fractionation
The TLEs were separated into neutral and acid fractions on an aminopropyl (NH2) solid
phase extraction (SPE) column by elution with DCM/iso-propanol (2:1 v/v; neutral
fractions), followed by 2% (by volume) acetic acid in diethyl ether (acid fractions). The
columns used were glass cartridges containing 500 mg of silica-bonded stationary phase,
manufactured by Isolute®. Column preparation involved flushing 4 times with MeOH
followed by 4 washes of DCM/iso-propanol (2:1 v/v). Neutral fractions were collected
using 3 column volumes (c. 18 ml) of solvent into a 20 ml glass vial (neutral fractions),
acid fractions were collected using 4 column volumes (c. 24 ml) of solvent into a 50 ml
round-bottom flask. The solvents were then removed under a gentle stream of N2 (neutral
fractions) or using a rotary evaporator (acid fractions). Neutral fractions were stored in the
glass vials in preparation for further work-up. The acid fractions were transferred to 7 ml
vials using 2 % (by volume) acetic acid in diether, and the solvent was then removed under
N2.
2.2.2.2. Alumina Column Fractionation
The neutral fractions were fractionated further using a short glass pipette column packed
with pre-extracted glass wool and (activated; 110°C) alumina (Al2O3). Fractions were
separated into 8 ml glass vials; apolar fractions were eluted in 3 column volumes (c. 4.5
ml) of hexane/DCM (9:1 v/v), neutral polar fractions were eluted in 4 column volumes (c.
6 ml) of DCM/MeOH (1:2 v/v). Fractions were then dried under N2.
41
Chapter 2
Experimental, Instrumental and Statistical Methods
2.2.3. Preparation of Polar Fractions for Liquid Chromatography – Mass Spectrometry
Analysis
Neutral polar fractions were either split (50 %) and stored for later preparation and analysis
by liquid chromatography mass-spectrometry (LC-MS), or taken through the following
procedures analysed by LC-MS analysis prior to derivatisation and analysis by GC and
GC-MS.
For liquid chromatography-mass spectrometry (LC-MS) analysis of glycerol dialkyl
glycerol tetraethers (GDGTs), neutral polar fractions were dissolved in c. 2 ml of
hexane/iso-propanol (99:1 v/v) and filtered through 0.45 μm Polytetrafluoroethylene
(PTFE) filters into 3 ml glass vials. The filtered neutral polar fractions were then dried
under N2 for storage. For analysis, fractions were transferred to 2.5 ml LC-MS vials
equipped with 300 μl inserts by dissolving in 150 – 200 μl of hexane/iso-propanol (99:1
v/v).
2.2.4. Derivatisation
Figure 2.1 Derivatisation reaction schemes for (A) silylation of hydroxyl function groups
with BSFTA and pyridine, and (B) methylation of carboxylic acids using BF3/MeOH.
42
Chapter 2
Experimental, Instrumental and Statistical Methods
Acid fractions were methylated using BF3/MeOH complex (14% w/v; 100 μl; 60°C for 30
min; Fig. 2.1). After cooling to room temperature, ca. 1 ml of double-distilled water
(DDW) was added, before extracting the sample with ca. 2 ml of DCM. The extracts were
passed through a short glass pipette column packed with pre-extracted glass wool and
sodium sulphate (Na2SO4) (to remove residual water) and collected in a 7 ml glass vial.
A further two repeat extractions were performed on each fraction (eluted into the same
vial), resulting in a combined extract of c. 6 ml per sample. The extracts were then dried
under N2.
Neutral polar and methylated acid fractions were then silylated with N,O-bis(
trimethylsilyl)trifluoroacetamide (BSTFA) and pyridine acting as a Lewis acid catalyst (30
μl BSTFA and 30 μl pyridine; 70°C for 1 h; Fig. 2.1). Excess BSTFA and pyridine were
removed under N2.
2.3. Analytical techniques
2.3.1. Elemental Analysis
Total carbon analyses were carried out on a Carlo Erba EA1108 Elemental Analyser.
Sediment samples were weighed into tin capsules and introduced into the combustion
furnace at 1020°C. The furnace was flushed with O2 and the sample combusted at c.
1800°C. Combustion products passed over chromium oxide and silvered cobalt oxide
catalysts and the resultant gasses, CO2, H2O and nitrogen oxides, introduced into a coppercontaining tube to reduce the nitrogen oxides to N2. Gasses were separated using a Porpac
Q column and their percentage composition determined with a thermal conductivity
detector. Inorganic carbon determination was carried out on a Modified Coulomat 702
analyser equipped with a coulometric cell. CO2 was generated via heating in orthophosphoric acid in order to selectively liberate inorganic carbon. Total organic carbon
(TOC) contents were determined by difference between total carbon and total inorganic
carbon.
43
Chapter 2
Experimental, Instrumental and Statistical Methods
2.3.2. Gas Chromatography
Gas chromatography (GC) analyses were performed on a CarloErba or Hewlett Packard
(HP) 5890 gas chromatograph equipped with a flame ionisation detector (FID) and fitted
with a Chrompack fused silica capillary column (50 m x 0.32 mm i.d.) coated with a CP
Sil-5CB stationary phase (100% dimethylpolysiloxane equivalent, 0.12 μm film thickness).
H2 gas was used as the mobile phase and ca. 1 μl of sample was injected at 70°C using an
on-column injector. The temperature was then increased to 130°C with an initial ramp of
20°C min-1, then to 300°C at 4°C min-1, followed by an isothermal hold for 20 min.
2.3.3. Gas Chromatography-Mass Spectrometry
Gas chromatography/mass spectrometry (GC-MS) analysis was performed on a
Thermoquest Finnigan Trace GC interfaced with a Thermoquest Finnigan Trace MS
operating with an electron ionisation source at 70 eV and scanning over m/z ranges of 50 to
850 Daltons. The GC was fitted with a Zebron™ fused silica capillary column (50 m x
0.32 mm i.d.) coated with a ZB1 stationary phase (100% dimethylpolysiloxane equivalent,
0.12 μm film thickness). The interface was set to 300 °C and the ion source at 200°C. GC
conditions were as for GC analysis, except that He was the carrier gas.
2.3.4. Gas Chromatography-Combustion-Isotope Ratio Mass Spectrometry
Gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) was
conducted using a Hewlett Packard 6890 gas chromatograph connected to a Thermoquest
Finnigan Delta plus XL spectrometer, via a GC III combustion interface (comprising Cu,
Pt and Ni wires within a fused alumina reactor at a constant temperature of 940°C). GC
conditions were as for GC and GC–MS. Duplicate or triplicate analyses were conducted
for each sample, with values are reported in standard delta (‰) notation relative to Vienna
Pee Dee Bee Belemnite (VPDB). Analytical precision, based on replicate analysis of a
standard of mixed fatty acid methyl esters (FAMEs) are < ±0.5‰. For derivatised samples,
standard mass balance correction procedures were used (Jones et al., 1991).
44
Chapter 2
Experimental, Instrumental and Statistical Methods
2.3.5. Liquid Chromatography-Mass Spectrometry
High performance liquid chromatography/atmospheric pressure chemical ionisation – mass
spectrometry (HPLC/APCI-MS) was used for the analysis of GDGTs. Analysis was
conducted on filtered neutral polar fractions using a Thermo Scientific TSQ Quantum
Access equipped with Accela Autosampler, Accela Pump and Xcalibur software.
Separation was achieved with an Alltech Prevail Cyano column (150 mm x 2.1 mm; 3 μm
stationary phase thickness), and injection volumes varied from 10 to 20 µl in partial loopno waste injection setting, or 25 µl in full loop injection setting. GDGTs were eluted
isocratically with 99% A and 1% B v/v for 7 min, then a linear gradient to 1.6% v/v B in
43 min, where A = hexane and B = iso-propanol. Flow rate was 0.2 ml min-1. Detection
was achieved using atmospheric pressure positive ion chemical ionization mass
spectrometry (APCI-MS) analysis of the eluent. Conditions were: corona discharge current
4 µA, vaporiser temperature 355°C, capillary temperature 280°C and sheath gas 0.15 L
min-1. Ion detection was performed in selected ion monitoring (SIM) mode. The m/z values
selected relate to the [M+H]+ (protonated molecular ion) of the isoprenoidal and branched
GDGT analytes:
Table 2.1. [M+H]+ m/z of isoprenoidal and branched GDGTs analysed for by
HPLC/APCI-MS in SIM mode. GDGT structures are given in Appendix 1.
[M+H]+ m/z
GDGT structure
1302
1300
1298
1296
1292
1022
1020
1018
1036
1034
1032
1050
1048
1046
GDGT-0
GDGT-1
GDGT-2
GDGT-3
Crenarchaeol and GDGT-4’
bGDGT-1
bGDGT-1b
bGDGT-1c
bGDGT-2
bGDGT-2b
bGDGT-2c
bGDGT-3
bGDGT-3b
bGDGT-3c
45
Chapter 2
Experimental, Instrumental and Statistical Methods
2.4. Quantification
2.4.1. GC and GC-MS Internal standards
Known quantities (typically c. 2 μg) of 5α-androstane and hexadecan-2-ol (Fig. 2.2) were
added to the TLEs prior to separation over the aminopropyl SPE columns. Following the
aminopropyl SPE and alumina flash column chromatography, 5α-androstane and
hexadecan-2-ol are eluted in the apolar and neutral polar fractions, respectively. Known
quantities (typically c. 2 μg) of normal nonadecane (n-C19) (Fig. 2.2) were added to the
methylated acid fractions following aminopropyl column fractionation and prior to
derivatisation.
Figure 2.2. Internal standards used for quantification of biomarkers analysed by GC and
GC-MS. (A) 5α-androstane (eluting in the apolar fraction), (B) hexadecan-2-ol (eluting in
the neutral polar fraction) and (C) n-nonadecane (added to the acid fraction prior to
methylation).
Concentrations of analytes are semi-quantitatively determined using internal standards;
analyte peak areas are integrated from either total ion current (TIC) chromatograms, or
partial mass chromatograms of a known characteristic fragment ion, and related to the peak
area of a known amount of internal standard:
(2.1)
46
Chapter 2
Where
Experimental, Instrumental and Statistical Methods
is the peak area of the analyte as integrated on its respective mass
chromatogram or TIC,
is the peak area of the internal standard integrated on the TIC,
is the known mass of internal standard added, and
is the calculated mass of
analyte GDGT. However, full (accurate) quantification was not performed in this thesis, as
the response factor (RF) of standards to analytes was not determined. Ideally,
quantification of GC-amenable compounds would be performed on GC-FID for the
purpose of quantification, as RF between similar compounds are likely to be less variable
than analogous analysis using GC-MS; however, many compounds required the use of
mass chromatography to accurately integrate the peak due to low concentrations or coelution with other compounds.
2.4.2. Glycerol Dialkyl Glycerol Tetraether Internal Standard
Concentrations of individual GDGTs were semi-quantitatively determined in some
samples using a GDGT46 internal standard (Fig. 2.3; Huguet et al., 2006b); GDGTs were
quantified by integrating peaks from [M+H]+ mass chromatograms and relating to a known
amount of GDGT46 integrated on the m/z 744 trace. Full quantification was not possible as
the response factor of GDGT46 to crenarchaeol could not be determined, due to
unavailability of crenarchaeol standard. Standard was added prior to filtration, after SPE
extraction and flash column chromatography.
Figure 2.3. Structure of C46 GDGT internal standard.
47
Chapter 2
Experimental, Instrumental and Statistical Methods
2.4.3. Compound Identification
The identification of compounds were made based on comparisons with literature spectra,
known mass fragmentations and comparisons of relative retention times with known
compounds.
2.5. Errors and Statistical Treatments
2.5.1. Overview of Types of Data
Wherever possible, an estimation of the error in determining a parameter has been
calculated based on replicate analyses. Types of data presented in this thesis are :

Quantification of GC amenable analytes, based on the comparison of analyte peak
area with peak area of a known amount of internal standard, integrated on GC-MS.

Ratios of GC amenable analytes, to give relative proportion of one analyte (or
group of analytes) in comparison with another.

Quantification of GDGTs, based on comparison of GDGT peak areas with peak
area of a known amount of C46 GDGT internal standard, integrated on LC-MS
APCI mass chromatograms.

Ratios of GDGTs, e.g. raw TEX86 indices, ratios of certain GDGTs against others
to interrogate distributions; based on ratios of [M+H]+ ion peak areas integrated on
LC-MS APCI.

TEX86 sea surface temperature (SST) estimates, based on the ratio of GDGTs
determined on LC-MS APCI, converted to SST using a calibration of known
calibration error.

Compound specific carbon isotope ratio measurements; carbon isotopic
composition of analyte is measured relative to a gas standard of known carbon
isotopic composition, and expressed relative to VPDB.
48
Chapter 2
Experimental, Instrumental and Statistical Methods
2.5.2. Estimation of Precision: Error Handling
Where one or more replicate analysis is available, the measurement error is estimated by
calculating the standard deviation :
SD =
(2.2)
Where SD = standard deviation,
= each value in the population,
= mean of the values,
N = number of values.
The ‘pooled standard deviation’ or ‘pooled variance’ is a method which may be used to
estimate variance given several different samples or sets measurements which have
associated standard deviations, where the mean may vary between samples but the true
variance (equivalently, precision) is assumed to remain the same. For example, when
calculating the mean weighted average δ13C value of a group of n-alkanoic acids, e.g. C16
and C18, the δ13C measurement of the of each n-alkanoic acid is associated with a standard
deviation, based on a group of replicate analysis. The mean δ13C value of each compound
may be different, thus grouping all the raw data (δ13C values of C16 and C18 in each
replicate) and treating them as equivalent may over-estimate the variability (precision) in
measurement of δ13C. Pooled standard deviation gives an estimate on the precision of the
overall measurement, based on the standard deviations associated with each group of
replicates.
Pooled SD =
Where
= number of replicates in the ith group of measurements,
(2.3)
= standard
deviation of ith group of measurement. Group of measurement is e.g. replicates of
measurement of C16 n-alkanoic acid.
49
Chapter 2
Experimental, Instrumental and Statistical Methods
Pooled standard deviation will be reported as a measure of variance in the calculation of
weighted mean average δ13C values for groups of compounds. The measurement can also
be used to estimate the precision of a given method, if pooling all data generated; e.g., to
calculate the measurement error in estimation of sea surface temperature (SST) using
TEX86, standard deviations from all TEX86-derived SST estimates based on replicate
analyses can be pooled to estimate the precision of the measurement. Table 2.2. is a
synthesis of pooled standard deviations for many of the types of measurement used
throughout the thesis, based on the data generated (Raw data and statistical treatments for
all data sets are available in Appendices II – V).
Note that the pooled standard deviation in TEX86 values (Table 2.2) represents the
precision in measurement of raw GDGT ratios, whilst SST estimation is essentially the
measurement error in calculation of those ratios translated to an error in SST estimation, in
addition to any given calibration errors. Overall, measurement of GDGT ratios ranges from
c. ±2 – 5 % error, precision of TEX86-derived SST estimates is c. ±0.7 – 1.2 °C, and δ13C
measurements are precise to within c. ± 1.0 ‰. Precision of GDGT quantification is c. 8
%; although not calculated her, precision of quantification of GC-MS amenable
compounds is also c. 10%, based on replicate analysis of standards.
Calibration errors may be propagated with the measurement errors, using the ‘root of the
sum of squares’ method:
σ=
Where σ = propagated error,
(2.4)
= calibration error,
= measurement error (standard
deviation of replicate analyses).
50
Chapter 2
Experimental, Instrumental and Statistical Methods
Table 2.2. Pooled standard deviations (SD) for types of data generated. Dataset 1 = midWaipara K/Pg boundary (Appendix III) , 2 = mid-Waipara Column 2 (Appendix, IV) 3 =
Bass River Paleocene (Appendix II), 4 = ODP Site 1121 (Appendix V) Paleocene. n = total
number of replicate analyses forming each dataset.
TEX86 / TEX86H
244
166
782.27
Pooled
SD
2.17
TEX86L
244
166
2438.66
3.83
Kim et al., 2008
245
166
73.65
0.67
°C
Liu et al., 2009
245
166
209.59
1.12
°C
245
245
166
166
82.10
76.28
0.70
0.68
°C
°C
GDGT quantification (LC-MS)
342
167
10026.94
7.75
%
BIT Index
69
43
0.008
0.014
dimensionless
(Ratio)
n-alkanoic acids
1035
530
503.57
0.97
‰
1,2
Hopanoic acids
124
65
88.0
1.16
‰
2
n
TEX86
values
SST
estimation
δ13C
analysis
Kim et al., 2010 :
Kim et al., 2010 :
TEX86H
TEX86L
∑ (n-1) ∑(n-1)*SD2
Units
Datasets
%
1,2,3,4
1,2,3,4
1
1
In order to correctly estimate errors in TEX86-derived SST reconstructions, the
measurement error in raw TEX86 value is added and subtracted from the mean to produce
an upper and lower estimate (e.g. Appendix III.l.), and SST estimates calculated from those
estimates. The difference between the mean SST estimate and the upper/lower SST
estimates is then taken, producing an upper and lower expression of the measurement
error. This is necessary because three of the SST calibrations utilised in this study (those of
Liu et al., (2009) and Kim et al., (2010)) are non-linear; i.e. a constant error in TEX86
value will reconstruct as a slightly different error in SST, depending on whether it is
representing an upper or lower limit (as the shape of the calibration curve changes
depending on direction). The upper and lower SST errors may then be propagated with the
calibration error (equivalent in either direction) to produce an estimate of precision in SST
reconstruction (e.g. Appendix III.m).
2.5.3. Statistical Cluster Analysis of Compound Distributions
Where cluster analysis was utilised to produce a dendrite cluster tree, agglomerative
hierarchal cluster analysis of compound distributions was performed using PAST
(PAleontological STatistics) version 2.08© software (Hammer et al., 2001). Ward's
minimum variance method (Ward, 1963) was applied using Euclidean distances.
51
Chapter 3
Terrestrial and Marine Climate across the
Cretaceous/Paleogene Boundary at midWaipara River, New Zealand
52
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
3.1. Introduction
The extent of mass extinction and ecological perturbation at the Cretaceous/Paleogene
(K/Pg) boundary has been extensively studied and is generally attributed to a bolide impact
(Alvarez et al., 1980; Shulte et al., 2010a), although debate regarding the cause(s) of the
perturbation persists (Archibald et al., 2010; Courtillot and Fluteau, 2010; Keller et al.,
2010; Schulte et al., 2010b). The climate preceding and especially following the K/Pg
boundary has also been the subject of much scrutiny, in order to understand the context of
the global extinction and its longer-term consequences on the Earth system.
Previous workers have described an episode of climatic warming preceding the event at c.
66.0–65.6 Ma (Stott & Kennett 1990; Barrera & Savin 1999; Abramovich and Keller 2002;
Adatte et al., 2002a; Wilf et al., 2003) that may have been associated with a marked
increase in pCO2 (Nordt et al., 2002). Increased CO2 is suggested to have been the result
of outgassing during the main episode of Deccan Traps volcanism at 66–65 Ma (Barrera
and Savin 1999; Adatte et al,. 2002a; Wilf et al., 2003). In contrast, rapid cooling is
inferred in the last 0.1 My of the Cretaceous (Stott & Kennett 1990; Srivastava, 1994;
Frank and Arthur, 1999; Keller, 2001; Abramovich and Keller 2002; Adatte et al., 2002a;
Nordt et al., 2003; Wilf et al., 2003; Thibault and Gardin, 2007). Such trends have been
reconstructed from the oxygen isotopic composition of foraminiferal calcite from sites
such as ODP Sites 689 and 690, on the east side of the Weddell Sea (Stott and Kennett et
al., 1988).
None of these climatic trends have been clearly identified in New Zealand sections.
Sporadic occurrences of low latitude foraminifera (Rosita contusa, Pseudotextularia
elegans, and Globotruncanella spp.), the only such records from New Zealand, in the
uppermost Cretaceous at Flaxbourne River (Strong, 2000) could be a local expression of
late Maastrichtian warming (Olsson et al., 2001; Abramovich and Keller 2002). However,
there is no evidence for a latest Cretaceous cooling episode in the Marlborough K/Pg
boundary sections. Indeed, the thin marl bed that underlies the K/Pg boundary at
Flaxbourne River is thought to represent warmer oceanic conditions than underlying
limestone beds (Hollis et al., 2003a).
Numerical models simulating the effects of the K/Pg boundary impact predict a brief (10 –
2000 years) period of global cooling induced by the sulphate aerosols blocking the sun –
the so-called ‘impact winter’ (Siggurdsson et al., 1992; Pope et al., 1997; Pierasso et al.,
2003) – followed by a period of more gradual warming caused by CO2 released by the
53
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
impact (Kring, 2007). Hollis (2003) inferred significant cooling in the early Paleocene
based on siliceous microfossil and geochemical records in NZ K/Pg boundary sections. He
suggested that an abrupt “impact winter” would be consistent with the marine plankton and
terrestrial vegetation survivorship pattern described for New Zealand – extinctions or local
disappearances of thermophilic taxa. Similarly, benthic planktonic and dinoflagellate
records at El Kef testify to the expansion of the Boreal (north Atlantic) province into the
western Tethys following the K/Pg, indicating a profound cooling lasting only c. 2 ky
(Galleoti et al., 2004). Similar dinoflagellate migrations reflecting transient cooling are
recorded in Spain and Denmark (Brinhuis et al., 1998). Fossil leaf morphology (Wolfe,
1991) and survivorship patters (Wolfe and Upchurch, 1987) provide evidence for freezing
conditions in the immediate aftermath of the K/Pg in the western interior of North
America. Together, the geographic range of these lines of evidence suggests a globally
pervasive cooling.
However, palaeotemperature determinations from δ18O values across the K/Pg boundary
transition itself and into the early Danian are hampered by poor preservation, CaCO3
dissolution, low sampling resolution and extinction of planktic calcifying organisms at the
K/Pg (Zachos and Arthur, 1986; Keller and Benjamini, 1991; Magaritz et al.,1993). As
such, many existing records are based on bulk carbonate isotope analysis (e.g. Margolis,
1987; Perch-Nielsen, 1982; Smit 1990; Kroon et al., 2007), use mixed species assemblages
across the K/Pg (e.g. Douglas and Savin, 1971 ), or different species before and after the
K/Pg (e.g. Boersma and Shakleton, 1981). The value of bulk carbonate δ18O records is
limited because variations in the relative amounts of different components with different
isotopic compositions may to a large extent determine the measured isotopic trends (Paull
and Thierstein, 1987). Moreover, if only whole-rock data are considered, it is very difficult
to assess to what degree isotopic signals are original or diagenetically modified.
Combining data from different species can be problematic due to the possibility of
different interspecies offsets of precipitated calcite δ18O values from equilibrium (Urey et
al., 1951; Wefer and Bergen, 1991; Rohling and Cooke, 2002; Erez, 2003; Katz et al.,
2003). Large ranges of apparent vital effects are even found in monospecific assemblages
(Kozdon et al., 2009). The possibility of early Danian planktonic foraminifera occupying a
deeper habitat is also cited as a possible factor affecting SST reconstructions based on
these organisms (Boersma and Shakleton, 1979). However, attempts to reconstruct post
K/Pg climate have been made, with often conflicting and widely ranging results; sea
surface and/or deep sea cooling (Boersma and Shackleton, 1977; 1979; Boersma and
Shackleton, 1981; Keller and Lindinger, 1989) and warming (Douglas and Savin, 1971;
54
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
Oberhänsli, 1986; Barrera and Keller, 1990; Smit, 1990; Stott and Kennett, 1990; Schmitz
et al., 1992; Barrera and Keller, 1994) of varying degrees have all been inferred. Indeed, it
has also been suggested that no discernable significant change occurred (Zachos and
Arthur, 1986). Disagreement with regards to the direction (warming or cooling) of climate
change is documented in sediments from the same ocean basins (Zachos et al., 1986), and
even between relatively proximal sites (Boersma and Shackleton, 1977; 1979).
Palaeotemperature determinations from high-latitude stable oxygen isotopes (Stott and
Kennett, 1990; Barrera and Keller, 1994) and North Dakota leaf fossil assemblages (Wilf
et al., 2003) indicate that, apart from c. 2°C warming directly above the K/Pg boundary,
cool climatic conditions prevailed for the first 1 My of the Paleocene. Cool climatic
conditions for the early Paleocene are also inferred from low-resolution studies of
Antarctic plant fossils and sediments (Francis, 1991; Askin, 1992; Dingle and Lavelle,
1998) and New Zealand fossil leaf physiognomy (Kennedy, 2003). Despite evidence for
cooling, some records indicate that significant transitory warming occurred in the earliest
Paleocene (Stott and Kennett, 1990; Brinkhuis et al., 1998; Wilf et al., 2003), which could
be related to post-impact greenhouse conditions (O’Keefe and Ahrens, 1989; Pope et al.,
1997). Greenhouse-warming has been suggested as the reason for a short-lived (c. 100 000
y) post-K/Pg proliferation of planktic foraminifera in earliest Paleocene in New Zealand
(Hollis, 2003). Following this, trends in biogenic silica and barium across several K/Pg
boundary sites in New Zealand indicate high biological productivity within cool marine
conditions in the early Danian (Hollis, 2003; Hollis et al., 2003a,b).
A global understanding of the K/Pg boundary events requires the reconstruction of climate,
environment and ecology across a wide variety of locations. However, K/Pg boundary
sections are rare in Southern high latitude settings (Nøhr-Hansen and Dam, 1997). New
Zealand contains the only South Pacific records of the K/Pg, representing a well defined
event stratigraphy across an environmental transect (Strong, 1984; Brooks et al., 1986a,b;
Hollis 1993, 1997; Strong et al., 1995; Vajda et al., 2001; Hollis and Strong, 2003; Hollis
et al., 2003a,b; Vajda and Raine, 2003; Morgans et al., 2005; Willumsen 2000, 2002,
2006, 2011). Of the New Zealand sections, the mid-Waipara River section is the most
complete known record from a neritic setting (Strong, 1984, Brooks et al., 1986b, Hollis
and Strong, 2003; Morgans et al., 2005), providing a crucial link between bathyal marine
and terrestrial records. The section contains abundant and diverse palynomorphs, including
dinoflagellate cysts (Willumsen 2000; 2006) and terrestrial miospores (Vajda et al., 2001;
Vajda and Raine, 2003), which provide qualitative indications of local and regional
climate. The section also contains significant occurrences of biostratigraphically important
55
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
foraminiferal, calcareous nannofossil, and radiolarian species. However, calcareous
foraminifera are scarce or poorly preserved, precluding the reliable reconstruction of sea
surface temperature (SST) or deep sea temperature (DST) based on the δ18O values or
Mg/Ca ratios of biogenic calcite (Hollis, 2003; Hollis and Strong, 2003).
This study, therefore, aims to reconstruct SSTs across the mid-Waipara K/Pg boundary
using organic geochemical biomarker-based approaches. In contrast to the poor
preservation of inorganic geochemical records, the presence of sufficiently abundant and
thermally immature organic carbon makes the mid-Waipara River site ideal for organic
geochemical analysis. Here, GDGT distributions, including TEX86 values, have been
determined for 25 sediments spanning the mid-Waipara Cretaceous–Paleocene succession.
These GDGT distributions are critically evaluated in order to examine the response of the
Thaumarchaeota community. Modern field-based investigations have shown that the
relative distribution of isoprenoidal GDGTs produced by pelagic Thaumarchaeota
(formerly Crenarchaeota Group I; Brochier-Armanet et al., 2008; Spang et al., 2010;
Pester, 2011) correlate to these organisms’ growth temperature, forming the basis of the
TEX86 SST proxy (Schouten et al., 2002; Kim et al., 2008, 2010; Liu et al., 2009). SST
records are evaluated in the context of existing corresponding palynological and
geochemical data to elucidate the climate succession before and after the K/Pg boundary.
In particular, TEX86 will be employed to establish whether the climate trends inferred for
the latest Maastrichtian are recorded at New Zealand. Secondly, the post-K/Pg climatic
conditions will be determined which, as discussed, remain widely debated. Lastly, the
longer-term climate post-K/Pg will be investigated to determine the recovery of the climate
system following the K/Pg boundary event, and will ultimately establish a global context
for the Southern Ocean K/Pg climate record, based on comparison with other globally
distributed terrestrial and marine palaeoclimate records.
56
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
3.2. Site Description and Stratigraphy
A large number of paleontological and biostratigraphic collections have been made from
the mid-Waipara River section, located in North Canterbury, New Zealand (Fig. 3.1) by
Institute of Geological and Nuclear Sciences (GNS) scientists in order to facilitate study of
the Cenozoic succession (Morgans et al., 2005).
Figure 3.1. Geographical locations of the mid-Waipara River Section, New Zealand. (A)
Present day site location. (B) Site location juxtaposed on New Zealand palinspastic
reconstruction for K/Pg boundary (after King et al., 1999).
The geology of the Waipara area was first mapped and described by Wilson (1963), and
later reviewed by Field et al. (1989). The Waipara River, north Canterbury, trends
northwest-southeast through a Mesozoic – Cenozoic sedimentary succession. The midWaipara River section incorporates the area downstream from Doctors Gorge (Ohuriawa
Gorge, grid reference NZMS topomap 260-M34/7530 9470) to the top of the Amuri Group
in the ‘Lower Gorge’ (grid reference NZMS topomap 260-M34/789-944; Fig. 3.2). Grid
references relate to NZMS topomap series 260-M34 (NZMS 260, M34, 1:50000; Morgans
et al., 2005). Structurally, the mid-Waipara River section lies on the southeastern flank of
the Doctors Anticline (Wilson, 1963) and the lowest beds comprise the Torlesse
Supergroup (Jurassic-Early Cretaceous). The mid-Waipara River K/Pg boundary section is
located between Doctors Gorge and the Canterbury Plains (M34/7605 9402; 172° 34’ 56”
E, 43° 3’ 44” S), along the middle course of the Waipara River (Fig. 3.2).
57
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
In order to review the K/Pg boundary at mid-Waipara, a total of 187 selected samples from
New Zealand Geological Survey (NZGS) and GNS collections made prior to 2003 were
compiled into an integrated collection by C. J. Hollis of GNS (Morgans et al., 2005). Of
this compilation, new geochemical results for 25 samples will be presented in this chapter.
Figure 3.2. Location of the K/Pg boundary at the mid-Waipara River section (Adapted
from Vajda and Raine, 2003). Also indicated in grey is Column 2 (Morgans et al., 2005)
containing Paleocene material, as discussed in Chapter 5. Scaling according to NZMS
topomap series 260-M34.
The K/Pg boundary is located at the base of a 4-m thick, largely non-calcareous,
glauconitic sandstone, which forms the uppermost unit of the Conway Formation (Fig.
3.3). The underlying Conway Formation is a more mud-rich and calcareous glauconitic
sandstone. The boundary itself is an irregular c. 5-cm thick, ‘rusty’ iron-stained weathered
interval which stands out from the background sandstone on weathered surfaces but is very
difficult to trace on fresh surfaces. The base of this interval provides the stratigraphic
position of the K/Pg boundary, herein given as 0 cm (Fig. 3.3). The irregularity appears
due to intense bioturbation both above and below the boundary.
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Figure 3.3. (A) Lithology, sample locations, biozonation and (B) age model of the midWaipara river K/Pg boundary sequence, as provided by C. J. Hollis of GNS (NZ). The age
model (plotted on same depth scale as (A)) is based on identification of key age diagnostic
taxa. Green triangles represent the stratigraphically lowest estimate of the biostratigraphic
age datum, blue squares represent the upper estimate in terms of depth. The red line
indicates the best estimate of age (Ma) with stratigraphic depth (m), and thus sedimentation
rate (given in m My-1). The K/Pg boundary is indicated herein by a dashed line at 0 m
coinciding with the first rusty weathered horizon. The second rusty horizon at c. 25 cm
indicates a probable unconformity and associated haitus; this is represented by the zigzag
line.
The Conway Formation is conformably overlain by the Loburn Mudstone, which is
actually a glauconitic siltstone at this locality. These sediments were deposited in neritic
inner to mid-shelf palaeoenvironments. Geochemical studies of the K/Pg boundary interval
(Brooks et al., 1986a,b) have shown that the K/Pg boundary is defined by a single spike of
Ir (0.49 ng g-1 or c. x50 crustal average) within the rusty zone, and more variable
concentrations of other elements (Ni, Cr, Zn, Co, and Fe) associated with the K/Pg
boundary geochemical anomaly worldwide (Alvarez et al., 1980; Strong et al., 1987;
Gilmour & Anders 1989). Multiple peaks close to the boundary of Ni, Zn, Cr, and Co are
probably due to the intense bioturbation noted above (Brooks et al.,1986b, Hollis et al.,
2005).
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The Ir anomaly therefore marks the stratigraphic position of the K/Pg boundary. The K/Pg
boundary also coincides with a marked decrease in CaCO3 concentration (Brooks et al.,
1986b). However, in contrast to the sudden decrease of CaCO3 recorded at the K/Pg
boundary in Marlborough (NZ) sections (Brooks et al. 1986b; Strong et al., 1987; Hollis et
al., 2003), carbonate concentration begins to decrease c. 0.3 m below the boundary at midWaipara. This is likely to be an artefact of post-depositional leaching in this section rather
than indicating a decline in carbonate accumulation in the latest Cretaceous; iron staining
suggests that the boundary surface is a conduit for ground water (Hollis et al., 2005). A
second rusty zone is apparent c. 25 cm above the K/Pg boundary (Fig. 3.3), and may
represent an unconformity marking a hiatus in sedimentation.
3.2.1. Palynology
The terrestrial palynology has been studied in detail for the mid-Waipara River section
(Vajda and Raine, 2003). Miospores are abundant in the lower part of the section (from -2
m to 8 m) but decline in abundance from around 8 m above the K/Pg boundary where
dinoflagellates instead dominate the palynological assemblage. Three successive terrestrial
palynological assemblages are distinguishable, based on average percentages of groups and
individual taxa. Gymnosperm pollen and fern spores constitute the dominant miospore
groups during the late Maastrichtian (-6.88 m to 0 m), with Gymnosperm pollen grains
comprising an average of 45% of the total palynoflora and ferns comprising c. 40%. The
K/Pg boundary coincides with an abrupt increase in fern spores, from an average of 40% to
>70% in the overlying c. 25 cm, a so-called “fern spike” (Vajda et al., 2001; Vajda and
Raine, 2003). The proliferation of ferns is initially driven largely by an increase in spores
of Gleicheniaceae (interpreted as deriving from ground ferns) from an average of 9%
below the boundary to 29% in the earliest Paleocene. Abundance of angiosperm pollen
drops abruptly at the boundary, and averages only 4.5% of the total pollen abundance in
the overlying c. 25cm. Gymnosperms also decrease in abundance, representing around
20% of the assemblage in the lower 25 cm of Danian strata. The assemblage above c. 25
cm is characterised by a shift from fern spore dominance (>65% fern spores) to a more
cosmopolitan assemblage dominated by gymnosperms (<60% gymnosperm pollen,
including podocarps and Phyllocladidites mawsonii). However, this transition occurs
between two samples (at 18 cm and 28 cm) and may be truncated by the possible hiatus at
c. 25 cm.
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Detailed marine palynology for mid-Waipara has been published by Willumsen (2000,
2006). Sediments below the K/Pg boundary (-2 m to 0 m) are characterised by the
occurrence of Manumiella druggii, correlating to the regional Manumiella druggii
dinoflagellate zone and indicating a Maastrichtian age (Wilson, 1987; 1988, Wilson et al.,
1989, Willumsen et al., 2006). Sporadic occurrences of Palynodinium minus in a sample 3
cm below the K/Pg boundary, and low abundances of Danian index species Trithyrodinium
evittii in samples at 3 cm and 13 cm below the K/Pg, are interpreted as reflecting
downward displacement due to the intense bioturbation discussed above.
Danian strata are characterised by a succession of dinoflagellate acmes; sediments from
immediately above the K/Pg boundary (0 to 32.5 cm) are dominated by Trithyrodinium
evittii, representing up to 38% of the assemblage. This acme is followed by an acme of
Palaeoperidinium pyrophorum, dominating the assemblage with abundances of up to 85%
from 42.5 cm to 2.25 m, before a second acme of T. evittii invades at 2.65 m (up to 76% of
assemblage). This palynological succession (i.e. initial dominance of T. evittii succeeded
by an interval with abundant P. pyrophorum, followed by an acme interval of T. evittii) has
been observed in several other New Zealand sections and is a characteristic feature of the
early Danian dinoflagellate cyst assemblages of the region (Wilson, 1987, 1988; Wilson et
al., 1989, Willumsen 2006; 2011).
3.2.2. Age Model
Correlation of New Zealand Stages with Global epochs and microfossil zones are based on
the stratigraphic ranges of key taxa of foraminifera, calcareous nannofossils, dinocysts and
radiolarians. The New Zealand Paleogene timescale of Cooper (2004) is correlated to the
Geological Time Scale 2004 (GTS2004; Gradstein et al., 2004) and that timescale is used
throughout this Chapter. Elucidating the age control for the mid-Waipara K/Pg boundary
section is problematic due to a lack of age diagnostic taxa through much of the section;
throughout the early Paleocene (Teurian), nannoplankton are absent and foraminifera and
radiolarians are scarce. The most recent age model for mid-Waipara is based on the revised
biostratigraphy of Hollis and Strong (2003) and has been subsequently revisited by C. J
Hollis of GNS (Fig. 3.3).
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The presence of planktonic foraminifera Globigerinelloides multispina, Heterohelix
globulosa, and Bulimina rakauroana at -8 cm indicates a Late Maastrichtian (Haumurian)
age. This is confirmed by the presence of the nannoplankton Nephrolithus frequens
(Edwards, 1966), and by correlation of the uppermost 5 m of Cretaceous strata with the
Manumiella druggii dinoflagellate zone (Wilson, 1984). Age diagnostic radiolarians are
absent.
Above the K/Pg (marked by the geochemical anomaly), the lowest 25 cm of Danian strata
are correlated with foraminiferal zones P0 and Pα; this assignment is based on the lowest
occurrence (LO) of Parvulorugoglobigerina eugubina and Eoglobigerina eobulloides. LO
of Trithyrodinium evittii also provides an early Paleocene indicator (Wilson et al., 1984;
1987, Helby et al., 1987). Radiolarian zone RP1 is tentatively identified above the K/Pg
based on the high abundance of small actinommid spumellarians. LO of Lithostrobus wero
places the base of RP2 tentatively at 13 cm. The unconformity at 25 cm probably truncates
the transition from Pα to P1a zones. The strata above the unconformity are correlated with
zones P1a - P1c, based on the LO of Globoconusa daubjergensis and absence of P.
eugubina. The base of zone RP3 may be tentatively assigned at 1.95m. The highest sample
to contain index species for Paleocene P zones occurs at 1.25 m, above which (record
spans up to 29.5 m) foraminifera are extremely rare.
Dinoflagellate events (Roncaglia et al., 1999; Crampton et al., 2000) indicate that 200 m of
uppermost Cretaceous strata in this section were deposited at an average (compacted)
sedimentation rate of c. 25 m My-1. The overlying Paleocene sediments above the
unconformity have a fairly well constrained sedimentation rate of c. 10.5 m per million
years, assuming the stratigraphic thickness determined by Wilson (1964) is reliable (Vajda,
2001, Vajda and Raine, 2003). The relatively uniform lithology throughout the Conway
Formation supports a uniform sedimentation rate. Elucidating the duration of the lowest 25
cm of the Danian-age sediment is problematic due to the unconformity and scarcity of age
diagnostic taxa. Based on event stratigraphy, the interval could span between 24 to 300
Kyrs (constrained by the high sedimentation rate of the late Cretaceous and relatively
lower sedimentation of the Paleocene), and the unconformity may span up to c. 0.945 My.
The relatively weak iridium anomaly at mid-Waipara is argued to be related to high
sedimentation (and bioturbation) at the K/Pg boundary (Brooks et al., 1986b), thus the
higher sedimentation rate is suggested for the post K/Pg interval preceding the
unconformity at 25 cm. The succession of dinoflagellate events throughout the Paleocene
support and constrain the timings described through correlation with several other New
Zealand K/Pg boundary sections, notably at Marlborough (Willumsen 2004, 2006, 2011).
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The stratigraphic ranges of New Zealand dinoflagellate successions has recently been
shown (Vajda, 2011) to correlate with Southern Hemisphere dinoflagellate zonations
(Partridge, 1976; Helby et al., 1987; Wilson, 1988), radiolarian zonation (Hollis, 1993,
1997), foraminiferal zones (Berggren et al., 1995) via datums of Strong et al. (1995) and
Hollis et al. (2003c), and indirectly to nannoplankton zones (Martini, 1971).
3.3. Methods
3.3.1. Biomarker Analyses.
The methodologies used are described in full in Chapter 2. In summary, sediments were
extracted under reflux for 24 h using a Soxhlet apparatus. TLEs were subsequently
fractionated on aminopropyl SPE to generate neutral and acid fractions and the neutral
fraction fractionated using an (activated) alumina flash column to generate apolar and polar
fractions. The neutral polar fraction was filtered and analysed using LC-MS APCI. Ion
detection was performed in SIM mode, and GDGTs were quantified based on their
respective [M+H]+ m/z values (Schouten et al., 2007b).
3.3.2. GDGT Quantification
Concentrations of individual GDGTs were semi-quantitatively determined using the
GDGT46 internal standard (Huguet et al., 2006; Fig. 2.3); GDGT peak areas were
integrated from their respective [M+H]+ m/z mass chromatograms and related to a known
amount of GDGT46 integrated on the m/z = 744 mass chromatogram:
(3.1)
Where
is the peak area of the analyte GDGT as integrated on its respective [M+H]+
m/z mass chromatogram,
is the peak area of the GDGT46 standard integrated on the
m/z =744 mass chromatogram,
is the known mass of GDGT46 added, and
is the
calculated mass of analyte GDGT.
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
3.3.3. Statistical Analysis of GDGT Distributions
Agglomerative hierarchal cluster analysis of GDGT distributions was performed using
PAST (PAleontological STatistics) version 2.08© software (Hammer et al., 2001). Ward's
minimum variance method (Ward, 1963) was applied using Euclidean distances.
3.4. Results
3.4.1. Elemental Analysis
Total Organic Carbon (TOC) contents are less than 1 % throughout the section (Fig. 3.4).
Values are variable and range from c. 0.25 % to 0.50 % throughout the late Maastrichtian
(-70 cm to 0 m), with a general trend towards lower values approaching the K/Pg
boundary. Values fall within a similar range above the K/Pg boundary, fluctuating from c.
0.20 % to 0.45 % throughout the lower 22 cm of Danian strata and continuing the weak
Maastrichtian trend towards declining values
.
Figure 3.4. TOC content throughout the mid-Waipara River section. Note the change in
depth scale above 5 m, herein indicated by a break in the ordinate axis.
64
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
Above the unconformity at c. 25 cm, TOC drops to lower and less variable values of c.
0.12% from 28 cm to 75 cm, before increasing to a maximum value of c. 0.78 % at 7.84 m.
A longer term decline in TOC to c. 0.50 % is then evident across the early Danian in the
upper part of the section (7.84 m to 20 m).
3.4.2. Glycerol Dialkyl Glycerol Tetraether Distributions and Concentrations
3.4.2.1. GDGT Concentrations
Both Isoprenoidal (Fig. 3.5) and non-isoprenoidal GDGTs are present throughout the midWaipara River section, with isoprenoidal GDGTs clearly dominant.
Figure 3.5. Typical LC-MS chromatogram of isoprenoidal GDGTs, sample f561 (- 7 cm).
Ion scanning performed in SIM mode to monitor GDGT [M+H]+ m/z values exclusively.
Peaks labelled with numbers according to number of cyclopentyl rings within GDGT
structures, as per structures in Appendix 1. Crenarchaeol labelled as [cren], isomer as [4’].
Internal standard GDGT46 highlighted in red; note co-elution with [GDGT-4’].
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Isoprenoidal GDGT concentrations relative to dry weight (DW) of sediment (Fig.
3.6A,B,C) are generally an order of magnitude greater than concentrations of branched
GDGTs (represented by bGDGT-I; Fig. 3.6D). Concentrations of bGDGT-I (Fig. 3.6D),
GDGT-0 (Fig. 3.6A), crenarchaeol (Fig. 3.6B) and all other isoprenoidal GDGTs (herein
referred to as GDGT-1, GDGT-2, GDGT-3 and GDGT-4’; Fig. 3.6C) all exhibit similar
trends throughout the Maastrichtian (-70 cm to 0 m) and the lower 25 cm of Danian strata,
with crenarchaeol exhibiting the highest concentrations overall. Between -70 cm to -44 cm,
concentrations of all GDGTs decrease, before variably trending towards higher
concentrations up to the K/Pg boundary (0 m).
Values fluctuate in the lower 25 cm of Danian strata, with all GDGT concentrations
reaching minima in samples f556 (16 cm) and f197 (19 cm). However, there is a sharp
increase in the concentration of GDGT-0 above the unconformity at c. 25 cm, concomitant
with a decrease in concentrations of crenarchaeol and the other isoprenoidal GDGTs
(except GDGT-0) and bGDGT-I. Concentrations of GDGT-0 remain high and dominate
the GDGT assemblage from 25 cm to 1.55 m, at which point crenarchaeol and bGDGT-I
concentrations begin to recover. In contrast, the summed total concentration of the other
isoprenoidal GDGTs gradually increases upwards from 25 cm. Maximum concentrations
of all GDGTs are reached at 7.84 m, before gradually decreasing through the upper c. 12 m
of Danian strata.
Concentrations expressed relative to total organic carbon (TOC) reveal subtle differences
among the different GDGTs (Fig. 3.7). Records of all GDGTs reflect the trends exhibited
in Fig. 3.6 from the Maastrichtian to the early Danian unconformity (-70 cm to c. 25 cm),
but with greater variability, reflecting a similar variability to the TOC record (Fig. 3.7E)
However, normalisation of concentrations to TOC results in different GDGT trends above
the unconformity, from c. 25 cm up to 1.55 m. Whilst concentrations of crenarchaeol (Fig.
3.7B) and bGDGT-I (Fig. 3.7D) mirror each other, reflecting similarly and consistently
low values, the other isoprenoidal GDGTs (Fig. 3.7C) and GDGT-0 (Fig. 3.7A) exhibit a
prominent increase in concentration, especially in the two samples above the unconformity
(f199, 27.5 cm; f202, 42.5 cm). Concentrations of GDGT-0 then decrease while those of
other isoprenoidal GDGTs continue to increase. Above the sample at 1.55 m (f218), all
GDGT concentration trends are again parallel (in both TOC normalised and DW
normalised records).
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67
Figure 3.6. Concentrations of (A) GDGT-0, (B) crenarchaeol, (C) sum of GDGT-1. GDGT-2, GDGT-3 and GDGT-4’, and (D) branched GDGT-I
throughout the mid-Waipara River section, normalised to dry weight of sediment. Note due to insufficient amount of sample, GDGTs could not be
quantified for sample f232 (2.75 m).
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68
Figure 3.7. Concentrations of (A) GDGT-0, (B) crenarchaeol, (C) sum of GDGT-1. GDGT-2, GDGT-3 and GDGT-4’, and (D) branched GDGT-I
throughout the mid-Waipara River section, normalised to (E) TOC.
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
3.4.2.2. GDGT Distributions
3.4.2.2.1. Relative Proportions of Individual GDGTs Used in SST Reconstruction
Proportions of GDGT-1, GDGT-2, GDGT-3 and GDGT-4’ (relative to the sum of those
four compounds) exhibit major shifts through the Mid-Waipara K/Pg interval (Fig. 3.8). In
the transition from upper Maastrichtian (-70 cm to – 7 cm) to K/Pg boundary and earliest
Danian sediments (- 7cm to 22 cm), relative proportions of GDGT-1 decrease from c. 0.44
to c. 0.38, while proportions of GDGT-4’ increase from c. 0.16 to 0.18. Relative
proportions of GDGT-2 slightly increase from variable values around 0.26 to relatively
more constant values of c. 0.30. GDGT-3 proportions remain at values of c. 0.14, although
they are less variable throughout the earliest Danian interval. Large shifts in relative
proportions of individual GDGTs occur across the probable unconformity at c. 25 cm.
From 22 cm to 47.5 cm, relative proportions of GDGT-1 and GDGT-2 increase from c.
0.38 to c. 0.57 and from 0.27 to 0.36, respectively, whereas proportions of GDGT-4’ and
GDGT-3 decrease from c. 0.21 to c 0.04 and 0.13 to 0.04, respectively. At c. 1 m, relative
proportions of GDGT-1 and GDGT-2 start to decrease, while proportions of GDGT-3 and
GDGT-4’ begin to increase; Maastrichtian distributions are achieved at 2.75 m.
These shifts in relative GDGT proportions can be used to define stratigraphic zones (Fig.
3.8). Zone I represents upper Maastrichtian distributions from -70 cm to 0 m. Zone II
represents sediments above the K/Pg boundary but below the unconformity at ca. 25 cm,
although the sample at -7 cm (f561) may also represent a Zone II distribution due to
downward displacement via bioturbation; relative proportions of GDGTs for this sample
are similar to those of Zone II. Zone III occurs above the unconformity at c. 25 cm, extends
up to (but not including) the sample at 2.75 m (f232) and is characterised by the
aforementioned dramatic shifts in GDGT proportions. The base of Zone IV (2.75 m; f232)
is defined as the interval where GDGT assemblages exhibit a return to Maastrichtian
distributions.
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
Figure 3.8. Relative proportions of (A) GDGT-1, (B) GDGT-2, (C) GDGT-3, (D) GDGT-4 normalised to total of [GDGT-1+ GDGT-2 + GDGT-3 +
GDGT-4’] and expressed as fractional percentage.
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Statistical analysis (agglomerative hierarchal cluster analysis) was used as an independent
test of these stratigraphic groupings. As with the arbitrary stratigraphic zonation, the
GDGTs considered are GDGT-1, GDGT-2, GDGT-3 and GDGT-4’. GDGT-0 and
crenarchaeol are excluded as their combined dominance over the distributions (GDGT-0 +
crenarchaeol = 85 – 95% of total GDGTs) throughout the record can skew the statistical
analysis. Such analysis confirms that sediments from Zone III cluster separately from all
other samples (Fig. 3.9A) and that sediments of Zone II cluster separately from samples in
Zones I and IV which are indistinguishable in terms of relative GDGT distribution (Fig.
3.9B). The analyses also confirm that sample f561 (-7 cm) clusters with Zone II samples,
despite its stratigraphic occurrence below the K/Pg boundary. Cluster analysis also reveals
two sub-groups in Zone III (Fig. 3.9C). One group represents the most extreme relative
GDGT proportion values, while the other represents the trend towards and recovery away
from those extreme values.
The distinctly different distributions of Zone III are also evident from examination of the
LC-MS chromatograms (Fig. 3.10); while chromatograms from representative samples in
Zones I, II and IV are generally similar, the chromatogram of GDGTs in sample f203 from
Zone III is visually distinct.
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72
Figure 3.9. Agglomerative hierarchal cluster analysis of isoprenoidal GDGT distributions (excluding GDGT-0 and crenarchaeol), using Euclidean
distances. Cophenetic coefficient is 0.8871. (A), (B) and (C) indicate the 3 greatest distances; (A) represents the clustering of Zone III away from all other
zones, (B) indicates the statistical difference between Zones I and II, and (C) indicates a sub-group within Zone III. Samples are plotted with GDGT
distributions and stratigraphic depth, clusters are described relative to corresponding GDGT Zones.
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
73
Figure 3.10. Average GDGT distributions for GDGT ‘Zones’, expressed as a bar chart of fractional abundances, with representative LC-MS GDGT
chromatograms for each Zone. Colour coding for GDGTs to relate bar chart to chromatograms is given in the key. Abscissa axis of chromatograms is
relative retention time, ordinate axis is relative intensity.
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
3.4.2.2.2. Crenarchaeol and GDGT-0
The relative proportions of acyclic GDGT-0 and crenarchaeol also change appreciably
throughout the mid-Waipara River section (Fig. 3.11), exhibiting the greatest proportional
shifts of all isoprenoidal GDGTs. In Zone I, GDGT-0 represents c. 30% of the total
isoprenoidal GDGT distribution, decreasing to c. 25% across the K/Pg boundary into Zone
II as the proportion of crenarchaeol increases from c. 55% to c. 60%.
Figure 3.11. Relative proportions of (A) GDGT-0, and (B) crenarcheaol, normalised to
sum total of all isoprenoidal GDGTs and expressed as fractional percentage.
GDGT-0 and crenarchaeol then exhibit a dramatic shift in relative proportions across the
transition from Zone II to Zone III and throughout the interval; GDGT-0 increases to a
maximum of c. 95% of the distribution, whereas crenarchaeol decreases to a minimum of
c. 5%. Proportions of GDGT-0 and crenarchaeol increase at c. 1 m, and recover back to
late Maastrichtian values in Zone IV, remaining stable throughout the remaining strata.
Thus, shifts in relative proportions of GDGT-0 and crenarchaeol follow the zonation
pattern established from relative GDGT proportions (Fig. 3.8, 3.10) and statistical cluster
analysis (Fig. 3.9).
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However, there are some differences; for example, relative proportions of crenarchaeol
begin to decrease (from 0.58 at 16 cm, to 0.49 at 19 cm and 0.45 at 22 cm) before the
transition from Zone II to Zone III, albeit less dramatically than the decrease exhibited
across the transition.
3.4.2.2.3. Degree of GDGT Cyclisation
In order to examine further the changes in GDGT distributions, the degree of cyclisation
was calculated (e.g. Uda et al., 2001; Schouten et al., 2002), described by the weighted
average number of cyclopentyl moieties within isoprenoidal GDGT biphytanyl chains (e.g.
Shimada et al., 2002, Schouten et al., 2007d, Pearson et al., 2008). This is based on the
physiological principle that the degree of cyclisation of GDGTs increases as a response to
growth temperature (De Rosa et al., 1980; Gliozzi et al., 1983; De Rosa and Gambacorta,
1988; Uda et al., 2001), initially identified for hyperthermophiles before the ubiquity of
Thaumarchaeota was recognised (Karner et al., 2001) and the calibration of isoprenoidal
GDGTs to SST was determined (Schouten et al., 2002). The observation is based on
fundamental understanding of membrane lipid homeoviscous adaptation (De Rosa et al.,
1994; Gabriel and Chong, 2000): a higher degree of membrane lipid cyclisation creates a
higher thermal transition point for the membrane, consistent with adaption to warmer
temperatures (Gliozi et al., 1983).
Calculations of degree of cyclisation are often made for distributions of GDGTs produced
by non-Group I archaeota thriving in environments which are not expressed in the global
marine SST calibration, such as those in geothermal hot springs (Schouten et al., 2007d,
Pearson et al., 2008, Pitcher et al., 2009). The relative proportion of each GDGT is
multiplied by a weighting according to the number of cyclopentyl moieties contained
within its biphytanyl chains, and the summed total is divided by the sum of the unweighted
proportions of each GDGT, (e.g. Shimada et al., 2002, Schouten et al., 2007d). A variety
of such weighted GDGT ratios can be calculated: GDGT-0 and crenarchaeol can be
excluded (Fig. 3.12B) to determine the degree of cyclisation in terms of only those GDGTs
used in the TEX86 SST reconstructions:
(3.2)
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
GDGT-0 and crenarchaeol can be included (Fig. 3.12A), acknowledging that GDGT-0 is
synthesised by Thaumarchaeota (Schouten et al., 2000) but also a wide range of other
archaea, e.g. methanogenic (Koga et al., 1993; Schouten et al., 2000; 2002; Blaga et al.,
2009) and thermoacidophilic (Shimada et al., 2002) archaea. Note that as GDGT-0 is
acyclic, its weighting (0) effectively removes it from the numerator of Equation 3.3:
(3.3)
Fig. 3.12 demonstrates broad agreement between the two weighted average trends
throughout the mid-Waipara River section. Both records document an increase in the
weighted average number of cyclopentyl moieties from Zone I to Zone II, suggesting a
warming trend. This is followed by a significant drop in the weighted average number of
cyclopentyl moieties (and inferred temperature) between Zone II and Zone III, and a
subsequent gradual recovery throughout Zone IV to distributions similar to those of Zone I.
Figure 3.12. Weighted average number of cyclopentyl rings in isoprenoidal GDGT
biphytanyl moieties through the mid-Waipara River section using (A) all isoprenoidal
GDGTs and (B) excluding GDGT-0 and crenarchaeol. Error bars represent one standard
deviation of the mean from replicate determinations.
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
The only difference between the calculations is that inclusion of GDGT-0 and crenarchaeol
broadens the range of weighted average number of cyclopentyl ring values, exacerbating
the shift to lower values across the transition from Zone II to Zone III.
3.4.2.3. GDGT Proxies
3.4.2.3.1. TEX86 and SST reconstruction
SSTs were reconstructed at mid-Waipara River section across the K/Pg boundary using the
most recently proposed calibrations (Fig. 3.13). Applying
(Kim et al., 2010) yields
very similar temperatures across the record to those constructed by the earlier calibrations
of Kim et al. (2008) and Liu et al. (2009) (Fig. 3.13B). However,
and
reconstructions (Raw values used are shown in Fig. 3.13A) record different absolute
temperatures as well as different temporal trends through the mid-Waipara River K/Pg
section (Fig. 3.13C).
SSTs reconstructed using
throughout the Maastrichtian (Zone I, -70 cm to 0 cm)
range from 21°C to 22°C (
= c. 0.55). Higher temperatures of c. 24°C (
= c.
0.60) are recorded in the uppermost Maastrichtian sample (f561, -7 cm), although as
discussed above, geochemical signals in this horizon could have been influenced by
bioturbation and mixing of post-K/Pg boundary sediments. SSTs in the lowermost 22 cm
of Danian strata (Zone II) are similarly estimated to range from 23°C to 24°C (
= c.
0.60), with the highest temperatures for the whole record recorded at 5 cm and 10 cm
above the K/Pg boundary.
(Kim et al., 2010) records significantly cooler and more
variable SSTs in both Zone I (12°C - 15°C;
17°C;
= c. 0.30 - 0.33) and Zone II (16°C -
= c. 0.36). Despite the significant difference between
reconstructed SSTs, the
and
record does corroborate reworking of the post-K/Pg
boundary geochemical signal into the uppermost Maastrichtian sediments (f561, -7 cm).
The offset between
and
reconstructed SSTs throughout Zone I varies from c.
7°C to c. 9.5°C, with variability in the offset driven by variability in the
record.
Offset across Zone II is much less variable at c. 7°C (Fig. 3.13D)
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
Figure 3.13. Mid-Waipara River K/Pg boundary section (A) raw
and
values with analytical precision given as error bars, (B) TEX86
reconstructed SSTs using various calibrations (calibration errors given as single points with error bars above plot), (C)
and
derived SST
reconstructions, with simple propagated calibration error and analytical precision given as error bars, (D) offset between
and
derived SST
reconstructions, calculated as
. Grey shaded area highlights interval through which offset between
and
derived SST tends
towards zero and into negative values, indicating convergence and reversal of offset (i.e.
estimates SSTs closer to, and warmer than
estimates).
Interval is coeval with GDGT Zone III.
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
Above the probable unconformity at c. 25cm, dramatic sea surface cooling of up to 11°C is
recorded by
: the transition from Zone II to Zone III represents SST cooling of c.
7°C, with a further drop of 4°C (
= c. 0.43) at 42.5 cm within Zone III. In contrast,
records only a slight cooling of c. 1.5°C across the transition, and then records an
apparent warming of c. 2.5°C at 42.5 cm. Both
and
record a gradual
warming of c. 3°C from 42.5 cm to 1.05 m, although SSTs estimated by
this interval are between 2.5°C and 4°C warmer than those estimated by
through
(Fig.
3.13B,C) and are in fact warmer than those reconstructed throughout Zones I and II,
whereas
estimates are the coolest for the whole record. This is also illustrated by the
shift in offset between
and
reconstructed SSTs, from c. 7°C in Zone II to c. -
4°C (Fig. 3.13D). The
and
SST records then converge again at 1.25 m, with
recording a warming to c. 19°C (
c. 18°C (
= c. 0.52), and
indicating cooling to
= c. 0.37).
continues to record cooling to c. 10°C (
of Danian strata, whereas
stable. Both
and
= c. 0.29) over the subsequent 1.5 m
records slight warming of c. 0.5°C but is essentially
SST records indicate gradual warming and stabilisation of
SSTs from 2.75 m and throughout the upper most strata of the section (Zone IV), with a
temperature offset between the two records of around 7°C (Fig. 3.13D), similar to the
offset recorded in upper Maastrichtian sediments of Zone I (-70 cm to 0 cm) and
lowermost Danian sediments of Zone II (0 cm to 22 cm).
3.4.2.3.2. BIT Index
BIT (branched vs. isoprenoidal tetraether) indices (Hopmans et al., 2004) were determined
throughout the mid-Waipara River section. Branched GDGTs are thought to derive from
anaerobic non-photosynthetic soil bacteria (Sinninghe Damsté et al., 2000; Weijers et al.,
2006a; Weijers et al., 2006b), possibly acidobacteria (Weijers et al., 2009); indeed,
branched tetraethers have recently been isolated from cultures of acidobacteria (Sinninghe
Damsté et al., 2011). The predominant source of crenarchaeol in marine sediments is
thaumarchaeota (Sinninghe Damsté et al., 2002; Weijers et al., 2006b). The BIT index
therefore reflects the relative amount of soil organic matter input to the sediment; the index
approaches unity with greater influence of terrestrially derived organic carbon (Hopmans
et al., 2004).
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Figure 3.14. (A) BIT index, and (B) concentration of crenarchaeol and (B) bGDGT-I
normalised to TOC at the mid-Waipara River section.
BIT indices are low throughout the record, with values not exceeding 0.11 (Fig. 3.14). As
previously described, the concentrations of crenarchaeol and bGDGT-I exhibit similar
trends throughout the mid-Waipara River section. However the BIT index reveals a general
long term trend towards decreasing values from the base of Zone I (f161; - 70 cm) through
to the uppermost sample of Zone III (f218; 1.55 m). The trend is moderately interrupted by
a small shift of c. 0.01 at -27 cm (f172), but continues to decrease after this with no large
shift in values observed at the K/Pg boundary. A more significant shift in values is
observed across the transition from Zone II into the base of Zone III, where BIT indices
decrease from c. 0.09 to 0.06, and remain around this value for much of Zone III. A further
decrease at 1.55 m (f218) is observed, and then a shift to relatively higher values is
recorded across the transition from Zone III to Zone IV, with values ranging from c. 0.6 to
0.9 throughout the interval.
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3.5. Discussion
3.5.1. GDGT Concentrations
Dramatic shifts in the concentrations of GDGTs, relative to both DW and TOC, are evident
across the interval from Zone II to Zone III (Fig. 3.6; Fig. 3.7), coeval with a shift in the
relative distributions of GDGTs (Fig. 3.8, 3.9, 3.10) across the same interval. A number of
mechanisms may be responsible for the decreased and dramatically altered concentrations
of GDGTs preserved in Zone III sediments. TOC also decreases across the interval
between Zone II and Zone III (Fig. 3.4; Fig. 3.7) which could indicate more oxidising
bottom water or sedimentary conditions and enhanced degradation of OM (e.g. Emerson
and Hedges, 1988; Stein, 1991; Meyers, 1997; Killops and Killops, 2005). If so, the
observed trends could be explained by preferential degradation of crenarchaeol and
bGDGT-I relative to GDGT-0 throughout Zone III.
Investigation into the effect of redox conditions on preservation of GDGTs (Schouten et
al., 2004) indicated no evidence for preferential degradation of any particular GDGT
across a range of bottom water redox conditions and GDGT accumulation rates. However,
GDGTs were analysed from different sections of turbidites at the Madeira Abyssal Plain
that experienced different degrees of oxygen exposure to investigate the effects of long
term oxic degradation on GDGT proxies (Huguet et al., 2008; 2009). These analyses
revealed evidence for preferential degradation of some GDGTs, leading to overestimations, underestimations, or no change in TEX86 SST reconstructions (Huguet et al.,
2008, 2009). This apparent variability was attributed to the preferential preservation of soil
derived GDGTs, perhaps as a result of matrix protection (Huguet et al., 2008, 2009). As
isoprenoidal GDGTs can also be present in soils as well as branched GDGTs (Weijers et
al., 2006), it is suggested that this mechanism of degradation leads to preferential
expression of terrestrially derived isoprenoidal GDGT distributions over the marine
derived signal. This also leads to an increase in the BIT index, as soil derived branched
GDGTs are preferentially preserved over marine derived crenarchaeol. However, at the
mid-Waipara River section a decrease in BIT is observed across Zone III (Fig. 3.14A).
Furthermore, concentrations of GDGT-0 increases; as a marine isoprenoidal GDGT, it
would be expected to decrease with crenarchaeol and other isoprenoidal GDGTs if
preferential degradation occurred in the manner described.
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An alternative is that the seasonality of thaumarchaeota productivity is altered in Zone III,
such that the peak archaeal biomass occurs during low primary productivity seasons
(Murray et al., 1999; Wuchter et al., 2005, 2007) and as such there is less suspended
particulate matter (SPM) available to transport the GDGTs, via packaging and sinking, to
the sediment. However, this scenario is postulated as a mechanism by which archaea
reduce competition for nutrients in oligotrophic environments (Lieder et al., 2010); as
discussed, high nutrient levels are indicated for Zone III. Moreover, such environments do
not necessarily preclude export of GDGTs during peak primary productivity season (e.g.
Wuchter et al., 2007), and the reduction of TOC coeval with decreases in GDGT
concentrations would not be explained as there is no inferred reduction in overall SPM.
A final possibility is that the net export of GDGTs from the water column to the sediment
may have been reduced. The most widely accepted mechanism for the transport of GDGTs
to the sediment is via packaging onto sinking SPM such as faecal pellets or aggregates
(Wuchter et al., 2005; Huguet et al., 2006a). If there is less particulate matter sinking to the
sea floor, the export of GDGTs to the sediment may therefore be attenuated. However,
reduction in the export of organic carbon from the surface waters would most likely be
caused by decreased primary productivity (Seuss, 1980; Emerson and Hedges, 1988), and
primary productivity is inferred to be high throughout the early Paleocene at mid-Waipara,
based on the abundance of peridinioid dinoflagellates (Willumsen, 2000, 2006) and
siliceous microfossils (Hollis et al., 2003; Hollis and Strong, 2003). In particular, Zone III
correlates with a period of elevated Si/Al and Ba/Al ratios (Hollis and Strong, 2003),
suggesting perhaps even higher siliceous productivity (Zachos and Arthur, 1989) in Zone
III than in Zones I, II and IV. Furthermore, the acme of Palaeoperidinium pyrophorum,
coinciding with Zone III, is argued to indicate cooler water and possibly upwelling
conditions (Askin, 1988; Willumsen 2000, 2006) which could enhance surface primary
productivity (Wetzel, 1977; Lyle, 1988; Meyers, 1997).
Normal or enhanced surface productivity but low OM flux to the sediment agrees with the
theorised model of a post-K/Pg boundary ‘Living Ocean’ (D’Hondt, 1998; Adams et al.,
2004). The living ocean model invokes a decrease in the biological pump (i.e. reduced
export of planktic carbon to the benthic systems) as the cause of low planktic-to-benthic
δ13C gradients, rather than a decrease in productivity, persisting for up to 3 My after the
K/Pg boundary event. The authors infer that a decline in zooplankton could cause reduced
marine snow and organic carbon export to the sediments due to lack of repackaging and
aggregation of organic material (Emerson and Hedges, 1988).
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However, more recent studies suggest a decline in abundance of zooplankton could have
the opposite effect; zooplankton may in actual fact break up aggregates of phytoplankton
(Sarmiento and Gruber, 2005) which may be more efficient at transporting OC to the
sediments than faecal pellets (Armstrong et al., 2001; Jackson, 2001). Thus reduction in
zooplankton abundance might not necessarily cause a decline in OC transport from the
surface. Alternatively, a reduction in mean size of phytoplankton could have lead to a
reduction in the packaging of biomass into particles large enough to sink (D’Hondt et al.,
1998), a phenomenon which has been recorded in post-K/Pg boundary nannoplankton
(Gardin and Monechi, 1998) and planktonic foraminiferal assemblages (Premoli-Silva and
Luterbacher, 1966; Norris et al., 1999). Enhanced respiration of the slowly sinking SPM
by opportunistic bacteria (Seuss et al., 1980; Wakeham et al., 1980; Emerson and Hedges,
1988) could further reduce flux of OM to the sediment (Hollander et al., 1993). In any
case, a change in the nature, depth and intensity of SPM export in Zone III could impact
both the amount and distribution of GDGTs exported from to sediments.
The different trends in concentrations of GDGT-0 and other isoprenoidal GDGTs relative
to crenarchaeol and bGDGT-I are not adequately explained by changes in export
mechanism alone. The most likely explanation for the observed trends is a shift in the
relative distributions of GDGTs across the unconformity from Zone II to Zone III,
concomitant with an altered oceanographic regime and change in OM export mechanisms.
Surface water ecology may be significantly altered across the unconformity at c. 25 m, and
possibly reflects a reduced export of surface OM to the sediment relating to the early
stages of marine recovery postulated for the ‘Living Ocean’ model (D’Hondt, 1998).
Altered benthic redox conditions may have reduced the amount of TOC preserved in the
sediments. These mechanisms would not affect the relative distributions of GDGTs,
therefore the climate signals reflected by those distributions may be interrogated further.
3.5.2. GDGT-derived Sea Surface Temperature Reconstructions
Various calibrations relating the distribution of isoprenoidal GDGTs to SST have been
proposed since the inception of the proxy. Among the most recent are a linear calibration
(Kim et al., 2008; n=223) which removes data from (sub) polar regions and the Red Sea
and produces a standard error of ±1.7°C, and a calibration based on the reciprocal of TEX86
(Liu et al., 2009; n=287) which includes (sub) polar and Red Sea data, thus producing a
calibration characterised by greater scatter with a standard error of ±5.4°C.
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The most recent TEX86 global core-top calibration invokes two separate indices and
calibrations for high (
) and low (
temperature reconstructions (Kim et al.,
2010; n=426). Those authors suggested that
be used to reconstruct when SSTs
throughout a record are all warmer than 15°C, and
for records with reconstructed
temperatures above and below 15°C. (Kim et al., 2010). This is based on the observation in
the modern calibration data set that both calibrations reconstruct similar temperatures
above the 15°C threshold, but
temperatures. However,
is apparently less likely to over-estimate colder
is subject to a calibration error of ±4.0°C due to greater
scatter in the (sub) polar data, whereas
Thus, where applicable,
is given with a standard error of ±2.5°C.
is preferable to
.
SST reconstructions for mid-Waipara River are similar to those derived from the
calibrations of Kim et al. (2008) and Liu et al. (2009) (Fig. 3.13B). This reflects the fact
that all three calibrations utilise the same ratio of four GDGTs and that the distributions
fall well within the modern calibration range, where the three calibrations do not
appreciably differ. In contrast, the
derived SSTs are both markedly lower and
exhibit fundamentally different temporal trends (Fig. 3.13C). The different trends are
obviously difficult to reconcile. However, the large offset between
and
reconstructed temperatures at mid-Waipara in Zones I, II and IV (Fig. 3.13D) is also in
disagreement with expectations derived from the modern calibration dataset, in which both
calibrations typically yield similar SSTs at temperatures greater than 15°C (Kim et al.,
2010).
These issues complicate the application of GDGT-based proxies through the mid-Waipara
River record. Moreover, it may not be appropriate to apply one calibration across a whole
record; GDGT distributions shift dramatically (Fig. 3.9) across the transition from Zone II
to Zone III and cluster discretely in Zone III from all other samples in the record (Fig.
3.10). The offset between
and
SST reconstructions also dramatically shifts in
Zone III (Fig. 3.13D), indicating that relative proportions of GDGTs in Zone III reflect
distributions which respond very differently to
and
than distributions in
Zones I, II and IV. The possible causes of GDGT distribution shifts and the unusual
SST reconstructions in Zone III are investigated below.
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3.5.2.1. What is causing the unusual differences in reconstructed SSTs?
The previous discussion indicates that some variable other than annual sea surface
temperature governs GDGT distributions in the Waipara section.
fundamentally different GDGT index (Eq. 1.8) than
is based on a
, with the latter comparing the
concentration of four GDGTs relative to GDGT-1 and the former comparing the
concentration of three GDGTs relative to GDGT-2. Moreover,
is a less robust
measure of degree of cyclicity; proportions of GDGT-2 can change relative to both
GDGT-1 and GDGT-3. Hence an increase in GDGT-2 to GDGT-3 ratios, for example,
would yield a decrease in cyclicity but also reconstruct warmer temperatures.
In the mid-Waipara River section, it is the relationship between GDGT-2 and GDGT-3 that
appears to be unusual compared to most modern and other ancient data. In modern GDGT
distributions used for TEX86 calibrations, relative proportions of both GDGT-2 and
GDGT-3 generally increase with increasing temperature (Kim et al., 2010). However, at
the transition between Zone II and Zone III, relative proportions of GDGT-3 decrease but
relative proportions of GDGT-2 increase (proportions of other GDGTs also change in a
manner consistent with cooling: relative proportions of GDGT-1 increase and proportions
of GDGT-4 decrease; Fig. 3.8). This increase in the ratio of GDGT-2/GDGT-3 across Zone
III coincides with the dramatic shift from a high offset between
and
derived
SSTs to a low and negative offset (Fig. 3.13). Thus, the ratio of GDGT-2/GDGT-3 is
closely associated with the offset between
and
reconstructed SSTs.
3.5.2.1.1. Contribution of GDGTs from Sedimentary Inputs
One possible mechanism for shifting GDGT distributions in Zone III is the contribution of
GDGTs to the sediments by in situ production by benthic archaea, which has been inferred
for some modern settings by the presence of GDGTs occurring as intact polar lipids (IPLs)
(Shah et al., 2006; Lipp et al., 2008; Lipp and Hinrichs, 2009). Although the in situ
production of these particular glycolipid IPLs is debated (see Schouten et al., 2010), there
is little doubt that sedimentary archaea could produce at least some of the GDGTs
observed in ancient materials. At a range of locations (Liu et al., 2011), GDGT-0, GDGT-2
and GDGT-3 are generally more abundant in the IPL-GDGT pool, whereas crenarchaeol
tends to be more abundant in the core-GDGT pool, suggesting the former are particularly
associated with sedimentary inputs.
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With respect to temperature reconstruction, proportions of GDGT-1 are more variable but
generally lower in the IPL pool relative to the core lipid counterparts, such that TEX86
reconstructions from IPL-GDGT distributions produce warmer temperatures. However, in
all of these settings GDGT-2 and GDGT-3 concentrations co-vary, an observation that is
inconsistent with the record at mid-Waipara River which is characterised by a stratigraphic
decoupling of those two compounds.
Various studies indicate that methanogenic or methanotrophic archaea involved in the
anaerobic oxidation of methane (AOM) can also contribute isoprenoidal cyclic GDGTs to
the sediments. Elevated relative proportions of GDGT-1 and GDGT-2 have been found
associated with mat and crust samples from cold seeps in the Mediterranean (Pancost et al.,
2001), with variability in relative proportions of GDGT-3. An increase in the relative
proportion of GDGT-0 is also evident, but the most striking difference between pelagic
crenarchaeal and AOM archaeal GDGT assemblages is the larger proportions in the latter
of GDGT-1, GDGT-2 and (more variably) GDGT-3 relative to crenarchaeol. Similar
patterns were observed for particulate matter samples throughout the deep anoxic region of
the Black Sea (Wakeham et al., 2004). Values for ratio of GDGT-2/GDGT-3 are also
much higher and GDGT-2 is dominant over GDGT-1 in most AOM settings including the
Black Sea (Pancost et al., 2001; Wakeham et al., 2004), sediments from Guaymas Basin
(Schouten et al., 2003) and samples from a hydrate site in Mississippi Canyon (Zhang et
al., 2011).
Based on such observations, Zhang et al. (2011) proposed a ‘Methane Index’ to measure
the contribution of AOM-related GDGTs based on the proportions of GDGT-1, GDGT-2
and GDGT-2 relative to crenarchaeol and GDGT-4’:
(3.4)
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
Figure 3.15. (A) Ratio of GDGT-2/GDGT-3, (B) Methane Index (Zhang et al., 2011), (C) ratio of GDGT-2/GDGT-1 and (D) offset between
and
derived SST reconstructions. Grey shaded area highlights previously defined interval of convergence and reversal of
offset, coeval
with GDGT Zone III.
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
The ‘Methane Index’ does indeed increase in Zone III (Fig. 3.15B). However, an AOM
contribution to the GDGT assemblage is considered to be unlikely in this setting for three
reasons. First, the relative proportions of GDGT-2 remain lower than relative proportions
of GDGT-1 (Fig. 3.15C); in AOM settings, the ratio of GDGT-2/GDGT-1 is generally ≥1.
Second, low OM throughout the mid-Waipara River section indicates that it is not a
methanogenic setting (Sivan, 2007; Knittel and Boetis, 2009; Shuia et al., 2010). Third,
the mid-Waipara River section lacks biomarkers of archaeal origin that have been found
elsewhere associated with the anaerobic oxidation of methane. Such biomarkers include
acyclic C20 isoprenoid 2,6,11,15-tetramethylhexadecane (crocetane), C25 isoprenoids
2,6,10,15,19-pentamethylicosane (PMI), hydroxyarchaeol, and cyclic C40-biphytanols
(Schouten et al., 1998; Hinrichs et al., 1999; 2000; Pancost et al., 2000; 2001; Blumenberg
et al., 2004; Birgel et al., 2008). The absence of archaeol is particularly compelling as a
reason to discount contribution from methanotrophic or methanogenic archaea, as it is
found even in AOM settings characterised by diffusive methane flux (Aquilina et al, 2010)
and other ancient organic rich sediments (Pancost and Sinninghe Damsté, 2003; also see
Chapter 5; late Paleocene mid-Waipara River).
3.5.2.1.2. Interrogation of Modern GDGT Distributions
If the differences between
and
are not due to sedimentary inputs, they likely
reflect a combination of oceanographic and or ecological phenomena that have affected the
GDGT distributions of specific pelagic archaea preserved in Mid-Waipara River
sediments. There has been much work in modern oceanographic settings suggesting that at
least some aspects of GDGT distributions are caused by changes in archaeal assemblages
(i.e. a contribution from group II Euryarchaeota) rather than simply an adaptive response
to temperature (DeLong, et al., 2006; Ingalls, et al., 2006). Turich et al. (2007, 2008)
argued that community changes within meosphilic marine archaea regulate the lipid
patterns distinguishing discrete epipelagic and mesopelagic/upwelling zones, based on
GDGT distributions in suspended particulate matter (SPM) from a range of globally
distributed settings (Wuchter et al., 2005; Turich et al., 2007, 2008). Although archaeal
DNA studies by the authors were consistent with this, they were not performed on the
same sample set (Schouten et al., 2008). In fact, a study on surface waters of the North Sea
(Wuchter et al., 2006) indicated that GDGT concentrations track cell numbers of
Thaumarchaeota, suggesting that group II Euryarchaeota do not significantly contribute to
the flux of GDGTs to the sediments.
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Figure 3.16. Ratio of GDGT-2/GDGT-3 measured in suspended particulate matter (SPM)
through the water column at a range of localities. Adapted from Turich et al., (2007).
Revisiting the available raw GDGT data for SPM (Turich et al., 2007) in the context of
GDGT distributions reconstructed at mid-Waipara, it is observed that that proportions of
GDGT-3 relative to GDGT-2 generally exhibit large increases with depth (Fig. 3.16),
shifting the offset between
and
to negative values.
depth, but the ratio of GDGT-2/GDGT-3 increases such that
decreases with
reconstructions
become relatively warmer. This illustrates a theoretical scenario whereby a shift towards
deeper GDGT export depth causes a cooling in
concomitant with warmer absolute
temperatures, driven by an increase in the ratio of GDGT-2/GDGT-3 (Fig. 3.17). It
is therefore plausible that the transition from MW Zone II to Zone III reflects a shift in the
depth at which SPM is transported from, or an integration of SPM throughout the mixed
layer that is less influenced by surface SPM.
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Figure 3.17. Concept schematic diagram of GDGT export and the effect of the changes in
GDGT distributions (ratio of GDGT-2/GDGT-3) on the offset between
and
reconstructed SST. Grey band represents depth habitat of GDGT export. L and H refer to
and
reconstructed SST, respectively.
Intriguingly, there are several other modern settings associated with GDGT distributions
similar to those of Zone III, i.e. characterised by high GDGT-2/GDGT-3 ratios and
reversed offset between
-
reconstructed SSTs. In fact, a robust relationship
between these two parameters is evident in the modern ocean calibration dataset;
increasing GDGT-2/GDGT-3 ratios are associated with lower (and ultimately negative)
differences between
-
derived temperatures (Fig. 3.18B).
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Figure 3.18. Crossplot of GDGT-2/GDGT-3 ratio against offset between
and
reconstructed SSTs for (A) the mid-Waipara River section, with coloured points
indicating GDGT Zones, and (B) the modern core-top calibration data set (Kim et al.,
2010).
Most of the modern sites which exhibit a reversed offset between
and
SST
estimates of at least -1°C are located in the low latitude Atlantic. SSTs for these settings
are generally above 15°C and therefore expected to give similar
and
SST
estimates (Kim et al., 2010). However, satellite measured SSTs for the calibration core-top
samples from the Washington Margin and Santa Barbara Basin (SBB) are 15°C or lower;
they are also characterised by very high GDGT-2/GDGT-3 ratios (>10), making them
similar in some respects to the MW Zone III GDGT distributions.
SBB sediment trap data indicate that GDGT fluxes to the sediments during times of
enhanced productivity and upwelling reflect greater contribution from surface waters,
compared to low upwelling oligotrophic seasons where GDGTs distributions are inferred
to derive predominantly from the sub-surface (Huguet et al., 2007). This phenomena may
be attributed to enhanced transport via sinking particles during primary productivity
blooms (Wuchter et al., 2005; Huguet et al., 2006a), or transport of archaea to the surface
during upwelling (Huguet et al., 2007). Furthermore, Thaumarchaeota are consistently
detected in sub-surface waters throughout the year, but only detected in surface waters
during intervals of upwelling, and maximum thaumarchaeota productivity is found to occur
during periods of low primary productivity (Murray et al., 1999). Therefore, during periods
of low upwelling, relatively less of the surface temperature signal will be incorporated into
sedimentary GDGT distributions due to decreased SPM sinking from the surface and/or
less archaeal production in the surface waters.
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Investigation of raw sediment trap data (collected 2002/2003; unpublished, provided by
Carme Huguet) reveals high ratios of GDGT-2/GDGT-3 and reversed offsets between
and
across the low upwelling season, and a return to lower GDGT-2/GDGT-
3 ratios throughout the high upwelling interval, with warmer
relative to
SST reconstructions
. Based on the these sediment trap observations and inferences from the
SPM GDGT distributions, it is possible that the high ratio of GDGT-2/GDGT-3 in the SBB
core-top sediment (Kim et al., 2010) reflects the deeper GDGT export associated with low
productivity seasons.
The SBB does indeed share other oceanographic characteristics with the MW Zone III.
Primary productivity in the SBB is dominated by silica-secreting phytoplankton driven by
seasonal upwelling (Kincaid et al., 2000), similar to the high siliceous plankton
productivity and inhibited calcareous plankton productivity in MW Zone III, indicated by
elevated Si/Al and Ba/Al ratios and presumably caused by an incursion of cool, nutrientrich waters (Zachos and Arthur, 1989; Hollis and Strong, 2003). Dominance of the
peridinioid (assumed heterotroph; e.g. Jacobsen and Anderson, 1986; Askin, 1988)
dinoflagellate Palaeoperidinium pyrophorum in MW Zone III also indicates strengthened
upwelling and associated high productivity and nutrient availability (e.g. Bujak, 1984;
Wall et al., 1977; Bradford and Wall, 1984; Powell et al., 1990; Lewis et al., 1990; Powell
et al., 1992; Eshet et al., 1994; Fensome et al., 1993; Dale and Fjellså, 1994). Thus, MW
Zone III may reflect a similar regime of GDGT export to the SBB, with low contributions
of GDGTs from surface waters reflected in sediments, despite seasonally high primary
productivity.
Other modern sites which display a reversed offset between
and
at SSTs ≤
15°C occur in the high Southern latitudes. While offsets in these settings are less extreme
at ≤ -1°C, GDGT-2/GDGT-3 ratios are high and are also associated with seasonal
productivity (and therefore, potentially, seasonal GDGT export) variations (Rintoul and
Trull, 2001; Sokolov and Rintoul, 2007), perhaps associated with seasonal changes in the
‘thickness’ of the mixed layer (McCartney, 1977; Sarmiento et al., 2003). Seasonally
influenced GDGT distributions may therefore have relatively higher GDGT-2/GDGT-3
ratios than distributions less reflective of seasonal productivity.
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Based on the inferences from interrogation of SPM data described above (Fig. 3.16) and
inferences from contemporary SBB and Southern Ocean settings, high ratios of GDGT2/GDGT-3 within sediments may reflect a GDGT export regime weighted towards subsurface distributions (e.g. Fig. 3.17), as either a function of low GDGT contribution from
surface archaea, or a predominantly sub-surface thaumarchaeota habitat perhaps as a result
of an expansion of the mixed layer.
3.5.2.1.3. Revised Approach in the Application of TEX86 : Inferences From GDGT2/GDGT-3 Ratios.
The interrogation of modern settings (Fig. 3.16, 3.18) indicates that the ratio of GDGT2/GDGT-3 could reflect a change in oceanographic conditions that is partially related to
the depth of GDGT export and independent of SST in the modern calibration dataset (e.g.
Fig. 3.17). As the ratio of GDGT-2/GDGT-3 increases, the offset between
and
reconstructed SSTs decreases and eventually reverses (Fig. 3.13, 3.15), with
producing warmer temperatures than
. As such, the decision to apply
and or
should be based not only on the inferred growth temperature (Kim et al., 2010) but
also on the actual GDGT distributions. At GDGT-2/GDGT-3 ratios (≤ c. 3), the offset
between
and
is ≥ c. 4°C (Fig. 3.18B). These low GDGT-2/GDGT-3 values
are generally found in colder, high latitude sites which are included in the
calibration (Kim et al., 2010), and as such
may be better suited for such
conditions/distributions. In contrast, ratios higher than c. 6 correspond to situations where
estimates warmer SSTs than
(Fig. 3.18B); because the
calibration
excludes polar data, and consequently settings with low GDGT-2/GDGT-3 ratios, the
calibration may represent a better fit to distributions with these high GDGT2/GDGT-3 ratios.
and
yield similar SSTs when GDGT-2/GDGT-3 ratios are
between c. 4-6.
Samples from MW Zone III exhibit a higher GDGT-2/GDGT-3 ratios than samples in all
other zones (Fig. 3.18A). Samples from Zones I, II and IV all have GDGT-2/GDGT-3
ratios of < 3, corresponding to a large
and -
SST offset as observed in the
modern dataset (Fig. 3.18B). Samples in Zone III exhibit increased proportions of GDGT-2
relative to GDGT-3, and as such the offset between
and
SST trend towards
lower or negative values, but within ranges observed in the modern dataset for both
parameters.
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Based on these findings, the shift in distributions from MW Zone II to Zone III reflects a
shift in oceanographic conditions, perhaps related to the depth of GDGT export or altered
seasonal productivity, as also discussed previously in terms of GDGT concentrations. The
shift in the ratio of GDGT-2/GDGT-3 could indicate that the sole application of either
or
may not be appropriate across the entirety of the MW record. Instead,
could be more appropriate for the oceanographic conditions in Zone III, whereas
may be more applicable for Zones I, II and IV. Interestingly, if calibrations are
interchanged in this manner for MW, a cooling is still apparent in Zone III (as indicated by
the record degree of cyclisation, Fig. 3.12), but is less dramatic. The details of such
reconstructions will be discussed below.
3.5.3. Climate Succession at mid-Waipara River K/Pg Boundary Section
3.5.3.1. Maastrichtian and Earliest Danian Climate
The GDGT zonation scheme described for the mid-Waipara River K/Pg boundary section
may reflect changes in oceanographic and climatic conditions at mid-Waipara, and as such
provides a framework for interpreting the post-K/Pg boundary SO climate succession.
The high proportion of ferns in the late Maastrichtian (Zone I) strata suggests relatively
high rainfall and lack of severe winter freezing (Fig. 3.19A; Vajda and Raine, 2003).
GDGT derived SST estimates (Fig. 3.19C) range from 13-14°C (
based on earlier discussion,
) to ~22°C (
);
is assumed to be the more reliable indicator of SST
throughout this period, and SSTs of 12-14°C correspond well with the relatively mild
conditions indicated by the terrestrial palynological record. Furthermore, Maastrichtian
oxygen isotope records for DSDP Site 690 in the Weddell Sea (Stott and Kennett, 1988;
Kennett and Barker, 1990) indicate Antarctic SSTs of around 10-12°C in the final 20-30
Ky before the K/Pg boundary event; these are in good agreement with the
record for
mid-Waipara, as they fall within a similar range, but are slightly cool, reflecting the lower
paleolatitude of the mid-Waipara River section compared to ODP Site 690. Pre-K/Pg
boundary SSTs of c. 14-15°C are reported for DSDP Site 525 (Li and Keller, 1998), a midlatitude South Atlantic location (Walvis Ridge, near SW Africa). Although these
temperatures are warmer than the mid-Waipara
reconstructed SSTs, they may be
affected by diagenetic alteration of the carbonate, and as such may be biased towards
colder reconstructed SSTs (Zachos and Arthur, 1986). The latitudinal gradient may
therefore be stronger than suggested from the oxygen isotope data. The good agreement of
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SST reconstructions in Zone I with other climate records for the same period
indicates that
SST reconstructions are probably anomalously high, potentially
confirming the use of GDGT-2/GDGT-3 ratios to identify the most appropriate GDGTbased SST estimates.
The SST trends reconstructed for the ODP Site 690, however, also reflect a cooling in the
last 200 ky of the Maastrichtian, with SSTs decreasing from c. 16°C to ~10°C recorded
immediately prior to the K/Pg boundary. A cooling episode at the close of the
Maastrichtian has been regarded as a global event occurring within the final c. 100 ky of
the Maastrichtian by various authors (e.g. Srivastava, 1994; Frank and Arthur, 1999;
Keller, 2001; Nordt et al., 2003; Wilf et al., 2003; Habib and Saeedi, 2007; Thibault and
Gardin, 2007), although estimates of its duration vary. At mid-Waipara, the TEX86
reconstructions record relatively stable SSTs throughout Zone I (discounting the sample at
– 7 cm as an artefact of bioturbation);
SST estimates vary by c. 2°C, but the record
of weighted average number of cyclopentyl rings (Fig. 3.19D) confirms stable GDGT
distributions, with no evident cooling trend. The age model estimates the base of Zone I as
pre-dating the K/Pg boundary by c. 28 ky; thus a late Maastrichtian cooling trend may have
occurred earlier, although data from Bass River indicates a later timing of the cooling
trend, initiating just 22 ky before the K/Pg boundary (Olsen et al., 2002, Wilf et al., 2003).
Other New Zealand records, such as the K/Pg boundary sections in Marlborough, also do
not exhibit clear evidence for Maastrichtian cooling (Hollis, 2003; Hollis et al., 2003a). As
such, no noteworthy climate change trends are determined preceding the K/Pg boundary.
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96
Figure 3.19. Compiled climate indicators and palynological features of the mid-Waipara River section, including (A) distribution and percentage abundance
of major miospore groups; horizontal lines represent sample level (adapted from Vajda et al., 2001), (B) relative abundances of Trithyrodinium evittii and
Palaeoperidinium pyrophorum marine dinoflagellate cysts (from Willumsen, 2006), (C)
and
SST reconstructions and (D) weighted average
number of cyclopentyl rings for isoprenoidal GDGTs, excluding GDGT-0 and crenarchaeol. Features presented relative to GDGT zones. Note palynological
data extends up to 5 m, GDGT data extends to 20 m.
Chapter 3
Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
In terms of the more immediate (decadal to several ky time scale) post-K/Pg boundary
climate record, the differential survival pattern in New Zealand indicates extinction of
thermophilic planktic foraminifera and persistence of virtually all radiolarians and many
cosmopolitan planktic foraminifera (Hollis, 1997; 2003; Strong, 2000). This observation
lends support to the ‘impact winter’ hypothesis which predicts very transient (10 y – 2000
y) cooling, possibly as a result of the introduction of aerosols and dust from a bolide
impact into the atmosphere (Siggurdsson et al., 1992; Pope et al., 1997; Pierasso et al.,
2003). However, TEX86 records at mid-Waipara do not reflect cooling of SSTs across the
K/Pg boundary. This may in part be due to the intense bioturbation documented at the
K/Pg boundary layer, which may have diluted the expression of any extremely transient
climate perturbation. The irregularity of the K/Pg boundary layer may also indicate that the
horizon represents a condensed or truncated interval which fails to record the immediate
events of the K/Pg boundary. The sampling resolution and sedimentation rates are also
likely inadequate to record the very short duration of immediate events at the K/Pg
boundary; based on a sedimentation rate of 10.5 m My-1 given for Zone II, centennial scale
change would be recorded in millimetres of sediment.
It is contested that hiatuses may be present in the basal Danian of many K/Pg boundary
sites (Keller and MacLeod, 1991), perhaps linked to global regression (Schmitz et al.,
1992; Keller and Stinnesbeck, 1996, but see Kiessling and Claeys, 2001), although records
of local sea-level change are inconsistent, reflecting both regressions (e.g. Keller et al.,
1998) and transgressions (Pardo et al., 1999) even in tectonically stable areas. Such a
hiatus at the mid-Waipara River section would be particularly difficult to detect due to the
intense bioturbation at the K/Pg boundary.
Instead of recording a post-K/Pg boundary cooling, the transition from Zone I to Zone II
across the K/Pg boundary is marked by a shift to relatively warmer SSTs indicated by both
(c. 23-24°C) and
(c. 16-17°C) reconstructions (and confirmed by trends in
relative degree of GDGT cyclisation) (Fig. 3.19C, D). Warmer conditions at mid-Waipara
are also corroborated by the acme of Trithyrodinium evittii (Willumsen, 2006; Fig. 3.19B),
a well characterised tropical warm-water habiting dinoflagellate (Smit and Brinkhuis
1996). Its first occurrence is located just above the K/Pg boundary in the higher latitudes of
both Northern and Southern Hemispheres. This is interpreted as bipolar migration of this
species in response to the global warming during the early Danian (Smit and Brinkhuis,
1996; Nøhr Hansen and Dam, 1997; Brinkhuis et al., 1998; Willumsen 2000; 2006,);
Additionally, a short lived c. 100 ky proliferation of planktic foraminifera at Flaxborne
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River has also been cited as possible evidence for warming following the K/Pg boundary
event in New Zealand (Hollis, 2003; Hollis et al., 2003b).
As with Zone I,
SST reconstructions are considered in Zone II for comparison with
other records due to low GDGT-2/GDGT-3 ratios across this interval. The record therefore
indicates a c. 2-3°C sea surface warming immediately after the K/Pg boundary (using
across both Zone I and II would produce an analogous warming trend. It also
coincides with an abrupt increase in fern spores from an average of 40% to >70% in the
overlying c. 25 cm, a so-called “fern spike” (Vajda et al., 2001, Vajda and Raine, 2003;
Fig. 3.19A). The duration of Zone II is estimated to be c. 24 ky, but it is truncated by the
unconformity at c. 25cm. As a result, speculation on the true duration of this warm
interval is not possible. However, the magnitude of warming agrees with other high
latitude SST records derived from foraminiferal and fine fraction carbonate oxygen
isotopes for the earliest 100 ky of the Danian (Stott and Kennett, 1990; Barrera and Keller,
1994). Earliest Danian SST warming of c. 2-3°C is also inferred at several globally
distributed DSDP and ODP sites, such as in the Indian Ocean, from the oxygen isotopic
composition of calcareous nannoplankton (Oberhänsli, 1986), and from planktonic
foraminiferal δ18O records in northwest and central Pacific (Douglas and Savin, 1971;
Boersma and Shackleton, 1981). Analysis of fossil leaf physiognomy suggests post-K/Pg
boundary continental warming of c. 2°C in the Western interior of North America,
although a comparatively shorter duration of warm climate is inferred (Wilf et al., 2003).
A warming in the earliest Danian is corroborated by dinoflagellate records across the K/Pg
boundary in Tunisia, Denmark and Spain, albeit occurring after a transient cooling at the
K/Pg boundary itself (Brinkhuis et al., 1998).
Furthermore, recently reported high resolution benthic oxygen isotope records (Westerhold
et al., 2011) indicate a gradual bottom water warming of c. 2°C in the equatorial Pacific
over c. 500 ky post-K/Pg. Observations of decreasing carbonate δ13C values suggest that
the warming could have been driven by the third phase of the Deccan Trap volcanism
(Knight et al., 2003; Baksi, 2005; Knight et al., 2005; Chenet et al., 2007; Chenet et al.,
2008; Chenet et al., 2009) which occurred after the K/Pg boundary for a duration of c. 500
ky. In contrast, modeling results indicate that flood basalt volcanism might not emit carbon
at a sufficient rate to cause noticeable warming, particularly during the early Paleocene
(Caldeira and Rampino, 1990; Self et al., 2006). Alternatively, CO2 release as a result of a
bolide impact (O’Keefe and Ahrens, 1989; Pope et al., 1997; Kring, 2007), or the
diminished CO2 drawn down by a reduction in oceanic export production after the K/Pg
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boundary event might have contributed to warming (Hsü and McKenzie, 1985; Zachos et
al., 1989; D’ Hondt et al., 1998).
The relatively instantaneous SST warming across the K/Pg boundary at mid-Waipara (Fig.
3.19C) suggests a relatively rapid warming mechanism, which may be in disagreement
with the more gradual benthic warming inferred from the equatorial Pacific (Westerhold et
al., 2011). Zachos and Arthur (1986) suggested that the high variability of trends between
sites is evidence for no systematic major systematic change in benthic temperatures across
the K/Pg boundary. However it is compelling that numerous proxies from multiple low and
high latitude sites record a similar magnitude of overall warming. Causes of warming
remain the subject of debate. Impact related theories for pCO2 increase do invoke transient
climate change mechanisms, such as vaporisation of carbonate rich target rock (O’Keefe
and Ahrens, 1989; Hildebrand et al., 1991). Reconstructions of pCO2 from fossil leaves
(Beerling et al., 2001) also suggest a transient increase in atmospheric CO2 in the wake of
the K/Pg boundary event, (pCO2 value of >2300 ppm) although the absolute values are
contested as they are based on leaf stomatal indices of uncalibrated fern leaves (Wilf et al.,
2003). Furthermore, the magnitude of warming reconstructed at mid-Waipara is of similar
magnitude to the suggested increase in global mean average temperature based on
estimates of amount of CO2 which could be added to the atmosphere by the impact (1 –
1.5°C; Pierazzo et al., 1998).
In summary, the record of warm earliest Danian climate in New Zealand may be reflective
of a global post-K/Pg boundary warming trend, likely reflecting elevated atmospheric
pCO2. However, estimation of the exact duration of the warm period is confounded due to
bioturbation at the K/Pg boundary and truncation of Zone II by an unconformity.
3.5.3.2. Danian Climate: Recovery Following the K/Pg Boundary Event
The transition between Zone II and Zone III, dated at c. 24 ky post K/Pg boundary, is
truncated by an unconformity at c. 25 cm representing up to 0.945 My of non-deposition or
an erosional event. The base of Zone III is therefore tentatively dated at c. 64.53 Ma, with
a duration of c. 240 ky. This hiatus may be related to similar events in other New Zealand
sections; unconformities in the basal 100 ky of Paleocene strata at Mead and Branch
streams (Marlborough, neritic) and a correlated increase in biogenic silica concentration at
Flaxborne River (Marlborough, mid-bathyal) are thought to reflect relative sea-level fall, in
turn possibly related to cool climatic conditions and strengthened Antarctic bottom water
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(AABW) flow (Hollis, 2003; Hollis et al., 2003a,b). Several lines of geochemical and
palynological evidence also suggest a relatively cool climate through Zone III; these are
compiled in Figure 3.19, and discussed below.
High gymnosperm and relatively low tree fern abundance across Zone III (Fig. 3.19A) are
indicative of a cool-temperate terrestrial climate, whilst lower total abundance of ferns
compared to the Maastrichtian assemblage suggests relatively cooler and perhaps drier
conditions (Vajda and Raine, 2003). As discussed earlier, the use of
to reconstruct
SSTs across Zone III is tentatively proposed, based on the high values of GDGT-2/GDGT3 which have here been inferred to indicate sub-surface depths of GDGT export. SSTs
reconstructed in this manner indicate a slight cooling of c. 2°C at the base of the interval,
with subsequent warming to c. 19°C, i.e. warmer than
SST estimates for Zones I
and II. However, the decrease in weighted average number of cyclopentyl rings clearly
indicates a shift to the lowest degrees of GDGT cyclisation for the entire record, indicating
a relatively cooler growth environment in Zone III. This is corroborated by the coeval
acme of peridinioid dinoflagellate P. pyrophorum throughout Zone III (Fig. 3.19B), which
as an assumed heterotrophic peridinioid (Jacobsen and Anderson, 1986; Askin, 1988) also
indicates cooler marine conditions (Matsuoka, 1992) possibly reflective of strengthened
upwelling (Fensome et al., 1993), and has been interpreted at mid-Waipara to reflect a
regional pulse of cool water (Willumsen 2000, 2002).
A cooler climate across Zone III at mid-Waipara is also suggested, based on an increase in
inferred biogenic silica and barium throughout this interval (Hollis and Strong, 2003).
Absolute values of Si and Ba are low throughout mid-Waipara, and thus may be
complicated by terrigenous input, but a tentative correlation may still be made between this
interval and highly biosiliceous sediments from the Marlborough portion of the East Coast
Basin to the north (Hollis, 2003; Hollis et al., 2003a; 2003b). These sediments exhibit
parallel trends in biogenic silica, barium and the abundance of diatoms, relative to
radiolarians indicate that the siliceous sediments in Canterbury and Marlborough signal
high biological productivity. Low abundance of planktic foraminifer also indicates a very
cool climatic regime. Furthermore, the timing attributed to this cool interval (c. 64.53 –
64.29 Ma) corresponds to a carbonate minima believed to represent cool oceanic
conditions in South Atlantic DSDP Site 528 (D'Hondt et al., 1996a) and an episode of
maximum cooling based on δ18O records from North Pacific DSDP Site 577 (Zachos et al.,
1989).
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This inconsistency between the TEX86 SST reconstructions and the other indicators of
climate highlights the limitations of the approach taken in alternating the current TEX86
calibrations.
SST reconstructions in Zone III are warmest for the upper two samples
(f215, 1.25m; f218, 1.55m), in which GDGT-2/GDGT-3 ratios trend towards lower values.
Indeed, a shift in oceanographic conditions is also indicated by the scarcity of planktic
calcareous foraminifera above 1.25 m; this is inferred to indicate shallower water depth or
distinctly different oceanographic conditions than the underlying sediments (Hollis, 2003;
Hollis and Strong, 2003). It could be speculated that these oceanographic changes may
provide a mechanism for shallower GDGT export depths, in agreement with the decreasing
GDGT-2/GDGT-3 ratios in the upper samples of Zone III and into Zone IV. Cluster
analysis (Fig. 3.10C) revealed that these upper two samples of Zone III clustered together
with the basal sample (f199; 28 cm), essentially representing more ‘intermediate’ GDGT
distributions. Selection of calibration based solely on GDGT-2/GDGT-3 ratio for these
samples is therefore particularly tenuous. Because a change in GDGT export depth is
inferred as a mechanism for shifting GDGT distributions independently of SST, the
intermediate distributions could represent the progression of changing conditions. There is
also likely to be a range of export depths (rather than two discrete end members) expressed
in the calibration data-set, thus the accuracy of TEX86 SST estimations may be affected by
progressive change throughout a record. The calibrations were not constructed using the
ratio GDGT-2/GDGT-3 as a device to differentiate discrete settings, thus its use to inform
alternation of calibrations here is accepted to be tenuous. Therefore the absolute
temperatures reconstructed for Zone III should be treated with caution. However, based on
the other geochemical and palynological evidence discussed, the inferred cooling from the
decrease in degree of GDGT cyclisation across Zone III likely represents the true relative
climate signal.
Cool climatic conditions for the first 1 My of the Paleocene are consistent with pCO2
estimates from paleosols in Alberta, Canada (Nordt et al., 2002), which indicate relatively
low values of c. 850 ppmv for the latest Cretaceous and earliest Paleocene, apart from one
value of c. 1500 ppmv that is assumed to represent the late Maastrichtian warm episode
(Barrera and Savin 1999). An extremely high pCO2 value of >2300 ppmv for the earliest
Paleocene is suggested based on stomatal indices of fossil ferns in North America
(Beerling et al. 2002), although these are considered tenuous as they are based on a fern
species with uncalibrated stomatal indices (Wilf et al. 2003).
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Based on the ratio of GDGT-2/GDGT-3, use of
is again indicated for Zone IV,
which estimates SSTs for Zone IV of c. 12°C (Fig. 3.19C). The transition from Zone III to
Zone IV is reconstructed as a cooling, despite an increase in the degree of GDGT
cyclisation (Fig. 3.19C,D). As discussed for the transition from Zone II to Zone III, this
discrepancy is likely to be an artefact of shifting depths of GDGT export and the tentative
nature of calibration selection for each GDGT Zone, particularly for the more
‘intermediate’ GDGT distributions. However, the
SST reconstructions across Zone
IV are in agreement with other indicators of climate throughout this interval. Increase in
the relative degree of GDGT cyclisation from Zone III into Zone IV reflects a warming
into the longer-term trend towards stable marine climate conditions similar to late
Maastrichtian reconstructions of Zone I. (Fig. 3.12, 3.19E). Moreover, the second acme of
T. evittii occurs in Zone IV (Fig. 3.19B), also indicating a warmer marine climate than
Zone III, although
reconstructions indicate that the SSTs in Zone IV are cooler than
the prior T. evittii acme in Zone II. SSTs are also estimated to be slightly cooler in Zone IV
(c. 12°C) than Zone I (c. 13-14°C), which is corroborated by the inferences from terrestrial
palynology described above. Furthermore, the dominance of Phyllocladidites mawsonii
also suggests cool-temperate conditions (Vajda and Raine, 2003; Fig. 3.19A).
Interestingly, continental palaeotemperature reconstructions for North America based on
leaf fossil assemblages also suggest cool climate conditions for the first 1 My of the
Paleocene (Wilf et al., 2003; Peppe, 2010), with a shift to warmer conditions possibly
marked by the development of tropical rainforest in the western interior of North America
at c. 64.1 Ma (Johnson and Ellis, 2002); the base of Zone IV is dated at c. 64.3 Ma and
thus may reflect expression of the same climate succession, allowing for uncertainties in
the mid-Waipara River section age model associated with the unconformity. Relatively
cool Danian climate is also inferred from clay mineralogy at sites in Bulgaria (Adatte et
al., 2002b) and Kazakhstan (Pardo et al., 1999).
The trends in GDGT distributions considered together suggest that the early c. 1.2 My of
the Danian at mid-Waipara (from the base of Zone II at 65.5 Ma to the base of Zone IV at
c. 64.3 Ma) was characterised by climate instability, resulting from the perturbations to
ecosystems and biogeochemical cycles at the K/Pg boundary, culminating in cool
conditions similar to latest Maastrichtian climate. Although much of this time interval is
considered to be missing due the unconformity at c. 25 cm, related sections in
Marlborough indicate correlative trends; oscillations in biogenic silica throughout the early
Danian at these sections are thought to reflect high-amplitude climate cycles within a cool
climatic regime (Hollis, 2003; Hollis et al., 2003a,b).
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An overall relatively cooler but unstable Danian climate is also indicated by a synthesis of
evidence based on reconstruction of dinoflagellate successions from Tunisia, Spain and
Denmark, which indicate fluctuating periods of warmth and cooling, although the interval
studied is estimated to be c. 100 ky post K/Pg boundary (Brinkhuis et al., 1998 and
references within) and so is perhaps less reflective of the longer term Danian trends.
A high resolution bulk carbonate δ18O record from ODP Site 208 (south Atlantic, Walvis
Ridge) also reveals high amplitude variations throughout the initial c. 1.2 – 1.5 My of the
Danian (Fig. 3.20). Although the palaeoclimatic utility of such bulk carbonate δ18O records
is limited (Paull and Thierstein, 1987), it may be noted that Zone III appears to correspond
with a δ18O maximum (i.e. coldest temperatures) at ODP Site 1262, likely relating to a sea
surface cooling. However, due to the tenuous nature of the mid-Waipara age model, Zone
III could correlate to a number of other δ18O maxima in the record. D’Hondt et al. (1996a)
also observe high-amplitude low-frequency climate instability in the first 1 My of the
Danian, based on a succession of carbonate minima at DSDP Site 528 (also located at
Walvis Ridge).
Figure 3.20. Time scaled comparison of (A) bulk carbonate δ18O from ODP site 1262
(Kroon et al., 2007), and (B) mid-Waipara River TEX86 SST reconstructions. Error bars
represent simple propagated analytical and standard calibration error. Age model for ODP
Site 1262 converted to GTS2004 from Option 1 of Westerhold et al., 2008 (using the
orbital solution of Laskar et al., 2004) based on geomagnetic chronographic tie points
(Westerhold, 2008) to facilitate comparison with mid-Waipara.
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The minima are argued to reflect a c. 100 ky pacing; the authors attribute this to enhanced
oceanic response to orbital eccentricity as a result of long term disruption to
biogeochemical cycles which moderate seasonal variations in climate forcing factors
(D’Hondt et al., 1996a). In particular, CO2 release as a result of a bolide impact (O’Keefe
and Ahrens, 1989; Pope et al., 1997; Kring, 2007) together with the disruption and
prolonged recovery of marine productivity throughout the early Danian (up to 3 My) is
cited as a likely mechanism for carbon cycle instability (Hsü et al., 1992; Zachos and
Arthur, 1986; D’Hondt et al., 1996a, 1998; Coxall et al., 2006; Thomas et al., 2009). The
nature of biogeochemical perturbations and disruption to the carbon cycle at mid-Waipara
will be investigated in Chapter 4.
3.6. Conclusions
The first application of TEX86 across the K/Pg boundary to date has been presented here
for the mid-Waipara River section, New Zealand. The dramatic shifts in GDGT
distributions stimulated an interrogation of modern GDGT distributions in sediments and
suspended particulate matter, the results of which illustrate important considerations for the
continued application of TEX86. The relative offset between
and
SST
estimates have been shown here to be essentially determined by the relative proportion of
GDGT-2 to GDGT-3, and this parameter appears to be largely independent of SST.
Furthermore, the ratio of GDGT-2/GDGT-3 may reflect the depth of GDGT export. As
such,
may reconstruct SSTs more reliably for distributions with high ratio of
GDGT-2/GDGT-3, and
may therefore be more favourable for distributions with
low GDGT-2/GDGT-3 ratios. However, the calibrations have not been constructed using
the ratio of GDGT-2/GDGT-3 as a means of distinguishing discrete environments, and as
such the approach described is currently tentative. The limitations of alternating the current
calibrations across the record has been outlined, and further work on TEX86 proxy
development should focus upon reconciling the relationship between ratio of GDGT2/GDGT-3, depth of GDGT export and the expression of growth temperature.
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Terrestrial and Marine Climate Across the K/Pg Boundary at mid-Waipara River, New Zealand
The climate succession across the mid-Waipara River K/Pg boundary section has been
interrogated by integrating the analysis of GDGT distributions with previously detailed
climate indicators such as terrestrial (Vajda et al., 2001; Vajda and Raine; 2003) and
marine (Willumsen, 2006) palynomorphs, and inferences from other geochemical analysis
(Hollis, 2003; Hollis and Strong, 2003). No evidence for pre-K/Pg boundary climate
change, as suggested by other workers (Stott and Kennett 1990; Abramovich and Keller
2002; Adatte et al., 2002a; Olsson et al., 2002; Wilf et al., 2003), has been determined at
mid-Waipara, although the record may not extend back far enough to record a cooling
trend. A warming of 2-3°C persisting for at least 24 ky has been reconstructed in the
earliest Danian, perhaps related to elevated pCO2 as a result of volcanism (Knight et al.,
2003; Baksi, 2005; Knight et al., 2005; Chenet et al., 2007; Chenet et al., 2008; Chenet et
al., 2009) or bolide impact related release of CO2 (O’Keefe and Ahrens, 1989; Pope et al.,
1997; Kring, 2007).
A relatively cooler marine climate is inferred for sediments above an unconformity at c. 25
cm which truncates the earliest Danian warm period, based on GDGT distributions and the
correlation of this interval with highly biosiliceous intervals elsewhere in New Zealand,
which are suggested to be indicative of enhanced upwelling and cool climatic conditions.
TEX86 reconstructions are somewhat hampered by the limited applicability of the current
calibrations in terms of the ratio of GDGT-2/GDGT-3, and it is possible that both
calibrations over-estimate temperatures at this interval. Warmer SSTs are reconstructed
across Zone IV, approaching temperatures similar to, but slightly cooler than SSTs
reconstructed for the Maastrictian. Based on the climatic succession reconstructed at midWaipara, and correlation with other New Zealand K/Pg boundary records at Marlborough,
an unstable climate is suggested for the first c. 1.2 My of the Danian. This is in agreement
with records from the south Atlantic (D’Hondt, 1996a; Kroon et al., 2007), and lends to the
suggestion that the events at the K/Pg boundary caused long-term disruption to
biogeochemical cycles.
105
Chapter 4
Ecological and Carbon Cycle Perturbation
Across
the
Cretaceous
/
Paleogene
Boundary at mid-Waipara River, New
Zealand
106
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.1. Introduction
The Cretaceous/Paleogene (K/Pg) boundary is associated with one of the five largest mass
extinction events to occur in Earth history and major changes in the global environment.
Extinctions in the marine realm were extreme (e.g. up to 90% for foraminiferal species)
(D’Hondt et al., 1996), and homogenization of the marine surface-to-deep water carbon
isotope gradient immediately following the K/Pg boundary event (Arthur et al., 1979;
Boersma and Shakleton, 1981; Shakleton and Hall, 1984; Zachos and Arthur, 1986;
Zachos et al., 1989; Kump, 1991; Coxall et al., 2006) has been attributed to cessation of
primary productivity in the surface ocean, the so-called ‘‘Strangelove Ocean’’ (Hsü et al.,
1982; Hsü and McKenzie, 1985; Keller and Lindinger, 1989; Stott and Kennett, 1989;
Zachos et al., 1989; Zachos et al., 1992). A shutdown or reduction in the uptake of 12C by
photosynthetic phytoplankton, and increased biomass burning (Wolbach et al., 1988; Ivany
& Salawitch, 1993), could together have led to an accumulation of relatively 13C-depleted
CO2 in the atmospheric reservoir. Evidence for the transfer of 12CO2 from the atmosphere
to the terrestrial biosphere reservoir (via photosynthesis) is reflected in a negative carbon
isotope excursion (CIE) recorded in δ13C values of terrestrial biomarkers in Europe
(Arinobu et al., 1999) and bulk terrestrial organic matter from sites in North America
(Schimmelmann and DeNiro 1984; Arens and Jahren, 2000).
Although plankton populations apparently recovered quickly from K/Pg boundary
mortality, initial recovery of the surface-to-deep water carbon isotope gradient occurred
over approximately 0.5 – 1 My (Alcalá-Herrera et al., 1992; Hollander et al., 1993;
D’Hondt et al., 1998), indicating that the initial stages of marine recovery were likely to
have been characterised by instability and fluctuations in the global biogeochemical cycles
(Hollander et al., 1993, D’Hondt et al., 1996a, Hollis, 2003). Superimposed on the earlier
stages of recovery were periodic episodes of unusual plankton productivity (Perch-Neilson
et al., 1982; Hollander, 1993), which are inferred to reflect the inherent instability of the
early Danian marine system. High amplitude-low frequency (c.100 ky) variations in
magnetic susceptibility in records from the mid-latitude Atlantic up to 1 My post-K/Pg
boundary are inferred to reflect enhanced sensitivity to eccentricity-forcing (D’Hondt et
al., 1996); this is suggested to either indicate the reduced capacity of terrestrial or marine
ecosystems in buffering seasonal variation in climate forcing factors (i.e. CO2)
concentrations, or the formation of an equatorial ring of impact-debris (Schultz and Gault,
1990) enhancing insolation in the low-mid latitudes.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
The full re-establishment of the surface-to-deep water carbon isotope gradient (i.e. the
transport of reduced carbon into the deep ocean) may not have occurred for up to 1–3 My
post-K/Pg boundary (Keller and Lindinger, 1989; Zachos et al., 1989; Zachos et al., 1992;
D’Hondt et al., 1998; Coxall et al., 2006). This long interval of a low deep-sea carbon flux
has been interpreted as reflecting unusually low flux of organic carbon to the deep sea in
an ecologically-altered normal-productivity ocean, termed the ‘‘Living Ocean’’ model
(D’Hondt et al., 1998).
In contrast, terrestrial ecosystems are believed to have recovered faster from the events of
the K/Pg boundary than counterpart marine ecosystems (Beerling et al., 2001). Severe
extinctions in terrestrial palynoflora are documented in southern North America (Tschudy
et al., 1984; Wolfe and Upchurch, 1986; Johnson 1992; Sweet et al., 1999; Sweet and
Braman, 2001). Orth et al. (1981) first documented an abrupt replacement of diverse flora
with fern spores at the K/Pg boundary in New Mexico, interpreted as rapid colonisation by
opportunistic fern species following widespread deforestation. Extinctions outside North
America were apparently less severe (Beerling et al., 2001, Vajda and McLoughlin, 2009),
although dramatic short term changes in relative abundances of plant groups reflect the
global nature of the perturbation and widespread mass-kill of vegetation, with associated
colonisation by opportunistic species. (Vajda and McLoughlin, 2009).
In general, terrestrial floral recovery manifested as a vegetation succession from mixed
cosmopolitan Maastrichtian assemblages to less diverse assemblages above the K/Pg
boundary, exhibiting a ‘quasi-succession’ (Wolfe and Upchurch, 1986) from pioneer-type
species such as ferns (Orth et al., 1981; Tschudy et al., 1984; Jerzykiewicz & Sweet, 1986;
Nichols et al., 1986; Saito et al., 1986; Wolfe & Upchurch, 1986; Bohor et al., 1987;
Lerbekmo et al., 1987; Upchurch & Wolfe, 1987; Johnson et al,. 1989; Upchurch 1989;
Sweet et al., 1990, 1999; Wolfe 1991; Sweet & Braman, 1992, 2001; Nichols et al., 1992;
Braman et al., 1993; Vajda et al., 2001; Vajda and Raine; 2003), bryophytes (Brinkhuis &
Schiøler, 1996; Herngreen et al., 1998) or opportunistic angiosperms (Sweet et al., 1990)
to gradually more diverse flora. In some sections from northern Canada, a rise in
angiosperm pollen abundance occurred following the K/Pg boundary, comparable to the
fern spike (Sweet et al., 1990). In these localities, the pioneer vegetation was most
probably made up of opportunistic, herbaceous angiosperms instead of ferns. The fern
spike, followed by a Paleocene gymnosperm dominated assemblage, has also been
reported from marine rocks in Hokkaido, Japan (Saito et al., 1986). In Europe a bryophyte
spike, comparable to the fern spike, is reported from K/Pg boundary sections in The
Netherlands at Curf Quarry (Herngreen et al., 1998) and in the Geulhemmerberg caves
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
(Brinkhuis & Schiøler, 1996). Disruption of the vegetation at the K/Pg boundary in New
Zealand is recorded by an increase in fern spores, reduction in gymnosperm pollen, and
temporary loss of angiosperm pollen both in mid-Waipara and in the terrestrial sections of
Moody Creek Mine and Compressor Creek (Vajda et al., 2001; Vajda and Raine, 2003).
The mid-Waipara River section is the most complete known record of the K/Pg boundary
from a neritic setting (Strong, 1984, Brooks et al., 1986b, Hollis and Strong, 2003;
Morgans et al., 2005), providing a crucial link between bathyal marine and terrestrial
records. The presence of sufficiently abundant and thermally immature organic carbon
makes the mid-Waipara River site ideal for organic geochemical analysis. Changes in
sources of organic matter across the K/Pg boundary at mid-Waipara River are explored,
documented by exceptionally preserved terrestrial and marine derived biomarkers. The
carbon isotopic composition of a suite of biomarkers determined to evaluate the
relationships between terrestrial and marine carbon cycling, and the extent to which the
carbon cycle was perturbed and subsequently recovered in both systems across the K/Pg
boundary and into the early Danian. A further aim of the study is to determine whether
Danian climate instability suggested from the GDGT distributions (as discussed in Chapter
3) is related to instability in the carbon cycle, and to estimate how prolonged the instability
of the carbon cycle may have been.
4.2. Site Description
The K/Pg boundary at mid-Waipara is located at the base of a 4-m thick, largely noncalcareous, glauconitic sandstone, which forms the uppermost unit of the Conway
Formation (Chapter 3, Fig. 3.3). The underlying Conway Formation is a more mud-rich
and calcareous glauconitic sandstone. The boundary itself is an irregular c. 5-cm thick,
‘rusty’ iron-stained weathered interval which stands out from the background sandstone on
weathered surfaces but is very difficult to trace on fresh surfaces. The base of this interval
provides the stratigraphic position of the K/Pg boundary, herein given as 0 cm (Chapter 3,
Fig. 3.3). The irregularity appears due to intense bioturbation both above and below the
boundary. Detailed site description and age controls are described in full in Chapter 3;
correlations of New Zealand Stages with International epochs and microfossil zones are
based on the stratigraphic ranges of key taxa of foraminifera, calcareous nannofossils,
dinocysts and radiolarians. The New Zealand Paleogene timescale of Cooper (2004) is
109
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
correlated to the Geological Time Scale 2004 (GTS2004; Gradstein et al., 2004) and that
timescale is used throughout this Chapter.
4.3. Materials and Methods
4.3.1. Biomarker Analyses.
The methodologies used are described in full in Chapter 2. In summary, sediments were
extracted under reflux for 24 h using a Soxhlet apparatus. TLEs were subsequently
fractionated on aminopropyl SPE to generate neutral and acid fractions and the neutral
fraction fractionated using an (activated) alumina flash columns to generate apolar and
polar fractions. Polar fractions were derivatised with BSTFA, acid fractions were
methylated with BF3/MeOH, then derivatised with BSTFA. All fractions were analysed by
GC, and biomarkers quantified by GC-MS. The carbon isotopic compositions of
methylated n-alkanoic acids were determined by GC-C-IRMS.
4.4. Results
Four stratigraphic zones were identified for the mid-Waipara River section in the previous
chapter, based on key boundary intervals (i.e. the K/Pg boundary and an unconformity at c.
25 cm above the K/Pg boundary) and the relative distributions of glycerol dialkyl glycerol
tetraether lipids (GDGTs) produced by pelagic Thaumarchaeota. Those GDGT zones were
inferred to represent distinct marine depositional environments and/or climatic conditions
in the SW Pacific Ocean, and that same stratigraphic framework is maintained here in
order to interrogate carbon cycle dynamics and ecological changes through the section.
4.4.1. Bulk Analysis
Total Organic Carbon (TOC) contents are less than 1% throughout the section (Fig. 4.1).
Values are variable and range from c. 0.25% to 0.50% throughout the late Maastrichtian (70 cm to 0 m), with a general trend towards lower values approaching the K/Pg boundary.
Values fall within a similar range above the K/Pg boundary, fluctuating from c. 0.20% to
0.45% throughout the lower 22 cm of Danian strata and continuing the weak Maastrichtian
trend towards declining values. Above the unconformity at c. 25 cm, TOC contents drop to
110
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
lower and less variable values of c. 0.12% from 28 cm to 75 cm, before increasing to a
maximum value of c. 0.78 % at 7.84 m. A longer term decline in TOC contents to c. 0.50%
is then evident in the upper part of the section (7.84 m to 20 m).
Figure 4.1. TOC content throughout the mid-Waipara River section. Note the change in
depth scale above 5 m, herein indicated by a break in the ordinate axis.
Bulk organic carbon isotope analysis (δ13C values) of 30 sediments spanning -60 cm to
1.31 m was performed at GNS (NZ), and the results were provided by Christopher Hollis
(GNS Science, NZ). δ13CTOC values are relatively stable (Fig. 4.2), ranging from c. -27 ‰
to -29 ‰ through the upper 60 cm of Maastrichtian strata. A transient positive shift to c. 24 ‰ is observed at 5 cm above the boundary; there is no apparent change associated with
the K/Pg boundary horizon at 0 cm. δ13CTOC values then increase in the overlying sample
to c. – 26.5 ‰, with higher values persisting to 10 cm above the K/Pg boundary. δ13CTOC
then remain essentially stable at c. -28 ‰ to -28.5 ‰, exhibiting only one deviation to
more negative values of c. -29.3 ‰ at 23 cm, just prior to the inferred haitus indicated by
the unconformity at c. 25 cm.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.2. Carbon isotopic composition of bulk organic carbon (δ13C) at the mid-Waipara
K/Pg boundary section. Results provided by Christopher Hollis (GNS Science, NZ)
4.4.2. Biomarker Sources, Concentrations and Distributions
All hydrocarbon fractions contain a homologous series of n-alkanes (Fig. 4.3A, B) with a
relatively strong odd-over-even predominance. Low molecular weight (LMW; C15-21) nalkanes dominate throughout GDGT Zones I, II and III (-0.7 m to 2.75 m), whereas high
molecular weight homologues (HMW; C25-33) dominate in Zone IV (4.11 m to 21 m). A
series of hopanes ranging from C27 to C33 (Fig. 4.3C), as well as hop-13(18)-enes and hop17(21)-enes, are present throughout the section, usually in concentrations similar to HMW
n-alkanes. 17β(H),21β(H)-homohopane (C31ββ hopane) and 17β(H),21β(H)-hopane (C30ββ
hopane) are predominant, reflecting the relatively low thermal maturity of the section
(Ourisson et al., 1979; Peters and Moldowan, 1991; 1993). The acyclic isoprenoidal
hydrocarbons pristane (Pr) and phytane (Ph) are present in concentrations similar to cooccurring LMW n-alkanes (Fig. 4.3B). Also present in many samples is a pentacyclic
triterpenoid, tentatively identified as taraxer-14-ene.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.3. Apolar fraction of sample f539 (7.84 m). (A) Total ion current (TIC)
chromatogram. Numbers correspond to carbon chain length of n-alkanes. I.S = internal
standard (5α-androstane), resolved in full with m/z = 71 partial chromatogram (B). Pr =
pristane, Ph = phytane. (C) Hopanes and hopenes resolved on m/z=191 partial
chromatogram. Numbers correspond to number of carbon atoms in hopane/hopene
structure, annotated with stereoisomeric configuration of 17(H)21(H) for hopanes.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Polar fractions contain a series of predominantly even-carbon number n-alcohols in a
generally tri-modal distribution: dominant components throughout most of the section are
C18, C22 and C28, with subordinate concentrations of C16, C26 and C30. LMW and C22 nalcohols dominate across Zones I, II and III, whereas relative proportions of C28 are
elevated in Zone IV. Also present in the polar fraction are sterols; amongst those identified
are cholest-5-en-3β-ol (cholesterol; 27Δ5), 5α-cholestan-3β-ol (cholestanol; 27Δ0), 24ethylcholest-5-en-3β-ol (β-sitosterol; 29Δ5) and 24-ethyl-5α-cholestan-3β-ol (sitostanol;
29Δ0).
A mono-unsaturated 4-methyl C30 sterol was also identified in the polar fractions, together
with a structurally similar saturated 4-methyl C30 sterol. These sterols are tentatively
identified as 4α,23,24-trimethylcholest-22-en-3β-ol (dinosterol; 30Δ22) and 4α,23,24trimethyl-5α-cholestan-3β-ol (dinostanol; 30Δ0), respectively. However, these compounds
are present in relatively low abundances, making it difficult to confirm identification and it
is possible that 4-methy,24-ethyl analogues (4α-methyl-24-ethyl-5α-cholestan-3β-ol and
4α-methyl-24-ethyl-5α-cholest-5-en-3β-ol, respectively) are instead present or co-eluting.
Trace amounts of 24-methyl-5α-cholest-5-en-3β-ol (campesterol; 28Δ5) were also detected
in some samples characterised by relatively high sterol content. A pair of hopanones, 22,
29,30-trisnorhopan-21-one and 30-norhopan-22-one, were also identified in all samples,
based on published mass spectral information (Barakat et al., 1990).
Acid fractions are dominated by a homologous series of n-alkanoic acids (Fig. 4.4A). In
particular C16 and C18 are the predominant components throughout much of the section,
with subordinate maxima of the C22 and C26-28 homologues. However, LMW (C14-20)
compounds are less dominant over the HMW components in much of Zone I (e.g. Fig.
4.4B), and throughout Zone IV. C30, C31 and C32 17(H),21(H)-hopanoic acids are present at
concentrations similar to or slight greater than those of HMW (C26-34) n-alkanoic acids
throughout the mid-Waipara River section, with a predominance of 17β(H),21β(H)bishomohopanoic acid (C32) (Fig. 4.4A).
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.4. Methylated acid fraction of sample f172 (-27 cm). Total ion current (TIC)
chromatogram. I.S = internal standard (n-nonadecane). Numbers above 17(H)21(H)hopanoic acid markers correspond to number of carbon atoms in hopane/hopene structure,
annotated with stereoisomeric configuration of for hopanes. Numbers above n-alkanoic
acid markers correspond to carbon chain length, resolved in full (and to scale with respect
to retention time of A) on the m/z = 74 partial chromatogram (B).
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116
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
116
Figure 4.5. Concentrations of (A) total n-alkanes and n-alkanoic acids, (B) high molecular weight (HMW) n-alkanes (≥C25) and n-alkanoic acids (≥C24),
(C) low molecular weight (LMW) n-alkanes (≤C21) and n-alkanoic acids (≤C20) normalised to dry weight of sediment, as well as (D) TOC contents
throughout the mid-Waipara River section. Depth is presented relative to GDGT Zones established in Chapter 2. The K/Pg boundary is indicated herein
by a dashed line at 0 m coinciding with the first rusty weathered horizon. The second rusty horizon at c. 25 cm indicates a probable unconformity and
associated haitus, represented by the zigzag line. Note change in depth scale above 5m, herein indicated by a break in the ordinate axis.
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.4.2.1. n-Alkanes and n-Alkanoic Acids
Total concentrations of n-alkanes and n-alkanoic acids range from 8.9 ng g-1 dry weight of
sediment (DW) to 1500 ng g-1 DW and from 1.0 ng g-1 DW to 1300 μg g-1 DW,
respectively (Fig. 4.5A). HMW n-alkanoic acid concentrations, like TOC contents, are
variable and generally increase through Zone I, ranging in concentration from c. 0.5 ng g-1
DW to 80 ng g-1 DW. Concentrations of HMW n-alkanes are lower and less variable,
ranging from c. 5 - 30 ng g-1 DW (Fig. 4.5B). LMW n-alkanes are present in higher
concentrations, generally decreasing through Zone I from c. 500 ng g-1 DW to 30 ng g-1
DW. The LMW n-alkanoic acid concentrations are relatively stable, averaging c. 35 ng g-1
DW (Fig. 4.5C).
The ratios of HMW/LMW n-alkanoic acids are highly variable across Zone I, ranging from
near 0 up to c. 7 (Fig. 4.6A), whereas HMW/LMW ratios of n-alkanes are low and stable
throughout Zone I. The terrigenous/aquatic ratio (TAR; Cranwell et al., 1987;
Bourbonniere and Meyers, 1996) is a more widely used, mathematically similar version of
HMW/LMW ratios:
TAR n-alkane = (C27 + C29 + C31) / (C15 + C17 + C19)
(4.1)
TAR n-alkanoic acid = (C24 + C26 + C28) / (C12 + C14 + C16)
(4.2)
TARs therefore record essentially the same trends as HMW/LMW ratios (Fig. 4.6). Across
the K/Pg boundary, both HMW n-alkane and n-alkanoic acid concentrations decrease, but
the latter are generally more abundant. Concentrations of LMW n-alkanoic acids remain
low across the K/Pg boundary and concentrations of LMW n-alkanes decrease. There is a
spike in concentrations of all n-alkyl components at 19 cm (f197); concentrations increase
dramatically for each compound class, with the largest relative increase exhibited by LMW
n-alkanoic acids and n-alkanes. LMW n-alkanoic acid concentrations then remain high
through Zone II, as concentrations of all other n-alkanoic acids and n-alkanes decrease.
Consequently, HMW/LMW n-alkanoic acid and n-alkane ratios and TARs are consistently
low throughout Zone II, although two samples at 0.5 cm (f560) and 16 cm (f556) have
slightly higher values (Fig. 4.6).
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.6. (A) Ratio of HMW/LMW n-alkanes and n-alkanoic acids, (B)
terrigenous/aquatic ratio (TAR; Cranwell et al., 1987; Bourbonniere and Meyers, 1996) of
n-alkanes [C27+C39+C31] / [C15+C17+C19] and TAR of n-alkanoic acids ([C24+C26+C28] /
[C14+C16+C18])
LMW and HMW n-alkanoic acid concentrations, and to a lesser degree LMW n-alkane
concentrations increase in Zone III (Fig 4.5); in contrast, HMW n-alkane concentrations
remain low. Consequently, HMW/LMW and TAR ratios remain generally low throughout
Zone III (Fig. 4.6). Zone III also contains two maxima in n-alkyl compound concentrations
– in the lower c. 50-cm and at 1.25 m (f 215) – where LMW n-alkanes and n-alkanoic acid
concentrations are significantly elevated and HMW n-alkane and n-alkanoic acid
concentrations are slightly higher.
4.4.2.1.1. Distribution of High Molecular Weight n-Alkanoic Acids and n-Alkanes
The carbon preference index (CPI; Bray and Evans, 1961) and the odd-over-even
predominance (OEP; Scalan and Smith, 1970) of n-alkanes describe the ratio between oddcarbon numbered n-alkanes and even-carbon numbered n-alkanes. A predominance of oddcarbon numbered n-alkanes in the C25–C35 range is characteristic of terrestrial higher plant
debris to the shelf sediments; epicuticular waxes of higher plants typically have n-alkane
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
maxima at C27, C29 and C31 with CPIs typically >5 (Eglinton and Hamilton, 1963; 1967;
Eglinton and Calvin, 1967; Cranwell et al., 1987; Rieley et al., 1991; Nott et al., 2000;
Pancost et al., 2002). Petrogenic inputs typically have a CPI of c. 1.0 (Gearing et al., 1976;
Farrington and Tripp, 1977; Cranwell, 1982; Eganhouse and Kaplan, 1982; Simoneit,
1984; Nishimura and Baker, 1986; Saliot et al., 1988; Pendoley, 1992). CPI and OEP
values close to 1 are also thought to indicate greater input from marine microorganisms
and/or recycled organic matter (Kennicutt et al., 1987).
Terrestrially derived n-alkanoic acids occur as C16-C36 homologues with an even-carbonnumber preference, the most common being C22, C24, C26, C28, and C30 compounds (Eglinton
and Hamilton, 1963; Kvenvolden, 1967; Tullock, 1976; Kolattukudy,1980; Rieley et al.,
1991). Many plant waxes also contain odd-carbon-number n-alkanoic acids, but in
concentrations up to an order of magnitude lower than co-occurring even-carbon-number
homologues (Řezanka and Sigler, 2009). Furthermore, HMW n-alkanoic acids can be
biosynthesised, albeit in lower quantities than LMW homologues, by some microalgae
(Volkman et al., 1980, 1998; Canuel and Martens, 1993) and bacteria (Gong and
Hollander, 1997; Řezanka, and Sigler, 2009). The preference of odd-over-even (n-alkane)
or even-over-odd (n-alkanoic acid) carbon chain length are expressed as follows:
CPIHMW n-alkane = (2 x Σ odd C25-31 ) / (C24 + 2 x (C26+ C28 +C30) + C32)
(4.3)
CPIHMW n-alkanoic acid = (2 x Σ even C26-32 ) / (C25 + 2 x (C27 + C29 +C31) + C33)
(4.4)
OEPHMW n-alkane = C27 + (6 x C29) + C31 / (4 x C28) + (4 x C30)
(4.5)
EOPHMW n-alkanoic acid = C26 + (6 x C28) + C30 / (4 x C27) + (4 x C29)
(4.6)
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Throughout the mid-Waipara River K/Pg boundary section, HMW CPIs and OEP/EOP
ratios exhibit similar trends for n-alkanes and n-alkanoic acids, although n-alkanoic acid
ratios are consistently higher (Fig. 4.7); CPIs and OEPs of n-alkanes range from c. 1 - 3,
whereas CPIs and EOPs of n-alkanoic acids range from c. 2-4, indicating a stronger HMW
even-carbon preference in n-alkanoic acids than the odd-carbon preference in coeval nalkanes. All records exhibit a trend towards lower values throughout Zones I and II,
reaching a minimum in lower Zone III at 75 cm (f209). All records then exhibit a gradual
shift towards higher values, with the greatest increases exhibited by CPIs and OEPs of nalkanoic acids, into Zone IV. Superimposed on the longer term trend is a relatively minor
excursion in the upper 3 samples (16 cm, f556; 19 cm, f197; 22 cm, f554) of Zone II
towards slightly higher values.
Figure 4.7. HMW n-alkane and n-alkanoic acid distributions. (A) Carbon preference index
(CPIHMW) of n-alkanes = (2 x Σ odd (C25-31) / (C24 + 2 x (C26+ C28 +C30) + C32) and nalkanoic acids = (2 x Σ even (C26-32) / (C25 + 2 x (C27 + C29 +C31) + C33) (Bray and Evans,
1961). (B) Odd-over-even predominance (OEPHMW) of n-alkanes = C27 + (6 x C29) + C31 /
(4 x C28) + (4 x C30), even-over-odd predominance (EOPHMW) of n-alkanoic acids = C26 +
(6 x C28) + C30 / (4 x C27) + (4 x C29) (Scalan and Smith, 1970).
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Figure 4.8. Distributions of n-alkanes and n-alkanoic acids of selected samples through
each Zone. Ordinate scale of each histogram is relative abundance, scaled to most
abundant component.
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Changes in overall distributions of n-alkyl compounds (Fig. 4.8) can also elucidate sources
of organic matter to the sediments. The most prominent change is the shift within Zone I
from distributions with a very high predominance of even-carbon numbered n-alkanoic
acids dominated by C30 (e.g. f161, -70 cm) to distributions with slightly lower EOPs
dominated by C24 at -7 cm (f561; geochemical signals in this sample likely reflect
downward displacement of post-K/Pg boundary sediment due to bioturbation, as discussed
previously). HMW n-alkanoic acid distributions remain similar to upper Zone I
distributions through Zone II, then exhibit even lower predominance of even-carbon
numbered homologues through Zone III, before recovering to distributions with high OEP
into Zone IV (Fig. 4.7).
The shift to distributions with higher relative proportions of mid-molecular-weight nalkanoic acids (C22 and C24) is also reflected by the ratio of (C22 + C24) to (C22 + C24 + C28
+ C30) homologues (Fig. 4.9D). This highlights an increase from low values around c. 0.1
in the base of Zone I, to values of c. 0.8 in upper Zone I (-7 cm, f561) which persist
through Zone II and much of Zone III. Values decrease above 1.05 m (f213), and stabilise
at c. 0.6 through Zone IV. Sources of C22 and C24 n-alkanoic acids are particularly
ambiguous (Meyers, 1997; Li et al., 2009), and these compounds may not only derive from
terrestrial plants (Eglinton and Hamilton, 1963; Kvenvolden, 1967; Tullock, 1976;
Kolattukudy,1980; Rieley et al., 1991), but also marine algae (Volkman et al., 1980, 1998;
Canuel and Martens, 1993) or bacteria (Pearson, A. et al., 2001), and possibly aquatic
macrophytes (Ficken et al., 2000; Hou et al., 2006). As such, a mixed marine and
terrestrial source for these compounds is likely (e.g. Liu et al., 2011).
The higher plant n-alkane average chain length (ACL) describes the average number of
carbon atoms per molecule based on the abundance of the odd-carbon-numbered higher
plant n-alkanes (Poynter and Eglinton, 1990), and as with CPI and OEP, may be adapted to
allow application to n-alkanoic acids:
ACLHMW n-alkane = Σ(i*Xn)/ ΣXn
(4.7)
ACLHMW n-alkanoic acid = Σ(i+1*Xi+1)/ ΣXi+1
(4.8)
Where i denotes the carbon-number of a given n-alkyl compound, ranging from 25 to 33,
and X is its concentration (after Schefuß et al., 2003).
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.9. Indicators of terrestrial plant communities through the mid-Waipara River section, including: (A) Average chain length (ACLHMW) of HMW n-alkanes (C25-33) and HMW n-alkanoic acids (C26-34). (B) C33 n-alkane ratio : C33 / (C29 + C31 + C33). (C) Proportion of mid-molecular-weight n-alkanoic
acids relative to high-molecular-weight components, expressed as the ratio of (C22 + C24)/(C22 + C24 + C28 + C30). (D) Concentration of taraxer-14-ene
relative to dry weight of sediment. Note change in scale of ordinate axis (concentration scale) at 1 μg g-1 DW. (E) Terrestrial palynology across the midWaipara River section (adapted from Vajda et al., 2001).
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Vegetation types are considered to be the main influence on the chain length of terrigenous
leaf lipids, e.g. leaf lipids derived from grasslands typically have longer carbon chain
lengths than leaf waxes from trees (Cranwell, 1973; Schwark et al., 2002). However,
environmental conditions are also suggested to exert a control on the chain length, e.g.
change in temperature (Gagosian and Pelzer, 1986; Poynter et al., 1989; Simoneit et al.,,
1991; Hinrichs and Rullkötter, 1997) or humidity/precipitation (Oros et al., 1999; Nott et
al., 2000; Schefuβ et al., 2003; Hughet et al., 2004; Sachse et al., 2006; van Dongen et al.,
2008). ACLs of HMW n-alkanoic acids through the mid-Waipara River section exhibit
only minor variability. They increase from c. 29 though Zones I and II to c. 29.5 in Zone
III (Fig. 4.9A). Values decrease again to c. 29 across the unconformity at 25 cm, and
increase through Zone III. Values through Zone IV range from c. 29 to 30.
The HMW n-alkane ACLs are generally more variable than those of the n-alkanoic acids
throughout the record, with more pronounced minima and maxima, but exhibit similar
trends (4.9A). In particular the n-alkane ACLs exhibit a shift to higher values across the
K/Pg boundary, from c. 29 to 30.5, consistent with relatively sharp increases in the C33 nalkane ratio (defined as C33 / (C29 + C31 + C33) ; Fig. 4.9B) and C31 / (C29 + C31) (Fig. 4.9C)
n-alkane ratio. The n-alkane ACLs drop in the upper strata of Zone II (from 16 cm; f556),
consistent with a drop in C33 n-alkane ratios and C31 / (C29 + C31) ratios.
C33 n-alkane ratios and n-alkane ACLs remain relatively high across the unconformity into
Zone III, although both do decrease slightly, in contrast with the n-alkanoic acid ACLs.
The n-alkane ACL at 43 cm (f202) is particularly low (c. 27.5), but that sample is also
characterised by no detectable concentrations of C29, C31 and C33 alkanes. Above that
horizon, n-alkane ACLs generally track the n-alkanoic acid ACL trend and gradually
increase from values of c. 28.5 in Zone III to values of c. 29.5 through Zone IV. The n-C33
alkane ratio decreases across the same interval, but the C31 / (C29
+
C31 ) n-alkane ratio
increases, driving the overall shift in ACLs. Overall then, this interval is characterised by a
shift from n-alkane distributions characterised by low CPI and OEP (Fig. 4.7) and similar
contributions of C27, C29, C31 and C33 (e.g. f209, 75 cm; Fig. 4.8) to distributions with a
much stronger odd-carbon number preference, and dominance of C29 and C31 n-alkanes
(e.g. f536, 20 m; Fig. 4.7); i.e., contributions of n-C25 and n-C27 as well as n-C33 decreases,
driving an overall increase in ACL.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.4.2.1.2. Distribution of Low Molecular Weight n-Alkanoic Acids
Even-carbon-numbered LMW n-alkanoic acids can derive from a variety of sources.
Homologues in the range of C14-C20 are often attributed to macro and micro algal sources
(Harrington et al., 1970; Patterson, 1970; Kenyon et al., 1972; Volkman et al., 1980; 1981;
Gagosian, 1986; Clauster et al., 1989; Carrie et al., 1998), analogous to LMW n-alkanes
(C15-C21) (Broman et al., 1987; Colombo et al., 1989). Some fatty acids, such as palmitic
acid (16:0), are present in virtually all marine organisms (Carrie et al., 1998; Mudge et al.,
1998; Ali and Mudge, 2006) and have therefore be used as a measure of total marine
community biomass (Parkes, 1987). However, LMW n-alkanoic acids can also derive from
terrestrial higher plants (Kollatukudy, 1976), or terrestrially-derived soil microbes (Zelles
et al., 1992; Bååth et al., 1992; Frostegård et al., 1993; Cavigelli et al., 1995; Wander et
al., 1995; Zogg et al., 1997) and fungi (Jabaji-Hare et al., 1984; Olsson et al., 1995
Frostegård and Bååth, 1996; Olsson, 1999). Furthermore, Odd-carbon-number n-alkanoic
acids can also derive from multiple sources, but are typically attributed to bacteria (Parkes,
1987; Wakeham and Beier, 1991; Harvey, 1994), with C15 and C17 largely synthesised by
marine heterotrophic bacteria known to be abundant in sediments (Volkman et al., 1980a;
1998). Alternatively, input of diagenetically altered material can contribute to even-carbonnumber n-alkanes and odd-carbon-numbered n-alkanoic acids (Shimoyama and Johns,
1972; Tissot and Welte, 1984; Meyers and Eadie, 1993; Hedges and Oades, 1997).
CPIs and OEPs (or EOPs) can, therefore, also be determined for LMW n-alkanoic acids to
evaluate changes in source and composition of OM (e.g. Matsudo and Koyama, 1977;
Kelly et al., 2011):
CPILMW n-alkanoic acid = (2 x Σ even C16-22) / (C15 + 2 x (C17+ C19 +C21) + C23)
(4.7)
EOPLMW n-alkanoic acid = (C16 + C18) / (C17 + C19)
(4.8)
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Significant changes through the mid-Waipara River section are evident in the LMW nalkanoic distributions based on carbon preference indices (Fig. 4.10). CPILMW and EOPLMW
values for n-alkanoic acids range from c. 6 – 195 and c. 1.6 – 36 respectively. Zones I and
II are typified by values of c. 10 and 5 for CPILMW and EOPLMW, respectively, with little
variation across the transition from Zone I to Zone II. In the upper samples (f197, 19 cm;
f554; 22 cm) of Zone II there is a transient shift to high values in both indices. Two
maxima in n-alkanoic acid CPILMW are evident in Zone III, coincident with the maxima in
concentrations of LMW n-alkanoic acids noted previously at 43 cm (f202) and 1.25 m
(f215).
The EOPLMW record exhibits only the second maxima, although values in lower Zone III
are higher than those of Zones I and II. This indicates that the first maxima is driven by a
relatively higher proportion of the C20 and C22 n-alkanoic acids, the concentrations of
which are used in the CPILMW proxy, but not the EOPLMW. Throughout Zone IV, values of
n-alkanoic acid CPILMW and EOPLMW are similar to values throughout Zones I and II,
except for very high values in one sample at 7.84 m (f539).
The proportion of C16 relative to C18 n-alkanoic acid (Fig. 4.11D) may also reflect changes
in the source of organic matter to the sediment (Claustre et al., 1989; Scribe et al., 1991,
Viso and Marty, 1993; Budge et al., 2001; Reuss and Poulson, 2002). C16/C18 n-alkanoic
acid ratios increase through Zones I and II (Fig. 4.10), with values generally ranging from
c. 0.25 to 1.7, except for a much higher value of c. 6.2 at 19 cm (f197). No significant
change is recorded across the K/Pg boundary; a ratio of c. 0.6 occurs at -18 cm (f175),
followed by an increase to c. 1.3 at c. -7 cm (f561), and a subsequent decrease to c. 0.3 at
0.5 cm (f560). As discussed in Chapter 3, with respect to GDGT distributions, the postK/Pg boundary geochemical signals may be downwardly displaced and mixed due to
bioturbation. Thus, it is uncertain as to which value reflects the actual post-K/Pg boundary
event signal. Zone III is characterised by a shift to higher C16/C18 ratios, from c. 2.3 at 28
cm (f199) to c. 4.3 at 1.25 m (f215). The relative proportions of C16 then generally
decrease through the remainder of Zone III and into Zone IV; C16/C18 ratios reach c. 0.13 at
7.84 (f539). C16/C18 ratios in the upper 10 m of Zone IV are relatively higher at c. 1.6.
126
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
127
Figure 4.10. Low molecular weight n-alkanoic acid distributions through the mid-Waipara River K/Pg boundary section. (A) n-alkanoic acid EOPLMW =
(C16 + C18) / (C15 + C17) (Kelly et al., 2011). Note the change in scale at 60, denoted by break in the axis. (B) CPILMW = (2 x Σ odd (C16-22 / C15 + 2 x (C17+
C19 +C21) + C23) (adapted from Scalan et al., 1970). (C) Ratio of C16/C18 n-alkanoic acids.
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.4.2.2. Algal Biomarkers: Sterols, Pristane and Phytane
Concentrations of total pristane and phytane (Pr + Ph; Fig. 4.11A) range from c. 3.2 μg g-1
DW to 1000μg g-1 DW, decreasing throughout Zone I and across the transition into Zone
II, with a transient increase in concentration at 19 cm (f197) concomitant with a similar
increase in LMW n-alkanes and n-alkanoic acids as previously described. Although
concentrations of (Pr + Ph) are higher throughout Zone III than Zone II, trends in (Pr + Ph)
concentration differ slightly from LMW n-alkyl compound concentration trends; a maxima
in (Pr + Ph) occurs at 75 cm (f209), between the two maxima in LMW n-alkanoic acids at
43 cm (f202) and 1.25 cm (f215). Trends are again similar across Zone IV, with
concentrations of (Pr + Ph) decreasing above 2.75 m (f232) to minimum values for the
record, in parallel with the LMW n-alkyl compounds (Fig. 4.5C; 4.11E).
Sterols are present in varying relative proportions of stenols and stanols. For simplicity, the
sum of each group is considered based on carbon-number (Fig. 4.11B). All sterols exhibit
largely similar trends through mid-Waipara; concentrations are generally low (total sterol
concentrations generally not exceeding 30 ng g-1 DW) and stable through Zone I. With the
exception of the lowermost sediment, the relative proportion of ΣC30 generally increases
through Zone I (Fig. 4.11C). The trend in increasing proportion of ΣC30 continues across
the K/Pg boundary interval and then declines through the lower strata of Zone II. This is
also coeval with a decrease in concentrations of all sterols. All sterol concentrations
increase above 16cm (f556) towards the unconformity at 25 cm.
Sterol concentrations exhibit a second sharp increase in concentrations across the
unconformity between Zone II and Zone III; ΣC29 is dominant at c. 530 ng g-1 DW, and
concentrations of ΣC30 and ΣC27 are c. 180 ng g-1 DW and 250 ng g-1 DW, respectively. All
sterol concentrations then exhibit a subsequent steep decrease at 75 cm (f209) to
concentrations similar to those in Zone I, which prevail through the remainder of the
Section. However, relative proportions of ΣC30 sterols are generally high through Zones III
and IV (Fig. 4.11B).
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Chapter 4
129
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.11. Concentrations of algal biomarkers throughout the mid-Waipara River section: (A) Sum of pristane (Pr) and phytane (Ph), (B) ΣC27 , ΣC29
and ΣC30 sterols, (C) C30 Sterol ratio : ΣC30 / (ΣC27 + ΣC29 + ΣC30), (D) ratio of C16/C18 n-alkanoic acids and (E) concentration of LMW n-alkanes and nalkanoic acids (ng g-1 DW) Concentrations normalised to dry weight of sediment. Note due to a very low polar fraction concentrations, sterol data for f213
(1.05 m) is unavailable.
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.4.2.3. Taraxer-14-ene
A pentacyclic triterpenoid is present in the mid-Waipara River hydrocarbon fractions and
tentatively identified as taraxer-14-ene. Pentacyclic triterpenoids are common in higher
plants (e.g. Pancost and Boot, 2004); taraxer-14-ene and similar compounds have been
identified in some peat-forming plants (Pancost et al., 2002), but are also particularly
abundant in mangrove leaves (Wannigama et al., 1984; Koch et al., 2003; Versteegh et al.,
2004) and seagrass blades (Gillian et al., 1984). Concentrations of taraxer-14-ene are
generally low throughout Zone I, from c. 0.05 – 0.2 μg g-1 DW (4.9E). A sharp increase in
concentration to c. 0.9 μg g-1 occurs at -7cm (f561), followed by a decrease above the
stratigraphic K/Pg boundary into Zone II. Concentrations continue to decrease through
Zone II, and taraxer-14-ene is entirely absent or low in concentration (<0.2 μg g-1)
throughout Zone III. Zone IV is characterised by increased but highly variable
concentrations of taraxer-14-ene, ranging from 0.61 to 5.7 μg g-1.
4.4.2.4. Soil Derived Branched GDGTs and BIT Index
BIT (branched vs. isoprenoidal tetraether) indices (Hopmans et al., 2004) were determined
throughout the mid-Waipara River section (Fig. 4.12), and have been discussed in the
previous chapter. Branched GDGTs are thought to derive from soil anaerobic nonphotosynthetic bacteria (Sinninghe Damsté et al., 2000; Weijers et al., 2006a; Weijers et
al., 2006b), possibly acidobacteria (Weijers et al., 2009; Sinninghe Damsté et al., 2011),
whereas the predominant source of crenarchaeol is Thaumarchaeota (Sinninghe Damsté et
al., 2002; Weijers et al., 2006b). The BIT index therefore reflects the relative amount of
soil organic matter input to the sediment, approaching unity with greater influence of
terrestrially derived organic carbon (Hopmans et al., 2004). BIT indices are low
throughout the record, with values not exceeding 0.11 (Fig. 4.12A).
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.12. (A) BIT index, and concentrations of (B) crenarchaeol and (C) branched
GDGT I normalised to TOC through the mid-Waipara River Section
Concentrations of crenarchaeol and bGDGT-I exhibit similar trends throughout the midWaipara River section (Fig. 4.12C). However, the BIT index reveals a general long term
trend towards lower values from the base of Zone I (f161; - 70 cm) through to the
uppermost sample of Zone III (f218; 1.55 m), interrupted by a few intervals of where
values do not change (e.g. 40 cm to 1.25 m). BIT indices are then relatively stable through
the upper part of Zone III and Zone IV.
4.4.3. Compound Specific Isotope Analysis
Carbon isotopic compositions of individual lipids reflect both the isotopic composition of
the carbon source utilised by the organism and the isotopic fractionations accompanying
carbon fixation and biosynthesis, which are, in turn, dependent on environmental
conditions (e.g. Hayes, 1993). In this study, high molecular weight (HMW; C26-C34) and
low molecular weight (LMW; C14-C18) n-alkanoic acids are analysed, likely reflecting
higher plant and mixed algal sources, respectively.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.4.3.1. High Molecular Weight n-Alkanoic Acids
The carbon isotopic compositions (δ13C values) of higher plant derived HMW evencarbon-number n-alkanoic acids (C26, C28, C30 and C32) were determined, and an abundance
weighted mean average carbon isotope (δ13CHMW) value calculated for the compounds.
δ13CHMW values decrease through Zone I, from c. -31 ‰ to -28.5 ‰, varying by c. 0.8 ‰
throughout the interval (Fig. 4.13). This trend is reflected in the δ13C values of individual
HMW n-alkanoic acids, with each component generally reflecting similar values. In the
lowermost Zone II, the δ13C values of C28, C30 and C32 n-alkanoic acids are generally
similar to those in the uppermost Zone I (barring a single data point at 5 cm). However, as
discussed previously, the sample below the K/Pg boundary (-7 cm, f561) could reflect a
downwardly displaced post-K/Pg boundary signal resulting from bioturbation. Hence, the
true δ13CHMW value change across the K/Pg boundary event is difficult to define but overall,
post K/Pg boundary HMW n-alkanoic δ13C values are lower than those in pre-K/Pg
boundary sediments: δ13CHMW values in Zone II vary from c. -30 ‰ to -31 ‰, with a
particularly low value of -32.5 ‰ 19 cm (f 197). Across the unconformity between Zone II
and Zone III, there is a further c. 2 ‰ decrease in δ13CHMW values to c. -33 ‰, followed by
a return to higher values throughout Zone III. However, the very low concentrations of the
two lowermost Zone III sediments result in larger analytical uncertainty, and that aspect of
the trend profile should be interpreted cautiously. δ13CHMW values in upper Zone III and
Zone IV are relatively stable at c. -31‰.
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Chapter 4
133
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.13. Compound specific carbon isotope analysis of HMW n-alkanoic acids (C26-34) across the mid-Waipara River section. (A) Weighted mean
average of carbon isotope measurements of C24-C34 n-alkanoic acids (δ13CHMW) Error bars represent pooled standard deviation. Note replicate analyses
were not performed for C32 at -35.5 cm (f170), -18 cm (f175), and 0.5 cm (f560) due to prohibitively low concentrations. (B) δ13C values of individual nalkanoic acids C28, C30 and C32. Error bars represent standard deviations of replicate analyses. (C) Zoom of δ13CHMW record from -0.7 m to 1.6 m; thick
dark grey line represents δ13CHMW values (weighted mean average trend). δ13C values reported relative to VPDB.
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.4.3.2. Low Molecular weight n-alkanoic acids
Although sources of LMW n-alkanoic acids are more ambiguous than the HMW
counterparts, carbon isotopic compositions of LMW even-carbon-number homologues
ranging from C14-C18 were determined, as these may reflect marine – potentially algal –
signals. Presented here are the records of δ13C values of C16 and C18 n-alkanoic acids, as
well as the mean weighted average δ13C values of the LWM n-alkanoic acids (C14, C16,
C18), herein referred to as δ13CLMW.
The Maastrichtian sediments of Zone I are characterised by highly variable n-alkanoic acid
δ13CLMW values that range from c -23 ‰ to -29 ‰. There are particularly sharp changes
associated with the transition from upper Zone I into Zone II sediments across the K/Pg
boundary. δ13CLMW values shift from c. -26.5 ‰ at -18 cm (f175) to c. -29.5 ‰ at -7 cm
(f561), then exhibit a positive shift to c. -26 ‰ at 0.5 cm (f560), above the stratigraphic
K/Pg boundary. As described above, the exact δ13C excursion associated with the K/Pg
boundary is difficult to determine due to bioturbation. δ13CLMW values then decrease to c. 29 ‰ and remain relatively stable through Zone II, except in one sample at 19 cm (f197)
which is characterised by a lower value of c. -32 ‰ (although the negative shift in this
horizon is exhibited only in the C16 compound). Across the unconformity between Zone II
to Zone III, there is no appreciable change in δ13C values of C16 and C18 or δ13CLMW nalkanoic acids.
However from 75 cm (f209), δ13C values of C16 and C18 n-alkanoic acids decrease and
begin to deviate from each other; δ13C values of C16 n-alkanoic acid decrease to a greater
extent than those of C18, such that the former becomes more depleted in 13C. The δ13CLMW
values are primarily driven by the C16 n-alkanoic acid, reflecting its enhanced contribution
(due to higher concentrations) throughout Zone III. The offset between δ13C values of C16
and C18 n-alkanoic acids is greatest at 1.05 m (f213): c. -36 ‰ vs. c. -31 ‰, associated
with the most negative values for Zone III. A subsequent positive shift is exhibited in δ13C
values of C16, and to a lesser extent in C18 n-alkanoic acids at 1.25 m (f215).
134
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Figure 4.14. Compound specific carbon isotope analysis of LMW n-alkanoic acids (C14-18)
across the mid-Waipara River section. (A) Weighted mean average of carbon isotope
measurements of C14-C18 n-alkanoic acids (δ13CLMW). Error bars represent pooled standard
deviation (i.e. propagated error calculated from standard deviations of replicate
measurements of each n-alkanoic acid comprising the weighted mean average
composite).(B) δ13C values of individual n-alkanoic acids C16 and C18. Error bars represent
standard deviations of replicate analyses. δ13C values reported relative to VPDB. Note
analysis of samples f161 (-70 cm) and f 232 (2.75 m) could not be performed due to low nalkanoic acid concentrations and insufficient quantity of acid fraction respectively.
The transition from Zone III into Zone IV is characterised by a return to similar δ13C
values for C16 and C18 n-alkanoic acids and a positive shift in δ13CLMW values from c. -31
‰ to -28 ‰. This is followed by a decrease to values of c. -29.5 ‰ which generally
persists throughout the remaining c. 13-m of Zone IV.
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Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.5. Discussion
4.5.1. Sources of Organic Matter
Biomarker reconstructions for the mid-Waipara river section indicate complex changes in
the sources of organic matter. In general, the presence of HMW n-alkanes with relatively
high odd-over-even predominance and n-alkanoic acids with high even-over-odd
predominance indicate a terrigenous input of organic matter to the sediments (Eglinton and
Hamilton, 1963, 1967; Eglinton and Calvin, 1967; Cranwell et al., 1987; Kvenvolden,
1967; Tullock, 1976; Kolattukudy,1980; Rieley et al., 1991). A terrestrially derived source
of OM is also corroborated by the high abundances of terrestrial palynomorphs (Vajda et
al., 2001; Vajda and Raine, 2003), the presence of taraxer-14-ene (Versteegh et al., 2004),
and the presence of branched GDGTs which indicate fluvially transported soil organic
matter input (Hopmans et al., 2004; Kim et al., 2006; Herford et al., 2006; Weijers et al.,
2006b; 2009).
LMW n-alkanoic acids with even-over-odd predominance, particularly the C16 and C18
homologues (Carrie et al., 1998; Mudge et al., 1998; Ali and Mudge, 2006), indicate a
marine contribution to the sediment (Harrington et al., 1970; Patterson, 1970; Kenyon et
al., 1972; Volkman et al., 1980; 1981; Gagosian, 1986; Clauster et al., 1989; Carrie et al.,
1998). However, even-carbon-number LMW n-alkanoic acids are very non-specific
biomarkers, and may in fact derive from a variety of sources, including higher plants
(Kollatukudy, 1976), or terrestrially-derived soil microbes (Zelles et al., 1992; Bååth et al.,
1992; Frostegård et al., 1993; Cavigelli et al., 1995; Wander et al., 1995; Zogg et al.,
1997) and fungi (Jabaji-Hare et al., 1984; Olsson et al., 1995 Frostegård and Bååth, 1996;
Olsson, 1999). Pristane and phytane are also abundant, and are here considered to be
marine derived and likely products of alteration of the phytyl sidechain of chlorophyll a in
photoautotrophic organisms (Dean and Whitehead, 1961; Brooks et al., 1969; Powell and
McKirdy, 1973; Rowland, 1990; Rontani and Volkman, 2003).
None of the sterols indentified at mid-Waipara have unambiguous sources. C29 sterols can
be attributed to terrestrial higher plant sources (Goad and Goodwin, 1972; Huang and
Meinschen, 1976; Johns et al., 1980; Volkman et al., 1980b, 2008), but its occurrence in
highly productive oceanic settings is often attributed to a contribution by non-specific
planktonic sources (Lee et al., 1980; Volkman et al., 1981; Walters and Cassa, 1985;
Volkman, 1986, 2003; Pearson et al., 2000). At mid-Waipara, the concentration trends of
C29 sterols are generally similar to those of 4-methyl C30 sterols, which are more
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
definitively derived from marine microalgae. The 4-methyl sterols likely derive from
dinoflagellates (Withers et al., 1978; Boon et al., 1979; Robinson et al., 1984; Volkman,
1998, 2003; Serrazanetti et al., 2006), although minor quantities of 4-methyl sterols are
also biosynthesised by some diatoms (Volkman et al., 1993) and haptophytes (Volkman et
al., 1990; 1997). Cholesterol is biologically ubiquitous but is often considered an indicator
for zooplankton (Huang and Meinschein, 1976; Gagosian and Nigrelli, 1976), either
directly or through dietary alteration of phytosterols (Gagosian and Heinzer, 1979;
Volkman et al., 1987; Grice et al., 1998). However it can also derive from terrestrial (Itoh
et al., 1977; Nishimura and Koyama, 1977) and aquatic (Johns et al.,1980; Volkman et al.,
1980b; 2008) plants. Because the concentration profiles of C27 and C29 sterols generally
match those of the 4-methyl C30 sterols, a marine origin is assumed for all. However, this
suggests that no sterols at mid-Waipara are terrestrially derived, despite evidence from the
n-alkyl compounds and branched GDGTs for input of terrestrial material. It is possible that
a contribution of C29 and C27 sterols (and stanols) in the mid-Waipara sediments also
derived from terrestrial plants. However, such functionalised compounds may be degraded
over the course of riverine and coastal transport, through such mechanisms as
biodegradation, oxidation and photochemical reactions (Corbet et al., 1980; Hedges et al.,
1997; Hernandez et al., 2001; Jaffé et al., 2001, 2006), and as such any terrestrially derived
sterols may have been degraded before deposition to the sediments.
4.5.2. Changes in Sources of Organic Matter Through the Mid-Waipara River Section
Relative contributions of terrestrial and marine derived OM can be qualitatively assessed
from biomarker distributions. HMW/LMW ratios and TARs of n-alkanes are high
throughout Zone I, although the former is much more variable. This suggests a
predominantly terrestrial source of OM, which is consistent with the relatively low
concentrations of LMW n-alkanoic acids, algal-derived sterols and pristane and phytane. It
is also consistent with the relatively high CPIs in this interval for both n-alkanoic acids and
n-alkanes. However, it is inconsistent with the low concentrations of taraxer-14-ene.
Throughout the section, taraxer-14-ene concentrations do not track those of any other
terrestrial biomarker, and its changes are interpreted to reflect changes in the land plant
community; as such, it is discussed in Section 4.5.2.1.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
In Zone II, n-alkanoic acid and n-alkane HMW/LMW ratios and TARs decrease
significantly, indicating a relatively decreased contribution of terrestrially derived higher
plant organic matter to the sediment post-K/Pg boundary. The co-occurring low CPIHMW
and OEPHMW/EOPHMW ratios could be an artefact of the relatively low concentrations of nalkyl compounds but could also reflect a greater contribution from more degraded material
(Shimoyama and Johns, 1972; Cranwell, 1982; Nishimura and Baker, 1986; Saliot et al.,
1988; Pendoley, 1992, Meyers and Eadie, 1993; Hedges and Oades, 1997; Meyers, 1997),
possibly weathered kerogen (e.g. Eglinton et al., 1997; Petsch et al., 2000; Dickens et al.,
2003). Similarly, BIT indices are slightly lower in Zone II than in underlying sediments.
This interval is coincident with the ‘fern spike’ identified from palynological analysis
(Vajda et al., 2001; Vajda and Raine, 2003). The fern spike is thought to reflect an early
successional vegetation dominated by ferns, such as those following mass-kill of climax
communities by volcanoes (Tschudy et al., 1984; Wolfe and Upchurch, 1987). Although
mass-kill from volcanic eruptions typical results in a localised vegetation impact, more
global effects associated with the putative K/Pg boundary bolide impact could include
global darkness, cooling and subsequent warming, wildfires, SOx and/or NOx poisoning,
dust and acid rain (Alvarez et al., 1980; O’ Keefe and Ahrens, 1982; Brett 1992; Pope et
al., 1994; Toon et al., 1997; Arinobu et al., 1999; Smit, 1999; Premovic et al., 2000;
Kieseling and Claeys, 2001), all of which could have impacted more distal locations such
as NZ.
Such a mass-kill event could be documented by the dramatic decrease in higher plant
biomarker concentrations in Zone II. Although BIT values decrease from Zone I to Zone
II, the shift is small, suggesting that decreased erosion and fluvial delivery of terrestrial
organic matter cannot explain the higher plant biomarker trends. Instead they might reflect
a smaller terrestrial biomass. The re-colonisation of the terrestrial biosphere in New
Zealand is considered to have been relatively rapid, based on the pollen record (Vajda et
al., 2001; Vajda and Raine, 2003). However, the pollen record of the K/Pg boundary at
other sites, e.g. the Raton Basin (North America), indicates a lower level of extinction than
the leaf megafossil record, possibly due to extinction of groups which do not have pollen
or have generalised pollen that is not diagnostic to specific or generic levels (Wolfe and
Upchurch, 1987). Thus terrestrial biomass reduction at mid-Waipara could be greater than
estimated from the pollen record, providing an explanation for suppressed concentrations
of higher plant biomarkers through Zone II. Alternatively, the impact of the mass-kill on
biomarker concentrations in Zone II could have been more indirect, e.g. via the change in
the higher plant community.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
BIT indices decrease across the unconformity between Zones II and III; TARs,
HMW/LMW ratios and CPIs also decrease. These shifts likely reflect lower inputs of soil
and plant OM to the sediment, perhaps indicative of lower precipitation and run-off. Drier
conditions at mid-Waipara are also inferred from the conifer dominated palynoflora (Vajda
and Raine, 2003). It should be noted, however, that LMW n-alkanoic acid and n-alkane,
(Pr + Ph), and sterol concentrations are higher throughout Zone III, compared to Zones I
and II, such that the decrease in TAR and HMW/LMW ratios might alternatively reflect
increased algal production.
The HMW/LMW ratios and TARs of n-alkanes and n-alkanoic acids increase through
Zone IV. BIT indices through Zone IV are also slightly higher than in Zone III, but lower
than in Zones I and II. Intriguingly, the pollen record is inferred to reflect a decrease in
terrestrial influence from 8 m above the boundary, based on the dominance of
dinoflagellate cysts over terrestrial palynomorphs (Vajda and Raine, 2003), yet
concentrations of HMW n-alkyl compounds and BIT indices increase above this horizon,
reflecting a disagreement between the miospore record and the biomarker record through
this interval. This disagreement may be due the fact that biomarkers and pollen have
different taphonomies, and as such can be transported from land to the marine
environments in different ways (i.e., via aeolian or fluvial transport). Furthermore,
biomarkers and pollen may experience different preservation and sedimentation rates.
Winnowing and changes in plant communities also differentially affect pollen and plant
biomarker burial (e.g. Schouten et al., 2007c). In any case, the concentrations of both
LMW and HMW n-alkanoic acids (and other biomarkers) are relatively high, suggesting
that both marine and terrestrial contributions to the sediment are persistent or increasing
through Zone IV, consistent with the increase in TOC contents.
4.5.2.1. Changes in the Terrestrial Plant Community
Significant changes in terrestrial higher plant communities at mid-Waipara River are
indicated by shifts in the palynoflora record (Vajda and Raine, 2003). Higher plant
biomarker assemblages, including leaf wax chain length distributions (i.e. ACLs), also
exhibit significant variability but the trends are somewhat less clear. Chain-length
distributions are sensitive to changes in the composition of their source vegetation or the
environment, such as temperature and aridity, with longer chain lengths generally
indicating warmer and/or drier conditions (Hall and Jones, 1961; Gagosian and Peltzer,
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
1986; Poynter et al., 1989; Rommerskirchen et al., 2003; Schefuβ et al., 2003; Sachse et
al., 2006; van Dongen et al., 2008). Furthermore, the ratio of C31 / (C29 + C31) is considered
to be more closely related to aridity than temperature (Schefuβ et al., 2003).
ACLs of HMW n-alkanoic acids increase through Zone I, whereas ACLs of n-alkanes are
somewhat more variable and coeval with a decrease in the C33 n-alkane ratio and the ratio
of C31 / (C29 + C31). The decreasing C31 / (C29 + C31) and C33 n-alkane ratios may reflect
lower aridity, which is in agreement with the expansion of ferns documented in the pollen
record for the interval. Increased ACLs of n-alkanoic acids appear to conflict with the nalkane trends, but they may reflect the changing vegetation as ACLs vary widely between
plant class, taxa and species (e.g. Chikaraishi and Naraoka, 2003). However, a lower ACL
has been observed in other K/Pg boundary sediments for a similar replacement of tree
pollen with fern spores (Zhou et al., 2005).
ACLs for n-alkanoic acids remain similar across the K/Pg boundary into Zone II, whereas
n-alkane ACLs initially shift to higher values, coincident with an increase in C 31 / (C31 +
C31) and n-C33 ratios. Following the K/Pg boundary, all n-alkane parameters exhibit a
decrease to essentially pre-boundary values. A similar decrease in n-alkane ACLs and C31 /
(C29 + C31) ratios is recorded for n-alkane distributions above the K/Pg boundary in Central
Cuba (Yamamoto et al., 2010) and Japan (Mita and Shimoyama, 1999), which is thought
to reflect the changes in plant community structure. The decrease in n-alkane parameters at
the section in Japan is also coeval with palynological evidence for the fern spike (Saito et
al., 1986). Further evidence for a change in the higher plant community across the K/Pg
boundary comes from the spike in taraxer-14-ene concentrations in the -7 cm sample (and
to a lesser degree, in the overlying horizons). This could reflect a brief shift in the
terrestrial vegetation or, given its brevity, reflect a transient input of specific plant remains
(e.g. mangroves) associated with a mass-kill event.
The somewhat contradictory trends in n-alkane and n-alkanoic acid distributions make it
difficult to distinguish between a vegetation or environmental control on the observed
distributions at Waipara. Increased aridity and/or temperature suggested by the n-alkanoic
acid ACL increase is apparently contradicted by the dominance of ferns (and expansion of
tree ferns) which suggest less water stressed conditions. Higher temperatures, at least in the
marine realm, through Zone II are confirmed by the TEX86 SST proxy (Chapter 3).
Furthermore, recent work has shown that fern gametophytes can exhibit well-developed
tolerance to desiccation (Watkins et al., 2007), and radiation into xeric habitats is inferred
to have occurred independently multiple times over the evolutionary history of ferns
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
(Schuettpelz and Pryer, 2007). Thus, it may be possible for a fern expansion to occur in an
environment with limited precipitation. The trends in n-alkane distributions are however in
better agreement with the inference of wetter conditions from the pollen record, and global
observations of n-alkane distributions at temporally comparable settings (Mita and
Shimoyama, 1999; Yamamoto et al., 2010). Future work will need to employ other
geochemical parameters (e.g. n-alkane D values) to resolve these issues.
Relatively low n-alkanoic acid ACLs occur across the unconformity into Zone III, with nalkane distributions exhibiting similar trends but with more variability, possibly as an
artefact of lower OEPs and CPIs biasing the proxy with even-number alkanes (e.g. Jeng et
al., 2006). The lower n-alkanoic acid ACLs are again consistent with the reconstruction of
a cooler climate determined for Zone III at mid-Waipara (Chapter 3). Lower values could
also indicate a higher proportion of forest vegetation as opposed to grasslands (Cranwell,
1973; Schwark et al., 2002), as reflected in the pollen record (Vajda and Raine, 2003). C31
/ (C29 + C31) and n-C33 n-alkane ratios are generally high but decrease throughout Zone III,
again suggesting a relatively arid climate and possibly cooling through the interval; these
trends are consistent with the pollen record, as the prevalence of conifer species also
indicate cooler and possibly drier conditions compared with underlying Zone II (Vajda and
Raine, 2003). A trend towards higher ACLs starts in the upper part of Zone III at 1.55 m
(f218) and continues through Zone IV, co-occurring with a decrease in C33 n-alkane ratios.
Thus, many of the vegetation parameters, despite much variability in Zones II and III, have
returned to pre-K/Pg boundary values in the upper part of the section.
4.5.2.2. Changes in Marine Algal Abundances and Assemblages
Low concentrations of sterols, and LMW n-alkanoic acids with a relatively high evenover-odd predominance (CPILMW > c. 2, EOPLMW > 5), together with generally low nalkane and n-alkanoic acid HMW/LMW and TAR ratios characterises sediments of Zone I
and much of Zone II. Together these parameters indicate a generally low but
predominantly algal source of marine OM (Harrington et al., 1970; Patterson, 1970;
Kenyon et al., 1972; Volkman et al., 1980, 1981; Gagosian, 1986; Clauster et al., 1989;
Carrie et al., 1998). Although there is apparently little change in algal biomarker
concentrations (LMW n-alkanoic acids and sterols) across the K/Pg boundary, TOC
decreases which may suggest lower export productivity, although decreased higher plant
biomarkers also suggests that terrestrial organic matter is reduced and as such may also be
partly responsible for lower TOC.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
A sharp increase in concentrations of LMW n-alkanoic acids with very high CPILMW and
EOPLMW occurs in the upper part of Zone II (19 cm and 22 cm), contemporaneous with a
similar increase in the concentration of (Pr + Ph). Sterol concentrations also increase, albeit
lower in the section at the K/Pg boundary. This is particularly true for the 4-methyl C30
sterols, resulting in a change in the overall sterol distribution (Fig. 4.9). A large increase in
the ratio of C16/C18 n-alkanoic acids possibly also indicates a shift in the dominant algal
type, as different classes exhibit various distributions of LMW n-alkanoic acids
(Harrington et al., 1970; Patterson, 1970; Kenyon, 1972 Volkman et al., 1980a; Volkman,
1981; Zhang et al., 2004; van der Meer et al., 2007). All of these changes, including both
increased algal biomarker concentrations and changes in their distribution, could indicate
an algal productivity bloom; in fact, unusual monospecific nannoplankton blooms have
been observed in globally distributed K/Pg boundary sections for up to 1 My following the
event (Perch-Nielsen et al., 1982; Hollander, 1993; Kaiho et al., 1999).
Zone III is characterised by even higher concentrations of LMW alkanoic acids which also
exhibit higher CPIs. Sterols are also particularly abundant in the lower part of Zone III (28
cm – 75 cm), coeval with high C16/C18 n-alkanoic acid ratios and elevated C30 sterol ratios.
Together these trends suggest generally high marine productivity through Zone III relative
to Zones I and II,. High productivity through Zone III as suggested by biomarker trends
also correlates with a period of elevated Si/Al and Ba/Al ratios at mid-Waipara (Hollis and
Strong, 2003), suggesting enhanced siliceous productivity (Zachos and Arthur, 1989).
Furthermore, the TEX86-derived SSTs (Chapter 3) and the acme of Palaeoperidinium
pyrophorum coinciding with Zone III both indicate cooler water and possibly upwelling
conditions (Askin, 1988; Willumsen 2000; 2006) which could enhance surface primary
productivity (Wetzel, 1977; Lyle, 1988; Meyers, 1997). The trends in biogenic silica
correlate to similar intervals at other K/Pg boundary sections in New Zealand, where
siliceous (diatom and radiolarian) productivity dominate the early Paleocene and represent
a restructured post-K/Pg boundary marine community. (Hollis, 2003; Hollis et al.,
2003a,b). The higher n-alkanoic acid C16/C18 ratios and proportions of 4-methylsterols
relative to total sterols through Zone III relative to Zones I and II may reflect similar algal
community changes.
The increasing relative proportion of ΣC30 sterols from early Zone I through to Zone III
suggests that changes in algal community may have been occurring from the latest
Maastrichtian through into the early Danian at mid-Waipara. The trend in C16/C18 nalkanoic acids, also indicative of algal community change, closely matches the trend in
relative proportions of C30 sterols. However, the precise change in terms of which type of
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
algae dominate cannot be determined, as the biomarkers are insufficiently source-specific
to make such assignments.
Algal community structure is perhaps still dynamic through Zone IV but biomarker ratios
and concentrations generally return almost to pre-excursion values. The exceptions to this
are the values of C30 sterol ratios and C16/C18 n-alkanoic acid ratios, which are variable but
remain consistently higher than values observed in Zones I and II. Such changes in algal
productivity through Zone IV, and specifically a return to pre-K/Pg boundary conditions
but with perhaps altered algal communities, occurs through an interval inferred to represent
the period from c. 64.3 – 62.6 Ma. This is in general agreement with the 3 My marine
biogeochemical cycle recovery period suggested by the re-establishment of the planktic to
benthic carbon isotope gradient. The ‘Living Ocean’ model (D’Hondt et al., 1998) forms
the basis of the argument that the recovery of the surface-deep water carbon isotope
gradient reflects the recovery of the mechanisms for transporting organic matter to depth,
rather than a 3 My suppression of algal productivity. Indeed, the algal biomarker records
discussed indicate that marine primary productivity re-established relatively soon after the
K/Pg boundary: i.e. the presence of algal biomarkers (although in suppressed
concentrations coeval with decreased TOC) in Zone II indicates the presence of primary
producers.
4.5.2.3. Overview of Ecological Changes at Mid-Waipara River
The sediments of the mid-Waipara K/Pg boundary section clearly record major changes in
terrestrial and marine ecosystems as a result of the K/Pg boundary event. Shifts in
terrestrial vegetation are documented by both pollen and biomarker distributions. These
may also have been accompanied by a longer term decrease in biomass as a result of eventrelated mass kill, suggested by the suppression of terrestrial plant biomarker concentrations
but perhaps inconsistent with the pollen record. Biomarker distributions from terrestrial
plants may also reflect changes in climate and environment; n-alkanoic acid ACLs appear
to agree with climate reconstructions determined from GDGT distributions (Chapter 3)
through Zones II and III (warm and then cool, respectively). The n-alkane ACLs, n-C33 and
C31 / (C29 + C31) proxies also record responses to aridity or the change in vegetation via
dramatic shifts in Zones II and III, and the trends in these parameters at mid-Waipara
generally agree with those at globally distributed sites. Importantly, biomarker
distributions and concentrations generally return to pre-K/Pg boundary values in the
studied section, typically starting in Zone III and continuing into Zone IV.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Marine ecosystems were also perturbed at the K/Pg boundary; changes in algal community
structure are indicated by shifts in relative proportions of ΣC30 sterols and C16/C18 nalkanoic acids. Decreased sterol and (Pr + Ph) concentrations, as well as decreased TOC
contents, in Zone II suggest suppressed marine productivity, although the presence of these
compounds indicates that productivity was not shut down altogether. Biomarker analyses
of a high northern latitude site in Denmark also record a relatively rapid recovery of
marine productivity post-K/Pg boundary based on the presence of algal biomarkers,
particularly C30 steranes (Sepúlveda et al., 2009).
Transient shifts of increased algal biomarkers through Zone II and more sustained
increases in Zone III could reflect episodes of unusual opportunistic phytoplankton
productivity (e.g. Perch-Nielsen et al., 1982; Hollander et al., 1993; Coccioni and Galeotti,
1994; Kaiho et al., 1999). This early recovery of productivity also agrees with the ‘Living
Ocean’ model (D’Hondt et al., 1998), which suggests cessation of primary productivity
was not as prolonged (a few thousand years) as the reduction in surface – deep water δ13C
gradient. The flux of carbon to the deep sea, however, could have been suppressed for a
more sustained period of time; initial early recovery of the surface – deep gradient δ13C is
placed at c. 500 ky post-K/Pg boundary, and a full return to pre-K/Pg boundary conditions
up to 3 My post-K/Pg boundary. The reduced surface-deep δ13C gradient is thus thought to
be tempered by the emergence of new algal assemblages (D’Hondt et al., 2005; Coxall et
al., 2006; Algret and Thomas, 2007). This is consistent with the observation of algal
biomarkers (albeit suppressed and coeval with low TOC) in Zone II, indicating the
presence of marine algae and thus some recovery of marine productivity. Zone III (the base
of which is tentatively dated at c. 1 My post K/Pg boundary) contains biomarker
assemblages that appear to reflect different and dynamic algal communities, relative to
Zones I and II, reflecting restructuring of the marine ecosystem. Biomarker concentrations
and distributions generally return to pre-K/Pg boundary values in Zone III and persist
through Zone IV, reflecting a recovered, possibly restructured, algal ecosystem.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
145
Figure 4.15. Long-term composite of δ13C values from late Maastrichtian to early Danian: (A) globally compiled δ13C values of benthic carbonate
(Cramer et al., 2009), (B) single site benthic carbonate carbon isotope record from ODP Site 1209 (Shatsky Rise, mid-latitude north Pacific) (Westerhold
et al., 2011), (C) single site bulk carbonate (inferred pelagic) carbon isotope record from ODP Site 1262 (Walvis Ridge, south Atlantic) (Kroon et al.,
2007), and (D) δ13CHMW and (E) δ13CLMW n-alkanoic acid records of mid-Waipara River (this study). All δ13C values reported relative to VPDB. Note the
different scales of (A), (B) and (C) relative to (D) and (E).
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
4.5.3. Carbon Isotope Records
4.5.3.1. Terrestrial Response to Carbon Cycle Perturbations Across the K/Pg Boundary and
Subsequent Recovery
Higher plant δ13C values are governed by the isotopic composition of substrate carbon, i.e.
CO2 (Popp et al., 1989, Arens et al., 2000), fractionation during carbon assimilation ( )
(Farquhar et al., 1982; 1989; Popp et al., 1989) and environmental conditions that
influence
values, such as water stress (e.g. Diefendorf et al., 2010; 2011; Kohn, 2010).
In addition, higher plant physiology, for example the differences between C3 and C4
plants, exerts an important control on their carbon isotopic compositions (Bender, 1971;
Smith and Epstein, 1971; O’ Leary, 1981; Marino and McElroy, 1991).
The δ13CHMW values in the Maastrichtian (Zone I) are essentially similar to, or slightly
lower than δ13CHMW values c. 1 My post-K/Pg boundary (Fig. 4.16C), suggesting that the
events of the K/Pg boundary did not cause a long-term effect on the terrestrial higher plant
δ13C value. This is in contrast to the global marine records (Fig. 4.15) which exhibit a shift
to more negative δ13C values throughout the Danian, both in benthic (Fig. 4.15A,B) and
pelagic settings (Fig. 4.15C), indicating a globally widespread shift in the carbon isotopic
composition of ocean-atmosphere reservoir. Dramatic shifts in δ13CHMW through the
Danian are, however, imposed upon the longer-term δ13CHMW trend, indicating that the
terrestrial higher plant communities were impacted by changes in the carbon cycle
resulting from events at the K/Pg boundary.
The absence (or suppression) of a clear long-term trend to more negative values in
δ13CHMW compared to the global carbonate records suggests that the higher plant sources of
the HMW n-alkanoic acids may be exhibiting a lower
relative to the pre-K/Pg boundary
plants. This could be a reflection of environmental change; in terms of physiological
response to environmental change, C3 plants exhibit lower
in response to decreased
water availability, e.g. in relatively low/irregular precipitation environments (Farquhar et
al., 1982; Madhaven et al., 1991; Meinzer et al., 1992; Diefendorf et al., 2010, 2011;
Kohn, 2010). However, most of the indications from the biomarker reconstructions suggest
that environmental conditions had returned to a state similar to pre-K/Pg boundary; e.g.
ACLs, n-alkane C33 and C31/(C29 + C31) ratios and BIT indices as indicators of runoff
and/or aridity largely returned to pre-K/Pg boundary values, and TEX86 SST
reconstructions suggest a return to pre-K/Pg boundary climate in terms of SST.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Restructuring of vegetation could be responsible for the observed trend, as different plant
types can exhibit different
values (e.g. Schouten et al., 2007c; Smith et al., 2007).
Indeed, the pollen record indicates that the distribution of vegetation types in Zone IV
differs considerably from that of Zone I; Zone IV is dominated by gymnosperms, whereas
Zone I is characterised by a more cosmopolitan assemblage dominated by ferns and
gymnosperms (Vajda and Raine, 2001). Gymnosperms typically exhibit lower
values
than angiosperms (Leavitt and Newberry, 1992; Flanagan et al., 1997; Chikaraishi and
Naraoka, 2003; Diefendorf et al., 2010), whereas angiosperms and ferns typically exhibit
similar
values (Ehleringer et al., 1987). Thus, replacement of ferns with gymnosperms
may decrease the net average
exhibited by the assemblage. Lower (average)
for the
Zone IV terrestrial plant community could offset the longer term trend towards lower
atmospheric CO2 δ13C values, accounting for the lack of, or a suppressed, long-term shift
in δ13CHMW values through the section.
Maastrichtian n-alkanoic acid δ13CHMW values increase somewhat through Zone I from c.
-31 ‰ to c. -30 ‰ (Fig. 4.16E). A δ 13C C29 n-alkane record at Caravaca, Spain (Arinobu
et al., 1999; Fig. 4.16A) also indicates a c. 1 ‰ positive shift in values before the K/Pg
boundary, although the estimated timing is later than observed at mid-Waipara, which may
be due to age-model uncertainties. A gradual increase in δ13C values of bulk organic
carbon is also noted in the Sugartite coal section in New Mexico, USA (Beerling et al.,
2001), although the exact timing for this trend is also not well constrained. The carbon
isotopic records of benthic and planktic carbonate also indicate a long term enrichment in
13
C leading up to the K/Pg boundary, particularly in the Pacific benthic records (Fig.
4.15A,B; Cramer et al., 2009; Westerhold et al., 2011) and in the bulk (pelagic) carbonate
carbon isotope record in the south Atlantic (Fig. 4.15C; Kroon et al., 2007), although the
shift (c. 1 ‰) occurs over c. 200 ky, rather than the c. 20 ky period observed at midWaipara. Thus, it is possible that the observed increase in δ13CHMW values in the latest
Maastrichtian record further evidence for a change in the δ13C composition of the
atmosphere-ocean reservoir.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
148
Figure 4.16. High resolution composite of carbon isotope (δ13C) values across the K/Pg boundary. (A) δ13C values of C29 n-alkanes at Caravaca, Spain
(Arinobu et al., 1999), (B) Bulk carbonate δ13C values at Walvis Ridge – ODP Site 1262 (Kroon et al., 2007), DSDP Sites 527 and 528 (Quillévére et al.,
2008). Zones I and II of the mid-Waipara River section: (C) weighted mean average δ13C values of HMW (C26-34) n-alkanoic acids (δ13CHMW). Note that
the carbon isotopic composition of C16 in sample f560 could not be determined due to low concentration. (D) Carbon isotopic composition of total organic
carbon (δ13CTOC) and (E) Weighted mean average of δ13C (C14-18) n-alkanoic acids (δ13CLMW). Error bars in (C) and (E) represent pooled standard
deviation. All δ13C values are expressed relative to VPDB. Note the different abscissa scale of (B) relative to (A), (C), (D) and (E) (which are plotted to
the same scale). The yellow band represents possible range of downward displacement at mid-Waipara due to bioturbation. K/Pg boundary is indicated by
red dashed line at 65.5 Ma. Unconformity at 25 cm is indicated by zig-zag line.
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Alternatively, the apparent difference between the longer-term shifts documented in the
marine record and the more rapid shifts documented in globally widespread terrestrial
sections suggests that the former instead reflect changing environmental conditions prior to
the K/Pg boundary. In particular, the increasing δ13C values of terrestrial vegetation could
reflect increased water stress. Indeed, some of the biomarker proxies from mid-Waipara
suggest a shift to more arid conditions through Zone I (e.g. n-alkanoic acid ACLs increase
and BIT indices decrease). However, the high proportion of ferns throughout the interval is
thought to be indicative of relatively high/regular precipitation (Vajda and Raine, 2003;
although note caveats above). As discussed earlier, the biomarker and perhaps pollen
records are ambiguous in terms of aridity. Further work should include the determination
of higher plant lipid δD values, to evaluate the hydrology through this interval.
The mid-Waipara section is marked by a c. 1 – 2 ‰ negative shift in terrestrially derived
δ13CHMW values across the K/Pg boundary (Fig 4.16C), a shift that is also consistent with
global records. Similar carbon isotope excursions of c. -2 ‰ in terrestrial organic carbon
have been observed in the records of n-alkane δ13C values at Caravaca, Spain (Arinobu et
al., 1999; Fig. 4.16A), and in bulk organic carbon isotope records from the Raton Basin,
USA (Beerling et al., 2001). Furthermore, shifts of a similar magnitude have also been
observed in other organic carbon isotope records from the Western Interior of the USA
(Schimmelmann and DeNiro, 1984; Arens and Jahren, 2000). The negative shift in
δ13CHMW values across K/Pg boundary therefore may be reflective of a globally pervasive
shift in the carbon isotopic composition of the ocean-atmosphere reservoir.
Relatively negative δ13CHMW values persist into the earliest Zone III. The hiatus between
Zones I and II means that definite trends from c. 23 ky – 1 My post K/Pg boundary cannot
be ascertained, and definite observations with respect to carbon cycle perturbations through
that interval are difficult to define. If the low δ13CHMW values at the base of Zone III are
representative of the missing strata, that is broadly consistent with records from other
terrestrial settings. Previous observations of terrestrial bulk organic carbon isotopic
compositions and coeval megafloral and microfloral analysis indicates the persistence of
negative values through the plant community recovery phases into the relatively well
established restructured assemblages (Beerling et al., 2001). The authors interpret this as
evidence to infer that while terrestrial plant communities recovered relatively quickly after
the K/Pg boundary event, perturbations in biogeochemical cycling by marine ecosystems
continued well after the terrestrial recovery. Furthermore, terrestrial δ13Corg analysed from
continental sections in Montana, Wyoming, Dakota and New Mexico in the Western
149
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
Interior of the United States (Arens and Jahren , 2000; Maruoka et al,. 2007; Beerling et
al., 2001) and China (Clyde et al., 2010) also exhibit a return to late Cretaceous δ13C
values after c. 1 My.
4.5.3.2. Perturbations in the Marine Carbon Cycle Across the K/Pg Boundary
The δ13C value of marine algae, determined by the magnitude of total carbon isotope
discrimination during photosynthesis ( ), is a function of the isotope fractionations
associated with carbon transport and fixation, and the concentrations of extra- and
intercellular [CO2(aq)] (Popp et al., 1989; Hayes et al., 1993). The
is also affected by cell
size and volume, nutrient availability and growth rate (Verity et al.,1992; Rau et al. 1996,
Cassar et al.,2002;). The n-alkanoic acid δ13CLMW is used here to reconstruct marine algal
δ13C, assuming an algal (likely mixed) source of LMW n-alkanoic acids.
Across the K/Pg boundary bioturbated interval, both relatively positive and negative
δ13CLMW values are recorded (Fig. 4.16E). This could reflect unstable productivity
suggested for the aftermath of the K/Pg boundary event (Hollander et al., 1993), or may be
a consequence of the dramatic changes in algal community structure as a result of the mass
extinction (Zachos et al., 1989). Speculatively, the monospecific nannoplankton blooms
observed (Perch-Neilson et al., 1982; Hollander et al., 1993; Kaiho et al., 1999) may
represent relatively small algal cell size compared to more cosmopolitan algal
assemblages; algal
decreases with decreasing cell size, or increasing growth rate (Laws
et al., 1995; Korb et al., 1996; Popp et al., 1998). Monospecific blooms of small algae
could therefore express anomalously low
(i.e. high
13
CLMW values). However, in
general, there is a c. -2 ‰ to -2.5 ‰ shift in average δ13CLMW values across the K/Pg
boundary.
Negative shifts in δ13C values of a similar magnitude across the K/Pg boundary are
recorded in pelagic carbonate elsewhere, e.g. in the south Atlantic ODP Site 1262 (Kroon
et al., 2007; Fig. 4.16B). Transient 13C-depletion of surface dissolved inorganic carbon of
-1.5‰ to -2‰ has also been documented in association with the K/Pg boundary at the
global stratotype section in El Kef, Tunisia (Keller and Lindinger, 1989; Keller et al.,
1995), and at other marine sections worldwide (Arthur, 1979; Boersma et al., 1979; Hsü et
al., 1982; Perch-Nielsen et al., 1982; Zachos et al., 1985, 1989; 1992; Zachos and Arthur,
1986; Stott and Kennett, 1989; Stott and Kennett, 1990; Robin et al., 1991; D’Hondt et
al.,1998) based on the carbon isotopic composition of pelagic carbonates.
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Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
The globally recorded decrease in surface δ13C is associated with little or no change in
deep-water δ13C (Norris et al., 2001a; 2001b; Fig. 4.15B, C), leading to homogenization at
the K/Pg boundary of the normally-positive marine surface-to-deep water carbon isotope
gradient. This has been attributed to a geologically brief cessation of primary productivity
in the surface ocean due to the extinction of surface ocean biota (Hsü et al., 1982; Zachos
and Arthur, 1986; D’Hondt et al., 1998; Norris et al., 2001a; 2001b), although it is argued
that
13
C-depleted carbon added to the surface ocean-atmosphere carbon reservoir would
also be required to produce the negative carbon isotope excursion (Kump, 1991; Ivany and
Salawitch, 1993).
Relatively negative δ13CLMW values persist across the hiatus from Zone II into Zone III,
indicating that the marine carbon cycle is still perturbed at mid-Waipara at c. 1 My postKpg. Low productivity could cause lower δ13CLMW; higher
is expressed by algae when
CO2 is less limiting, such as in the case of low productivity settings (e.g. Hollander et al.,
1993). However, biomarker evidence does not suggest suppressed productivity at this
interval, and the elevated levels of Ba and Si (inferred to be biogenic) through Zone III
corroborate a relatively high productivity setting (Hollis, 2003). Alternatively, the
relatively negative δ13CLMW values through Zone III may reflect high dissolved [CO2(aq)];
there is evidence for similarly sustained negative δ13C post-K/Pg boundary from pelagic
carbonate in the south Atlantic (Fig. 4.16B), suggesting that high [CO2(aq)] may have been
globally widespread, and as such may also reflect high atmospheric pCO2 relative to Zone
I. However, high marine surface [CO2(aq)] throughout Zone III may also be related to
colder SSTs, as inferred from several lines of evidence discussed in Chapter 3 (e.g. GDGT
distributions, presence of cool water indicating cysts of dinoflagellate P. pyrophorum);
colder temperatures may relate to greater CO2 saturation and thus algal growth under
elevated [CO2(aq)] (e.g. Mook et al., 1974; Pagani et al., 2006).
The transition from Zone III to Zone IV is characterised by a fairly large increase in
δ13CLMW, shifting from c. -32 ‰ to -28 ‰ possibly reflecting enhanced productivity or
reduced [CO2(aq)]. The apparent stabilisation of marine and terrestrial
through Zone IV
may reflect the timing (up to 1 My post K/Pg boundary) of the initial stages of more
permanent recovery in primary productivity and marine biogeochemical cycling (D’Hondt
et al., 1996a; D’Hondt et al., 1998; Coxall et al., 2006; Thomas et al., 2009). Indeed,
δ13CLMW values determined through Zone IV correspond to globally reported marine
carbon isotope records which appear to reflect similar trends (Fig. 4.16); bulk carbonate
151
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
from ODP 1262 (Kroon et al., 2007) reflects a similar trend in increasing δ13C values from
c. 63.8 to 62.8 Ma as recorded in mid-Waipara River δ13CLMW.
However, the marine carbon isotope record inferred from n-alkanoic acid δ13CLMW values
is very tentative, owing to the ubiquitous nature of C16 and C16 n-alkanoic acids; a
terrestrial higher plant source is generally discounted due to the difference between
δ13CLMW and δ13CHMW values observed (Fig. 4.16), although some contribution cannot be
discounted. However, C16 and C16 n-alkanoic acids may also be derived from terrestriallyderived soil microbes (Zelles et al., 1992; Bååth et al., 1992; Frostegård et al., 1993;
Cavigelli et al., 1995; Wander et al., 1995; Zogg et al., 1997) and fungi (Jabaji-Hare et al.,
1984; Olsson et al., 1995 Frostegård and Bååth, 1996). Low BIT indices (Fig. 4.12)
generally suggest a relatively low terrestrial-microbial influence in the mid-Waipara K/Pg
boundary sediments, but a contribution cannot be discounted. As the C30 sterols are more
definitively marine-algal derived, the carbon isotopic composition of those compounds
would likely represent a more reliable marine carbon isotope record.
4.5.3.3. Overview of Carbon Isotope Records at Mid-Waipara
The terrestrial carbon isotope record generated for mid-Waipara River, together with
similar records from Europe (Arinobu et al., 1999), the United States (Arens and Jahren
2000; Maruoka et al. 2007; Beerling et al. 2001) and China (Clyde et al., 2010) indicate a
global carbon isotope excursion of c. -2 ‰ in δ13C values of atmospheric carbon. Shifts in
terrestrial vegetation are documented by both pollen and biomarker distributions. These
may also have been accompanied by a longer term decrease in biomass as a result of eventrelated mass kill, suggested by the suppression of terrestrial plant biomarker concentrations
but is perhaps inconsistent with the pollen record. Biomarker distributions and terrestrial
plant derived δ13CHMW values may also reflect changes in climate and environment,
although δ13CHMW values are challenging to decipher due to the multiple factors which may
affect the carbon isotopic composition of plant tissues and, by extension, plant lipids.
The putative input of CO2 from breakdown of the carbonate-rich target rock of the
Chicxulub impact may have released isotopically heavy (with respect to carbon) CO2 into
the atmosphere (O’Keefe and Ahrens, 1989; Gardner and Gilmour, 2002). As such, a
positive excursion would be expected in δ13CHMW; however, no positive excursion in the
carbon isotopic composition of higher plant biomarkers was observed. Therefore, these
δ13CHMW values are not in agreement with the postulated δ13C-enriched source of increased
152
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
atmospheric carbon. Calculations by Arinobu et al. (1999) suggest that a negative carbon
isotope excursion of 1.4 ‰ – 2.8 ‰ could reflect a geologically instantaneous burning of c.
18-24 % of terrestrial above-ground biomass. The estimate of burnt biomass is based on a
model which incorporates estimates of Maastrichtian biome reconstructions, ‘amount’ of
atmospheric carbon, and end-Cretaceous biomass δ13C values determined by Ivany and
Salawitch (1993), an estimate of the end-Cretaceous atmospheric CO2 δ13C value (–7.5‰;
Hsü, 1986), and an estimate of biomass burning efficiency (Seiler and Crutzen, 1980).
Other workers interpret post K/Pg boundary changes in δ13C values of atmospheric CO2 as
a response to various climatic and eustatic factors (Gröcke et al., 1999; Kaiho et al., 1996).
The persistence of relatively negative δ13CHMW values into the earliest Zone III suggests
this is evidence that while terrestrial plant communities recovered relatively quickly after
the K/Pg boundary event, perturbations in biogeochemical cycling by marine ecosystems
continued well after the terrestrial recovery (Beerling et al., 2001). Furthermore, terrestrial
δ13Corg values derived from organic carbon analysed from continental sections in Montana,
Wyoming, Dakota and New Mexico in the Western Interior of the United States (Arens
and Jahren 2000; Maruoka et al. 2007; Beerling et al. 2001) and China (Clyde et al., 2010)
also exhibit a return to late Cretaceous values levels after c. 1 My, in agreement with the
record at mid-Waipara.
It has also been argued that homogenization of the marine surface-to-deep water carbon
isotope gradient immediately following the K/Pg boundary event (Arthur et al., 1979;
Boersma and Shakleton, 1981; Shakleton and Hall, 1984; Zachos and Arthur, 1986;
Zachos et al., 1989; Kump, 1991; Coxall et al., 2006) reflects cessation of primary
productivity in the surface ocean, (Hsü et al., 1982; Hsü and McKenzie, 1985; Keller and
Lindinger, 1989; Stott and Kennett, 1989; Zachos et al., 1989; 1992; D’Hondt et al., 1998),
and as such a shutdown or reduction in the uptake of 12C by photosynthetic phytoplankton
could have lead to an accumulation of 12CO2 in the atmospheric reservoir (Wolbach et al.,
1988; Ivany & Salawitch, 1993).
The recovery of putative marine δ13CLMW values at mid-Waipara by c. 1 – 1.5 My postK/Pg boundary is also reflected in the pelagic carbonate carbon isotope record of the south
Atlantic (Fig. 4.15C). This indicates that surface productivity had recovered by this time,
likely on a global scale. This is a shorter time-scale than the 3 My global recovery of the
planktic-benthic gradient, in agreement with the ‘Living Ocean Model’ (D’Hondt, 1998;
Adams et al., 2004), which infers that while surface productivity may have recovered
relatively quickly (up to 1 My) after the K/Pg boundary event, mechanisms which reduce
153
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
transport of carbon to the deep-waters, e.g. absence of zooplankton faecal packaging
(Emerson and Hedges, 1988) or inhibited size of phytoplankton (Premoli-Silva and
Luterbacher, 1966; D’Hondt et al., 1998; Gardin and Monechi, 1998; Norris et al., 1999),
were still prevalent. Moreover, the combined biomarker and isotope records from midWaipara indicate that although ecological restructuring occurred immediately post-K/Pg
boundary and persisted through the Danian, marine primary productivity recovered
relatively rapidly, much sooner than the initial stages of recovery suggested by the ‘Living
Ocean’ model; earlier recovery of continental margins is also documented elsewhere
(Kaiho et al., 1999; Mita and Shimoya, 1999; Sepúlveda et al., 2009), and is considered
likely due to opportunistic species with opportunistic benthic cysts or resting stages which
are likely to have selectively survived (Sheehan et al., 1996; Brinkhuis et al., 1998;
Wendler and Willems, 2002), particularly at high latitudes (Keller et al., 1993).
4.6. Conclusions
The events of the K/Pg boundary disrupted terrestrial and marine ecosystems, and as such
perturbed biogeochemical cycles both immediately following the K/Pg boundary event,
and persisting into the early Danian. Across the K/Pg boundary, a c. 2 ‰ negative
excursion is recorded in globally distributed terrestrial (Arens and Jahren 2000; Maruoka et
al. 2007; Beerling et al. 2001; Clyde et al., 2010) and marine pelagic carbon isotope
records, reflecting a global perturbation of the carbon cycle (Arthur, 1979; Boersma et al.,
1979; Hsü et al., 1982; Perch-Nielsen et al., 1982; Zachos et al., 1985, 1989; Zachos and
Arthur, 1986; Keller and Lindinger, 1989; 1992; Stott and Kennett, 1989; Stott and
Kennett, 1990; Robin et al., 1991; Keller et al., 1995; D’Hondt et al.,1998; Kroon et al.,
2007).
The negative CIE in pelagic carbonate and homogenisation of the planktic-benthic carbon
isotope gradient is generally attributed to cessation of primary productivity in the surface
ocean (Hsü et al., 1982; Hsü and McKenzie, 1985; Keller and Lindinger, 1989; Stott and
Kennett, 1989; Zachos et al., 1989; Zachos et al., 1992; D’Hondt et al., 1998) and, as such,
a possible increase in pCO2 as a result of depressed marine CO2 drawdown. However, no
evidence for a complete cessation of primary productivity at mid-Waipara has been
determined in this study, although low TOC and suppressed algal biomarker concentrations
suggest lower export productivity. Biomarker evidence supports the suggestion of unusual
algal ‘blooms’, such as those documented elsewhere (Perch-Neilson et al., 1982; Hollander
154
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
et al., 1993, Kaiho et al., 1999), i.e. periods of enhanced algal productivity within usual
monospecific communities. Increases in algal biomarker concentrations indicate periods of
enhanced algal productivity, while shifts in the relative proportions (i.e. C16/C18 and C30
sterol ratios) indicate reorganisations of dominant algal types.
Early recovery of primary productivity at continental margins is also documented
elsewhere (Kaiho et al., 1999; Mita and Shimoya, 1999; Sepúlveda et al., 2009), and is
considered likely due to opportunistic species, e.g. those which utilise benthic cysts or
resting stages, which selectively survived (Sheehan et al., 1996; Brinkhuis et al., 1998;
Wendler and Willems, 2002), particularly at high latitudes (Keller et al., 1993). The
changes in algal assemblages determined from changes in algal biomarker ratios also
support this suggestion of a shift in dominant algal types from cosmopolitan assemblages
to more opportunistic species.
The ‘Living Ocean’ model also suggests that cessation of primary productivity post-K/Pg
boundary was not as prolonged (a few thousand years) as the reduction in surface-deep
water carbon isotope gradient. The flux of carbon to the deep sea, however, could have
been suppressed for a more sustained period of time; initial early recovery of the surfacedeep carbon isotope gradient is placed at c. 500 ky post-K/Pg boundary, and a full return to
pre-K/Pg boundary conditions up to 3 My post-event. The reduced surface-to-deep carbon
isotope gradient is thus thought to be tempered by the emergence of new algal assemblages
(D’Hondt et al., 2005; Coxall et al., 2006; Algret and Thomas, 2007). This is also
consistent with the observation that Zone III (the base of which is tentatively dated at c. 1
My post K/Pg boundary) contains biomarker assemblages that appear to reflect different
and dynamic algal communities, relative to Zones I and II, indicating a restructuring of the
marine ecosystem. Biomarker concentrations and distributions generally return to pre-K/Pg
boundary values in Zone III and persist through Zone IV, reflecting a recovered, possibly
restructured, algal ecosystem. Reduced CO2 drawdown as a result of the cessation of
primary productivity may not have been as prolonged or widespread as earlier models of a
‘Strangelove Ocean’ suggest (Hsü et al., 1982; Hsü and McKenzie, 1985; Keller and
Lindinger, 1989; Stott and Kennett, 1989; Zachos et al., 1989; Zachos et al., 1992), and as
such a different mechanism for the negative CIE across the K/Pg boundary is required,
although the periodic algal blooms and unstable marine ecosystems reflected by the
restructuring of algal assemblages are likely to have affected long-term biogeochemical
cycles (D’ Hondt et al., 1996a; Hollis, 2003).
155
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
It is argued that isotopically light carbon added to the surface ocean-atmosphere carbon
reservoir would also be required to produce the negative CIE (Kump, 1991; Ivany and
Salawitch, 1993). This is supported by the coeval negative CIE in terrestrial records;
terrestrial higher plant
photoautotroph
is generally less sensitive to changes in pCO2 than marine
, as the former organisms can also adjust their stomatal density to alter
intercellular CO2 (Freeman and Hayes, 1992; White et al., 1994). That the terrestrial and
marine carbon isotope records reflect a similar magnitude CIE suggests that both terrestrial
and marine systems were affected by a shift in the isotopic composition of substrate carbon
(CO2) of the same origin. A negative carbon isotope excursion of 1.4 ‰ – 2.8 ‰ could
reflect a geologically instantaneous burning of c. 18-24 % of terrestrial above-ground
biomass (Arinobu et al., 1999), and would be reflected in both marine and terrestrial
carbon reservoirs. Warming through the interval is also recorded in the TEX86 SST
reconstructions described in Chapter 3, and as such could reflect increased pCO2, possibly
as a result of biomass burning. Hydrological conditions are more difficult to determine; nalkane proxies and the prevalence of ferns (Vajda and Raine, 2003) suggest wetter
conditions, but n-alkanoic acid distributions and BIT indices suggest the opposite.
Terrestrial biomass may have been reduced, despite lack of evidence for this in the pollen
record (Vajda et al., 2003). Terrestrial biomarker concentrations are suppressed through
Zone II, and although BIT indices are slightly lower, the decrease is probably not large
enough to invoke a significant decrease in precipitation and/or run-off.
Long-term
13
C-depletion (persisting into the early Danian) of global marine benthic
(Westerhold et al., 2011) and pelagic (Kroon et al., 2007) carbonates is reflected in the
putatively marine-derived δ13CLMW values at mid-Waipara, but is not reflected in the
terrestrial δ13CHMW values. Due to the apparent global nature of the long-term 13C-depletion
in the marine carbon isotope records, the relative suppression of the trend in the terrestrial
δ13CHMW values at mid-Waipara may be the result of the terrestrial community
restructuring as suggested by the pollen record (Vajda and Raine, 2003); the terrestrial
assemblages of Zone I are cosmopolitan, whereas assemblages of Zone IV are dominated
by gymnosperms which generally exhibit lower
than ferns or angiosperms (Leavitt and
Newberry, 1992; Flanagan et al., 1997; Chikaraishi and Naraoka, 2003; Diefendorf et al.,
2010; Ehleringer et al., 1987). The marine
13
C-depletion may reflect increased [CO2(aq)]
relative to Zone I, as suppressed productivity is not supported from the algal biomarker
records at mid-Waipara. The extent of increased [CO2(aq)] may be enhanced relative to the
global records at mid-Waipara, due to colder SSTs which in turn would increase the
surface water capacity for dissolved [CO2(aq)].
156
Chapter 4
Ecological and Carbon Cycle perturbation across the K/Pg Boundary at mid-Waipara River, NZ.
From the biomarker and compound specific isotope records at mid-Waipara, together with
the global records, return to pre-K/Pg boundary conditions was observed in both the
marine and terrestrial realms in Zone III at mid-Waipara, persisting through Zone IV; i.e.
both systems have recovered by c. 1 – 1.2 My post-K/Pg boundary, indicating a return to
more stable biogeochemical cycles. This timing is also in agreement with findings from the
previous chapter, where climate had also apparently stabilised by this time. As such, these
records suggest that the perturbations of the K/Pg boundary event had both immediate and
persisting effects, affecting marine biogeochemical cycling and causing instability in the
carbon cycle. These effects impacted upon early Danian climate, causing instability which
was relieved by the eventual emergence of stable marine ecosystems and, perhaps locally
at mid-Waipara, resurgence of terrestrial biomass (although suppression of biomass is a
tentative suggestion).
157
Chapter 5
The Paleocene Carbon Isotope Maximum
in the Southwest Pacific of the Southern
Ocean
158
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.1. Introduction
The Paleocene carbon isotope maximum (PCIM), first reported in the calcite of
foraminifera from Deep Sea Drilling Project cores from Legs 74 (Shackleton et al., 1985)
and 84 (Shackleton et al., 1987b), is the most prominent feature of the Cenozoic benthic
carbon isotope record (Zachos et al., 2001; Cramer et al., 2009). The PCIM was initiated
around 2.5 My after the K-Pg boundary event, reached its maximum in the middle
Paleocene (mid C26r to mid C25r; 58.7 – 56.4 Ma), and waned through the latest
Paleocene and into the Paleocene-Eocene transition. The δ13C values of bulk calcium
carbonate reach 4 ‰ (a total enrichment relative to pre-PCIM δ13C values of c. 2 ‰) at c.
57 Ma, persisting for around 2 – 4 My. The negative carbon isotope excursion of the
Paleocene Eocene Thermal Maximum (Bralower et al., 1995; Corfield and Cartlidge, 1992;
Shackleton, 1987b; Shackleton and Hall, 1984a,b) is superimposed upon the waning stage
of the PCIM. The PCIM also appears to be coincident with isotopic evidence for cooling in
the globally compiled benthic carbonate oxygen isotope record (Cramer et al., 2009).
It is suggested that the cooling resulted from an increased drawdown of CO2 as a
consequence of enhanced productivity (Corfield and Cartlidge, 1992; Shackleton et al.,
1984, 1987b; Thompson and Schmitz, 1997). On the basis of sedimentary barium
concentrations, there is evidence for a large increase in marine organic carbon burial (6fold) in oligotrophic regions of the oceans. (Thompson and Schmidtz, 1997). It is also
suggested that the maximum 13C-enrichment occurred at a time when the planktic-benthic
13
C gradient was also at a maximum (Shackleton and Hall, 1984a,b), which the authors
infer suggests that the isotope maximum was enhanced by photosynthetic removal of
carbon from the ocean system. However it is argued that an increase in marine
photosynthesis is insufficient to account for the observed
13
C enrichment, and it has been
suggested instead that the PCIM was the result of increased production of terrestrial
organic carbon (Oberhänsli and Perch-Nielsen, 1990). Indeed, late Paleocene coal deposits
are amongst the thickest in the entire geological record (Shearer et al., 1995; Ellis et al.,
1999, Ziegler et al., 2003; Kalkreuth, 2004). Modelling by Kurtz et al. (2003) suggest it is
reasonable to assume that the total carbon sequestered terrestrially in the late Paleocene
could account for the global positive carbon isotope excursion and inferred OM burial.
Climate records of the Southern Ocean are essential in reconstructing the global climate
and oceanographic response to the PCIM, particularly as the influence of ocean heat
transport in cooling Southern Ocean is likely to be minimised due to the lack of fully
opened ocean gateways; during the Paleocene, both the Tasman Gateway (between South
159
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Tasman Rise and Antarctica) and Drake Passage (between South America and Antarctica)
seaways were closed (Kennett et al., 1972, Wise et al. 1991, Lawver, and Gahagan, 1992,
Abreu & Anderson 1998). The SW Pacific region of the Southern Ocean is considered to
be influenced predominantly by undifferentiated subtropical surface waters circulating
from (north)west to east through the region as part of a large South Pacific warm-water
gyre (Barron and Peterson 1991). New Zealand contains several exposed and ‘pristine’
Paleocene sections (Hollis et al., 2002, 2005; Killops et al., 2000; Morgans et al., 2005),
and such provides an ideal setting to interrogate the expression of the PCIM in the
Southern Ocean.
However, on-land sediment records of New Zealand are either carbonate-lean or the
carbonate has frequently undergone significant diagenesis (Field and Browne, 1989;
McMillan and Wilson, 1997; Hollis and Manzano-Kareah, 2005; Hollis et al., 2005).
Diagenesis has not affected the δ13C record significantly, but interaction with meteoric
waters has produced strongly negative δ18O values (Hollis et al., 2005). As such, SST
reconstructions for these settings using carbonate oxygen isotope analysis is severely
hampered.
One aim of this study is to determine whether the PCIM was associated with cooling in the
Southern Ocean using the organic geochemical proxy TEX86, which is not affected by the
diagenetic processes which can confound oxygen isotopic analysis of carbonates. This
study reconstructs SSTs for the mid-Waipara River section and ODP Site 1121, and
integrates records previously published from ODP Site 1172 (Bijl et al., 2009); the midWaipara River Section in the Canterbury Basin, New Zealand has long been recognised as
an exceptional geological record for Paleogene palaeoclimate studies as it contains a near
complete succession of neritic to upper bathyal sediments from the Late Cretaceous to
Middle Eocene. The relative thermal immaturity and high TOC contents allows for
application of organic geochemical analysis. ODP Sites 1121 and 1172 provide
complementary SST records to construct a regional climate.
A further aim is to evaluate the timing of oceanographic changes and carbon cycle shifts,
in relation to the global records of the PCIM, and to determine whether the SW Pacific
region of the Southern Ocean was a possible location for the burial of organic carbon. This
will address the hypothesis that environmental change in the region contributed to the
global
13
C-enrichment recorded in the global benthic foraminiferal carbonate record
(Cramer et al., 2009).
160
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Compound-specific carbon isotope analysis of terrestrial plant and marine algal biomarkers
will also be performed on sediments from mid-Waipara River Column 2, to facilitate
interrogation of terrestrial and marine responses to climate and carbon cycle change at the
PCIM.
5.2. Site Descriptions
Analysis of sediments from two sites in the southwest Pacific have been undertaken for
this study: 24 samples from an outcrop at mid-Waipara River, Canterbury (New Zealand),
and 40 samples from marine sediments recovered at ODP Site 1121, Campbell Plateau,
offshore southeast New Zealand (Fig. 5.1). This study also integrates evaluation of data
from another marine sediment core recovered from the southwest Pacific, ODP Site 1172
at East Tasman Plateau.
5.2.1. Mid-Waipara River Column 2
Figure 5.1. Palaeolocations for mid-Waipara River (MW), ODP Site 1121 (1121) and
ODP Site 1172 (1172). Site locations juxtaposed on Paleocene New Zealand palinspastic
reconstruction for the Paleocene (57 Ma) (after King et al., 1999).
161
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Paleocene – Eocene sediments in the Waipara area were deposited at upper bathyal depths
(200-500 m) in a northern, semi-enclosed sub-basin in the Canterbury Basin.
Palaeogeographic reconstructions indicate a palaeolatitude of 55°S at this time (Stock and
Cande 2004). Rock samples were collected at 1-2 m intervals as part of a “tape and
compass” mapping survey of the two sections studied (Morgans et al., 2005). The 80-m
thick section Column 2 (Morgans et al. 2005; Fig. 5.2) samples a Paleocene interval from
the upper Loburn Formation to uppermost Waipara Greensand. The Waipara Greensand is
sharply overlain by a 1.5 m thick interval of poorly exposed slightly calcareous mudstone,
possibly displaced Ashley Mudstone. Biostratigraphy suggests there is a major
unconformity between the two units, although it is possible that the contact is faulted.
Figure 5.2. Location of mid-Waipara River Column 2 (Morgans et al., 2005; figure
adapted from Vajda and Raine, 2003). Also indicated in grey is the K/Pg section discussed
in Chapters 2 and 3. Scaling according to NZMS topomap series 260-M34.
24 samples (MW63-MW29; Appendix VII.d) from a stratigraphic range of 53.8 m to 132.5
m were processed for biomarker and GDGT analysis, as well as bulk TOC. Of the 24
samples, 22 are presented here; the uppermost 2 samples (MW48 and MW49) were
collected from the sediment in the 1.5-m thick mudstone unit above the Waipara
Greensand, and as such likely does not reflect late Paleocene strata (See Appendix VII.e).
Bulk organic δ13C analysis was performed on a sub-sample of each at GNS Science, NZ
and the results were provided by Christopher Hollis (GNS Science, NZ).
162
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Column 2 extends from the northwest corner (GR M34/7677-9441) to a bluff outcrop on
the south-eastern end of the western limb of the ‘horseshoe bend’ (GR M34/7706-9420)
The lower part of the section incorporates the Loburn Formation (Late Paleocene), from
which three samples (MW63-MW60) were collected. The sequence grades up into
Paleocene Waipara Greensand (Morgans et al., 2004b), from which further samples
(MW58-MW49) were taken; the upper part of the column (MW29-MW49) was collected
from outcrop exposed in a bluff on the north-eastern side of the river, in the south-eastern
end of the western limb of the ‘horseshoe bend’ (see Appendix VII.e for lithologic column
and sample depths, and Appendix VII.f for photographs of collections).
The age model for mid-Waipara (Fig. 5.3) is based on the identification of key age
diagnostic taxa; e.g. The base (62.23 m) contains the lowest occurrence of calcareous
nannofossil index species Chiasmolithus bidens, marking the base of biozone NP4
(Gradstein et al., 2004) and the onset of the Selandian (61.5 Ma). Correlations of New
Zealand Stages with International epochs and microfossil zones are based on the
stratigraphic ranges of key taxa of foraminifera, calcareous nannofossils, dinocysts and
radiolarians. The New Zealand Paleogene timescale of Cooper (2004) is correlated to the
Geological Time Scale 2004 (GTS2004; Gradstein et al., 2004), and that timescale is used
throughout this Chapter.
Figure 5.3. Age model for mid-Waipara Column 2 provided by Christopher Hollis (GNS,
NZ). Age determinations are based on identification of key age diagnostic taxa, with linear
sedimentation rates solutions indicated. “AM?” denotes the tentative assignment of this
unit as Ashley Mudstone, possibly slumped.
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The age model for mid-Waipara (Fig. 5.3) is based on the identification of key age
diagnostic taxa; e.g. The base (62.23 m) contains the lowest occurrence of calcareous
nannofossil index species Chiasmolithus bidens, marking the base of biozone NP4
(Gradstein et al., 2004) and the onset of the Selandian (61.5 Ma). Correlations of New
Zealand Stages with International epochs and microfossil zones are based on the
stratigraphic ranges of key taxa of foraminifera, calcareous nannofossils, dinocysts and
radiolarians. The New Zealand Paleogene timescale of Cooper (2004) is correlated to the
Geological Time Scale 2004 (GTS2004; Gradstein et al., 2004), and that timescale is used
throughout this Chapter.
5.2.2. Ocean Drilling Program Leg 181, Site 1121.
Figure 5.4. Age model for ODP Site 1121, provided by Christopher Hollis (GNS, NZ).
Age determinations are based on identification of key age-diagnostic taxa, a single welldefined normal polarity interval correlated with Chron C26n, and correlation of carbon
isotope stratigraphy with DSDP 577. Linear sedimentation rate solutions indicated. Note
the change in sedimentation rate at 94 m indicated. See Appendix VII.i for carbon isotope
correlation of Wei et al., (2005); green stars represent isotope events carried through in this
age model.
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
ODP Site 1121 is situated on the eastern edge of the Campbell Plateau (50.9°S, 177°E,
4488 meters below sea level) (Carter et al. 1999). A 100-m thick Paleocene interval
comprising siliceous nannofossil chalk underlies 30 m of Neogene sediments. A palaeowater depth of 3500 m, close to the carbonate compensation depth, and a palaeo-latitude of
62°S are inferred for the Paleocene (Carter et al. 1999; Stock and Cande 2004). Previous
studies have been undertaken on radiolarians (Hollis 2002), calcareous nannofossils and
bulk carbonate stable isotopes (Wei et al. 2005). The age model for ODP Site 1121(Fig.
5.4) is based on nannofossil and radiolarian bioevents and a single well-defined normal
polarity interval correlated with Chron C26n (Carter et al. 1999; Hollis 2002; Wei et al.
2005).
Wei et al. (2005) constructed an age model for ODP Site 1121(Appendix VII.i) by
correlating the bulk carbonate carbon isotope record of ODP Site 1121 with the analogous
bulk carbonate carbon isotope record of ODP Site 577, as reported by Shackleton et al.
(1985) and using age ties based on a revised ODP Site 577 chronology (Quillévére et al.,
2002). Two of these events (points 3 and 5) are used in this age model, but there is
insufficient evidence that the other events are well-defined or isochronous.
A suite of 44 samples from ODP Site 1121 Hole B (CP01 – CP44) were processed for
GDGT analysis; the samples were chosen to stratigraphically match those analysed for
carbon and oxygen isotopic composition of bulk carbonate as described in Wei et al.
(2005). Out of the 44 samples, organic geochemical data for 14 are presented here (see
Appendix V); the other 30 samples were generally too low in OC to provide reliable
GDGT data, or exhibited distributions deemed unsuitable for TEX86 SST reconstructions.
A suite of 40 samples from similar horizons were also analysed for bulk carbon content
and δ13C at GNS (NZ) and the results provided by Christopher Hollis (GNS, NZ)
5.3. Methods
5.3.1. Biomarker Analyses.
The methodologies used are described in full in Chapter 2. In summary, sediments were
extracted under reflux for 24 h using a Soxhlet apparatus. TLEs were subsequently
fractionated on aminopropyl SPE to generate neutral and acid fractions, and the neutral
fraction was fractionated using an (activated) alumina flash columns to generate apolar and
polar fractions. The neutral polar fraction was filtered and analysed using LC-MS APCI.
165
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Ion detection was performed in SIM mode, and GDGTs were quantified on their respective
[M+H]+ ion values (Schouten et al., 2007b). Polar fractions were derivatised with BSTFA,
acid fractions were methylated with BF3/MeOH, then derivatised with BSTFA. All
fractions were analysed by GC, and biomarkers quantified by GC-MS. The carbon isotopic
compositions of methylated n-alkanoic acids were determined by GC-C-IRMS.
5.3.2. Statistical Cluster Analysis of n-Alkanoic Acid δ13C
Agglomerative hierarchal cluster analysis of GDGT distributions was performed using
PAST (PAleontological STatistics) version 2.08© software (Hammer et al., 2001). Ward's
minimum variance method (Ward, 1963) was applied using Euclidean distances.
5.4. Results
5.4.1. Bulk Organic Geochemical Analysis
Figure 5.5. Bulk organic geochemical analysis of samples from mid-Waipara River
Column 2: (A) TOC content and (B) carbon isotopic composition of organic carbon. δ13C
values are reported relative to VPDB. The green band highlights an interval of elevated
TOC and relatively high δ13C values .
166
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Total organic carbon (TOC) is relatively low throughout the lower c. 65 m of the Waipara
section (Fig. 5.5A), decreasing from c. 0.5 % at 53.8 m (MW63) to c. 0.1 % at 64.8 m
(MW58), and remains low until 121.2 m (MW35), at which point TOC begins to increase
sharply and reaches 1.7 % at 129.5 m (MW43) before declining again to c. 0.6 % at 131.1
m (MW46).
The carbon isotopic composition of organic carbon (δ13CTOC) through mid-Waipara
Column 2 exhibits an analogous trend (Fig. 5.5B); δ13C values increase by c. 1 ‰ through
the lower 65 m of the section, from c. -28 ‰ at 53.8 m (MW63) to -27‰ at 121.2 m
(MW35). The upper c. 15 m of section represents an interval of remarkably higher δ13CTOC,
with values increasing from c -24 ‰ at 119.6 (MW34) to c -17‰ at 130.7 m (MW45).
This is the interval characterised by high TOC contents, and as such will herein be referred
to as the high-TOC interval for the purpose of discussion and comparison of trends through
the section.
A total of 40 samples from ODP Site 1121 (Hole B) between 135 m and 50 m were
analysed at the GNS stable isotope laboratory for % TOC and carbon isotopic composition
of organic carbon. Results were provided by Christopher Hollis of GNS, NW. The samples
were selected from similar horizons to those described in Wei et al. (2005), to enable
comparisons with previously determined bulk carbonate carbon and oxygen isotopic
compositions. TOC contents are low throughout the core (Fig. 5.6A), with highest values
generally around 0.2 % (except one sample at 126.1 m exhibiting a value of 0.4 %).
Sampling resolution is low from 135 mbsf to 120 mbsf, thus any trends are difficult to
identify. TOC decreases variably from average values of c. 0.15 % to c 0.02 % through the
remainder of the core.
The carbon isotopic composition of organic carbon (δ13CTOC) at ODP Site 1121 generally
increases through the section (Fig. 5.6B). From 100 m to 50 m, δ13CTOC values are variable
but increase from c. -28.5 ‰ to -26 ‰. The carbon isotopic composition of bulk
carbonate(δ13Ccarb) (Fig. 5.6C; Wei et al., 2005) exhibits a similar trend, increasing from c.
2.8 ‰ to 3.4 ‰. Variability in δ13Ccarb is particularly high between c. 80 m to 55 m, with
successively larger transient negative shifts of between c. -0.3 to 1 ‰ exhibited at 74.7 m,
66.6 m and 58.5 m.
167
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
168
Figure 5.6. Bulk organic geochemical analyses from ODP Site 1121. (A) Total organic carbon content (TOC), (B) carbon isotopic composition of bulk
organic carbon (δ13CTOC), (C) organic carbon composition of bulk inorganic carbonate (δ13Ccarb; Wei et al., 2005), and (D) difference between δ13Ccarb and
δ13CTOC (Δ13C(carb-TOC)). As δ13Ccarb and δ13CTOC measurements were not performed on the same samples, samples have been allocated into bins (I to X)
based on depth intervals and sampling resolution as described in the text. Average δ13Ccarb and δ13CTOC values were calculated for the determination of
Δ13C(carb-TOC) in each bin.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Assuming minor contribution of TOC from terrestrially derived organic carbon, the
difference between δ13Ccarb and δ13CTOC (Δ13Ccarb-TOC) predominantly reflects the
fractionation (p) between dissolved inorganic carbon (DIC) and primary photosynthate.
For modern photoautotrophs assimilating CO2aq and using diffusional transport, there is a
negative and linear correlation between [CO2]aq-1 and p, with the slope of that relationship
dependant on physiological variables such as growth rate, cell geometry and the
permeability of the cell membrane (Popp et al., 1998; Riebesell et al., 2000). By extension,
changes in Δ13Ccarb-TOC could reflect a combination of biological, oceanographic and global
carbon cycle processes.
For ODP Site 1121, δ13Ccarb and δ13CTOC values were determined but not on the same
sediments. Therefore, samples have been grouped into bins (I to X; Table 5.1, Fig. 5.6D)
based on depth intervals and sampling resolution to calculate Δ13Ccarb-TOC. Stratigraphic
intervals of 7 m or 8 m were selected for samples between 100 m and 50 m with the aim of
balancing bin size with sampling resolution. Below 100 m, sample resolution is low and
thus stratigraphic range of bin size is increased, to 26 m and 15 m for bins IX and X,
respectively. Average δ13Ccarb and δ13CTOC values were calculated for the determination of
Δ13Ccarb-TOC in each bin. Δ13Ccarb-TOC decreases through the core, from c. 31.5‰ at the base
of the record (Bin X), to c. 29 ‰ at the top (Bin I). Although sample resolution is lower
below 94 m and thus the bins are considerably larger in terms of depth interval, a decrease
of 1 ‰ in Δ13Ccarb-TOC occurs above the horizon at 94 m. A relatively enhanced decline in
Δ13Ccarb-TOC occurs across the transition from Bin V to Bin IV (at 62 m) which is coeval
with enhanced 13C-enrichment of 13CTOC (but not 13Ccarb).
Table 5.1 Compiled carbon isotope data from ODP Site 1121. Source 1 = carbon isotopic
composition of bulk carbonate (δ13C(carb)), taken from Wei et al. (2005). Source 2 is carbon
isotopic composition of bulk organic carbon (δ13C(TOC)), provided by Christopher Hollis of
GNS, NZ). Table outlines bin allocations for calculation of Δ13C(carb-TOC), and includes the
mean average values of δ13C(carb) and δ13C(TOC) derived for the calculation.
Source
Depth / m
1
1
1
2
2
2
1
1
1
2
2
33.2
34.72
36.22
33.21
34.71
36.21
42.82
44.32
45.82
42.81
44.31
δ13C(carb) (‰ VPDB) δ13C(TOC) (‰ VPDB)
-25.75
-25.90
-26.30
3.5
3.1
3.09
-25.83
-25.40
-25.40
Bin
average δ13C(carb) average δ13C(TOC) 13
Δ C(carb-TOC)
(‰ VPDB)
(‰ VPDB)
I
(30 - 38 m)
3.23
-25.98
29.21
II
(38 - 46 m)
3.23
-25.54
28.78
3.36
3.14
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Chapter 5
2
1
1
1
1
2
2
2
2
1
1
1
1
1
2
2
2
2
2
1
1
1
1
1
2
2
2
2
2
2
1
1
1
1
2
2
2
2
2
1
1
1
1
2
2
2
2
1
1
1
1
2
2
1
2
2
2
1
1
1
1
1
2
2
2
2
2
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
45.81
47.32
48.82
50.25
52.46
47.31
48.81
50.31
52.51
53.96
55.52
56.96
58.52
59.87
54.01
55.51
57.01
58.51
59.86
63.55
65.05
66.55
68.05
69.55
62.11
63.61
65.11
66.61
68.11
69.61
71.73
73.23
74.65
76.01
71.71
73.21
74.71
76
76.83
81.42
82.85
84.35
85.85
81.41
82.91
84.41
85.91
86.95
90.95
92.45
93.77
91.01
92.51
119.9
94.01
109.74
119.91
121.4
126.05
130.5
131.95
133.45
121.41
126.51
130.51
132.01
133.52
3.20
-26.34
-27.04
-27.63
-27.00
3.43
3.16
3.22
3.06
-26.95
-27.14
-26.38
-27.56
-27.05
3.08
3.23
2.82
2.26
3.02
-28.08
-28.65
-27.82
-27.03
-26.90
3.33
3.18
3.08
2.53
3.11
3.24
-27.55
-27.52
-27.71
-28.05
3.28
3.06
2.68
3.01
3.05
-26.83
-27.35
-27.37
-28.37
3.30
3.17
3.40
3.05
-27.60
-27.21
-28.13
-26.90
III
(46 - 53 m)
3.22
-26.68
29.90
IV
(53 - 62 m)
2.88
-27.02
29.90
V
(62 - 70 m)
3.08
-27.86
30.93
VI
(70 - 78 m)
3.02
-27.71
30.72
VII
(78 - 86 m)
3.23
-27.48
30.71
VIII
(86 - 94 m)
3.02
-27.46
30.48
IX
(94 - 120 m)
2.90
-28.57
31.47
X
(120 - 135 m)
2.72
-28.71
31.43
3.14
2.89
-27.53
2.76
3.01
2.94
-29.61
-30.40
-26.38
-29.03
-29.02
2.70
3.09
2.95
2.56
2.10
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.4.2 Biomarker Concentrations and Distributions at mid-Waipara River
All hydrocarbon fractions contain a homologous series of n-alkanes. Low-molecular
weight (LMW; C15-19) n-alkanes generally dominate throughout, with a typical
predominance of C17. A series of mid-molecular weight n-alkanes (MMW; C21-25) with low
odd-over-even preference are also prevalent thought the section, and high-molecular
weight (HMW; C27-33) n-alkanes with relatively strong odd-over-even predominance are
present but generally in lower concentrations than LMW and MMW components.
A series of hopanes ranging from C27 to C33, as well as hop-13(18)-enes and hop-17(21)enes, are present throughout the section, typically in concentrations similar to HMW nalkanes. 17β(H),21β(H)-homohopane (C31ββ hopane) and 17β(H),21β(H)-hopane (C30ββ
hopane) are predominant, reflecting the relatively low thermal maturity of the section
(Ourisson et al., 1979; Peters and Moldowan, 1991; 1993). The acyclic isoprenoidal
hydrocarbons pristane (Pr) and phytane (Ph) are also present in low concentrations in most
samples.
Polar fractions contain very low concentrations of even-carbon number n-alcohols,
including the C18, C22 and C28 components. Sterols are present in higher abundances than nalcohols in the polar fraction (Fig. 5.7); amongst those identified are cholest-5-en-3β-ol
(cholesterol; 27Δ5), 24-ethylcholest-5-en-3β-ol (β-sitosterol; 29Δ5) and 24-ethyl-5αcholestan-3β-ol (sitostanol; 29Δ0). Also present are an unsaturated and mono-unsaturated
4-methyl C30 sterol, tentatively identified as 4α,23,24-trimethylcholest-22-en-3β-ol
(dinosterol; 30Δ22) and
4α,23,24-trimethyl-5α-cholestan-3β-ol (dinostanol; 30Δ0).
However, these compounds are present in relatively low abundances, making it difficult to
confirm identification, and it is possible that 4-methy,24-ethyl analogues (4α-methyl-24ethyl-5α-cholestan-3β-ol and/or 4α-methyl-24-ethyl-5α-cholest-5-en-3β-ol) are instead
present or co-eluting. These are the same 4α-methyl C30 sterol compounds noted
previously in the mid-Waipara K/Pg section in Chapter 4. Trace amounts of 24-methyl-5αcholest-5-en-3β-ol (campesterol; 28Δ5) and 24-methylcholesta-5,22E-dien-3β-ol (28Δ5,22;
brassicasterol) were also detected in some samples characterised by relatively high sterol
content. Samples from the upper c. 15 m of section are also characterised by relatively high
concentrations of the glycerol dialkyl diether 2,3-di-O-phytanyl-sn-glycerol (archaeol).
171
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.7. (A) Total ion current chromatogram of polar fraction of MW58 (64.81 m). I.S
= hexadecan-2-ol internal standard. Highlighted in green in the region in which sterols
elute; some of the sterols identified at mid-Waipara Column 2 are observed in (B), a zoom
of the sterol region.
Acid fractions are dominated by a homologous series of n-alkanoic acids with strong evenover-odd predominance (Fig. 5.8). Distributions are essentially bimodal; LMW acids (C14C19) exhibit distributions dominated by the C16 and C18
homologues, whereas the
distributions of higher molecular weight n-alkanoic acids exhibit varying maxima, with
mid-molecular weight (MMW) compounds (C20-C24) dominant over the HMW (C26-C34)
compounds at certain intervals throughout the section. C22 is typically the dominant MMW
compound, whereas C26 and C28 are the predominant HMW compounds.
C30, C31 and C32 17(H),21(H)–hopanoic acids are present at concentrations similar to or
slightly greater than those of HMW (C26-34) n-alkanoic acids throughout mid-Waipara
River Column 2, with a predominance of 17β(H),21β(H)–homohopanoic acid (C31) (Fig.
5.8), also reflecting the low thermal maturity (Bishop and Abbot, 1993; Bennett and
Abbot, 1999; Farrimond et al., 2002). Samples from the upper c. 15 m of section are also
characterised by relatively high concentrations of acyclic C40 biphytanoic diacids.
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.8. Representative total ion current (TIC) chromatogram of MW35 methylated
acid fraction. Numbers above coloured circles represent carbon-numbers.
5.4.2.1 n-Alkanes and n-Alkanoic Acids
Proportions of HMW (C25-C33) and LMW (C15-C19) n-alkanes relative to total n-alkanes
vary throughout the section (Fig. 5.9). Relative proportions of HMW n-alkanes (expressed
as a fractional percentage of the total C15 to C33 n-alkanes) are typically low but vary from
c. 0.02 to 0.63 throughout the lower c. 65 m of the section, whereas relative proportions of
LMW n-alkanes are generally higher but exhibit greater variability, ranging from c. 0.11 to
0.98. Relative proportions of HMW n-alkanes increase throughout the upper c. 15 m (highTOC interval) of section, as relative proportions of LMW n-alkanes decrease; HMW
compounds dominate over LMW homologues through the upper part (from 128.4 m to
132.5 m ) of the high-TOC interval.
Distributions of n-alkanoic acids exhibit similar trends to the n-alkanes, although MMW
compounds (C20-C24) appear to behave somewhat independently of HMW and LMW
homologues, particularly through the upper 15 m of section (Fig 5.9C). LMW and MMW
compounds are generally dominant through the lower 65 m; relative proportions of LMW
n-alkanoic acids range from c. 0.25 to 0.53, while proportions of MMW homologues range
from c. 0.14 to 0.64 and generally track the HMW trends up to 101.2 m (MW52).
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.9. Relative proportions of n-alkane and n-alkanoic acids at mid-Waipara River
Column 2: (A) HMW (C25-C33) and LMW (C15-C19) n-alkanes, (B) HMW (C26-C34) and
LMW (C14-C18) n-alkanoic acids, with a zoom in on the upper c. 15 m of section (C).
Proportions are expressed as fractional percentages of the total n-alkanes or n-alkanoic
acids. The green band herein highlights the interval of elevated TOC and 13C enrichment
as discussed in the text.
Proportions of HMW and MMW n-alkanoic acids are relatively elevated (both at values of
c. 0.4) and dominant over LMW components through the lower c. 8 m of the high-TOC
interval. Trends in relative distributions of LMW and HMW n-alkanoic acids are more
variable through the upper c. 7 m of the high-TOC interval, whereas relative proportions of
MMW compounds remain relatively stable and decrease slightly. The terrigenous/aquatic
Ratio (TAR; Cranwell et al., 1987; Bourbonniere and Meyers, 1996; Eq. 4.1, 4.2)
compares the relative proportions of HMW to LMW components.
TARs are generally low for both n-alkane and n-alkanoic acids through the lower c. 65 m
of section (Fig. 5.10A), although relatively higher values are recorded in the c. 10 m below
the high-TOC interval. Low n-alkane TARs persist through the lower c. 8 m of the highTOC interval, whereas n-alkanoic TARs are slightly higher compared to values recorded
through much of the lower 65 m of section. TARs of both n-alkanoic acids and n-alkanes
increase variably through the upper 5 m of the high-TOC interval, reflecting variable
contributions from HMW and LMW components with a general trend to increasing
contribution from HMW compounds.
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Chapter 5
175
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.10. Trends in n-alkane and n-alkanoic acid distributions through mid-Waipara River Column 2. (A) Terrigenous/aquatic ratios (TARs); note the
n-alkane TAR scale on the upper abscissa axis, n-alkanoic acid TAR scale on the lower abscissa axis. (B) odd-over-even predominance (OEP) of nalkanes and even-over-odd predominance (EOP) of n-alkanoic acids. (C) Carbon preference indices (CPIs) of n-alkanes and n-alkanoic acids. (D)
Average chain lengths (ACLs) of n-alkanes and n-alkanoic acids.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The carbon preference indices (CPI; Bray and Evans, 1961; Eq 4.3, 4.4) and odd-over-even
predominance (OEP; Scalan and Smith, 1970; Eq 4.5) of n-alkanes and even-over-odd
predominance (EOP; Eq. 4.6) of n-alkanoic acids all exhibit similar trends, with only
minor differences (Fig. 5.10B,C). CPIs and OEPs of n-alkanes decrease through the lower
65 m of the section, from values of c. 2.1 to 1.0 and from c. 2.5 to 1.0, respectively,
although the trends are variable through the lower c. 20 m. CPIs and EOPs of n-alkanoic
acids exhibit similar variability through the lower 20 m of section, but then remain
relatively constant at c. 1.8 and 1.6 respectively, before exhibiting a shift to relatively
higher values above 101.2 m (MW52). CPI and OEP n-alkane values at the base of the
high-TOC interval are initially low (<1), but increase and become more variable through
the interval. Trends in n-alkanoic acid CPIs and EOPs are similar through the high-TOC
interval, except that values are already relatively high at the base of the interval at c. 2.6
and 3.1 respectively. Values decrease through the lower 8 m of the high-TOC interval,
before returning to higher values through the upper 5 m of the interval, coeval with the
increased CPI and OEP n-alkane values.
The average chain length of n-alkanes and n-alkanoic acids (ACL; Poynter and Eglinton,
1990; Eq. 4.7, 4.8) exhibit similar trends as the CPIs and EOP through the section (Fig.
5.10D). The ACLs of n-alkanes decrease through the lower c. 20 m of the section, from c.
28.5 to 25.9; values then increase through the remaining 45 m of section, to c. 28.1 at
114.9 m (MW31). The ACLs of n-alkanoic acids are generally more stable though the
lower 65 m of section, exhibiting values of c. 27.8. An increase to c. 29.0 occurs above
101.2 m, but values decrease to c. 26.5 at the base of the high-TOC interval. The nalkanoic acid ACLs then increase, albeit with some variability, through the high-TOC
interval, reaching a maximum of c. 29.5 at 131.1 m (MW46). The n-alkane ACLs exhibit
greater variability through the high-TOC interval than the n-alkanoic acid ACL but do
record a similar trend towards increasing values through the upper c. 7 m of the interval.
5.4.2.2. Sterols
None of the sterols indentified at mid-Waipara (Fig 5.7) have entirely unique sources
associated with them. C29 sterols are usually attributed to terrestrial higher plant sources
(Goad and Goodwin, 1972; Huang and Meinschen, 1976; Johns et al.,1980; Volkman et
al., 1980b, 2008), but its occurrence in highly productive oceanic settings is often
attributed to a contribution by non-specific planktonic sources (Lee et al., 1980; Volkman
176
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
et al., 1981; Walters and Cassa, 1985; Volkman, 1986, 2003; Pearson et al., 2000). 4methyl C30 sterols are more definitively derived from microalgae, e.g. dinoflagellates
(Withers et al., 1978; Boon et al., 1979; Robinson et al., 1984; Volkman, 1998, 2003;
Serrazanetti et al., 2006), although minor quantities of 4-methyl sterols are also
biosynthesised by some diatoms (Volkman et al., 1993) and haptophytes (Volkman et al.,
1990, 1997). Furthermore, sterols with a fully saturated ring system such as the 5α(H)stanols often occur in dinoflagellates, but are uncommon in other marine microalgae
(Robinson et al. 1984, Volkman et al. 1998). Cholesterol, also present in sediments at midWaipara River Column 2, is usually considered an indicator for zooplankton (Huang and
Meinschein, 1976; Gagosian and Nigrelli, 1976), either directly or through dietary
alteration of phytosterols (Gagosian and Heinzer, 1979; Volkman et al., 1987; Grice et al.,
1998). However, minor amounts are reported from terrestrial (Itoh et al., 1977; Nishimura
and Koyama, 1977) and aquatic (Johns et al.,1980; Volkman et al., 1980b, 2008) plants.
Figure 5.11. Algal biomarkers at mid-Waipara River Column 2: (A) concentrations of
C29:0 sterol (β-sitostanol) and C30:0 (tentatively identified as 4,22,23-trimethyl-5α-cholestan3β-ol (dinostanol). Note the different C30:0 and C29:0 scales. (B) Proportions of LMW nalkanes and n-alkanoic acids (relative to total).
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Sterol distributions through mid-Waipara River Column 2 resemble those of the midWaipara K/Pg boundary section discussed in Chapter 4, although stanols are present in
relatively higher proportions than sterols and C27 sterols are generally less abundant. The
C29:0 sterol, identified as β-sitostanol, is the dominant sterol throughout the section, cooccurring with subordinate concentrations of the 4α-methyl C30:0 sterol (Fig. 5.11A).
Concentration profiles of C29:0 and C30:0 sterols are almost identical through the section;
concentrations of C29:0 range from c. 0.0 to 64 μg g-1 TOC, and concentrations of C30:0
range from c. 0.0 to 0.26 μg g-1. Concentrations are generally low but variable throughout
the lower 65 m of section, with single samples at 64.8 m (MW58), 101.2 m (MW52) and
114.9 m (MW31) exhibiting relatively higher concentrations of both sterols. The latter two
concentration ‘spikes’ also correlate with high proportions of LMW n-alkanes (Fig.
5.11B).
Concentrations of C29:0 and C30:0 sterols throughout the high-TOC interval are generally
low, varying from c. 0.0 to 10.6 μg g-1 TOC and c. 0.0 to 0.03 μg g-1 TOC respectively,
except in on sample at 126.4 m (MW39); concentrations of C29:0 and C30:0 are c. 38 and
0.13 μg g-1, respectively). Trends in the C29:0 and C30:0 sterols share similar features to the
trends in relative proportions of LMW n-alkanes and n-alkanoic acids, including the shift
to lower values in the high-TOC interval. LMW n-alkanoic acids also exhibit a slight
increase in proportion relative to total n-alkanoic acids at 126.4 m (MW39), coeval with
the sharp increase in sterol concentrations.
Because the trends in C29:0 and C30:0 are so closely correlated, and share features with the
trend in relative proportions of LMW n-alkanoic acids, it is likely they derive from the
same source. Although the source of C29:0 sterols is often considered to be terrestrial (Goad
and Goodwin, 1972; Huang and Meinschen, 1976; Johns et al.,1980; Volkman et al.,
1980b, 2008), 4α-methyl C30:0 sterols are unambiguously marine in origin, and as such this
also suggests a predominantly marine origin for the C29:0 sterols. This does suggest that
there are no terrestrially derived sterols present in the mid-Waipara sediments, despite the
identification of higher plant (HMW n-alkanoic acid) and soil microbial (branched
GDGTs) biomarkers in the sediments. Functionalised compounds such as sterols may be
degraded over the course of riverine and coastal transport, through such mechanisms as
biodegradation, oxidation and photochemical reactions (Corbet et al., 1980; Hedges et al.,
1997; Hernandez et al., 2001; Jaffé et al., 2001, 2006), and as such any terrestrially derived
sterols may have been degraded before deposition to the sediments.
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5.4.2.3. Archaeal Lipids
Archaea are partly distinguished from the Bacteria and Eukarya because of the unique sn2,3 rather than sn-1,2 stereochemistry of the glycerol moieties within their membrane
lipids (Koga et al., 1998a,b), and because they contain ether-bound membrane lipids with
isoprenoidal carbon skeletons rather than ester-linked alkyl lipids (De Rosa and
Gambacorta, 1988). Such compounds or their degradation products have been found in
hypersaline environments (Teixidor et al., 1993), anoxic swamp sediments (Pauly and van
Fleet, 1986; Pancost et al., 2000b), and diverse pelagic settings (Hoefs et al., 1997;
DeLong et al., 1998; King et al., 1998; Schouten et al., 1998; Sunamara, et al., 1999).
Archaeol (2,3-di-O-phytanyl-sn-glycerol) has been identified in halophiles, thermophiles,
and methanogens and is the most common of the archaeal diethers (Koga et al., 1998a,b).
Archaeol, identified from comparison with a published mass spectrum (Teixidor et al.,
1993; Fig. 5.12), is observed only in the high-TOC interval of the mid-Waipara Column 2
section (Fig. 5.13A). Its lowermost occurrence is at 119.63 m (MW34) at a concentration
of c. 3.1 μg g-1 TOC, and is generally observed at concentrations of c. 1.4 to 6.0 μg g-1
TOC, except at its peak concentration of c. 27.2 μg g-1 TOC at c. 128.4 m (MW40; Fig.
5.12) and 9.4 μg g-1 TOC in the subsequent sample at 129.3 m (MW42).
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
180
Figure 5.12. (A): GC-MS Total Ion Current (TIC) chromatogram of MW40 (128.38 m) polar fraction, highlighting archaeol peak in blue with (B)
associated mass spectrum indicating major characteristic ion fragments.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Archaeol δ13C values were measured in samples MW40 (128.4 m), MW42 (129.3 m),
MW43 (129.5) and MW45 (130.7 m). δ13C values ranged from -23.5 ‰ to -27.3 ‰, with
no apparent depth trend. The average δ13C was -25.5 ± 1.5 ‰ (n = 8).
Figure 5.13. Concentrations of (A) archaeol and
through mid-Waipara Column 2.
(B) C40 acyclic biphytanoic diacid
The concentration profile of archaeol is similar to that of the C40 acyclic biphytanoic diacid
(Fig. 5.11B), which is also observed only in the high-TOC interval of the section (e.g. Fig.
5.13). Biphytanoic diacids are potentially degradation products of archaeal glycerol dialkyl
glycerol tetraethers (GDGTs), similar to suggested origins for widely occurring biphytane
diols in sediments. Biphytanoic diacids have been identified in Cenozoic methane seep
limestones and attributed to methanotrophic archaea (Birgel et al., 2008). However,
biphytanoic diacids containing 0–3 rings have also been found in non-seep sediments,
where distribution patterns suggest that they most likely derived from planktonic archaea
(Ahmed et al., 2001). In more recent studies, biphytanoic diacids have been found in
hydrothermally influenced sediments in the Guaymas Basin (Schouten et al., 2003a) and
New Zealand hot springs (Pancost et al., 2006). In the mid-Waipara Column 2 sediments,
only the acyclic structure was observed. On the basis of distributions of tetraether lipids in
modern settings and organisms, this likely indicates the source organism is methanogenic
(e.g. Koga et al., 1998a).
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
182
Figure 5.14. (A) Total ion current (TIC) chromatogram of MW40 methylated acid fraction, with n-alkanoic acids and hopanoic acids identified (nalkanoic acids are reported with carbon chain length, hopanoic acids are reported with number of carbons and the steroisomeric configuration. The acyclic
C40 biphytanoic diacid peak is highlighted with a blue box, and the corresponding mass spectrum given in (B). Characteristic ion fragments are
highlighted in red, and relate to characteristic peaks in reference spectrum (C), provided by Professor Richard D. Pancost (University of Bristol).
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Concentrations of the acyclic C40 biphytanoic diacid range from c. 0.8 μg g-1 TOC to 9.0
μg g-1 TOC through much of the high-TOC interval, with a peak concentration of c. 395 μg
g-1 TOC coeval with the peak concentration of archaeol at 128.38 m (MW40; Fig. 5.14).
Concentrations then decrease, exhibiting a very similar profile to archaeol concentrations.
5.4.3. Compound-Specific Isotope Analysis
The carbon isotopic compositions of n-alkanoic acids were determined to elucidate
information on the carbon cycle dynamics at mid-Waipara River. Cluster analysis of the nalkanoic δ13C values was also performed to determine appropriate groupings for
calculation of abundance weighted mean averages, i.e. which n-alkanoic acids are likely to
have derived from the same source.
5.4.3.1. High-Molecular Weight n-Alkanoic Acids
The carbon isotopic compositions (δ13C) of higher plant derived HMW even-carbonnumber n-alkanoic acids (C28, C30, C32 and C34) were determined, and abundance weighted
mean average δ13C (δ13CHMW) values calculated for the compound group.
The abundance weighted mean average carbon isotopic composition of C28-C34 n-alkanoic
acids (δ13CHMW) generally decreases by c. 1.8 ‰ through the basal 20 m of section, from c.
-31 ‰ at the base of the section to c. -32.8 ‰ at 70.4 m (MW57), before increasing to c. 31 ‰ through the overlying c. 45 m of strata (Fig. 5.13A). The δ13CHMW values vary from
c. -27.6 ‰ to -30.8 ‰ throughout the high-TOC interval in the upper c. 15 m of sediment.
Superimposed on the variability is a general trend towards increasing δ13CHMW values,
from c. -31 ‰ to maximum values of c. -27.6 ‰ in the upper c. 7 m of the interval.
δ13CHMW values then decrease to -32.2 ‰ in the uppermost sample at 131.1 m (MW46).
The δ13C values of individual n-alkanoic acids C28 and C30 are generally similar (Fig.
5.15B), and exhibit similar trends.
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.15. Compound-specific carbon isotope analysis of HMW n-alkanoic acids (C28-34)
through mid-Waipara River Column 2. (A) Abundance weighted mean average of carbon
isotope measurements of C28-C34 n-alkanoic acids (δ13CHMW). Error bars represent pooled
standard deviation. (B) δ13C records of individual n-alkanoic acids C28 and C30. Error bars
represent standard deviations of replicate analyses. Note δ13C analysis of C30 could not be
performed on samples MW60 (62.2 m), MW62 (58.3 m) and MW 63 (53.8 m) due to low
concentrations, and δ13C analysis of sample MW33 (117.9 m) could not be performed due
to low concentration of lipid extract. δ13C expressed relative to VPDB.
5.4.3.2. Mid-Molecular Weight n-Alkanoic Acids
Although the source of mid-molecular weight n-alkanoic acids is ambiguous (e.g. Meyers,
1997), trends in relative distributions (Fig. 5.9) suggest they derive from sources distinct
from those of HMW and LMW homologues at mid-Waipara Column 2. The abundance
weighted mean average of C20, C22 and C24 (δ13CMMW) is considered for representation of
the average mid-molecular weight n-alkanoic acid isotopic signal.
184
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.16. Compound-specific carbon isotope analysis of MMW n-alkanoic acids (C2024) through mid-Waipara River Column 2. (A) Abundance weighted mean average of
carbon isotope measurements of C20-C24 n-alkanoic acids (δ13CMMW) Error bars represent
pooled standard deviation. The grey line represents the δ13CHMW trend (Fig. 5.15), shown
here for comparison as discussed in the text. Note δ13C analysis of C20 could not be
performed on sample MW45 (130.7 m) due to low sample concentration. (B) δ13C records
of individual n-alkanoic acids C20, C22 and C24. Error bars represent standard deviations of
replicate analyses. Note δ13C analysis of sample MW33 (117.9 m) could not be performed
due to low concentration of lipid extract. δ13C expressed relative to VPDB.
The depth profile of δ13CMMW values resembles that of δ13CHMW values through the lower
65 m of strata at mid-Waipara Column 2 (Fig. 5.16A), and MMW n-alkanoic acids indeed
exhibit almost identical δ13C values throughout the interval (δ13CMMW values are generally
±0.5 ‰ relative to co-occurring δ13CHMW values). However, the trends become decoupled
in the high-TOC interval: δ13CMMW values exhibit greater
13
C-enrichment at 123.5 m
(MW37), 126.4 m (MW39), 129.5 m (MW43) and 131.1 m (MW46). For those samples,
the δ13CMMW values are about 1 – 1.5 ‰ greater than δ13CHMW values, except at 126.4 m
where the δ13CMMW value is c. -21.9 ‰, c. 5.7 ‰ higher than the coeval δ13CHMW value.
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
However, MMW n-alkanoic acids are
13
C-depleted relative to coeval HMW n-alkanoic
acids by c. 1.2 ‰ at 130.7 m (MW45) and 125.2 m (MW38).
5.4.3.3. Low-Molecular Weight n-Alkanoic Acids
Figure 5.17. Compound-specific carbon isotope analysis of LMW n-alkanoic acids (C14-18)
through mid-Waipara River Column 2. (A) Abundance weighted mean average of carbon
isotope measurements of C14-C18 n-alkanoic acids (δ13CLMW) Error bars represent pooled
standard deviation. The grey line represents the δ13CMMW trend (Fig. 5.16), shown here for
comparison as discussed in the text. Note δ13C analysis of C16 could not be performed on
samples MW45 (130.7 m) and MW40 (128.4) due to low concentrations and no δ13C
analyses were possible for sample MW33 (117.9 m). (B) δ13C records of individual nalkanoic acids C16 and C18. Error bars represent standard deviations of replicate analyses.
δ13C expressed relative to VPDB.
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Although sources of LMW n-alkanoic acids are less specific than the HMW counterparts,
their depth profiles, similar to those of sterols, suggests a marine origin and their δ13C
values could reflect marine algal signals. Presented here are the δ13C records of the C16 and
C18 homologues, as well as the mean weighted average δ13C of the LWM n-alkanoic acids,
herein referred to as δ13CLMW. The δ13CLMW profile is clearly similar to that of δ13CMMW
and δ13CHMW, although the values are somewhat higher in the lower 65 m of Column 2.
(Fig. 5.17). In general, δ13CLMW values are between c. 0.6 ‰ and 2.8 ‰ more positive than
co-occurring δ13CMMW values and 0.9 – 2.8 ‰ more positive than co-occurring δ13CHMW
values, except at 79.7 m (MW56). The offset between δ13CLMW and δ13CMMW values is
reduced through much of the high-TOC interval – generally being between c. 0.6 ‰ and
1.4 ‰. The exception to this is the sample (MW39) from 126.4 cm, where δ13CMMW values
are very high. The offset between δ13CLMW and δ13CHMW values remains generally
unchanged, between 0.8 ‰ and 2.7 ‰, throughout the high TOC interval. However,
although δ13CLMW exhibits a more positive shift than δ13CHMW at 126.4 m (MW39),
δ13CMMW values are still substantially higher than δ13CMMW, by c. 3.8 ‰. LMW n-alkanoic
acids are also substantially enriched in
13
C relative to both MMW and HMW n-alkanoic
acids at 129.6 m (MW42), by c. 2.5 ‰ and 2.7 ‰, respectively.
MMW n-alkanoic acids appear to exhibit different stratigraphic trends than the LMW and
HMW counterparts, particularly through the high-TOC interval of the upper 15 m of midWaipara Column 2. Presented here is a statistical analysis (agglomerative hierarchal cluster
analysis) based on the carbon isotopic composition of the n-alkanoic acids to test this (Fig.
5.18), and to determine compound groupings for further interrogation of δ13C records.
The analysis confirms that MMW n-alkanoic acids cluster separately from HMW and
LMW components based on their carbon isotopic compositions (Fig. 5.18A,B). The cluster
analysis also indicates that the MMW compounds are more similar in carbon isotopic
composition to the HMW compounds than the LMW homologues. Furthermore, C26 is
indicated as clustering with the MMW compounds, rather than the HMW compounds; this
is likely to also be derived from higher plants, and as such it is precluded from abundance
weighted mean average calculations.
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.4.3.4. Cluster Analysis of n-Alkanoic Acid Carbon Isotopic Compositions
Figure 5.18. Agglomerative hierarchal cluster analysis of δ13C of n-alkanoic acids, using
Euclidean distances. Cophenetic coefficient is 0.7132. (A), (B) and (C) indicate the 3
greatest distances; (B) represents the separation of HMW (C28-C32) and MMW (C20-C26)
component. (C) indicates further separation between C20 and the other MMW homologues.
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.4.3.5. Hopanoic Acids
Hopanoids are synthesised by some bacteria as membrane stabilising compounds
(Ourisson et al., 1979, 1987; Ourisson and Rohmer, 1982); hopanoic acids are generally
considered to be early diagenetic products of biohopanoids (Quirk et al., 1984; Buchholz et
al., 1993; Innes et al., 1997, 1998; Watson and Farrimond, 2000). As such, the compoundspecific carbon isotopic composition of hopanoic acids C30, C31 and C32 are presented here
alongside the abundance weighted mean average of the three hopanoic acids, herein
referred to as δ13Chop.
The δ13Chop profile (Fig. 5.19) exhibits less variability through the lower 65 m of sediment
than the contemporaneous n-alkanoic acid δ13C records. δ13Chop values increase relatively
steadily from c. -31 ‰ at the base of the interval to -29.4 ‰ at 114.9 m (MW31). δ13Chop
then exhibits a more rapid increase through the high-TOC interval, from c -29 ‰ at 119.6
m (MW34) to peak values of c. -25.2 ‰ at 128.3 m (MW40), coeval with the most
13
C-
13
enriched n-alkanoic acids. δ Chop values then decrease by c. 1.1‰ to c. -26.3 ‰ through
the overlying c. 1 m of sediment, before decreasing sharply to c. -31.4 ‰ at 131.1 m (MW
46), coeval with negative shifts of 3 – 4 ‰ in co-occurring n-alkanoic acids, and a decrease
in δ13CTOC of c. 6.5 ‰.
189
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.19. Compound-specific carbon isotope analysis of hopanoic acids (C30-32) through
mid-Waipara River Column 2. (A) Abundance weighted mean average of carbon isotope
measurements of C30, C31 and C32 hopanoic acids (δ13Chop). Error bars represent pooled
standard deviation. (B) δ13C records of individual n-alkanoic acids C26, C28 and C30. Error
bars represent standard deviations of replicate analyses. Note δ13C analysis of samples
MW33 (117.9 m) and MW45 (130.7) could not be performed due to low concentrations of
lipid extracts. δ13C expressed relative to VPDB.
5.4.4. Glycerol Dialkyl Glycerol Tetraether Distributions
GDGT distributions were determined for the 22 samples at mid-Waipara River, and 14
samples from ODP Site 1121. GDGT distributions of the published ODP Site 1172 dataset
(Bijl et al., 2009) was evaluated based on raw data provided by Peter Bijl (University of
Utrecht).
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
191
Figure 5.20. Example GDGT distributions at mid-Waipara River Column 2, plotted with % TOC and δ13CTOC, including: MW43 (129.53 m) in the highTOC / low δ13CTOC interval, and MW56 (79.66 m) in the lower Waipara Greensand formation. GDGTs plotted as fractional abundance of total GDGT
distribution, and labelled according to number of cyclopentyl moieties: 0 = GDGT-0, 1 = GDGT-1, 2 = GDGT-2, 3 = GDGT-3, GDGT-4’ = crenarchaeol
isomer.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
192
Figure 5.21. Relative proportions of (A) GDGT-1, (B) GDGT-2, (C) GDGT-3, (D) GDGT-4 normalised to total of [GDGT-1+ GDGT-2 + GDGT-3 +
GDGT-4’] and expressed as fractional percentage.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.4.4.1. Mid-Waipara River GDGT Distributions
Example GDGT distributions observed in low-TOC (MW56;79.66 m) and high-TOC
(MW43; 129.53 m) lithologies are given in Figure 5.20. Proportions of GDGT-1, GDGT-2,
GDGT-3 and GDGT-4’ (relative to the sum of those four compounds) at mid-Waipara
River Column 2 are shown in Figure 5.21. Proportions of GDGTs are somewhat variable
through the lowest 20 m of the section. From c. 70 – 110 m, relative proportions of GDGT1 and GDGT-4’ exhibit mirrored profiles through the interval, with the former increasing
(from c. 0.38 to c 0.44) and the latter GDGT-4’ decreasing (from c. 0.18 to 0.12). Relative
proportions of GDGT-2 and GDGT-3 reflect similar trends through the lower 65 m of
sediment; relative proportions of GDGT-2 decrease from c. 0.28 to 0.30, and relative
proportions of GDGT-3 decrease from c. 0.14 to 0.12.
Increased variability characterises the GDGT distributions in the TOC-rich interval. In
general, however, proportions of GDGT-1 increase to a maximum of c. 0.50, as GDGT4’proportions decrease to a minimum of c. 0.11 at 128.4 m (MW40). GDGT-2 and GDGT3 proportions exhibit similar trends through the lower c. 8 m of the TOC-rich interval: the
former decreasing from c. 0.29 to 0.28 and the latter decreasing from c. 0.13 to 0.11.
However, trends are decoupled in the upper part of the TOC-rich interval, with proportions
of GDGT-2 decreasing from c. 0.30 to 0.27 and then increasing in the upper 2 m of the
section and GDGT-3 proportions exhibiting the opposite trends.
SSTs were reconstructed for the mid-Waipara River section using the most recently
proposed calibrations (Fig. 5.22A). Applying
(Kim et al., 2010) yields very similar
temperatures to those derived from the earlier calibrations of Kim et al. (2008) and Liu et
al. (2009; Fig. 5.22A).
and
reconstructions (Fig. 5.22B; raw index values
used are shown in Fig. 5.22C) record different absolute temperatures, but reflect the same
trends. The offset between
and
is shown in Figure 5.22E, together with the
ratio of GDGT-2/GDGT-3. As discussed in Chapter 3, the ratio of GDGT-2/GDGT-3 is
interrogated as an indicator of possible biases in reconstructed temperatures and to explain
the offset between
and
and
reconstructions.
both record variable temperatures, ranging from c. 21.5 °C to 24.4 °C
and 14.9 to 18.1°C, respectively, through the lower 20 m of section. Both indices then
record a cooling trend through the remaining 45 m of the interval. Cooling is slightly more
pronounced in the
20°C;
record, with reconstructed SSTs decreasing from c. 22.5°C to
reconstructions exhibit an SST cooling from c. 16.5°C to 15.0°C.
193
Chapter 5
194
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.22. Mid-Waipara River Column 2 section (A) TEX86 reconstructed SSTs using various calibrations (simple propagated calibration error and
analytical precision given as error bars), (B)
and
derived SST reconstructions, (C) raw
and
values with analytical precision
given as error bars (error bars not visible as they are smaller than the plot points), (D) ratio of [GDGT-2]/[GDGT-3] and (E) offset between
and
derived SST reconstructions, calculated as
.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The cooling trend continues through the high-TOC interval, and is particularly pronounced
in the upper c. 7 m of the interval:
SSTs decrease from SSTs of c. 20.5°C in the
lower c. 8 m of the interval, to c. 18°C at 128.4 m (MW40).
SSTs similarly
decrease from SSTs of c. 15.5°C in the lower 8 m of the high-TOC interval, to 13°C at
128.4 m (MW40). SSTs then warm gradually through the remainder of the section
The offset between
and
derived SSTs is c. 6.5°C in the lowermost 40 m of
the section. Offsets then decrease to c. 5°C at about 95 m and then become more variable
(4.5 to 6°C) in the high-TOC interval. Similar trends are reflected in the ratio of GDGT2/GDGT-3; higher SST offsets co-occur with lower GDGT-2/GDGT-3 ratios and vice
versa (Fig. 5.22D, E).
Figure 5.23. BIT index through mid-Waipara Column 2.
BIT indices are low throughout mid-Waipara River Column 2 (Fig. 5.23), not exceeding
values of 0.1. Values range from c. 0.04 to 0.06 throughout the lower 65 m of section, with
two maxima of 0.07 exhibited at 64.8 m (MW58) and 101.2 m (MW52). BIT indices
increase from c. 0.04 at 110.1 m (MW29) through the high-TOC interval, peaking at values
of c. 0.1 at 129.3 m (MW42) and remaining relatively high ( c.0.07 – 0.09) throughout the
remainder of the section.
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5.4.4.2. ODP Site 1121 GDGT Distributions
Representative LC-MS chromatograms showing GDGT distributions down-core at ODP
Site 1121 are reproduced in Figure 5.24. Proportions of GDGT-1, GDGT-2, GDGT-3 and
GDGT-4’ (relative to the sum of those four compounds) at ODP Site 1121 are shown in
Figure 5.25.
Figure 5.24. Example LC-MS chromatograms of GDGTs at ODP Site 1121, including:
CP12 (56.97 m), CP21 (69.57 m), CP26 (76.04 m) and CP36 (94.05 m). GDGTs are
labelled according to number of cyclopentyl rings within the structure: 0 = GDGT-0, 1 =
GDGT-1, 2 = GDGT-2, 3 = GDGT-3, GDGT-4’ = crenarchaeol regio-isomer.
The sample at 119.6 m (CP37) exhibits a distribution which is generally different from the
rest of the record; however, due to the low TOC contents of adjacent horizons it is not
possible to determine whether this distribution is anomalous or
indicates different
environmental conditions near the base of the section. Therefore this sample is excluded
from further discussion. GDGT distributions in the rest of the section fall into a relatively
narrow range (i.e. fractional abundance of GDGT-1 ranges from 0.35 to 0.45) and exhibit
only minor variability; longer-term trends from 94 to 57 m, however, are apparent.
Relative proportions of GDGT-1 increase, as relative proportions of GDGT-2 and GDGT-4
generally decrease; proportions of GDGT-3 are relatively stable.
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
197
Figure 5.25. Relative proportions of (A) GDGT-1, (B) GDGT-2, (C) GDGT-3, (D) GDGT-4 normalised to total of [GDGT-1+ GDGT-2 + GDGT-3 +
GDGT-4’] and expressed as fractional percentage.
Chapter 5
198
198
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.26. ODP Site 1121 (A) TEX86 reconstructed SSTs using various calibrations; simple propagated calibration error and analytical precision given
as error bars, (B)
and
derived SST reconstructions, (C) raw
and
values with analytical precision given as error bars, (D) ratio
of [GDGT-2]/[GDGT-3] and (E) offset between
and
derived SST reconstructions, calculated as
–
.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Applying
(Kim et al., 2010) yields very similar temperatures to those constructed
by the earlier calibrations of Kim et al. (2008) and Liu et al. (2009; Fig. 5.26A). SSTs of c.
24°C (
) and 23°C (
) are reconstructed at 94.0 m (CP36), followed by a
cooling trend through the section, with
and
SST reconstructions decreasing to c. 22°C,
SST estimates decreasing to c. 19°C. Offsets between
and
(Fig.
5.26E) are generally lower than those observed in the Waipara section (<3 °C), excepting
the sample at 119.6m that has been excluded and the sample at 90m.
5.4.4.3. ODP Site 1172 (Evaluation of Published Data)
Raw GDGT data from the Paleocene samples of ODP Site 1172 (East Tasman Plateau)
have been evaluated here for comparison with the data generated in this study from midWaipara River Column 2 and ODP Site 1121. TEX86 records were published by Bijl et al.
(2009), and raw GDGT data was provided by Peter Bijl (Univeristy of Utrecht). A total of
12 samples from depths of c. 690 m to 620 m represent the time interval spanning c. 63 –
57 Ma.
Relative proportions of GDGT-1 increase up-section, coeval with decreasing relative
proportions of GDGT-2. Relative proportions of GDGT-3 and GDGT-4’ exhibiting larger
shifts but at different horizons: from 10% to 9% at 659.9 m and from 18% to 15% at 639.2
m, respectively (Fig. 5.27)
As observed for TEX86 records through mid-Waipara River Column 2 and ODP Site 1121,
(Kim et al., 2010) yields very similar temperatures across the record to those
constructed by the earlier calibrations of Kim et al. (2008) and Liu et al. (2009) (Fig.
5.28A). However,
and
reconstructions are offset by c. 4-6°C (Fig. 5.28E),
again co-varying with the ratio of GDGT-2/GDGT-3 (Fig. 5.28D).Variable SSTs occur
from c. 682.8 m to 659.9 m (
reconstructed SSTs range from c. 22°C to 25°C,
derived SSTs range from c. 18°C to 22°C). A subtle but steady decline in SST occurs from
653.9 m to 634.1 m, from 25°C to 20°C for
and from 22°C to 16°C for
.
Relatively stable SSTs extend from 634.1 m to 626.6 m, followed by a warming to c. 23°C
(
) or c. 19°C (
) in the uppermost horizon.
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200
Figure 5.27. Relative proportions of (A) GDGT-1, (B) GDGT-2, (C) GDGT-3, (D) GDGT-4 normalised to total of [GDGT-1+ GDGT-2 + GDGT-3 +
GDGT-4’] and expressed as fractional percentage.
Chapter 5
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.28. ODP Site 1121 (A) TEX86 reconstructed SSTs using various calibrations; simple propagated calibration error and analytical precision given
as error bars, (B)
and
derived SST reconstructions, (C) raw
and
values with analytical precision given as error bars, (D) ratio
of [GDGT-2]/[GDGT-3] and (E) offset between
and
derived SST reconstructions, calculated as
–
.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The ratio of GDGT-2/GDGT-3 through ODP Site 1172 exhibits a similar relationship to
the offset between
and
reconstructed SSTs observed elsewhere (as discussed
in Chapter 3, and observed in the other sections in this Chapter); lower ratios of GDGT2/GDGT-3 correspond to higher offsets between
and
and
(Fig. 28D,E). The
offset decreases from 673.1 m to 653.9 m, and then increases from 653.9
m to 634.1 m, coeval with the cooling phase exhibited by the TEX86 SST records. The
overlying interval of stable SSTs followed by warming is associated with higher GDGT2/GDGT-3 ratios and smaller offsets between
and
.
5.5. Discussion
5.5.1. Environmental Change at mid-Waipara River Column 2
A long-term cooling trend is recorded by both the
and
proxies at mid-
Waipara River Column 2 between 79.7 m and 131.1 m. The age model (Fig. 5.3) dates the
timing of this interval to be from c. 60.6 Ma to 58.0 Ma. This cooling trend is corroborated
by the other southwest Pacific
and
SST reconstructions presented for ODP
Site 1121 (Fig. 5.26) and ODP Site 1172 (Fig. 5.28). Superimposed upon the long-term
cooling trend is a period of more enhanced cooling at mid-Waipara beginning at c. 58.5
Ma (Fig. 5.22) which is not generally reflected in δ18Ocarb record at ODP Site 1121, or the
TEX86 record of ODP Site 1172. However, at mid-Waipara, the latter part of the cooling
trend is also associated with environmental changes recorded by an increase in TOC
contents, 13CTOC values and changes in biomarker distributions, including elevated BIT
indices (Fig. 5.23) and relative proportions of HMW n-alkanoic acids and n-alkanes
exhibiting elevated CPIs and OEP/EOPs (Fig5.10).
Elevated archaeol and biphytanoic diacid concentrations are also associated with this
horizon (Fig. 5.13). The environmental changes through this horizon at mid-Waipara are
also associated with a shorter interval of enhanced cooling, superimposed upon the longer
term cooling trend (Fig. 5.22), and this is not evident in the ODP Site 1121 and ODP Site
1172 SST records. This enhanced cooling interval corresponds to even higher TOC
contents and δ13C values and further variations in biomarker assemblages (Fig. 5.29). The
base of this interval is at c. 58.3 Ma, subsequently defined as Horizon A. The implications
of these changes for the climate and environment of mid-Waipara in the Late Paleocene are
discussed below.
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203
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Figure 5.29. Compilation of environmental and ecological indicators at mid-Waipara River Column 2, including: (A) total organic carbon content (%),
(B) δ13C total organic carbon (δ13C; ‰VPDB), (C)
and
SST reconstructions, (D) concentrations of C29:0 and C30:0 sterols (μg g-1 TOC), (E)
concentration of archaeol (μg g-1 TOC), (F) BIT index. Green bar highlights the high-TOC interval, the brown bar represents Horizon A (i.e. the upper c.
5 m of the high-TOC interval).
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.5.1.1. Changes in Sources of Organic Matter
Relative proportions of HMW n-alkanes (exhibiting odd-over-even predominance) and nalkanoic acids (exhibiting even-over-odd predominance) are generally elevated through the
high-TOC interval, particularly within Horizon A (Fig. 5.9). In general, the presence of
HMW n-alkanes with relatively high odd-over-even predominance and n-alkanoic acids
with high even-over-odd predominance indicate a terrigenous input of organic matter to the
sediments (Eglinton and Hamilton, 1963, 1967; Eglinton and Calvin, 1967; Cranwell et al.,
1987; Kvenvolden, 1967; Tullock, 1976; Kolattukudy, 1980; Rieley et al., 1991). BIT
indices are similarly elevated through this horizon (Fig. 5.29F), which is associated with
contribution of terrestrial soil organic matter (Hopmans et al., 2004), as branched GDGTs
derive from anaerobic soil bacteria (Weijers et al., 2006a, 2006b, 2009; Sinninghe Damsté,
et al., 2011). Together these proxies suggest an enhanced contribution of terrestrial OM to
the sediment at mid-Waipara throughout the high-TOC interval and Horizon A.
Enhanced flux of terrestrially derived material through Horizon A could be caused by
increased transport of terrestrial material, as a likely result of enhanced precipitation and
run-off. However, the ACL of n-alkanes and n-alkanoic acids are also higher through the
high-TOC interval (Fig. 5.10D), and in particular through Horizon A, coeval with highest
BIT indices. Increased ACL has been tentatively suggested to be an adaptation of higher
plant
leaf
waxes
in
response
to
increased
temperature
and/or
decreased
humidity/precipitation (Hall and Jones, 1961; Gagosian and Peltzer, 1986; Poynter et al.,
1989; Rommerskirchen et al., 2003; Schefuβ et al., 2003; Sachse et al., 2006; van Dongen
et al., 2008). TEX86 SST records clearly indicate this interval to be the coolest of the entire
section (Fig. 5.29C); thus, if ACL is a response to environmental change in this instance, it
is likely to be a response to drier, not wetter conditions.
An alternative explanation for elevated flux of terrestrial material to the sediment is a sealevel change, with lower sea-level increasing the proximity of the site of deposition to
shore, increasing the influence of coastal and riverine OM on the overall organic matter
composition. Palynofacies analysis of contemporary sites in New Zealand signals a distinct
regression across several of New Zealand’s sedimentary basins, suggesting a eustatic sealevel fall (Hollis et al., 2009a; Andrew, 2010; Schiøler et al., 2010). Eastward of the main
depocentres, hardgrounds, lag deposits, phosphatic layers and glaucony suggest
intensification of Southern Ocean bottom water currents argued to be consistent with a
proto-western boundary current flow (Hollis et al., 2009; Andrew, 2010). This suggests
that the sea-level fall could be related to ephemeral ice formation in Antarctica (Anderson
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
et al., 1999, Hollis et al., 2009; Andrew, 2010). This is also consistent with the TEX86
record which reflects pronounced SST cooling contemporaneous with maxima in BIT (Fig.
5.29 C,F) and HMW n-alkyl compounds (Fig. 5.9). The sea-level fall could be a result of
local or regional tectonically-driven processes, or reflect a more global eustatic signal,
including either ice sheet expansion or thermal contraction of water masses in response to
cooling.
The low concentrations of sterols (relative to TOC; Fig. 5.29D) and decreased proportions
of putative algal-derived biomass (e.g. LMW n-alkanoic acids; Fig. 5.9, 5.10A) through the
high-TOC interval relative to the underlying c. 65 m of sediment may reflect the enhanced
terrigenous input discussed above, diluting the marine input. If concentrations relative to
sediment are considered, all biomarkers, including those or presumed marine origin, are
dramatically elevated in the TOC-rich interval, suggesting it was characterised by both
high productivity and enhanced terrestrial inputs. High productivity for the region through
the late Paleocene is also indicated by a pronounced and sustained increase in biosiliceous
productivity, argued to be due to enhanced upwelling at the continental margin (Hollis,
2002; 2006). Similar episodes of intensified upwelling offshore eastern New Zealand have
been proposed to account for biosiliceous sediment accumulation in the Late Cretaceous at
DSDP Site 275 (Andrews and Ovenshine, 1974), earliest Paleocene at Mead Hill
Formation in Marlborough (Hollis et al., 1995) and Late Paleocene strata on Chatham
Island (Hollis, 1997b), as well as mid-Waipara River post-K/Pg sediments (Hollis, 2003;
Hollis et al., 2003a,b; Chapter 3). The TEX86 SST records, and in particular the enhanced
cooling reconstructed in Horizon A, are in agreement with the suggestion of enhanced
upwelling.
5.5.1.2. Mid-Molecular Weight n-Alkanoic Acids: Evidence for a Third Source of OM?
Cluster analysis of n-alkanoic acids based on δ13C values revealed that MMW n-alkanoic
acids behave separately from HMW and LMW homologues (Fig. 5.18). This is consistent
with the different MMW n-alkanoic acid depth profiles (Fig. 5.9B) and suggests at least a
partially independent source. The MMW n-alkanoic acid δ13C values potentially provide
insight into that source(s): through the lower c. 65 m of section, δ13CMMW and δ13CHMW
values are similar (Fig. 5.15, 5.16), suggesting a common source, likely terrestrial plants.
However, in the high-TOC interval, the δ13CMMW profile shares some similarities with the
δ13CLMW (Fig. 5.16, 5.17). Moreover, δ13CMMW values are higher than δ13CHMW values in
that interval by c. 0.5 ‰ – 1.5 ‰ (except for one value at 128.4 m in which δ13CMMW is
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
much more 13C-enriched) and lower than δ13CLMW values (generally by c. 1 ‰ – 2 ‰). This
suggests that these compounds are at least in part derived from a third source in Horizon A,
although it is likely that they may instead derive from higher plants through parts of the
section.
Submerged or floating macrophytes, including macroscopic algae and bryophytes,
primitive vascular plants, such as ferns and fern allies, and angiosperms, are potential
sources of the MMW n-alkanoic acids. In terms of the biomarker distributions of such
organisms, the n-alkyl distributions of submerged and floating macrophytes are known to
maximize at MMW compounds (Cranwell, 1984; Ogura et al., 1990; Viso et al., 1993;
Ficken et al., 2000); the dominant n-alkanoic acids reported for such organisms are
consistently C20, C22 and C24 (Oritz et al., 2010), lending support to the hypothesis that
aquatic/marine macrophytes may be contributing MMW n-alkanoic acids to the
distributions in the sediments. Furthermore, sitosterol is known to be the major sterol
component of sea-grass, a submerged macrophyte known to occupy shallow marine
settings (Volkmann et al., 1981; Nichols et al., 1982; Nichols and Johns, 1985; Canuel et
al., 1997; Jaffé et al., 2001).
Such a source could also explain the observed δ13CLMW values. The application of
terrestrial photosynthetic categories to photoautotrophs that exist under water is considered
unsatisfactory, because when water replaces air as the primary bathing medium it imposes
very different constraints on gas exchange (Bowes and Salvucci, 1989). As a consequence,
the photosynthetic features of submersed aquatic macrophytes, although resembling those
of terrestrial species, do differ in a number of important respects. The most striking of
these is the intraspecific plasticity that submersed aquatic plants demonstrate associated
with photosynthesis (Bowes and Salvucci, 1989). A major distinction between terrestrial
and aquatic plant photosynthesis is that the latter potentially has access to HCO3concentrations in the environment (Smith and Walker, 1980; Keeley and Sandquist, 1992).
As a consequence, the δ13C values of submersed aquatic macrophytes from a range of
freshwater habitats in Britain and Finland are mostly intermediate between very negative
values (-39 ‰ to -42 ‰; indicative of free CO2 fixation), and less negative values (-12 to 15‰; indicative of diffusion limitations and HCO3- uptake; Osmond et al., 1981). Thus, an
aquatic macrophyte source for the MMW n-alkanoic acids is consistent with the relatively
intermediate 13C values observed at mid-Waipara, particularly through the high-TOC
interval.
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Macrophyte habitats may be coastal, estuarine or riverine (Osman et al., 1981; Zieman and
Zieman, 1989; Xu et al., 2006), and as such macrophyte lipids could either be
autochthonous, or fluvially transported to marine sediment. However, their increased
proportions in the TOC-rich horizon (Fig. 5.9B), corresponding to higher BIT indices (Fig.
5.23) and ratios of high to low molecular weight n-alkyl ratios (Fig. 5.10A), are consistent
with increased fluvial delivery to Waipara sediments, or increased proximity of the site of
deposition to shore (i.e. shallowing). This highlights the complexities of coastal
palaeoenvironmental reconstructions as discussed by other authors (Mead et al., 2005; Xu
et al., 2006), whereby traditional end-member descriptions of terrestrial and marine may be
confounded by macrophyte input to the sediment. However, measurement of sitosterol
carbon isotopic composition may provide further insight into the possibility of macrophyte
input into the organic matter at mid-Waipara. Comparison of sitosterol δ13C with nalkanoic acid δ13CLMW , δ13CMMW and δ13CHMW values may elucidate a common source; i.e.,
if sitosterol δ13C values are most similar to δ13CMMW values, a common macrophytic source
may be more definitively assigned (and input of OM from such a source considered more
likely). Alternatively, sitosterol δ13C values may be more similar to δ13CLMW values; that
would suggest a common source which is likely algal, and also provide stronger evidence
for an algal LMW n-alkanoic acid source, owing to the fact that bacteria do not produce
sterols (i.e. if the source of LMW n-alkanoic acids also produces sterols, it is unlikely to be
microbial). Finally, if sitosterol δ13C values are most closely matched with n-alkanoic acid
δ13CHMW values, a common higher plant source would be inferred, suggesting that the C 30
sterols are the only algal-derived sterols.
In summary, biomarker and compound specific carbon isotope analysis suggests a
submerged or floating macrophyte source of OM to the sediments at mid-Waipara; this
tentative source of OM apparently becomes more significant in the high-TOC interval,
suggesting an expansion of the source organism; such an expansion of shallow-water
thriving organisms could be a direct result of shallowing (i.e. a sea-level fall resulting in
expansion of shallower waters as a habitat for the macrophytes), or as a result of stimulated
growth due to increased flux of terrestrially derived nutrients as a consequence of an
enhanced hydrological cycle. Such scenarios remain consistent with the evidence for
enhanced terrestrial input to the sediment as evidenced by increased terrestrial plant
(HMW n-alkyl compounds) and soil microbial (branched GDGTs - increased BIT indices)
biomarker concentrations through the high-TOC interval (as discussed in Section 5.4.1.1).
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Chapter 5
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5.5.1.3. Changes in Sedimentary Redox Conditions
Elevated concentrations of archaeol and biphytanoic diacids are detected in the high-TOC
interval, particularly through Horizon A (Fig. 5.13, 5.29E). The compounds are likely to be
derived from sedimentary archaeal communities. Archaeol in particular is usually
associated with the anaerobic oxidation of methane in active seep settings (Thiel et al.,
1999; 2001; Pancost et al., 2000a, 2001) and has also been identified in settings which
exhibit a diffusive methane flux (Aquilina et al., 2010). However, the average δ13C value
of archaeol in the sediments at mid-Waipara (c. -25.5 ± 1.5 ‰) is inconsistent with a
methanotroph source (-60 ‰ to -120 ‰; Pancost and Sinninghe Damsté, 2003). Similarly,
archaeol has been found in Pliocene sediments of the Benguella Upwelling System (ODP
Site 1083), coeval with, and exhibiting similar δ13C values to lipids derived from sulfate
reducing bacteria; in this case, archaeol was suggested to derive from methanogenic
archaea (Pancost et al., 2009). Furthermore, methanogen biomarkers as much as 10 ‰
enriched relative to photoautotroph biomarkers were observed in sediments of Ace Lake,
Antarctica (Schouten et al., 2001). Ether lipids inferred to have been derived from
methanogens in the Eocene Messel Shale exhibit δ13C values ranging from -27 ‰ to -30
‰, which is believed to reflect a pronounced enrichment of the DIC pool (Hayes et al.,
1987). It has been suggested that methanogens growing heterotrophically on acetate or
other multi-carbon substrates could have δ13C values similar to those of the source carbon
(Pancost et al., 2000b). A methanogenic source is therefore assumed for the archaeol in the
high-TOC interval of mid-Waipara Column 2.
Biphytanoic acids have been identified in Cenozoic methane seep limestones and attributed
to methanotrophic archaea (Birgel et al., 2008). However, biphytanoic diacids containing
0–3 rings have also been found in non-seep sediments, where distribution patterns suggest
that they most likely derived from planktonic archaea (Ahmed et al., 2001). In more recent
studies, biphytanoic diacids have been found in hydrothermally influenced sediments in the
Guaymas Basin (Schouten et al., 2003a) and New Zealand hot springs (Pancost et al.,
2006). Here, only the acyclic structure was observed, which, on the basis of distributions of
tetraether lipids in modern settings and organisms, likely indicates a methanogen source
(e.g. Koga et al., 1998a). No δ13C values were determined for the biphytanoic diacid, so it
cannot be definitely assigned to the same source as archaeol; diacids have been reported to
derive both from both planktonic archaea and methanotrophic archaea (Ahmed et al., 2001;
Schouten et al., 2003a; Birgel et al., 2008). However, the concentration profiles of both are
very similar, and both occur only within the high-TOC interval (Fig. 5.13), thus it is highly
likely that both compounds derive from the same source.
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Chapter 5
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Methanogens are key agents of remineralization of organic carbon in continental margin
sediments and other aquatic sediments with high rates of sedimentation and high sediment
organic matter; they contribute a vital ecological role in anaerobic environments by
removing excess hydrogen and fermentation products that have been produced by other
forms of anaerobic respiration. Methanogens typically thrive in environments in which all
electron acceptors other than CO2 (such as oxygen, nitrate, sulfate, and trivalent iron) have
been depleted (Thauer, 1998; Chaban et al., 2006). As methanogenesis is an anaerobic
process, we infer that sedimentary conditions became anoxic during deposition of the highTOC interval at mid-Waipara, particularly during deposition of Horizon A where
methanogenic biomarkers are at peak concentrations. This is almost certainly a direct
consequence of the elevated TOC contents and provides evidence for a significant impact
of elevated carbon burial in the Late Paleocene on sedimentary geochemistry.
However there is no evidence that depletion of oxygen was sufficient to cause photic-zone
euxinia (anoxic and sulfidic conditions), as has been observed for Mesozoic oceanic anoxic
events (e.g. Jenkyns, 2010) or for the PETM Arctic Ocean (Sluijs et al., 2006).
Isorenieratene (or any product of its degradation) is not observed in any sediments from
mid-Waipara River; isorenieratene is a carotenoid produced by green sulfur bacteria that
perform photosynthesis using hydrogen sulfide as a reductant, indicative of photic-zone
euxinia and commonly observed during, for example, Mesozoic OAEs (e.g. Sinninghe
Damsté et al., 2001; Pancost et al., 2004).
5.5.2. Paleocene SST in the Southwest Pacific
Both the
and
derived SSTs indicate a clear climate succession at all three
SW Pacific sites discussed in this Chapter (Fig. 5.30B; mid-Waipara River Column 2;
ODP Sites 1121 and 1172 (Bijl et al., 2009). All document a long-term gradual cooling
trend initiated between 61 and 60 Ma. However, ODP Site 1121 TEX86 SST
reconstructions were hampered by particularly low resolution sampling in the lower part of
the core, and as such the timing of the initiation of cooling is harder to constrain there.
However, the bulk carbonate δ18O values (Fig. 5.30A; Wei et al., 2005) do indicate cooling
initiating at c. 60.7 Ma, consistent with SST reconstructions from the other study areas.
Localised proliferation of diatoms and radiolarians on the Campbell Plateau (Hollis, 2002)
and at Mead Stream (Hollis et al., 2005) during the late Paleocene is further evidence for
209
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
cool conditions, either related to climatic cooling or enhanced upwelling of southern
sourced deep water.
At mid-Waipara, a period of more enhanced cooling, from 58.5 to 58 Ma, is superimposed
on this trend. This is not observed in contemporaneous TEX86 SST reconstructions at ODP
Sites 1172 and 1121. However, the ODP Site 1121 record does not extend to this interval
and only one sample at ODP Site 1172 lies within it, such that the short-term episode
might not have been sampled. However, bulk carbonate δ18O values at ODP Site 1121 also
do not indicate an enhanced interval of cooling contemporaneous with the interval at midWaipara, although it does exhibit the continuation of the more gradual long-term cooling
trend.
Figure 5.30. Compiled SST data for study sites in the southwest Pacific: (A) bulk
carbonate δ18O for ODP Site 1121 (Wei et al, 2005) and (B)
and
SST
reconstructions for mid-Waipara River Column 2, ODP Site 1121 (this study) and ODP
Site 1172 (Bijl et al., 2009). The blue shading represents the interval characterised by a
long-term cooling trend at mid-Waipara. Error bars reflect simple propagated calibration
and analytical error of mid-Waipara and ODP Site 1121, and the calibration error of ODP
Site 1172 (data of replicate analysis were not available).
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Chapter 5
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Furthermore, the TEX86 SST reconstructions in the more coastal localities may be affected
by upwelling (as discussed in Section 5.4.13). A cold bias in TEX86 SST reconstructions
has been demonstrated in areas of strong upwelling (e.g. Lee et al., 2008). Because of the
ubiquity of GDGT-producing archaea throughout the water column (Karner et al., 2001;
Herndl et al., 2005), upwelling could enhance the contribution of GDGTs produced in
colder mesopelagic waters as a result of upward advection of those waters and subsequent
transport to the sediments via the same mechanisms invoked for epipelagic GDGTs , i.e.
association with sinking particles as a result of packaging into faecal pellets (Wuchter et
al., 2005; Huguet et al., 2006). Presumably also, at times of strong upwelling, the subsurface and mixed layer temperatures would become relatively cooler due to upward
mixing of deeper, colder waters compared to periods characterised by reduced vertical
temperature gradients. As GDGTs may also be exported from these sub-surface waters as
well as epipelagic waters (Menzel et al., 2006; Huguet et al., 2007), the overall GDGT
distributions exported to the sediments may reflect upwelling-induced cooling of
mesopelagic waters, and thus exhibit an overall cold bias. This is especially likely for the
mid-Waipara record, where there are indications of high biological productivity during
deposition of the high-TOC interval sediments (Fig. 5.11,
5.29). These include the
elevated TOC contents (Fig. 5.5), as well as elevated concentrations of putative marine
algal biomarkers (Fig. 5.11, 29A). Further evidence comes from the carbon isotopic
composition of putative marine biomarkers (δ13CLMW) which exhibit 3 to 4‰ positive
carbon isotope excursions (Fig. 5.17). Such a shift cannot explain the positive excursion
recorded by bulk OM, hence the need to invoke an additional mechanism (e.g.
sulfurization of labile 13C-enriched carbohydrates; discussed further in Section 5.4.3.2). It
does, however, suggest that carbon isotope fractionation by marine organisms was lower in
the ‘Waipawa-type’ high-TOC interval and that could be due to enhanced growth rates in
an upwelling regime as is commonly observed today (e.g. Bidigare et al., 1997; Pancost et
al., 1998; discussed further in Section 5.4.3.1).
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5.5.2.1. Assessment of the TEX86 Palaeothermometer at the Study Sites
One of the most striking aspects of the compiled TEX86 record is the difference in offset
between SST records constructed using
and
.
–reconstructed SSTs are
relatively similar through the records, particularly those of mid-Waipara and ODP Site
1172 (Fig. 5.30B), although
derived SSTs through ODP Site 1121 are generally
warmer (by c. 1 - 2°C). Collectively, these records document a long-term cooling trend in
the SW Pacific from a range of c. 24.5 – 23 °C to a range of c. 21.5 – 19.5 °C, i.e. 3 – 3.5
°C cooling overall. Cooling is also reflected in the carbonate δ18O values at ODP 1121.
However,
SST records reflect a much broader range of SSTs, i.e. larger offsets
between the three sites. The same overall trends are reflected, but ODP Site 1121
reconstructed SSTs are c. 3 °C warmer than ODP Site 1172
reconstructed SSTs,
which in turn differ but are typically warmer than reconstructed SSTs from Waipara.
Evaluation of the GDGT distributions (Fig. 5.31) indicates that while differences in
distributions of GDGTs are subtle between sites, there are appreciable differences,
particularly in the ratio of GDGT-2/GDGT-3. Key aspects to note are that the ratios of
GDGT-2/GDGT-3 for ODP Site 1172 and mid-Waipara River are relatively stable through
the late Paleocene, with values of c. 2.5 and c. 3.2, respectively. These differences cause
the two sites to have different
and
offsets as well as lower
derived
SSTs. GDGT-2/GDGT-3 ratios for ODP Site 1121 are significantly higher and more
variable than those of mid-Waipara and ODP Site 1172, associated with low but variable
–
offsets and higher reconstructed SSTs based on the latter.
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
213
Figure 5.31. (A) Ratio of GDGT-2/GDGT-3 and (B) offset between
and
reconstructed SSTs for mid-Waipara Column 2, ODP Site 1121 and
ODP Site 1172, with (C) average GDGT distributions for intervals denoted by green and orange shading. GDGT-1, GDGT-2, GDGT-3 and GDGT-4’ are
shown relative to the sum of those GDGTs. Crenarchaeol and GDGT-0 are shown relative to the sum total of all GDGTs. Abscissa scales are comparable
for each group (i.e. GDGT-1, GDGT-2, GDGT-2 and GDGT-4’ are plotted as one group on the same scale, crenarchaeol and GDGT-0 are a separate
group) and between the two distribution intervals.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Critically, the combined GDGT and TEX86 records of mid-Waipara and ODP Site 1172
highlight two key implications for the use of
have the same
and
. First, SST records which
values and derived temperatures can have different GDGT
distributions, enough to shift the offset between
and
when both are
reconstructed and compared. Secondly, as previously discussed in Chapter 3, SSTs of 15°C
and above do not necessarily exhibit similar
and
derived SSTs, contrary to
the conclusions arrived at by Kim et al. (2010) based on their analysis of the modern
global core-top dataset, and one of the key tests they used to propose separate indices. For
example, ODP Site 1172 sediments exhibit a consistent offset between
and
of c. 3.5 – 4 °C, yet both indices reconstruct SSTs warmer than 15°C through the record.
Similarly at mid-Waipara, most of the
and
derived SSTs are above 15°C.
Moreover, despite significant cooling through the high-TOC interval, GDGT-2/GDGT-3
ratios and offsets between
and
are not significantly altered, suggesting that
the GDGT-2/GDGT-3 parameter (and offset between
and
) is at least partly
independent of temperature.
Figure 5.32. Crossplot of GDGT-2/GDGT-3 ratio against offset between
and
reconstructed SSTs for (A) mid-Waipara River Colum 2, ODP Site 1121 and ODP
Site 1172, and (B) the modern core-top calibration data set (Kim et al., 2010).
214
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
As demonstrated for the GDGT distributions of mid-Waipara at the K/Pg boundary, a
crossplot of the ratio of GDGT-2/GDGT-3 with offsets between
and
reconstructed SSTs (Fig. 5.32A) exhibits a relationship comparable with the modern coretop GDGT calibration dataset (Fig. 5.32B). In Chapter 3 it was suggested that the
application of
is best suited to GDGT distributions that exhibit a ratio of GDGT-
2/GDGT-3 < 6; all but two of the samples analysed in this Chapter exhibit such values
(Fig. 5.27), and as the consideration of
derived SSTs at mid-Waipara, ODP Site
1121 and ODP Site 1172 is proposed here in terms of interrogating absolute temperatures.
Using
the differences between reconstructed SSTs at the three sites are appreciably
greater than if the
record is taken as the estimate of absolute SST. This may reflect
a real difference between SSTs at each site; if so the range of southern Pacific SSTs
through the cooling interval range from c. 23°C – 15°C. Furthermore, mid-Waipara is
reconstructed as generally the coolest site, despite being deposited at the lowest latitude of
the three sites. Mid-Waipara and ODP Site 1121 may therefore be influenced by different
ocean currents. In fact, the mid-Waipara is likely influenced by upwelling, as discussed
above. This could account not only for the enhanced cooling in Horizon A, but also for the
generally lower reconstructed SSTs throughout the record.
Modelled SSTs in an early Paleogene greenhouse system with pCO2 of 560 ppm have
predicted SSTs near NZ in the range of 12 to 18°C (Huber et al., 2004). Although
reconstructed SSTs from ODP Site 1121 are generally warmer than this, SSTs from midWaipara and ODP Site 1172 are in closer agreement, ranging from 14.5 – 19.5°C through
the compiled record. Even the enhanced cooling interval at mid-Waipara (c. 58.3 Ma), with
reconstructed SSTs of c. 12.5°C at peak cooling, falls into the range predicted by climate
simulations.
5.5.3. Carbon Cycle Dynamics Inferred From Carbon Isotopic Records
The total long term positive δ13C excursion (c. 61 Ma – 58 Ma) recorded at ODP Site 1121
(Fig. 5.33B) in δ13Ccarb (c. 1.6 ‰) and δ13CTOC (c. 2.5 ‰) is similar in magnitude to the
PCIM recorded in the global benthic foraminiferal δ13C carbonate compilation (c. 2 ‰;
Cramer et al., 2009). The δ13CTOC at mid-Waipara exhibits a much larger positive
excursion from c. 58.7 to 58 Ma, coeval with slightly enhanced positive excursions in
δ13CLMW and δ13CHMW values that are superimposed on longer-term more gradual
13
C
enrichments (Fig. 5.33A,C)
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The OM, and hence ODP Site 1121 δ13CTOC values, are likely dominantly marine derived
due to the distance from shore of the site of deposition. The tentatively marine-derived
δ13CLMW record at mid-Waipara exhibits a similar positive shift as exhibited by δ13CTOC at
ODP Site 1121 (Fig. 5.33), although somewhat larger; this suggests these records reflect at
least a regional phenomenon in the marine carbon cycle, with algal δ13C values shifting to
more positive values. This could be either as a result of a decrease in the 13C value of
dissolved inorganic carbon, a change in
, the photosynthetic fractionation expressed by
the marine algae, or both. However, even-carbon-number LMW n-alkanoic acids are very
non-specific biomarkers, and may in fact derive from a variety of sources, including higher
plants (Kollatukudy, 1976), or terrestrially-derived soil microbes (Zelles et al., 1992; Bååth
et al., 1992; Frostegård et al., 1993; Cavigelli et al., 1995; Wander et al., 1995; Zogg et al.,
1997) and fungi (Jabaji-Hare et al., 1984; Olsson et al., 1995 Frostegård and Bååth, 1996;
Olsson, 1999). Whilst the δ13CLMW values differ from δ13CHMW and δ13CHop, suggesting that
the even-carbon-number LMW n-alkanoic acids are not derived exclusively from higher
plants or bacteria (e.g. from soil), respectively, it is probable that δ13CLMW values represent
a mixed signal influenced in part by non-marine algal sources.
Determination of the carbon isotopic composition of sterols, particularly the algal-specific
C30 sterols, may elucidate a more reliable marine-algal carbon isotope record. As discussed
in Section 5.4.1.2, measurement of sitosterol carbon isotopic composition should also be
undertaken, in order to more rigorously elucidate the sources of sterols at mid-Waipara;
i.e., if sitosterol is truly algal-derived, it should exhibit similar δ13C values to the C30
sterols. If not, an alternative source of sitosterol is likely; this may then be elucidated by
comparison with the n-alkanoic acid carbon isotope records.
Trends similar to those observed in the LMW n-alkanoic acid carbon isotope record are
also identified in the HMW n-alkanoic carbon isotope record, i.e. δ13CHMW values increase
through the record (Fig. 5.33C), although the total enrichment is slightly less than that
observed for the LMW n-alkanoic acids. Higher plant δ13C values are governed by the
isotopic composition of substrate carbon (e.g. Arens et al., 2000), fractionation during
carbon assimilation ( ) (Farquhar et al., 1982; 1989; Popp et al., 1989) and environmental
conditions that influence
values (e.g. Diefendorf et al., 2010, 2011; Kohn, 2010).
216
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
217
Figure 5.33. Compilation of (A) TOC (B) and δ13Corg at mid-Waipara River Column 2 and ODP Site 1121, with (C) δ13CLMW and δ13CHMW from midWaipara River Column 2. The dashed line represents horizon of 94 m at ODP Site 1121, relating to an age of c. 59.3 Ma; this horizon represents a
dramatic increase in biosiliceous productivity at the site. The green and brown bars represent the time interval of high-TOC and Horizon A at midWaipara, respectively.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The long-term increase in δ13CHMW values, therefore, is probably partially caused by the
long-term increase in the δ13C values of atmospheric CO2. Reconstructed carbon isotopic
composition of Cenozoic atmospheric CO2 (based on δ13C values of planktonic and benthic
foraminifera; Tipple et al., 2010) indicate an increase of c. 2 ‰ initiating at c. 61 Ma and
peaking at c. 58 Ma. The latter reconstructed CO2 values represent the most 13C-enriched
values for the Cenozoic (Tipple et al., 2010). This reconstructed atmospheric CO2
enrichment of 2 ‰ is thus similar in magnitude to the shifts observed in Waipara strata
prior to the high-TOC interval. In fact, all of the SW Pacific carbon isotope records
documented in this study, including both those in both marine (δ13CLMW values at midWaipara, together with δ13CTOC and δ13Ccarb values at ODP Site 1121; Fig. 5.33B) and
terrestrial (δ13CHMW values) materials provide important confirmation that the PCIM truly
was a globally pervasive change in the carbon isotopic composition of the oceanatmosphere reservoir. The enhanced carbon isotope excursion in the TOC-rich interval at
mid-Waipara (Fig. 5.33A) is recorded by both δ13CHMW and δ13CLMW values, but to a lesser
extent. This likely represents a more localised phenomenon (discussed in Section 5.4.3.3).
5.5.3.1. A Decline in pCO2 during the Late Paleocene
The
13
C-enrichment characterising the PCIM is thought to be associated with carbon
burial, either in marine (Tucholke and Vogt, 1979; Thompson and Schmidtz, 1997) or
terrestrial ecosystems (Oberhänsli and Perch-Nielsen, 1990; Kurtz et al. (2003), although
the exact locus of burial is as yet unidentified. A sequestration of organic carbon of such a
scale was probably associated with a reduction in pCO2.
Δ13C(carb-TOC) largely reflects photoautotrophic algal
isotope discrimination
, i.e. the magnitude of total carbon
during photosynthesis (e.g. Arthur et al., 1988), which is a
function of the isotope fractionations associated with carbon transport and fixation. For
modern photoautotrophs assimilating CO2(aq) and using diffusional transport (Popp et al.,
1998), there is a negative and linear correlation between [CO2(aq)]-1 and
, with the slope
of that relationship dependant on physiological variables such as cell geometry and the
permeability of the cell membrane (Popp et al., 1998; Riebesell et al., 2000). As such,
largely reflects pCO2. By extension, the decreasing Δ13C(carb-TOC) values (and inferred
decreasing algal p) through the ODP Site 1121 record could document a Late Paleocene
pCO2 decrease (e.g. Popp et al., 1989; Freeman and Hayes, 1992; Tobin et al., 2005).
218
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
219
Figure 5.34. Climate and carbon cycle compilation for the southwest Pacific study sites: (A) bulk carbonate oxygen isotope record for ODP Site 1121,
(B)
SST reconstructions for mid-Waipara River Column 2, ODP Site 1121 and ODP Site 1172, (C) carbon isotopic fractionation between bulk
organic carbon and bulk carbonate (Δ13C(carb-org)) at ODP Site 1121 allocated into 10 data bins, and (D) carbon isotopic composition of n-alkanoic acids of
inferred algal origin (δ13CLMW).
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Alternatively, the inferred decrease in algal
could reflect enhanced algal growth rates
(Laws et al., 1995; Popp et al., 1998), which may result from enhanced nutrient
availability. Indeed, enhanced biosiliceous productivity has been suggested for ODP Site
1121, likely reflecting upwelling conditions (Hollis 2002), and upwelling conditions have
also been inferred for the mid-Waipara site (see above). Furthermore, the diffusive model
of carbon fixation does not hold for all photoautotrophs, with some organisms utilizing
carbon concentrating mechanisms when [CO2(aq)] is low (e.g. Sharkey and Berry, 1985;
Descolas-Gros and Fontunge, 1990; Raven and Johnston, 1993; Morel et al., 1994; Rost et
al., 2003).
Dominance of photoautotrophs with low surface area to volume ratios (Popp et al., 1998)
also exhibit lower
than organisms with relatively larger surface area to volume ratio.
Similarly, asynchronous changes in Δ13C(carb-TOC) and p values could arise from regionally
distinct shifts in ecology or ocean chemistry. Although the biostratigraphy of ODP Site
1121 does not indicate a major change in algal type through the core, diversity and
abundance increases above 94 m (59.3 Ma) and some changes in Δ13C(carb-TOC) could reflect
changes in algal physiology.
Thus, both the mid-Waipara 13CLMW and ODP Site 1121 13CTOC records suggest a
decrease in pCO2 could have occurred, but caution in interpretation is necessary and
further records are required. If a decrease in pCO2(aq) was associated with the positive
carbon isotope excursion, both could have been driven by globally enhanced productivity
and organic matter burial. In fact, there is compelling evidence for increased OM burial in
the NZ sector of the Southern Ocean; a similarly high-TOC,
13
C-enriched mudstone, the
Waipawa ‘black shale’ Formation, was deposited in the late Paleocene on the outer-shelf
upper-slope of the East Coast Basin, southeast Wairarapa (Moore, 1988; Lee and Begg,
2002; Tayler, 2011) to Northland (Isaac et al., 1994; Issac, 1996; Hollis et al., 2006).
In the sedimentary basins of southeast South Island, the correlative unit is identified as the
Tartan Formation (Cook et al., 1999; Schiøler et al., 2010). Correlative units have also
been identified in shallower settings of the Great South Basin (south of South Island, NZ;
Killops et al., 2000), and in a TOC-rich interval at Mead Stream, Marlborough, NZ
associated with an enrichment in 13C of bulk carbonate (Hollis et al., 2005).
220
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Equivalent units have also been identified in the West Coast, Taranaki and North Cape
Basins (Killops et al., 2000; Hollis et al., 2006). Geochemical evidence from the Waipawa
formation (e.g. abundant sulfur and negative δ34S values for kerogen and bitumen)
indicates a setting influenced by anoxia, likely resulting from enhanced productivity
stimulated by upwelling (Killops et al., 2000).
In total, the marine records of Δ13C(carb-TOC) at ODP Site 1121 and δ13CLMW at mid-Waipara,
together with the identification of several other organic rich facies thought to be deposited
through the same interval, strongly suggests enhanced organic matter burial in the
Southern Ocean, stimulated by an increase in productivity as a result of enhanced
upwelling. The enhanced burial of OM, as well as enhanced burial of OM in terrestrial
settings (Shackleton et al., 1984, 1987b; Oberhänsli and Perch-Nielsen, 1990; Corfield and
Cartlidge, 1992) could have contributed to a long-term decrease in global δ13C values as
observed in the benthic carbonate δ13C compilation and the new records reported here. The
long-term decrease in SSTs reconstructed for a wide range of SO sites could also reflect
the decrease in pCO2, although these records may also record lower SSTs due to
upwelling.
5.5.3.2. Strong 13C-Enrichment at Mid-Waipara River
The n-alkanoic acids and TOC δ13C records of mid-Waipara all exhibit a more enhanced
13
C enrichment through the TOC interval (spanning c. 58.7 – 58 Ma) than the
contemporaneous δ13Ccarb and δ13Corg records of ODP Site 1121(Fig. 5.33). The total longterm positive δ13C excursion (c. 61 Ma – 58 Ma) recorded at ODP Site 1121 in δ13Ccarb (c.
1.6 ‰) and δ13CTOC (c. 2.5 ‰) is also more similar in magnitude to the PCIM recorded in
the global benthic foraminiferal δ13C carbonate compilation (c. 2 ‰; Cramer et al., 2009).
The most striking aspect of the mid-Waipara n-alkanoic acid δ13C and δ13CTOC records
(Fig. 5.35) is that the former do not exhibit the same magnitude of
13
C-enrichment as
exhibited by TOC in the high-TOC interval.
221
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
222
Figure 5.35. Compiled carbon isotope analysis of (A) hopanoic acids, (B) HMW n-alkanoic acids, (C) MMW n-alkanoic acids and (D) LMW n-alkanoic
acids. For each plot, the δ13CTOC record is compared, as represented by the brown line along side each record. All δ13C reported relative to VPDB.
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Through the lower c. 65 m of sediment, each compound class exhibits a relatively
consistent offset from δ13CTOC: δ13CLMW values are lower than δ13CTOC by an average of c.
3.5 ‰ (Fig. 5.35D), δ13CMMW values are lower by an average of c. 4.9 ‰ (Fig. 5.35C), and
δ13CHMW values are lower by c. 4.7‰ (Fig. 5.35B). This is generally consistent with the
expected offset between lipids and bulk organic carbon; marine lipids are generally
13
C-
depleted relative to marine TOC (Degens, 1969; Hayes et al., 1989; Meyers, 1994), and
lipids from C3 terrestrial plants are depleted relative to biomass (Collister et al., 1994).
Furthermore, OM derived from C3 terrestrial plants is usually 13C-depleted relative to algal
OM under modern low pCO2 conditions (Smith and Epstein, 1971; Gearing et al., 1977;
Prahl et al., 1994; de Leeuw et al., 1995; Meyers, 1997), potentially analogous to the
Paleocene. Thus, the generally isotopically heavier δ13C values of putative marine derived
LMW n-alkanoic acids relative to those of terrestrial plant HMW homologues is expected.
However, through the high-TOC interval, the offset between δ13C values of n-alkanoic
acids and TOC is amplified. TOC is enriched in 13C by c. 7.3 ‰, 8.0 ‰ and 9.0 ‰ relative
to LMW, MMW and HMW n-alkanoic acids, respectively (Fig. 5.35). A greater offset is
also exhibited in the hopanoic acid δ13CHop record (Fig. 5.35A), which is likely to reflect
heterotrophic grazing of the sedimentary organic matter by the bacterial source of the
hopanoids; nonetheless, the offset between δ13CHop and 13CTOC values shifts from c. 2.8 ‰
to 6.6 ‰ between the lower 65 m to the high-TOC interval. This indicates that neither
marine (mixed algal), terrestrial or bacterial contributions to the OM can explain the
magnitude of the large positive shift in δ13CTOC exhibited in the upper 15 m high-TOC
interval.
Together, this suggests a change in the composition of OM, rather than a shift in the carbon
isotopic composition of the atmosphere-ocean reservoir (or changes in other factors
affecting
) is responsible for the enhanced positive carbon isotope excursion in δ13CTOC
at mid-Waipara. Such a phenomenon has been described for the upper Jurassic
Kimmeridge Clay Formation, UK (Sinninghe Damsté et al., 1998). The Kimmeridge Clay
sediments were determined to have been deposited under anoxic conditions, based on the
presence of isorenieratene derivatives.
223
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Large changes in δ13CTOC values of over 6 ‰ are recorded in the Kimmeridge Clay
sediments, coeval with much smaller shifts in the δ13C values of the algal, cyanobacterial
and green sulfur bacterial biomarkers. Sinninghe Damsté et al (1998) show that
carbohydrate carbon (CCHO), characterised by δ13C values 4 to 10‰ higher than biomass
(Degens, 1968; Tyson, 1995; Meyers, 1997), forms a large fraction of the organic matter of
the TOC-rich upper Jurassic Kimmeridge Clay Formation as a result of early diagenetic
sulfurization. It is therefore possible that the high-TOC interval of mid-Waipara may be
analogous to the TOC-rich/high δ13C sediments of the Kimmeridge Clay (Sinninghe
Damsté et al., 1998). Sedimentary anoxia at the high-TOC interval of mid-Waipara is
indicated by the presence of likely methanogenic biomarkers, as discussed previously. As
such, sulfate may have been rapidly reduced, producing hydrogen sulfide which could have
facilitated carbohydrate preservation. The enhanced carbohydrate production could then
have led to enhanced δ13CTOC values becoming increasingly offset from δ13C values of
coeval lipids.
The HMW n-alkanoic acid 13C values exhibit a long-term increase through the midWaipara section, from 70.4 m to 130.7 m, of c. 5 ‰ (Fig. 5.35D). Enhanced
13
C-
enrichment in the high-TOC interval, particularly through Horizon A, accounts for 3 ‰ of
the total shift in the record. As discussed above, the longer-term c. 2 ‰ shift is consistent
with global inorganic carbon isotopic records (Cramer et al., 2009). However, the larger c.
3‰ shift in the TOC-rich horizon is not observed elsewhere and likely reflects decreased
carbon isotope fractionation by higher plants on the NZ landmass.
In terms of physiological response to environmental change, C3 plant
values decrease in
response to increased water stress, e.g. in low precipitation environments (Farquhar et al.,
1982; Madhaven et al., 1991; Meinzer et al., 1992; Diefendorf et al., 2010, 2011; Kohn,
2010). As such, the trend towards more positive δ13C values could reflect a response to
drier conditions. Indeed, the ACL of HMW n-alkanes generally increases through the
section (Fig. 5.10D), which is thought to indicate warmer (Gagosian et al., 1986) or drier
conditions (Sachse et al., 2006; Seki et al., 2009), and the cool TEX86derived SST records
(Fig. 5.29C) preclude the former. Furthermore, changes in terrestrial ecology can influence
the δ13CHMW values; environmental changes, as suggested by cooling and changes in nalkane distribution, may cause restructuring of the terrestrial higher plant communities to
plants that are, for example, better suited to water stressed environments.
224
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
A possible scenario given the inferred changes in climate would be an increase in the
relative proportions of gymnosperms (e.g. conifers), which are generally considered
indicative of relatively cool and dry conditions (Vajda et al., 2001; Vajda and Raine,
2003). Several studies have shown that n-alkanes derived from gymnosperms are typically
more 13C-enriched compared to those found in angiosperms grown under the same climatic
conditions (Leavitt and Newberry, 1992; Flanagan et al., 1997; Chikaraishi and Naraoka,
2003; Diefendorf et al., 2010)
The LMW n-alkanoic acid 13C values also exhibit a long-term increase through the
section, from 70.4 m to 131.1 m, of c. 7 ‰ (Fig. 3.35D). Enhanced 13C-enrichment in the
high-TOC interval, particularly through Horizon A, accounts for 3 ‰ of the total shift in
the record. As discussed above, about 2 – 2.5 ‰ of this shift could reflect the global
change in the ocean-atmosphere reservoir (Cramer et al., 2009), and it is possible that an
additional 2 ‰ is associated with a decrease in algal p values due to a pCO2 decrease (see
above). However, the remainder likely reflects local environmental factors. Because we
assume an algal source for these compounds, potential factors include a shift towards even
lower surface water [CO2(aq)] or higher algal growth rates. Decreased [CO2(aq)] could be
associated with removal of surface water DIC via enhanced algal productivity (Talling,
1976; Hayes, 1993; Hollander et al., 1993). Depletion of surface water [CO2(aq)] to the
point that it becomes limiting could also cause submerged aquatic plants to use relatively
13
C-enriched HCO3- (Mook et al., 1974) as a carbon source (Sharkey and Berry, 1985;
Burns and Beardall, 1987; Tortell et al., 1997), thereby explaining the relatively high
δ13CMMW values (as high as -21.9‰) in the TOC-rich interval (Keeley and Sandquist,
1992).
Alternatively or additionally, the elevated δ13C values of putative aquatic biomarkers in the
TOC-rich interval could reflect elevated growth rates of primary producers (e.g. Laws et
al., 1995; Bidigare et al., 1997; Popp et al., 1998). The elevated TOC contents (this study,
and throughout the Waipawa Formation; Killops et al., 2000) and evidence for lower SSTs,
as well as micropaleontological evidence (Hollis, 2002; 2006), all suggest that productivity
increased around NZ due to upwelling. Indeed, nutrient-driven increases in primary
productivity in modern upwelling systems do cause lower carbon isotope fractionation by
photoautotrophs and associated increases in TOC and biomarker δ13C values (Pancost et
al., 1997, 1999; Popp et al., 1999).
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Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
5.6. Conclusions
A long-term late Paleocene SST cooling trend has been identified at three locations in the
SW Pacific, associated with increasing 13C values of carbonate and organic matter at ODP
Site 1121, and in higher plant and putative algal biomarkers at mid-Waipara River. These
trends may be associated with a decrease in pCO2, as suggested from the Δδ13C(carb-TOC)
record at ODP Site 1121 (Fig. 5.34C), and the enhanced magnitude of
13
C-enrichment in
LMW n-alkanoic acids at mid-Waipara, relative to the inferred change in global DIC 13C
(Fig. 5.34D). The possible decrease in pCO2 may be associated with enhanced carbon
burial in the Southern Ocean, stimulated by enhanced upwelling and productivity, as well
as burial in other terrestrial and marine settings. Localised proliferation of diatoms and
radiolarians on the Campbell Plateau (Hollis, 2002) and at Mead Stream (Hollis et al.,
2005) during the late Paleocene is further evidence for cool conditions, either related to
climatic cooling or enhanced upwelling of southern sourced deep water.
A period of enhanced SST cooling at mid-Waipara relative to ODP Sites 1121 and 1172
occurs from c. 58.3 – 58 Ma, and is likely a result of enhanced upwelling and productivity
through the high-TOC interval. This may be a local or regional response to the changing
climate, as evidenced by the biomarker and SST records from the section. This interval of
enhanced cooling at mid-Waipara is also associated with high TOC, indicating enhanced
organic matter burial, and enhanced 13C-enrichment of LMW and MMW n-alkanoic acids
(Fig. 5.35C, D) , relative to (predominantly algal derived) δ13CTOC values at ODP Site
1121. The relatively high δ13C values of tentative algal biomarkers in mid-Waipara
sediments possibly reflects higher algal growth rates at mid-Waipara through the cooling
interval. Furthermore, the increase in BIT indices (Fig. 5.29E) and HMW n-alkyl
compounds (Fig. 5.9) relative and absolute concentrations could indicate a lowering of sea
level.
In fact, the high-TOC and relatively 13C-enriched interval at mid-Waipara (and, to a lesser
extent, increased TOC and decreased δ13CTOC values at ODP Site 1121) appears to
correlate with several other similarly characterised units deposited in the late Paleocene
throughout New Zealand; the rock unit is identified as the Waipawa Formation in eastern
North Island sedimentary basins, where it has been recorded from southeast Wairarapa
(Moore, 1988; Lee and Begg, 2002) to Northland (Isaac et al., 1994; Hollis et al., 2006).
In the sedimentary basins of southeast South Island, the correlative unit is identified as the
Tartan Formation (Cook et al., 1999; Schiøler et al., 2010).
226
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The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
Geologically and geochemically similar units in northeast South Island and further afield in
western basins have been informally correlated with the Waipawa Formation [Killops et
al., 2000; Hollis et al., 2005a]. Equivalent units have also been identified in the West
Coast, Taranaki and North Cape Basins (Killops et al., 2000; Hollis et al., 2006).
Furthermore, Schiøler et al. [2010] observed that Waipawa/Tartan deposition is associated
with an increase in terrestrial OM, whilst biomarker evidence suggests enhanced marine
productivity (Killops et al., 2000); both of these observations are in agreement with
findings at mid-Waipara through the proposed corollary high-TOC interval, suggesting in
turn that the high-TOC interval at mid-Waipara is correlated to the Waipawa/Tartan
deposition.
The long-term cooling trend in the late Paleocene Southern Ocean, indicated by the
decreased TEX86-derived SSTs at three SO sites, could have been caused by a CO2 drawdown. Moreover, the change in climate and CO2 may have been sufficient to have brought
about early ephemeral Antarctic glaciations, and an associated drop in sea-level.
Regression across several of New Zealand’s sedimentary basins is suggested based on
geochemical and sedimentological evidence (Hollis et al., 2009a; Andrew, 2010) and has
been argued to be consistent with a proto-western boundary current flow (Hollis et al.,
2009; Andrew, 2010). Three lines of evidence indicate that typical Waipawa facies were
deposited during a eustatic fall in sea level: (i) foraminiferal assemblages indicate that
palaeodepth shallows from middle to outer shelf in the underlying unit to inner shelf within
Waipawa facies, both in the East Coast Basin (Moore, 1988) and Great South basin (Cook
et al., 1999); (ii) palynofacies record a pronounced increase in terrestrial organic matter,
consistent with closer proximity to the shoreline in East Coast, Canterbury and Great South
Basins (Schiøler et al., 2010); (iii) the distribution of the Tartan Formation in the Great
South Basin is consistent with a fall in base level, with deposition in the deepest parts of
the basin and erosion or non-deposition in shoreward parts of the basin (Schiøler et al.,
2010). Furthermore, the Waipawa facies are possibly correlated to other documented
eustatic and regional sea-level falls occurring within the late middle to early late Paleocene
(59-56 Ma, upper Chron 26r to lower Chron 24r), e.g. Haq et al. (1987), Hardenbol et al.
(1998), Luning et al. (1998; East Sinai), Rhodes et al., (1999), Guasti et al. (2005; El Kef,
Tunisia) and Schmitz et al. (2011; Zumia, Spain).
227
Chapter 5
The Paleocene Carbon Isotope Maximum in the Southwest Pacific of the Southern Ocean
The geographical extent of the Waipawa and correlated facies, indicates at least a
regionally (New Zealand Sector of the Southern Ocean) widespread event which may be
related to global eustatic change; together this suggest the possibility of a glacio-eaustatic
fall related to climate cooling, as evidenced by the TEX86 records at mid-Waipara and
ODP sites 1121 and 1172. Although such an inference is contentious, and evidence
presented here is circumstantial, such an event provides a mechanism for the pronounced
oceanographic changes occurring at mid-Waipara from 58.3 – 58 Ma. Such changes would
also support recent models of Southern Ocean palaeoceanography, which indicate that CO2
is a stronger force upon SO climate than ocean heat transport (DeConto and Pollard,
2003a,b; DeConto et al., 2008). I.e., open sea-ways are not necessarily a pre-requisite for
cooling of the Southern Ocean.
Southern Ocean cooling may also have implications for the Antarctic continent, including
the potential presence of permafrost and associated changes in soil carbon budget. Indeed,
orbitally paced melting of permafrost has been implicated as a source of carbon for the
PETM and subsequent Eocene hyperthermals (DeConto et al., 2012). If pCO2 can be
quantified for this time period, it will provide an opportunity to investigate the implications
of pCO2 changes in relation to Antarctic climate, ice and carbon budgets, particularly as
the lack of fully opened ocean gateways (i.e. Drake Passage and Tasman Gateway; Lawver
and Gahagan, 1992) precludes a major influence of ocean heat transport on cooling of the
continent (e.g. Kennett et al., 1972; Wise et al., 1991; Abreu & Anderson 1998).
228
Chapter 6
Overview and Integration of Preliminary
and Global Data
229
Chapter 6
Overview and Integration of Preliminary and Global Data
6.1. Introduction
The overall aim of the studies presented was to determine climate and ecological responses
to globally significant events in the Paleocene using organic geochemical techniques. Both
a transient and a long-term climate and carbon cycle perturbation have been presented;
namely the K/Pg boundary event and subsequent recovery into the early Danian, and a
long-term cooling trend in the Paleocene associated with an enrichment in global δ13C,
possibly reflecting a drawdown of CO2.
The utility of the most recent TEX86 palaeothermometer calibrations was also interrogated;
a pivotal finding is that the offset between
and
is essentially determined by
an aspect of GDGT distribution, specifically the ratio of GDGT-2/GDGT-3, which is
seemingly largely independent of temperature.
Here, the findings are summarised, and preliminary data from a low latitude northern
Hemisphere Paleocene record are briefly presented to compare with the high-latitude
Southern sites presented in Chapter 5. These are integrated with the SW Pacific data and
compared to global trends for an overview of the Paleocene, as well as synthesis of the
GDGT interrogations, to determine whether the suggestions made in previous chapters
regarding the controls of offset between
and
remain valid.
Finally, a synthesis of southwest Pacific Paleogene climate will be presented, and
compared to Paleogene climate and circulation simulations produced from a global
circulation model (GCM).
6.2. The Paleocene Carbon Isotope Maximum
A long-term SST cooling trend was determined at three locations in the SW Pacific,
associated with a coeval trend in decreasing δ13C exhibited in δ13Ccarb and δ13Corg at ODP
Site 1121, and in higher plant and putative algal biomarkers at mid-Waipara River. These
trends may be associated with decrease in pCO2, as suggested from the Δδ13C(carb-TOC)
record at ODP Site 1121, and the enhanced magnitude of
13
C-enrichment in δ13CLMW
relative to the inferred change in global DIC δ13C. The possible decrease in pCO2 may be
associated with enhanced carbon burial in the Southern Ocean, stimulated by enhanced
upwelling and productivity. Here, the findings are placed into global context and integrated
with the records from the SW Pacific with a preliminary Paleocene record from Bass
River, New Jersey, USA.
230
Chapter 6
Overview and Integration of Preliminary and Global Data
6.2.1. Bass River Site Description, Materials and Methods (Supplementary Preliminary
Low-Latitude Paleocene Study)
Figure 6.1. Palaeomap of New Jersey ODP Leg 174X drill sites. From west to east, sites
are Clayton (C), Wilson Lake (WL), Ancora (Anc), and Bass River (BR). Cenozoic (Cz),
Cretaceous (K), and pre-Cretaceous (pre-K) outcrop limits are shown (Van Sickel et al.,
2004). Paleolatitude, shown in brackets, is derived from the Faeroe Islands paleopole of
Riisager et al. (2002) rotated using the Rockall microplate parameters of Royer et al.
(1991).
The Bass River Site was drilled as part of ODP Leg 174X (Miller et al., 1998). The upper
Paleocene Vincentown Formation is divided into three sequences (1138.61178 ft ;
47.05359.6 m, 1240.81256.5 ft; 378.20382.98 m, and 1256.51258.7 ft ;
382.98383.66 m, and was deposited at a palaeodepth of c. 105 – 140 m water depth
(Kopp et al., 2007, Harris et al., 2010; see Appendix VI.i) and a palaeolatitude of c. 27°N
(Fig. 6.1).
The age model of Bass River (Fig. 6.2) is particularly tentative, due in part to the
incompleteness of the record due to hiatuses (Harris et al., 2010; see Appendix VI.h) and
missing biozones, but linear sedimentation rates are estimated to be 6.3 ft My-1 from
1256.2 ft to 1243.8 ft, and 91.2 ft My-1 from 1243.5ft to 1218 ft (Cramer, 1998,
unpublished).
231
Chapter 6
Overview and Integration of Preliminary and Global Data
Figure 6.2. Age model for Bass River (Cramer, 1998, unpublished). Note left scale is in
imperial units (ft). Linear sedimentation rates (not shown) for range through which
samples were collected for this study are tentatively estimated to be 6.3 ft My-1 from
1256.2 ft to 1243.8 ft, and 91.2 ft My-1 from 1243.5 ft to 1218 ft. PF = planktonic
formainifera, CN = calcareous nannofossil, CIE = carbon isotope excursion.
A total of 30 sediment samples from Bass River were analysed for GDGTs (see Appendix
II) using the same methods as described in detail in Chapter 2. In summary, sediments
were extracted under reflux for 24 h using a Soxhlet apparatus. TLEs were subsequently
fractionated on aminopropyl SPE to generate neutral and acid fractions and the neutral
fractions separated using (activated) alumina flash columns to generate apolar and polar
fractions. The neutral polar fractions were filtered and analysed using LC-MS APCI. Ion
detection was performed in SIM mode. Representative chromatograms of GDGT
distributions throughout the Bass River Section are given in Figure 6.3.
232
Chapter 6
Overview and Integration of Preliminary and Global Data
233
Figure 6.3. Representative LC-MS chromatograms of GDGTs at Bass River. GDGTs are numbered according to number of cyclopentyl rings in the
structure: 0 = GDGT-0, 1 = GDGT-1, 2 = GDGT-2, 3 = GDGT-3, 4’ = crenarchaeol regio-isomer.
Chapter 6
Overview and Integration of Preliminary and Global Data
6.2.2. Bass River GDGT and TEX86 Results and Discussion
In general, the GDGT distributions at Bass River (Fig. 6.4) do not exhibit any obvious
trends; the lower variability above 1240 ft is possibly an artefact of the lower sampling
resolution. GDGT-1 and GDGT-4’ generally exhibit a mirrored profile; increases in
relative proportions of GDGT-1 correspond to decreases in GDGT-4’, and vice versa.
The
and
SST reconstructions similarly do not exhibit any particularly
obvious trends throughout the section, maintaining fairly stable temperatures (Fig. 6.5).
The remarkable aspect of the record, however, is the very large (ranging from 7°C to 12°C
offset between
and
.
derived SSTs average c. 29°C, whereas
SST reconstructions are c. 19°C - 21°C.
As observed in previous chapters, this is related to a low ratio of GDGT-2/GDGT.
However, the ratio of GDGT-2/GDGT-3 is relatively stable, compared to the variability in
offset between
and
2009) is offset from the
. Also of note is that the reciprocal calibration (Liu et al.,
and linear (Kim et al., 2008) calibrations, which has not
been observed in the other records reconstructed in this study. This may be reflective of the
distribution which records relatively high
(and linear calibration; Kim et al., 2008)
and reciprocal TEX86 derived temperatures; the reciprocal calibration reconstructs
relatively lower SSTs for such distributions, as discussed in the construction of the
calibration (Liu et al,, 2009). Indeed, a similar offset between SSTs reconstructed using the
linear (Kim et al., 2008) and reciprocal (Liu et al,, 2009) calibrations is also observed for
Early Cretaceous SST reconstructions which exceed 30°C (Littler et al., 2011).
234
Chapter 6
Overview and Integration of Preliminary and Global Data
235
Figure 6.4. Bass River GDGT distributions: relative proportions of (A) GDGT-1, (B) GDGT-2, (C) GDGT-3, (D) GDGT-4 normalised to total of
[GDGT-1+ GDGT-2 + GDGT-3 + GDGT-4’] and expressed as fractional percentage.
Chapter 6
Overview and Integration of Preliminary and Global Data
236
Figure 6.5. Bass River (A) TEX86 reconstructed SSTs using various calibrations (simple propagated calibration error and analytical precision given as
error bars), (B)
and
derived SST reconstructions, (C) raw
and
values with analytical precision given as error bars (error bars
not visible as they are smaller than the plot points), (D) ratio of [GDGT-2]/[GDGT-3] and (E) offset between
and
derived SST
reconstructions, calculated as
.
Chapter 6
Overview and Integration of Preliminary and Global Data
6.2.3. Summary of Paleocene Climate and Carbon Cycle at the PCIM
A long-term SST cooling trend was determined at three locations in the SW Pacific (Fig.
6.6), correlating to a maximum in global benthic carbonate δ18O, and a species-specific
benthic carbonate δ18O from ODP Site 1209 (Fig. 6.5A). This cooling is associated with
increasing 13C values of carbonate and organic matter at ODP Site 1121, and in higher
plant and putative algal biomarkers at mid-Waipara River (PCIM), as well as increasing
δ13C values in both the global and ODP Site 1209 benthic carbonate records. These trends
may be associated with a decrease in pCO2, as suggested from the Δ13C(carb-TOC) record at
ODP Site 1121 (Fig. 6.7), and the enhanced magnitude of
13
C-enrichment in
13
CLMW
relative to the inferred change in global DIC 13C (Fig. 6.7). The possible decrease in pCO2
may be associated with enhanced carbon burial in the Southern Ocean, stimulated by
enhanced upwelling and productivity, as well as enhanced carbon burial in other terrestrial
and marine settings. Localised proliferation of diatoms and radiolarians on the Campbell
Plateau (Hollis, 2002) and at Mead Stream (Hollis et al., 2005) during the late Paleocene is
further evidence for cool conditions, either related to climatic cooling or enhanced
upwelling of southern sourced deep water.
The Bass River section TEX86-derived SST record (Fig. 6.5), with tentative age model,
provides further insight into the climate of the late Paleocene. As the sediments exhibit low
GDGT-2/GDGT-3 ratios, the application of
is suggested for consideration of
absolute temperatures. This reconstructs SSTs at Bass River of c. 20°C through the
suggested period of enhanced cooling in the Southern Ocean; in fact, the record exhibits
similar SSTs to the ODP Site 1121
reconstructions. This is unexpected, as the Bass
River section was deposited at a relatively low latitude (c. 27°N), and as such warmer
temperatures would be anticipated; a very weak or non-existent equator-pole temperature
gradient is implied by the
of
SST record. Indeed, the overall trend in the compilation
SSTs would appear more feasible; the Southern Ocean sites all reconstruct at
similar temperatures, while Bass River exhibits relatively warmer temperatures.
237
Chapter 6
Overview and Integration of Preliminary and Global Data
Figure 6.6. Compilation of climate indicators for the Paleocene, including (A) global benthic foraminiferal carbonate δ18O compilation (Cramer et al.,
2009), (B) single site high resolution benthic carbonate δ18O of ODP Site 1209 (mid-Latitude Pacific, Westerhold et al., 2011), and (C)
and (D)
derived SST records of mid-Waipara River, ODP Site 1121, ODP Site 1172 and Bass River.
238
Chapter 6
Overview and Integration of Preliminary and Global Data
Figure 6.7. Compilation of carbon isotope records for the Paleocene, including (A) global benthic foraminiferal carbonate δ13C compilation (Cramer et
al., 2009), (B) single site high resolution benthic carbonate δ13C of ODP Site 1209 (mid-Latitude Pacific, Westerhold et al., 2011), (C) n-alkanoic
acid δ13CLMW and (D) δ13CHMW at mid-Waipara River, and (E) Δ13C(carb-TOC) at ODP Site 1121.
239
Chapter 6
Overview and Integration of Preliminary and Global Data
Furthermore, the Bass River record does not appear to exhibit cooling through the interval
characterised by the coolest Southern Ocean sites; as the age model is tentative, no
definitive conclusions may be drawn, and the late Paleocene hiatus at Bass River may in
fact correlate to this period. Alternatively, this could indicate that cooling was more
enhanced in the Southern Ocean than in the mid-north Atlantic. However, most of the
samples in the global benthic carbonate compilation (Cramer et al., 2009) are located in the
North Atlantic, or the Pacific, with very few samples from elsewhere. Moreover, cooling
reconstructed from δ18O values of benthic carbonate could be reflective of a high-latitude
SST cooling and strengthening of cold high-latitude deep-water sources (Corfield and
Norris, 1996). As such, more globally pervasive study including SST reconstruction should
be undertaken to determine the geographical extent of sea surface cooling through the
PCIM.
A period of relatively enhanced SST cooling at mid-Waipara relative to ODP Sites 1121
and 1172 occurs from c. 58.3 – 58 Ma, and is also associated with high TOC and enhanced
13
C-enrichment of LMW and MMW n-alkanoic acids, relative to (predominantly algal
derived) δ13CTOC values at ODP Site 1121. The relatively high δ13C values of tentative
algal biomarkers in mid-Waipara sediments possibly reflects higher algal growth rates at
mid-Waipara through the cooling interval. Furthermore, the increase in BIT indices and
HMW n-alkyl compound relative and absolute concentrations could indicate a lowering of
sea level. Schiøler et al. [2010] observed that Waipawa/Tartan deposition is associated
with an increase in terrestrial OM, whilst biomarker evidence suggests enhanced marine
productivity (Killops et al., 2000); both of these observations are in agreement with
findings at mid-Waipara through the proposed corollary high-TOC interval, suggesting in
turn that the high-TOC interval at mid-Waipara is correlated to the Waipawa/Tartan
deposition. In fact, deposition of a high-TOC and relatively 13C-enriched unit is apparently
widespread in the late Paleocene throughout New Zealand; the rock unit is identified as the
Waipawa Formation in eastern North Island sedimentary basins, where it has been
recorded from southeast Wairarapa (Moore, 1988; Lee and Begg, 2002) to Northland
(Isaac et al., 1994; Hollis et al., 2006). In the sedimentary basins of southeast South Island,
the correlative unit is identified as the Tartan Formation (Cook et al., 1999; Schiøler et al.,
2010). Geologically and geochemically similar units in northeast South Island and further
afield in western basins have been informally correlated with the Waipawa Formation
(Killops et al., 2000; Hollis et al., 2005a). Equivalent units have also been identified in the
West Coast, Taranaki and North Cape Basins (Killops et al., 2000; Hollis et al., 2006).
240
Chapter 6
Overview and Integration of Preliminary and Global Data
The long-term cooling trend in the late Paleocene Southern Ocean, indicated by the
decreased TEX86-derived SSTs at three SO sites, could have been caused by a CO2 drawdown. Moreover, the change in climate and CO2 may have been sufficient to have brought
about early ephemeral Antarctic glaciations, and an associated drop in sea-level.
Regression across several of New Zealand’s sedimentary basins is suggested based on
geochemical and sedimentological evidence (Hollis et al., 2009a; Andrew, 2010) and has
been argued to be consistent with a proto-western boundary current flow (Hollis et al.,
2009; Andrew, 2010). Three lines of evidence indicate that typical Waipawa facies were
deposited during a eustatic fall in sea level: (i) foraminiferal assemblages indicate that
palaeodepth shallows from middle to outer shelf in the underlying unit to inner shelf within
Waipawa facies, both in the East Coast Basin (Moore, 1988) and Great South basin (Cook
et al., 1999); (ii) palynofacies record a pronounced increase in terrestrial organic matter,
consistent with closer proximity to the shoreline in East Coast, Canterbury and Great South
Basins (Schiøler et al., 2010); (iii) the distribution of the Tartan Formation in the Great
South Basin is consistent with a fall in base level, with deposition in the deepest parts of
the basin and erosion or non-deposition in shoreward parts of the basin (Schiøler et al.,
2010). The hiatuses in the late Paleocene sediments at Bass River are also inferred to be a
result of changes in glacio-eustacy; reconstructed eustatic falls (Harris et al., 2010) are
considered to be too fast and too large to be explained by mechanisms other than icevolume changes. Furthermore, the Waipawa facies and Bass River hiatuses are possibly
correlated to other documented eustatic and regional sea-level falls occurring within the
late middle to early late Paleocene (59-56 Ma, upper Chron 26r to lower Chron 24r), e.g.
Haq et al. (1987), Hardenbol et al. (1998), Luning et al. (1998; East Sinai), Rhodes et al.,
(1999), Guasti et al. (2005; El Kef, Tunisia) and Schmitz et al. (2011; Zumia, Spain).
The geographical extent of the Waipawa and correlated facies indicates at least a
regionally (New Zealand Sector of the Southern Ocean) widespread event which may be
related to global eustatic change; together this suggest the possibility of a glacio-eustatic
fall related to climate cooling, as evidenced by the TEX86 records at mid-Waipara and
ODP sites 1121 and 1172. Although such an inference is contentious, and evidence
presented here is circumstantial, such an event provides a mechanism for the pronounced
oceanographic changes occurring at mid-Waipara from 58.3 – 58 Ma. Such changes would
also support recent models of Southern Ocean palaeoceanography, which indicate that CO2
is a stronger force upon SO climate than ocean heat transport (DeConto and Pollard,
2003a,b; DeConto et al., 2008). I.e., open sea-ways are not necessarily a pre-requisite for
cooling of the Southern Ocean.
241
Chapter 6
Overview and Integration of Preliminary and Global Data
Southern Ocean cooling may also have implications for the Antarctic continent, including
the potential presence of permafrost and associated changes in soil carbon budget. Indeed,
orbitally paced melting of permafrost has been implicated as a source of carbon for the
PETM and subsequent Eocene hyperthermals (DeConto et al., 2012). If pCO2 can be
quantified for this time period, it will provide an opportunity to investigate the implications
of pCO2 changes in relation to Antarctic climate, ice and carbon budgets, particularly as
the lack of fully opened ocean gateways (i.e. Drake Passage and Tasman Gateway;
Lawver, and Gahagan, 1992) precludes a major influence of ocean heat transport on
cooling of the continent (e.g. Kennett et al., 1972; Wise et al. 1991; Abreu & Anderson
1998).
6.2.4. Recommendation for Future Work: Further Characterisation of Climate and
Oceanographic Change Through the PCIM
The records of SST and carbon cycle change through the PCIM revealed cooling and
13
C-
enrichment of ocean and atmosphere reservoirs. However, the TEX86-derived SST record
at ODP Site 1172 was determined at a relatively low resolution (i.e. sampling interval of
the core was large). As such, there is scope for a higher-resolution study through the
intervals of particular interest; analysis should focus on the interval c. 61 – 60 Ma to
constrain the timing of the cooling, and the interval 58.8 – 58 Ma (particularly 58.3 – 58
Ma), coinciding with the enhanced cooling, upwelling and sedimentary anoxia determined
at mid-Waipara. Indeed, a relatively TOC-rich interval has been noted in the late Paleocene
interval of the core (Peter Bijl, pers. comm.). Additionally, biomarker analysis and the
determination of terrestrial and marine compound-specific carbon isotope composition
may facilitate a more detailed comparison of the neritic mid-Waipara setting, and the
relatively deeper setting of ODP Site 1172. Determination of carbonate and bulk organic
δ13C at ODP Site 1172 would also provide a useful record for comparison with the
Δδ13C(carb-TOC) record constructed in this thesis for ODP Site 1121; a similar profile would
provide further evidence for a decline in pCO2. Higher resolution SST and compoundspecific carbon isotope records for mid-Waipara through the interval 61 – 60 Ma may also
facilitate a more precise determination of the onset of cooling, and the onset of
13
C-
enrichment in the ocean and atmosphere reservoirs. Further similar studies on sediments
from the Waipawa ‘black shale’ formation (e.g. at Mead Stream; Hollis et al., 2005) may
also provide further insight into the extent of marine carbon burial in the Southern Ocean
242
Chapter 6
Overview and Integration of Preliminary and Global Data
through the PCIM, and could confirm the setting as a likely locus for the burial of organic
carbon, contributing to the prolonged isotope excursion.
The age model of Bass River should be constrained in order to facilitate comparison with
the Southern Ocean compilation of geochemical data; other global records are necessary in
order to determine the global extent of climate change related to the 13C-enrichment of the
ocean-atmosphere reservoir through the PCIM. Preliminary analyses of sediments from
ODP Leg 207, Site 1262 (Kroon et al., 2004) indicated the presence of organic biomarkers,
but concentrations were too low to allow GDGT or compound specific biomarker analysis.
However, we propose that a low resolution study could be performed using larger masses
of sediment (e.g. > 50g), or the same mass could be achieved by compiling sediments from
several horizons (e.g. 5 x 10 g samples at 20 cm spacing, would give one result from a
range of 1 m). This may provide a general indication of the presence or absence of long
term cooling trends coincident with the PCIM as identified in the Southern Ocean. ODP
Site 1262 also has the advantage of a rigorous orbitally tuned age model (Westerhold et al.,
2008). Compounds of a similar structure to long-chain alkenones were observed in the
ODP Site 1262 sediments; if a high enough concentration of these can be obtained, they
may reflect a more explicitly algal derived carbon isotope signature, and may also be used
to semi-qualitatively assess pCO2. Similarly well age-constrained Paleocene material from
the equatorial-Pacific (Shatsky Rise) is available from the cores recovered from ODP Site
1209 (Westerhold et al., 2011); as such, similar studies as those proposed for ODP Site
1262 may provide a particularly pertinent link, from the SW Pacific to the equatorial.
6.3. Summary of K/Pg boundary Climate and Carbon Cycle Perturbations at midWaipara River
No evidence for pre-K/Pg boundary climate change was determined at mid-Waipara River,
which is in disagreement with some records which document an episode of climatic
warming preceding the K/Pg boundary event at c. 66.1–65.6 Ma (Stott & Kennett 1990;
Barrera & Savin 1999; Abramovich and Keller 2002; Adatte et al., 2002a; Wilf et al.,
2003), and rapid cooling in the last 0.1 myr of the Cretaceous (e.g. Stott & Kennett 1990;
Srivastava, 1994; Frank and Arthur, 1999; Keller, 2001; Wilf et al., 2003, Thibault and
Gardin, 2007).
243
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Overview and Integration of Preliminary and Global Data
The events of the K/Pg boundary disrupted terrestrial and marine ecosystems, and as such
perturbed biogeochemical cycles both immediately following the K/Pg boundary event,
and persisting into the early Danian. Across the K/Pg boundary, a c. 2 ‰ negative
excursion is recorded in the terrestrial and marine pelagic carbon isotope records,
reflecting a global perturbation of the carbon cycle as recorded in the pelagic carbonates
(Arthur, 1979; Boersma et al., 1979; Hsü et al., 1982; Perch-Nielsen et al., 1982; Zachos et
al., 1985, 1989; Zachos and Arthur, 1986; Keller and Lindinger, 1989; 1992; Stott and
Kennett, 1989; Stott and Kennett, 1990; Robin et al., 1991; Keller et al., 1995; D’Hondt et
al.,1998; Kroon et al., 2007) and terrestrial carbon isotope records (Arens and Jahren 2000;
Maruoka et al. 2007; Beerling et al. 2001; Clyde et al., 2010) of multiple globally
distributed sites.
Although the negative CIE in pelagic carbonate and homogenisation of the plankticbenthic carbon isotope gradient is generally attributed to cessation of primary productivity
in the surface ocean, (Hsü et al., 1982; Hsü and McKenzie, 1985; Keller and Lindinger,
1989; Stott and Kennett, 1989; Zachos et al., 1989; Zachos et al., 1992; D’Hondt et al.,
1998), no evidence for a complete cessation of primary productivity was identified in midWaipara sediments, although low TOC and suppressed algal biomarker concentrations
suggest lower export productivity. Early recovery of primary productivity at continental
margins is also documented elsewhere (Kaiho et al., 1999; Mita and Shimoya, 1999;
Sepúlveda et al., 2009), particularly at high latitudes (Keller et al., 1993). The changes in
algal assemblages determined from changes in algal biomarker ratios also supports this
suggestion of a shift in dominant algal types from cosmopolitan assemblages to more
opportunistic species. Although reduced CO2 drawdown as a result of the cessation of
primary productivity could account for an accumulation of relatively 13C-depeleted carbon
in the ocean-atmosphere reservoir (as a negative CIE in terrestrial and marine carbon
isotope records as a result), the biomarker records at mid-Waipara (and evidence
documented elsewhere) corroborate the ‘Living Ocean’ model (D’Hondt et al., 1996a)
which also suggests that cessation of primary productivity may not have been as prolonged
or widespread as earlier models of a ‘Strangelove Ocean’ suggest (Hsü et al., 1982; Hsü
and McKenzie, 1985; Keller and Lindinger, 1989; Stott and Kennett, 1989; Zachos et al.,
1989; Zachos et al., 1992). As such, a different mechanism for the negative CIE across the
K/Pg boundary is required. However, the periodic episodes of elevated ‘unusual’
monospecific algae and unstable marine ecosystems reflected by the restructuring of algal
assemblages are likely to have affected long-term biogeochemical cycles (Hollander et al.,
1993; D’Hondt et al., 1996a; Hollis, 2003).
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It is argued that isotopically light (13C-depeleted) carbon added to the surface oceanatmosphere carbon reservoir would also be required to produce the negative carbon isotope
excursion (CIE) observed at the K/Pg boundary in many sites (Kump, 1991; Ivany and
Salawitch, 1993). This is supported by the coeval negative CIE in terrestrial records;
terrestrial higher plant
photoautotroph
is generally less sensitive to changes in pCO2 than marine
, as the former organisms can also adjust their stomatal density to alter
intercellular CO2 (Freeman and Hayes, 1992; White et al., 1994). That the terrestrial and
marine carbon isotope records reflect a similar magnitude CIE suggests that both terrestrial
and marine systems were affected by a shift in the isotopic composition of substrate carbon
(CO2) of the same origin. A negative carbon isotope excursion of 1.4 ‰ – 2.8 ‰ could
reflect a geologically instantaneous burning of c. 18-24 % of terrestrial above-ground
biomass (Arinobu et al., 1999), and would be reflected in both marine and terrestrial
carbon reservoirs. Warming through the interval is also recorded in the TEX86 SST
reconstructions described in Chapter 3, and as such could reflect increased pCO2, possibly
as a result of biomass burning. Hydrological conditions are more difficult to determine; nalkane proxies and the prevalence of ferns (Vajda and Raine, 2003) suggest wetter
conditions, but n-alkanoic acid distributions and BIT indices suggest the opposite. New
Zealand early Paleocene terrestrial biomass may have been reduced relative to the late
Cretaceous, despite lack of evidence for this in the pollen record (Vajda et al., 2003).
Although terrestrial biomarker concentrations are suppressed through Zone II, and BIT
values are slightly lower than Zone I values, the decrease is probably not of a great enough
magnitude to invoke a significant decrease in precipitation and/or run-off.
The observation that Zone III (the base of which is tentatively dated at c. 1 My post-K/Pg
boundary) contains biomarker assemblages that appear to reflect different and dynamic
algal communities, relative to Zones I and II, indicates a restructuring of the marine
ecosystem and is consistent with the ‘Living Ocean’ model (D’Hondt et al., 1998) which
suggests that the flux of carbon to the deep sea could have been suppressed for a more
sustained period of time than the generally short-lived post-K/Pg cessation of primary
productivity; the reduced marine surface-deep δ13C gradient is thus thought to be
remediated by the emergence of new algal assemblages (D’Hondt et al., 2005; Coxall et
al., 2006; Algret and Thomas, 2007), with a full return to pre-K/Pg conditions up to 1 - 3
myr post-K/Pg.
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Evidence for SST cooling, based on GDGT distributions, through Zone III was also
determined. This reconstruction was in agreement with climate inferences based on
dinoflagellate assemblages (Willumsen 2002; 2006), pollen records (Vajda et al., 2001;
Vajda and Raine, 2003) and geochemical indicators of enhanced biosiliceous productivity
and/or locally strengthened upwelling (Hollis 2003; Hollis et al., 2003a,b). Sea surface
waters then warmed through into Zone IV to temperatures cooler than Zone II and
stabilise, indicating a relatively cool but stable climate. This is consistent with biomarker
concentrations and distributions from late Zone III into Zone IV, which generally return to
pre-K/Pg boundary values, reflecting a recovered and possibly restructured algal
ecosystem.
Long-term δ13C-depletion (persisting into the early Danian) of global marine benthic
(Westerhold et al., 2011) and pelagic (Kroon et al., 2007) carbonates is reflected in the
marine δ13CLMW record at mid-Waipara, but is not reflected in the terrestrial δ13CHMW
record, possibly as a result of the restructured terrestrial community exhibiting a relatively
lower average
compared to pre-K/Pg boundary assemblages. The marine
13
C-depletion
may reflect increased [CO2(aq)] relative to Zone I, although the extent of increased [CO2(aq)]
may be enhanced relative to the global records at mid-Waipara, due to colder SSTs which
in turn would increase the surface water capacity for dissolved [CO2(aq)].
A return to pre-K/Pg boundary conditions at mid-Waipara in the marine and terrestrial
realm in Zone III and persisting through Zone IV was identified. This inference was based
on the biomarker and compound specific isotope records, together with the global records
described in the literature; i.e. both systems had recovered by c. 1 – 1.2 My post-K/Pg
boundary event, indicating a return to more stable biogeochemical cycles. This timing is
also in agreement with the coeval climate reconstructions, which indicate that climate had
also apparently stabilised by this time. As such, the perturbations of the K/Pg boundary had
both immediate and persisting effects, affecting marine biogeochemical cycling and
causing instability in the carbon cycle. These effect in total impacted upon early Danian
climate causing instability which was relieved by the eventual emergence of stable marine
ecosystems and, perhaps locally at mid-Waipara, resurgence of terrestrial biomass.
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6.3.1. Recommendations for Future Work: K/Pg Boundary
6.3.1.1. Hydrology Across the K/Pg Boundary Into the Early Danian
The terrestrially derived δ13CHMW records at mid-Waipara indicated the possibility of
environmental change, such as changes in water stress, through the latest Maastrichtian and
early Danian. However, other influences upon the δ13CHMW record were not constrainable,
and as such no definite changes in hydrology through the record could be determined;
HMW n-alkane and n-alkanoic acid distributions also conflicted in terms of suggesting
precipitation regimes, and the changes in vegetation inferred from the pollen record may
not be entirely unambiguous. Thus, the determination of the deuterium isotopic
composition (δD) of the HMW n-alkanoic acids should be undertaken to evaluate the
hydrological changes (e.g. Sternberg, 1998; Huang et al., 2002, 2004; Yang and Huang,
2003; Sachse et al., 2006; Handley et al., 2011) across the K/Pg boundary at mid-Waipara.
Terrestrial higher plant leaf wax δD values record: a) the δD values of meteoric water
(Sauer et al., 2001; Chikaraishi and Naraoka, 2003; Sachse et al., 2004; Rao et al., 2009);
b) the extent of D-enrichment during soil evaporation and leaf evapotranspiration, which is
dependent on humidity (Smith and Freeman, 2006); and c) the physiological, biochemical
and/or ecological processes that affect the isotopic fractionation (
of deuterium that
occurs during leaf wax synthesis, although these processes are relatively poorly understood
(Zhou et al., 2011; Kahmen et al., 2011). Thus, higher plant leaf wax δD records can be
powerful tools in the reconstruction of past environmental conditions, although an
important caveat is the effect of vegetation change, as both evapotranspiration and
biosynthetic effects (and thus
) can vary amongst different taxa (Liu et al., 2006; Sachse
et al. 2006,2009; Smith and Freeman 2006; Hou et al. 2007; Liu and Yang, 2008;
Pedentchouk et al. 2008; Feakins and Sessions 2010).
6.3.1.2. Other K/Pg Boundary Sites in New Zealand
Preliminary data generated for a K/Pg boundary section at Branch Stream, Marlborough,
NZ indicates that the sediments may be thermally immature enough to allow reliable
TEX86 measurements. The section is more expanded post-K/Pg boundary than midWaipara (Hollis et al., 2003b) and as such may provide insight into the immediate climate
and biotic events resulting from the events of the K/Pg boundary that may have been
missed in analyses of the mid-Waipara sediments. Compound specific isotope analysis of
terrestrial and algal biomarkers will facilitate comparison with mid-Waipara, and may
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possibly aid correlation between the sites, if similar features in the carbon isotope records
are recognised.
6.4. Overview of Compiled GDGT and TEX86 Data: Implications for the Continued
Application of the TEX86 Palaeothermometer
Throughout the study, GDGT distributions have been interrogated to determine the
relationship between changes in distributions and the effects on
and
SST
reconstructions. A key finding was that the ratio of GDGT-2/GDGT-3 exhibits a strong
relationship to the offset between
and
SST estimates. The ratio of GDGT-
2/GDGT-3 may be related to the depth of GDGT export; this is based on interrogation and
evaluation of published GDGT distributions from sinking particulate matter (SPM) (Turich
et al., 2007), where proportions of GDGT-3 relative to GDGT-2 exhibit large increases
with depth, shifting the offset between
and
to negative values.
decreases with depth, but the ratio of GDGT-2/GDGT-3 increases such that
reconstructions become relatively warmer. This illustrates a theoretical scenario whereby a
shift towards deeper GDGT export depth causes a cooling in
warmer absolute
concomitant with
temperatures driven by an increase in the ratio of GDGT-
2/GDGT-3 (See Chapter 3, Fig. 3.17).
Furthermore, it is suggested to use
15°C, and to use
when all SSTs in a record reconstruct above
for the whole record if any SST is reconstructed below 15°C (Kim
et al., 2010). This is based on the general observation in the global core-top calibration that
and
record similar SSTs above 15°C, and diverge below 15°C, as a result of
having been calibrated using a sub-set of the core-top calibration dataset which
excluded data from the colder high latitudes. The
calibration data set (excluding the Red Sea, as with
record is based on the whole
) and as such is also calibrated to
the polar data sets, but exhibits more scatter and is therefore associated with larger
calibration errors. However, The studies presented in this thesis highlight examples in the
modern dataset of GDGTs distributions which reconstruct with a high offset between
and
at SSTs above 15°C; similarly, a high
and
offset was not
confined to palaeo-SSTs below 15°C, and in fact a reversal of the offset between
and
was observed during a period characterised by cooling at the mid-Waipara
River K/Pg boundary section. The degree of GDGT cyclisation, expressed as weighted
mean average number of cyclopentyl rings, reflected lower cyclisation through the same
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period, also indicating cooler archaeal growth temperatures; this parameter is a qualitative
measure of relative growth temperature (De Rosa et al., 1980; Gliozzi et al., 1983; De
Rosa and Gambacorta, 1988; Uda et al., 2000), established before the ubiquity of
Thaumarchatoa was realised (Karner et al., 2001), or the inception of the TEX86 SST proxy
(Schouten et al., 2008).
Figure 6.8. Crossplot of compiled GDGT-2/GDGT-3 ratio against offset between
and
reconstructed SSTs for (A) the palaeo-SST records presented in this thesis, with
coloured points indicating different GDGT records, and (B) the modern core-top
calibration data set (Kim et al., 2010).
Compiling of the GDGT-2/GDGT-3 ratios against
and
offset (Fig. 6.8)
together provides a compelling argument for the phenomena described for a diverse range
of
reconstructions. Critically, no relationship between the
–
SST
offset with the absolute TEX86 derived temperatures is observed. The Bass River data
provides the strongest evidence for the independent nature of the GDGT-2/GDGT-3 ratio
parameter relative to TEX86 reconstructed SST;
derived SSTs are c. 29°C - 30°C,
far above the recommended SST at which to apply
. Similarly,
reconstructed
SSTs are consistently higher than 15°C, at c. 19°C - 21°C. Furthermore, it appears that
sensitivity to the GDGT-2/GDGT-3 ratio parameter is greater at lower values; high
variability is apparent in the
and
offset relative to low variability in the
GDGT-2/GDGT-3 ratios.
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Upon evaluation of the crossplot, both in the compiled palaeodata (Fig 6.8A) and the
modern core-top calibration (Fig. 6.8B), it does appear that the sensitivity of
and
offset is higher at lower GDGT-2/GDGT-3. It is however also possible that other
changes in GDGT distributions exert more of an influence on the SST offset when GDGT2/GDGT-3 ratio is particularly low. In summary, the parameter of GDGT-2/GDGT-3 ratio
appears to indicate a change in growth environment of GDGT-producing Thaumarchaea,
possibly a change in depth habitat or a change in the depth of export, which may be
affected by changes in packaging of the GDGTs and subsequent delivery to the sediment
(e.g. Wuchter et al., 2004)
6.5.1. Recommendation for Future Work: Development of the TEX86 Palaeothermometer
The distribution of GDGTs in any sample should be interrogated before the application of
the TEX86 proxy. The ratio of GDGT-2/GDGT-3 ratio is the parameter which appears to
determine the offset between
and
, and this parameter is at least partly
independent of SST. A possibility worth investigation is the possibly relation of GDGT2/GDGT-3 ratio to GDGT export depth. Furthermore, the ratio of GDGT-2/GDGT-3 may
provide a parameter, independent of reconstructed SST, to inform the selection of which
‘calibration’ to apply; a very high offset between reconstructed SSTs can be exhibited both
in ancient and modern GDGT distributions which reconstruct above the threshold
suggested by Kim et al. (2010) of 15°C. Suggestions for further investigation to resolve
this issue are essentially two-fold:
Firstly, the calibration core-top data set (Kim et al., 2010) should be re-evaluated in terms
of GDGT-3/GDGT ratio; the sample set could be divided into bins based on their GDGT2/GDGT-3 ratio. The bins may then be calibrated to SST; essentially if GDGT-2/GDGT-3
expresses a depth bias, the calibration would ‘build-in’ an offset relating the deeper
environment to the SST, which would not be applicable for distributions which reflect an
export from surface waters. Correlations could also be attempted with sub-surface
temperatures for high-GDGT-2/GDGT-3 ratio distributions; although correlations of
TEX86 with such temperatures have been attempted and generally refuted (e.g. Kim et al.,
2008), they were not produced with the distinction between different ‘type’ distributions
(e.g. high or low GDGT-2/GDGT-3 ratio), and as such likely reflect a mix of deeper and
shallower export depths.
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Secondly, further evaluation of SPM and sediment trap GDGT distributions from a diverse
range of settings will be required to identify whether the ratio of GDGT-2/GDGT-3 is
definitively a reflection of GDGT export depth. Further analysis of settings which appear
to reflect seasonal changes in export depth (e.g. Santa Barbara Basin) may be particularly
important in establishing the relationship of the GDGT-2/GDGT-3 parameter with export
depth and other oceanographic parameters. Combining these studies with microbiological
assays may also aid in determining whether the different ‘type’ GDGT distributions (i.e
high and low GDGT-2/GDGT-3 ratios) are in fact a product of different archaeal
communities, as suggested by Turich et al (2007, 2008).
6.5. The Paleocene: Climate Instability
The central aim of this thesis was to determine whether there was significant climate
instability through the Paleocene. Evidence for transient climate change and ecological
disruption at the K/Pg boundary in the SW Pacific is discussed in Chapters 3 and 4.
Climate instability persisted for c. 1 – 1.2 My, and then proceeded to stabilise, with most
climate and ecological parameters returning to pre-K/Pg boundary values; a notable
exception is the algal biomarker distributions, which reflect a restructured algal
community, in keeping with the suggestion that algal community restructuring, and thus
the restructuring of trophic relationships, was responsible for the long-term term recovery
of the benthic-planktic carbon isotope gradient.
Late Paleocene climate reconstruction (Chapter 5) indicates cooling coeval with
13
C-
enrichment of terrestrial and marine reservoirs in the Southern Ocean, perhaps associated
with enhanced marine productivity and a drawdown of CO2, indicating that the PCIM
reflects a period of cooling association with carbon cycle changes. The tentatively dated
Bass River SST record does not indicate cooling; assuming a correct age assignment, this
could indicate that SST cooling was a more regionally restricted phenomenon, and that the
global benthic carbonate 18O-enrichment reflects the SO cooling and strengthening of SO
sourced bottom waters. It may be tentatively suggested that drawdown of CO2 and SO
cooling could have brought about early Antarctic glaciations and an associated drop in sea
level. Such an event provides a mechanism for the pronounced oceanographic changes
occurring at mid-Waipara from 58.3 – 58 Ma.
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Furthermore, these findings suggest that the Paleocene SO climate may have been more
sensitive to carbon cycle dynamics than the classic ocean heat transport models suggest;
this is in agreement with Paleogene climate models which predict a stronger influence of
CO2 on SO climate than the thermal isolation brought about by circum-Antarctic
circulation (Huber and Sloan, 2001; DeConto and Pollard, 2003a; 2003b; Huber and Nof,
2004; Huber et al., 2006; DeConto et al., 2008).
6.5.1. Recommendation for Future Work: Further Interrogation of Marine Carbon Cycling
Through the Paleocene
Determination of the carbon isotopic composition of C30 sterols identified at mid-Waipara
(both in the K/Pg boundary and Column 2 sediments) would provide a less ambiguous
marine carbon isotope record, as C30 sterols are more highly specific biomarkers for marine
algae than the LMW n-alkanoic acids utilised in the studies presented. Furthermore, the
isotopic composition of sitosterol may elucidate a macrophytic source for this sterol,
particularly in the mid-Waipara Column 2 sediments which contain MMW n-alkanoic
acids apparently derived from a source independent of the sources of HMW and LMW nalkanoic acids. Sitosterol is also a predominant component of mid-Waipara K/Pg boundary
sediments, thus it may be interesting to determine whether a macrophytic source of OM is
also important in that setting, and revisit MMW n-alkanoic acid δ13C values if an
independent source of sitosterol is implicated.
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6.6. A Synthesis of Southwest Pacific Early Paleogene Climate
The data generated in this thesis can be combined with existing published data in order to
interrogate the Paleocene climates determined in context of the early Paleogene. Selected
for this overview are: the TEX86-derived SST estimates from (i) the mid-Waipara River
K/Pg boundary section (this study), (ii) mid-Waipara River Column 2 (Paleocene; this
study), (iii) mid-Waipara Column 6 (Eocene; Hollis et al., 2009b), and (iv) the early
Paleogene TEX86-derived SST estimates from ODP Site 1172 (Bijl et al., 2009; Sluijs et
al., 2011). This synthesis of SST data is given in Figure 6.9, and a proxy/model data
comparison can be made from global circulation models (GCMs) simulating Paleogene
climates at a range of pCO2 values (Fig 3.10; Hollis et al., submitted).
In general, the GDGT distributions at mid-Waipara and ODP Site 1172 exhibit low
GDGT-2/GDGT-3 ratios, thus the
SST reconstructions are considered the more
reliable estimate of SST in these settings. The exception, as previously noted, is across the
earliest Danian unconformity at mid-Waipara River (c. 64.5 Ma), where the offset between
and
SST estimates is reversed, ratio of GDGT-2/GDGT-3 is high and
reconstructed values are suggested to be the more reliable SST estimate.
SST reconstructions (
ranging from 12 to 14°C) in the latest Cretaceous at mid-
Waipara River (Fig. 6.8) suggest a cool-temperate climate; this is relatively cool in
comparison with Eocene SSTs. Both the Eocene and Cretaceous climate are generally
considered to be classic greenhouse climates (e.g. Crowley and Zachos, 2000; Pearson et
al., 2001). This suggests that the latest Cretaceous climate reconstructions at mid-Waipara
may represent a relatively cooler climate, perhaps indicating pre-K/Pg climate change
related to the rapid cooling inferred in the last 0.1 My of the Cretaceous by other workers
(Stott & Kennett 1990; Srivastava, 1994; Frank and Arthur, 1999; Keller, 2001;
Abramovich and Keller 2002; Adatte et al., 2002a; Nordt et al., 2003; Wilf et al., 2003;
Thibault and Gardin, 2007). However, lack of data extending further back into the
Cretaceous at mid-Waipara prohibits further investigation into timings or magnitude of any
possible changes.
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Overview and Integration of Preliminary and Global Data
Figure 6.9. Synthesis of early Paleogene TEX86-derived sea surface temperature estimates
for the Southwest Pacific, including data from the mid-Waipara K/Pg boundary section
and Column 2 (Paleocene), generated in this study, as well as mid-Waipara River Eocene
(Hollis et al., 2009) and data from ODP Site 1172 (low resolution Paleogene - Bijl et al.,
2009; high resolution PETM - Sluijs et al., 2011). Envelopes represent upper and lower
bounds of SST estimates after error propagation. K = Cretaceous.
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Overview and Integration of Preliminary and Global Data
Across the K/Pg boundary, a shift to warm-temperate climate (
-derived SST = 16-
17°C) is observed. This shift and absolute SST estimations are generally well reproduced
in the climate model when shifting from a relatively low pCO2 (Fig 3.10A; 2240 ppm) to
high pCO2 (Fig 3.10B; 4480ppm) simulation, particularly considering that the site location
of mid-Waipara is at a slightly higher latitude than reconstructed in the model, owing to the
palaeogeography used in the model construction; i.e. the model simulations of slightly
higher latitude SSTs agree best with the TEX86 data in the latest Cretaceous/early Danian.
Summarily, this supports the hypothesis of a large release of CO2 (or other greenhouse gas)
across the K/Pg, but also perhaps suggests a relatively low pCO2 in the latest Cretaceous.
Alternatively, the events of the K/Pg boundary may have altered climate sensitivity to, or
the Earth system regulation of, CO2; the massive disruption to the aquatic and terrestrial
biosphere would likely have perturbed biogeochemical cycles (D’ Hondt et al., 1996a;
Hollis, 2003) such as the carbon cycle.
Despite the difficulty in determining actual SST across the unconformity at the midWaipara K/Pg boundary section, some of the coolest (12 – 14°C)
-derived SSTs for
the southwest Pacific Paleogene record are reconstructed across a period of c. 1.5 My
above the unconformity (Fig. 6.9). These SSTs are also similar to those estimated in the
late-Paleocene at mid-Waipara during the peak of cooling at c. 58 Ma, during the
deposition of high-TOC,
13
C-enriched sediments correlated to the Waipawa/Tartan facies
elsewhere in New Zealand. Again, these SSTs agree well with the ‘low’ pCO2 model
simulation, and are perhaps even slightly cooler than simulated SSTs, suggesting even
lower pCO2.
As discussed in previous chapters, both of these periods may represent intervals of CO2
drawdown and sequestration, in turn bringing about climatic cooling. The early Paleocene
interval is possibly correlated to the final oscillation in a series of climate fluctuations
reconstructed across many K/Pg boundary localities in New Zealand (see Chapter 3).
These fluctuations are thought to be a result of perturbed biogeochemical cycles, disrupted
by the K/Pg boundary events; cycles of warming and cooling are inferred to be
symptomatic of a climate system which is hampered in its ability to regulate atmospheric
CO2, likely as a result of mass marine extinctions and persistence of stressed ecosystems
post K/Pg boundary event. The cool period at mid-Waipara may represent the final cooling
phase before climate stabilisation; this in turn may be related to the final stages of marine
recovery in the aftermath of the K/Pg boundary (see Chapter 4).
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Figure 6.10. Southwest Pacific Paleogene proxy/model comparison (Hollis et al.,
submitted). Model is NCAR CCSM3(National Center for Atmospheric Research:
Community Climate System Model 3.0), with mean annual global climate and circulation
simulations for (A) 2240 ppm CO2(c. 6 x present day pCO2) and (B) 4480 ppm CO2 (c. 12
x present day pCO2). Yellow circles indicate sites with associated TEX86 SST
reconstructions, red circled numbers are approximate average SSTs reconstructed coevally
at each site which appear to match simulations.
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The late Paleocene cooling event may indicative of enhanced upwelling, which could also
bias the TEX86 proxy towards reconstructing relatively cooler temperatures (Lee et al.,
2008). The enhanced cooling event is superimposed on a longer term cooling initiating at
around 62 Ma, a trend evident in both mid-Waipara and ODP Site 1172 SST records (Fig.
3.9). The period of enhanced cooling at mid-Waipara may represent the culmination of
climate change, global carbon burial, and possible ephemeral Antarctic glaciation. Local
qualitative pCO2 records in the southwest Pacific (ODP Site 1121; Fig. 5.34) exhibit a
long-term decrease in CO2 from c. 62Ma;
-derived SST estimates at mid-Waipara
and ODP Site 1172 indicate a shift from moderately warm-temperate to cool-temperate
climate. This matches well with a shift from a ‘high’ pCO2 Paleogene circulation
simulation (Fig. 6.10B) to a ‘low’ pCO2 simulation (Fig. 6.10A); mid-Waipara SSTs shift
from c. 17°C to c. 14°C, while SSTs at ODP Site 1172 decrease from c. 19°C to 16°C.
This supports the hypothesis that the long-term cooling reconstructed in the southwest
Pacific is a climatic change associated with a change in pCO2, lending well to the
suggestion that a massive amount of carbon was buried during the PCIM, and that this had
a profound impact on climate, particularly in the Southern Ocean. Furthermore, if
ephemeral Antarctic glaciation is invoked as a mechanism for oceanographic change in the
Southern Ocean and eustatic changes globally, this suggests that Antarctic ice formation is
sensitive changes in pCO2 despite the absence of open seaways to enable circum-Antarctic
currents. If a drop in CO2 can bring about Antarctic glaciation in the absence of circumpolar current, the converse may also be true; that a rise in CO2 may drive Antarctic deglaciation, despite the cooling effects of a circum-polar current in the modern ocean where
the Drake Passage and Tasman Gateways are open. However, the evidence presented here
for Antarctic glaciation is tentative and circumstantial; further work is required to
determine whether climate change in the Paleocene could have brought about ephemeral
ice formation in Antarctica.
Considering the southwest Pacific record of climate in the Paleocene as a whole, in context
of the early Paleogene, indicates that the Paleocene represents a markedly different climate
system to the ‘hot-house’ greenhouse climate of the Eocene (Fig. 3.9). Whilst the GCM
simulations indicate that pCO2 levels in the Paleocene were much higher than present
(2240ppm, c. 6x present), and as such represent a greenhouse world, Paleocene pCO2 is
estimated to be around half or less of that in the Eocene (>4480ppm, c. 12x present).
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The TEX86 records indicate that a correspondingly cooler climate is reconstructed in the
Paleocene, compared to the Eocene (southwest Pacific Paleocene climates are
reconstructed in the cool to warm-temperate region, Eocene climates are estimated to be
sub-tropical to tropical). This indicates that even in high pCO2 systems, the Earth climate is
sensitive to changes in pCO2; indeed, as discussed above, fluctuations in pCO2 may
account for the changes in climate reconstructed through the Paleocene, and possibly even
changes in the cryosphere. In summary, these records indicate that relatively high pCO2
Earth systems can still exhibit dynamic climate evolution; the carbon cycle and climate
systems are intrinsically linked, and a perturbation of the former can dramatically impact
the later. In terms of implications for future climate change, if the Earth systems are
sensitive to carbon cycle dynamics in high pCO2 greenhouse systems, CO2 likely exerts a
major influence on climate across a range of environments, and ocean heat transport may
not impact upon climate to the degree it is classically attributed to.
258
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307
Appendix
Appendix
308
Appendix
Appendix I
GDGT Structures
Appendix I.a. Isoprenoidal GDGT structures, as used for calculation of TEX86. m/z =
[M+H]+, i.e. the ion scanned in SIM mode to detect the compound.
Appendix I.b. Branched GDGT structures, as used in the calculation of the BIT index. m/z
= [M+H]+, i.e. the ion scanned in SIM mode to detect the compound.
309
Appendix
Appendix II
Bass River Geochemical Data and Statistical Data
List of Tables :
II.a.
Table of raw isoprenoidal GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4)
II.b.
Table of raw isoprenoidal GDGT peak areas (GDGT-0 and crenarchaeol), and raw TEX86
values.
II.c.
Table of TEX86 derived sea surface temperature estimates.
II.d.
Average TEX86-derived sea surface temperature estimates.
II.e.
Table of n-1 values and (n-1)*SD2 values for TEX86-derived SST estimates, and calculated
pooled standard deviation (an overall estimate of the precision of the measurement for the
dataset).
310
Appendix II.a. Table of raw isoprenoidal GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4).
Top / ft
Bottom /
ft
Mean depth / ft
Sample
ID
GDGT-1
GDGT-2
+
m/z [M+H] = 1300
+
GDGT-3
+
GDGT-4' (cren isomer)
m/z [M+H] = 1298
m/z [M+H] = 1296
m/z [M+H]+ = 1292'
1228.0
-
1228.1
1228.05
BR01
4.6E+07
4.8E+07
2.4E+07
5.0E+07 5.3E+07 2.6E+07
2.7E+07 2.9E+07 1.4E+07
4.1E+07 4.8E+07 2.1E+07
1234.3
-
1234.4
1234.35
BR15
4.8E+07
3.7E+07
1.8E+07
4.4E+07 3.3E+07 1.8E+07
2.4E+07 1.9E+07 9.2E+06
3.3E+07 2.7E+07 1.3E+07
1240.6
-
1240.7
1240.65
BR02
3.9E+07
3.4E+07
1.8E+07
3.7E+07 3.3E+07 1.7E+07
2.1E+07 1.8E+07 8.6E+06
2.7E+07 2.4E+07 1.2E+07
1241.6
-
1241.7
1241.65
BR16
5.9E+07
5.0E+07
1.6E+07
5.6E+07 5.4E+07 1.6E+07
2.8E+07 2.7E+07 8.2E+06
4.5E+07 4.0E+07 1.2E+07
1242.7
-
1242.8
1242.75
BR03
3.2E+07
3.5E+07
1.8E+06
3.6E+07 3.5E+07 1.9E+06
1.8E+07 1.9E+07 9.8E+05
2.7E+07 2.7E+07 1.4E+06
1244.25 - 1244.35
1244.30
BR17
1.6E+07
1.5E+07
4.7E+06
1.8E+07 1.8E+07 5.7E+06
9.7E+06 9.3E+06 2.8E+06
1.6E+07 1.5E+07 4.1E+06
1245.9
1246.0
1245.95
BR04
1.7E+07
1.4E+07
8.8E+06
2.0E+07 1.7E+07 1.0E+07
1.0E+07 9.1E+06 5.3E+06
1.6E+07 1.3E+07 8.6E+06
1247.15 - 1247.25
-
1247.20
BR18
1.7E+07
1.7E+07
8.7E+06
1.8E+07 1.9E+07 9.3E+06
1.0E+07 9.6E+06 4.8E+06
1.3E+07 1.3E+07 5.7E+06
1248.3
-
1248.4
1248.35
BR05
2.9E+07
2.7E+07
1.4E+07
3.0E+07 2.9E+07 1.4E+07
1.7E+07 1.7E+07 8.0E+06
2.2E+07 2.2E+07 1.0E+07
1249.8
-
1249.9
1249.85
BR19
2.7E+07
2.6E+07
9.0E+06
2.7E+07 2.8E+07 9.0E+06
1.4E+07 1.5E+07 4.8E+06
1.9E+07 1.9E+07 5.7E+06
1251.3
-
1251.4
1251.35
BR06
2.3E+07
2.2E+07
4.8E+06
2.3E+07 2.2E+07 4.4E+06
1.3E+07 1.1E+07 2.5E+06
1.6E+07 1.7E+07 3.2E+06
1252.9
-
1253.0
1252.95
BR20
2.2E+07
1.7E+07
9.6E+06
2.0E+07 1.6E+07 9.1E+06
1.2E+07 9.6E+06 4.9E+06
1.4E+07 1.2E+07 6.1E+06
1254.5
-
1254.6
1254.55
BR07
5.4E+06
6.0E+06
2.3E+06
6.1E+06 6.5E+06 2.4E+06
2.7E+06 2.8E+06 1.1E+06
5.5E+06 5.6E+06 2.0E+06
1255.7
-
1255.8
1255.75
BR21
1.1E+08
1.0E+08
2.2E+07
1.3E+08 1.3E+08 2.5E+07
5.1E+07 5.1E+07 1.0E+07
1.2E+08 1.4E+08 2.4E+07
1231.16 - 1231.26
1231.21
BR08
4.3E+07
3.5E+07
1.6E+07
4.1E+07 3.5E+07 1.5E+07
2.4E+07 1.8E+07 8.9E+06
3.2E+07 2.6E+07 1.1E+07
1237.5
-
1237.6
1237.55
BR22
2.8E+07
2.9E+07
7.7E+06
2.8E+07 2.8E+07 8.1E+06
1.4E+07 1.5E+07 4.0E+06
2.2E+07 2.3E+07 5.9E+06
1241.2
-
1241.3
1241.25
BR09
6.2E+07
6.5E+07
5.8E+06
6.4E+07 6.8E+07 6.1E+06
3.4E+07 3.7E+07 3.1E+06
4.9E+07 5.5E+07 4.9E+06
1241.9
-
1242.0
1241.95
BR23
5.2E+07
4.9E+07
2.5E+07
5.3E+07 5.3E+07 2.6E+07
2.7E+07 2.8E+07 1.4E+07
4.4E+07 4.3E+07 2.1E+07
1243.6
-
1243.7
1243.65
BR10
2.9E+07
3.0E+07
1.6E+07
2.8E+07 2.9E+07 1.5E+07
1.5E+07 1.5E+07 7.8E+06
2.1E+07 2.1E+07 1.2E+07
1245.1
-
1245.2
1245.15
BR24
2.4E+07
2.1E+07
7.7E+06
2.9E+07 2.5E+07 9.6E+06
1.5E+07 1.4E+07 5.0E+06
2.8E+07 2.3E+07 7.6E+06
1246.6
-
1246.65
BR11
2.5E+07
1.3E+07
1.2E+07
2.8E+07 1.4E+07 1.3E+07
1.5E+07 7.7E+06 7.3E+06
2.1E+07 1.1E+07 1.0E+07
1247.60
BR25
3.0E+07
2.5E+07
8.4E+06
3.1E+07 2.4E+07 9.2E+06
1.7E+07 1.5E+07 5.0E+06
2.2E+07 1.8E+07 6.6E+06
1249.0
-
1249.1
1249.05
BR12
3.6E+07
3.1E+07
2.4E+07
3.7E+07 3.2E+07 2.3E+07
2.0E+07 1.8E+07 1.3E+07
2.5E+07 2.2E+07 1.7E+07
1250.5
-
1250.6
1250.55
BR26
1.7E+07
1.6E+07
7.6E+06
1.9E+07 1.6E+07 8.0E+06
9.7E+06 9.1E+06 4.1E+06
1.2E+07 1.2E+07 5.2E+06
1252.2
-
1252.3
1252.25
BR13
3.1E+07
2.8E+07
4.4E+06
3.0E+07 2.6E+07 4.1E+06
1.6E+07 1.4E+07 2.2E+06
1.9E+07 1.9E+07 2.4E+06
1253.7
-
1253.8
1253.75
BR27
1.7E+07
1.5E+07
5.9E+06
1.5E+07 1.5E+07 6.0E+06
8.5E+06 8.1E+06 3.1E+06
1.2E+07 1.1E+07 4.1E+06
1255.3
-
1255.4
1255.35
BR14
5.1E+07
5.1E+07
3.0E+07
5.9E+07 5.9E+07 3.5E+07
2.3E+07 2.4E+07 1.4E+07
5.8E+07 5.8E+07 3.2E+07
1256.0
-
1256.1
1256.05
BR28
5.9E+07
5.0E+07
3.5E+07
6.5E+07 5.9E+07 4.3E+07
2.7E+07 2.5E+07 1.7E+07
6.3E+07 5.1E+07 4.1E+07
311
Appendix
1246.7
1247.55 - 1247.65
Appendix II.b. Table of raw isoprenoidal GDGT peak areas (GDGT-0 and crenarchaeol), and raw TEX86 values.
Top / ft
Bottom /
ft
Mean depth / ft
Sample
ID
GDGT-0
GDGT-4 (crenarchaeol)
m/z [M+H]+ = 1302
m/z [M+H]+ = 1292
TEX86 / TEX86H
TEX86L
-
1228.1
1228.05
BR01
1.4E+08
1.6E+08
7.7E+07
3.7E+08 4.1E+08 2.1E+08
0.719
0.729
0.716
0.403
0.406
0.405
1234.3
-
1234.4
1234.35
BR15
1.3E+08
9.9E+07
5.0E+07
3.7E+08 3.0E+08 1.6E+08
0.679
0.683
0.685
0.381
0.374
0.391
1240.6
-
1240.7
1240.65
BR02
9.4E+07
8.6E+07
4.5E+07
3.1E+08 2.7E+08 1.5E+08
0.685
0.690
0.677
0.382
0.387
0.392
1241.6
-
1241.7
1241.65
BR16
1.2E+08
1.2E+08
3.8E+07
4.1E+08 3.9E+08 1.4E+08
0.685
0.705
0.696
0.392
0.412
0.406
1242.7
-
1242.8
1242.75
BR03
8.1E+07
8.6E+07
4.5E+06
2.7E+08 2.9E+08 1.7E+07
0.715
0.696
0.703
0.418
0.393
0.407
1244.25 - 1244.35
1244.30
BR17
3.6E+07
3.4E+07
1.0E+07
1.4E+08 1.3E+08 4.3E+07
0.732
0.731
0.730
0.417
0.416
0.430
1245.9
1246.0
1245.95
BR04
3.8E+07
3.2E+07
1.9E+07
1.4E+08 1.2E+08 7.9E+07
0.722
0.733
0.729
0.415
0.423
0.413
1247.15 - 1247.25
1247.20
BR18
4.0E+07
3.9E+07
2.0E+07
1.5E+08 1.4E+08 7.2E+07
0.708
0.711
0.696
0.399
0.413
0.408
1248.3
-
1248.4
1248.35
BR05
6.9E+07
6.9E+07
3.3E+07
2.2E+08 2.2E+08 1.1E+08
0.702
0.711
0.696
0.396
0.398
0.392
1249.8
-
1249.9
1249.85
BR19
6.4E+07
6.5E+07
2.1E+07
2.0E+08 2.0E+08 7.2E+07
0.693
0.704
0.684
0.398
0.404
0.395
1251.3
-
1251.4
1251.35
BR06
5.5E+07
5.2E+07
1.1E+07
1.8E+08 1.7E+08 3.9E+07
0.687
0.698
0.677
0.391
0.401
0.371
1252.9
-
1253.0
1252.95
BR20
5.3E+07
4.4E+07
2.4E+07
1.7E+08 1.4E+08 7.8E+07
0.686
0.677
0.385
-
1254.6
1254.55
BR07
1.6E+07
1.7E+07
5.9E+06
5.5E+07 5.8E+07 2.3E+07
0.713
0.711
0.370
0.429
0.378
1254.5
0.677
0.724
0.425
0.422
1255.7
-
1255.8
1255.75
BR21
2.6E+08
2.7E+08
5.9E+07
8.6E+08 9.2E+08 2.0E+08
0.730
0.752
0.728
0.444
0.449
0.438
1231.16 - 1231.26
1231.21
BR08
1.1E+08
9.0E+07
4.0E+07
3.4E+08 3.1E+08 1.3E+08
0.693
0.691
0.695
0.381
0.395
0.385
1237.5
-
1237.6
1237.55
BR22
7.2E+07
7.1E+07
1.9E+07
2.4E+08 2.4E+08 7.3E+07
0.698
-
1241.3
1241.25
BR09
1.5E+08
1.6E+08
1.5E+07
4.8E+08 4.9E+08 5.3E+07
0.710
0.700
0.710
0.399
0.400
0.392
1241.2
0.696
0.704
0.399
0.408
0.408
1241.9
-
1242.0
1241.95
BR23
1.2E+08
1.2E+08
5.8E+07
4.1E+08 4.0E+08 2.2E+08
0.708
0.405
1243.7
1243.65
BR10
7.2E+07
7.3E+07
3.7E+07
2.4E+08 2.4E+08 1.3E+08
0.685
0.686
0.400
0.388
0.408
-
0.703
0.688
0.718
1243.6
0.388
0.391
1245.1
-
1245.2
1245.15
BR24
5.3E+07
4.6E+07
1.7E+07
2.3E+08 2.0E+08 7.6E+07
0.749
-
1246.7
1246.65
BR11
5.6E+07
2.9E+07
2.8E+07
1.9E+08 1.1E+08 1.0E+08
0.742
0.726
0.424
0.408
0.424
1246.6
0.747
0.714
0.429
0.414
1247.55 - 1247.65
1247.60
BR25
7.0E+07
5.9E+07
2.0E+07
2.4E+08 2.0E+08 7.2E+07
1249.1
1249.05
BR12
8.5E+07
7.6E+07
5.7E+07
2.6E+08 2.4E+08 1.8E+08
0.699
0.712
0.688
0.396
0.401
0.376
-
0.700
0.696
0.697
1249.0
0.395
0.405
0.385
1250.5
-
1250.6
1250.55
BR26
4.1E+07
3.8E+07
1.9E+07
1.4E+08 1.3E+08 6.5E+07
0.700
0.699
0.695
0.406
0.393
0.406
1252.2
-
1252.3
1252.25
BR13
7.4E+07
7.1E+07
1.1E+07
2.4E+08 2.1E+08 3.5E+07
0.674
0.677
0.668
0.387
0.377
0.383
1253.7
-
1253.8
1253.75
BR27
4.2E+07
4.0E+07
1.5E+07
1.3E+08 1.2E+08 5.1E+07
0.683
0.696
0.691
0.379
0.397
0.400
1255.3
-
1255.4
1255.35
BR14
1.3E+08
1.3E+08
7.5E+07
4.4E+08 4.5E+08 2.8E+08
0.733
0.735
0.731
0.442
0.442
0.439
1256.0
-
1256.1
1256.05
BR28
1.4E+08
1.3E+08
9.1E+07
4.9E+08 4.2E+08 3.3E+08
0.726
0.729
0.431
0.441
0.451
-
0.720
0.742
0.411
Appendix
312
1228.0
Appendix II.c. Table of TEX86 derived sea surface temperature estimates.
Top / ft
Bottom Average Sample
/ ft
depth / ft
ID
-10.78+56.2*TEX86
50.475-16.332*(1/TEX86)
68.4*Log(TEX86H)+38.6
67.5*Log(TEX86L)+46.9
T / °C (Kim et al., 2008)
T / °C (Liu et al., 2009)
T / °C (Kim et al., 2010, TEX86H)
29.31
29.72
29.18
T / °C (Kim et al., 2010, TEX86L)
20.28
20.46
20.40
1228.0 - 1228.1
1228.05
BR01
29.62
30.21
29.43
27.75
28.08
27.65
1234.3 - 1234.4
1234.35
BR15
27.41
27.61
27.71
26.44
26.57
26.63
27.73
27.88
27.95
18.60
18.07
19.41
1240.6 - 1240.7
1240.65
BR02
27.69
27.98
27.29
26.62
26.79
26.37
27.94
28.14
27.64
18.67
19.10
19.48
1241.6 - 1241.7
1241.65
BR16
27.73
28.83
28.31
26.64
27.30
26.99
27.96
28.75
28.38
19.43
20.92
20.47
1242.7 - 1242.8
1242.75
BR03
29.42
28.32
28.74
27.64
27.00
27.25
29.17
28.39
28.69
21.30
19.51
20.54
1244.25 - 1244.35
1244.30
BR17
30.35
30.31
30.25
28.16
28.14
28.11
29.81
29.79
29.75
21.23
21.19
22.14
1245.9 - 1246.0
1245.95
BR04
29.81
30.44
30.20
27.86
28.21
28.08
29.44
29.87
29.71
21.14
21.70
20.98
1247.15 - 1247.25
1247.20
BR18
29.00
29.19
28.31
27.40
27.51
26.99
28.87
29.01
28.38
19.95
20.97
20.59
1248.3 - 1248.4
1248.35
BR05
28.66
29.17
28.34
27.20
27.50
27.01
28.64
28.99
28.41
19.72
19.88
19.47
1249.8 - 1249.9
1249.85
BR19
28.14
28.79
27.64
26.89
27.28
26.58
28.26
28.72
27.89
19.92
20.37
19.71
1251.3 - 1251.4
1251.35
BR06
27.82
28.46
27.24
26.70
27.08
26.33
28.03
28.49
27.60
19.36
20.10
17.87
1252.9 - 1253.0
1252.95
BR20
27.28
27.78
27.25
26.36
26.67
26.34
27.63
28.00
27.61
17.73
18.35
18.95
1254.5 - 1254.6
1254.55
BR07
29.94
29.30
29.17
27.93
27.57
27.50
29.53
29.09
29.00
22.07
21.80
21.60
1255.7 - 1255.8
1255.75
BR21
30.24
31.46
30.13
28.10
28.75
28.04
29.74
30.57
29.66
23.12
23.44
22.70
1231.16 - 1231.26
1231.21
BR08
28.15
28.07
28.29
26.90
26.85
26.98
28.26
28.21
28.37
18.59
19.66
18.93
1237.5 - 1237.6
1237.55
BR22
28.31
28.47
28.55
27.00
27.09
27.14
28.38
28.50
28.56
19.96
19.45
20.65
1241.2 - 1241.3
1241.25
BR09
28.79
29.14
29.14
27.28
27.48
27.48
28.72
28.97
28.97
20.07
19.93
20.59
1241.9 - 1242.0
1241.95
BR23
28.73
29.59
29.03
27.25
27.74
27.42
28.69
29.29
28.90
20.07
20.62
20.43
1243.6 - 1243.7
1243.65
BR10
27.90
27.72
27.77
26.75
26.64
26.67
28.09
27.96
27.99
19.16
19.18
19.41
1245.1 - 1245.2
1245.15
BR24
31.22
31.32
30.92
28.62
28.67
28.47
30.41
30.47
30.20
21.78
21.77
22.08
1246.6 - 1246.7
1246.65
BR11
29.37
29.68
30.05
27.62
27.79
27.99
29.14
29.35
29.61
20.64
20.83
21.03
1247.55 - 1247.65
1247.60
BR25
28.58
28.41
29.25
27.15
27.06
27.55
28.57
28.46
29.05
19.74
18.24
20.42
1249.0 - 1249.1
1249.05
BR12
28.36
28.48
27.86
27.02
27.10
26.72
28.42
28.51
28.06
20.11
19.70
18.95
1250.5 - 1250.6
1250.55
BR26
28.53
28.51
28.26
27.13
27.12
26.97
28.54
28.53
28.35
20.48
19.51
20.44
1252.2 - 1252.3
1252.25
BR13
27.10
27.25
26.76
26.24
26.34
26.03
27.50
27.61
27.24
19.07
18.30
18.76
1253.7 - 1253.8
1253.75
BR27
27.58
28.35
28.08
26.55
27.02
26.85
27.85
28.41
28.22
18.46
19.80
20.02
1255.3 - 1255.4
1255.35
BR14
30.41
30.55
30.28
28.19
28.27
28.12
29.85
29.95
29.76
22.99
23.00
22.79
1256.0 - 1256.1
1256.05
BR28
30.01
30.17
30.91
27.97
28.06
28.46
29.58
29.69
30.19
22.26
22.92
23.56
Appendix
313
Appendix II.d. Average TEX86-derived sea surface temperature estimates.
T/°C (TEX86H :
Kim et al.,
SD
2010)
29.40
0.28
T/°C (TEX86L :
Kim et al.,
SD
2010)
20.38
0.09
1228.0
-
1228.1
1228.05
BR01
56.10
Mean
TEX86 / TEX86H
Value
0.721
0.007
29.75
0.41
27.83
0.23
1234.3
-
1234.4
1234.35
BR15
56.33
0.693
0.002
28.17
0.11
26.91
0.07
28.28
0.08
18.69
0.67
1240.6
-
1240.7
1240.65
BR02
56.55
0.683
0.003
27.58
0.16
26.55
0.10
27.85
0.11
19.08
0.41
1241.6
-
1241.7
1241.65
BR16
56.78
0.698
0.002
28.45
0.12
27.08
0.07
28.48
0.09
20.27
0.77
1242.7
-
1242.8
1242.75
BR03
57.00
0.684
0.006
27.65
0.35
26.59
0.22
27.91
0.25
20.45
0.89
1244.25 - 1244.35
1244.30
BR17
57.08
0.708
0.004
29.02
0.20
27.41
0.12
28.89
0.14
21.52
0.54
1245.9
1246.0
1245.95
BR04
57.13
0.695
0.010
28.29
0.55
26.98
0.33
28.37
0.40
21.27
0.38
1247.15 - 1247.25
1247.20
BR18
57.17
0.710
0.008
29.12
0.43
27.47
0.25
28.96
0.31
20.51
0.51
1248.3
-
1248.4
1248.35
BR05
57.28
0.705
0.010
28.83
0.55
27.30
0.32
28.75
0.39
19.69
0.20
1249.8
-
1249.9
1249.85
BR19
57.39
0.689
0.005
27.92
0.25
26.76
0.15
28.10
0.18
20.00
0.34
1251.3
-
1251.4
1251.35
BR06
57.48
0.731
0.001
30.31
0.05
28.13
0.03
29.78
0.03
19.11
1.14
1252.9
-
1253.0
1252.95
BR20
57.59
0.746
0.004
31.16
0.21
28.59
0.11
29.86
0.14
18.34
0.61
1254.5
-
1254.6
1254.55
BR07
57.70
0.728
0.006
30.15
0.32
28.05
0.17
29.68
0.22
21.82
0.23
1255.7
-
Top / ft
-
Bottom /
ft
Average depth /
ft
Sample
ID
Approx age
/ Ma
SD
T/°C (Kim
SD
et al., 2008)
T/°C (Liu et
SD
al., 2009)
1255.8
1255.75
BR21
57.79
0.720
0.006
29.70
0.34
27.80
0.19
29.86
0.24
23.09
0.37
1231.16 - 1231.26
1231.21
BR08
57.86
0.705
0.008
28.83
0.46
27.30
0.27
28.76
0.33
19.06
0.55
1237.5
-
1237.6
1237.55
BR22
57.91
0.703
0.008
28.75
0.45
27.25
0.26
29.03
0.32
20.02
0.60
1241.2
-
1241.3
1241.25
BR09
58.01
0.703
0.007
28.72
0.42
27.24
0.24
28.68
0.30
20.20
0.35
1241.9
-
1242.0
1241.95
BR23
58.10
0.694
0.006
28.23
0.33
26.95
0.20
28.51
0.24
20.37
0.28
1243.6
-
1243.7
1243.65
BR10
58.21
0.693
0.010
28.19
0.58
26.92
0.35
28.29
0.42
19.49
0.50
1245.1
-
1245.2
1245.15
BR24
58.30
0.698
0.003
28.44
0.15
27.07
0.09
28.40
0.11
21.87
0.18
1246.6
-
1246.7
1246.65
BR11
58.50
0.687
0.011
27.84
0.61
26.70
0.37
28.04
0.44
20.83
0.20
1247.55 - 1247.65
1247.60
BR25
58.73
0.673
0.004
27.04
0.25
26.20
0.16
27.96
0.19
19.47
1.12
1249.0
-
1249.1
1249.05
BR12
58.90
0.680
0.005
27.44
0.30
26.46
0.19
27.75
0.22
19.59
0.59
1250.5
-
1250.6
1250.55
BR26
59.10
0.690
0.007
28.00
0.39
26.81
0.24
27.81
0.28
20.14
0.55
1252.2
-
1252.3
1252.25
BR13
59.30
0.716
0.007
29.47
0.41
27.67
0.23
29.20
0.29
18.71
0.38
1253.7
-
1253.8
1253.75
BR27
59.50
0.733
0.002
30.41
0.14
28.19
0.08
29.01
0.10
19.43
0.84
1255.3
-
1255.4
1255.35
BR14
60.47
0.736
0.013
30.61
0.74
28.29
0.39
29.99
0.50
22.93
0.12
1256.0
-
1256.1
1256.05
BR28
61.20
0.732
0.008
30.36
0.48
28.16
0.26
29.84
0.33
22.91
0.65
314
Appendix
SD = standard deviation
Appendix
Appendix II.e. Table of n-1 values and (n-1)*SD2 values for TEX86-derived SST estimates, and calculated
pooled standard deviation (an overall estimate of the precision of the measurement for the dataset).
Average
depth / ft
Sample
ID
T/°C (Kim 2008)
T/°C (Liu 2009)
T/°C (TEX86H : Kim
2010)
T/°C (TEX86L : Kim
2010)
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
1228.05
BR01
2
0.330
2
0.102
2
0.158
2
0.017
1234.35
BR15
2
0.025
2
0.009
2
0.013
2
0.905
1240.65
BR02
2
0.048
2
0.019
2
0.026
2
0.334
1241.65
BR16
2
0.030
2
0.011
2
0.016
2
1.176
1242.75
BR03
2
0.239
2
0.093
2
0.128
2
1.602
1244.30
BR17
2
0.082
2
0.028
2
0.041
2
0.578
1245.95
BR04
2
0.604
2
0.219
2
0.313
2
0.291
1247.20
BR18
2
0.378
2
0.125
2
0.187
2
0.527
1248.35
BR05
2
0.615
2
0.209
2
0.309
2
0.084
1249.85
BR19
2
0.128
2
0.048
2
0.068
2
0.226
1251.35
BR06
2
0.005
2
0.001
2
0.002
2
2.592
1252.95
BR20
2
0.087
2
0.024
2
0.039
2
0.748
1254.55
BR07
2
0.201
2
0.061
2
0.095
2
0.110
1255.75
BR21
2
0.229
2
0.072
2
0.111
2
0.276
1231.21
BR08
2
0.429
2
0.149
2
0.218
2
0.596
1237.55
BR22
2
0.396
2
0.135
2
0.200
2
0.727
1241.25
BR09
2
0.345
2
0.119
2
0.175
2
0.239
1241.95
BR23
2
0.218
2
0.080
2
0.114
2
0.154
1243.65
BR10
2
0.664
2
0.242
2
0.346
2
0.507
1245.15
BR24
2
0.046
2
0.017
2
0.024
2
0.063
1246.65
BR11
2
0.740
2
0.280
2
0.393
2
0.077
1247.60
BR25
2
0.127
2
0.052
2
0.070
2
2.494
1249.05
BR12
2
0.175
2
0.068
2
0.094
2
0.691
1250.55
BR26
2
0.303
2
0.113
2
0.160
2
0.610
1252.25
BR13
2
0.336
2
0.107
2
0.163
2
0.296
1253.75
BR27
2
0.039
2
0.011
2
0.018
2
1.421
1255.35
BR14
2
1.097
2
0.309
2
0.502
2
0.029
1256.05
BR28
2
0.455
2
0.132
2
0.212
2
0.854
Sum
Pooled SD
56
8.37
0.387
56
2.83
0.225
56
4.20
0.274
56
18.22
0.570
315
Appendix
Appendix III
Mid-Waipara River K/Pg Boundary Section : Geochemical Data and
Statistical Information
List of Tables :
III.a.
Sample preparation information.
III.b.
Table of raw isoprenoidal GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4)
III.c.
Table of raw isoprenoidal GDGT peak areas (GDGT-0, and crenarchaeol), and raw TEX86
values.
III.d.
Raw branched GDGT peak areas (bGDGT-Ia, bGDGT-Ib, bGDGT-Ic), and raw peak areas
of crenarchaeol for calculation of BIT indices.
III.e.
Raw branched GDGT peak areas (bGDGT-IIa, bGDGT-IIb, bGDGT-IIc, bGDGT-IIIa).
III.f.
Raw BIT indices, CBT and MBT values, pH and MAAT.
III.g.
Raw TEX86-derived SST estimates (Kim et al., 2008; Liu et al., 2009; Kim et al., 2010).
III.h.
Average TEX86 values, with statistical data for estimation of errors.
III.i.
Average TEX86-derived SST estimates (Kim et al., 2008; Liu et al., 2009), with statistical
data for estimation of errors.
III.j.
Average TEX86-derived SST estimates (Kim et al., 2010) and MAAT (Weijers et al.,
2007b) with statistical data for estimation of errors.
III.k.
Average BIT indices, CBT and MBT ratios and pH, with statistical data for estimation of
error.
III.l.
Calibration and measurement errors in TEX86-derived SST estimates.
III.m.
Propagated calibration and measurement errors.
III.n.
Raw GDGT peak areas used for quantification (including C46-GDGT internal standard).
III.o.
Quantification of GDGTs, normalised to dry weight of sediment.
III.p.
Quantification of GDGTs, normalised to total organic carbon.
III.q.
Average concentrations of GDGTs (1, 2, 3, 4’), normalised to dry weight of sediment and
total organic carbon , with statistical data for estimation of error.
III.r.
Average concentrations of GDGTs (0, cren, bGDGT-I), normalised to dry weight of
sediment and total organic carbon, with statistical data for estimation of error.
III.s.
Quantification of polar compounds (sterols and hopanols), normalised to dry weight of
sediment.
III.t.
Quantification of apolar compounds (low and mid-molecular weight n-alkanes), normalised
to dry weight of sediment.
III.u.
Quantification of apolar compounds (high-molecular weight n-alkanes, pristane and
phytane, taraxer-14-ene), normalised to dry weight of sediment.
316
Appendix
III.v.
Quantification of acid compounds (low and mid-molecular weight n-alkanoic acids),
normalised to dry weight of sediment.
III.w.
Quantification of acid compounds (high-molecular weight n-alkanoic acids), normalised to
dry weight of sediment.
III.x.
Quantification of acid compounds (hopanoic acids), normalised to dry weight of sediment.
III.y.
Raw δ13C values of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
III.z.
Raw δ13C values of mid and high-molecular weight n-alkanoic acids, corrected for
BF3/MeOH.
III.aa.
Average δ13C values of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
Standard deviations calculated for estimation of measurement error.
III.ab.
Average δ13C values of mid and high-molecular weight n-alkanoic acids, corrected for
BF3/MeOH. Standard deviations calculated for estimation of measurement error.
IIIac.
Raw peak areas for low molecular weight n-alkanoic acids, integrated from GC-C-IRMS
chromatograms, for the purpose of weighting each compound in the calculation of average
δ13C value for a group of compounds.
III.ad.
Raw peak areas for mid and high- molecular weight n-alkanoic acids, integrated from GCC-IRMS chromatograms, for the purpose of weighting each compound in the calculation of
average δ13C value for a group of compounds.
III.ae.
Table of n-1 values for n-alkanoic acid δ13C measurements.
III.af.
Table of (n-1)*SD2 values for n-alkanoic acid δ13C measurements.
III.ag.
Weighted mean average δ13C values for groups of n-alkanoic acids : low molecular weight
(δ13CLMW), mid-molecular weight (δ13CMMW) and high-molecular weight (δ13CMMW).
Estimate of measurement error for each group is given as the pooled standard deviation.
317
Appendix III.a. Sample preparation information.
Sample Depth /
Age / Ma DW/g
ID
m
TOC %
TLE Split (fraction) Polar Split (fraction)
1
0.5
2
0.5
1
0.5
0.5
1
Hexadecanol / μg
C46 GDGT / μg
Androstane / μg
x
1
2.18
2
x
1
x
2
1.38
x
2.18
x
x
1.38
2.06
2.06
f536
20
f537
13.74
62.65
63.25
12.97
15.15
0.607
0.503
f538
10.84
63.52
18.09
0.622
0.5
0.5
1
x
2.18
x
x
1.38
f539
7.84
63.81
15.07
0.744
0.5
0.5
1
x
2.18
x
x
1.38
f541
4.11
64.16
29.65
0.7155
0.25
0.75
1
x
2.18
x
x
f232
2.75
64.29
16.5
0.3365
1
x
1
x
2.18
x
f218
1.55
64.41
20.45
0.286
1
x
1
x
2.18
f215
1.25
64.43
21.76
0.2725
0.5
0.5
1
x
f213
1.05
64.45
26.15
0.18
0.5
0.5
1
f209
0.75
64.48
14.39
0.1185
0.5
0.5
f202
0.425
0.275
10.15
9.78
0.126
0.121
0.5
f199
64.51
64.53
65.48
25.38
1
2
x
n-C19 alkane / μg
1
x
1.99
1.99
2.06
x
2.06
x
1.38
2.06
x
1.38
x
x
2.18
x
x
2.18
1
x
0.5
1
0.5
0.5
0.3215
0.5
2
x
δ13C BF3/MeOH
1
2
x
-40.74
-40.74
-40.74
-40.74
1.99
x
-40.74
-40.74
1.99
x
-40.74
-40.74
x
1.99
x
-40.74
-40.74
2.06
x
1.99
x
-40.74
-40.74
1.38
2.06
x
1.99
x
-40.74
-40.74
x
1.38
2.06
x
1.99
x
-40.74
-40.74
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
x
2.18
x
x
1.38
x
x
2.18
x
x
1.38
x
1.99
1.99
x
1
2.06
2.06
x
-40.74
-40.74
-40.74
-40.74
0.5
1
x
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
x
1
x
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
f554
0.22
f197b
0.19
65.48
10.1
0.1945
1
f556b
0.16
65.48
32.73
0.3135
0.5
0.5
1
x
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
f558
0.1
65.49
21.06
0.231
0.5
0.5
1
x
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
f559
0.05
0.45
0.3495
0.5
1
x
2.18
x
x
1.38
0.75
1
x
2.18
x
x
1.38
x
1.99
1.99
x
0.25
2.06
2.06
x
0.005
21.88
26.8
0.5
f560
65.5
65.5
x
-40.74
-40.74
-40.74
-40.74
f561
-0.07
65.5
27.72
0.3505
0.5
0.5
1
x
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
f175
-0.18
65.51
x
0.5
x
2.07
x
1.38
-0.273
65.51
0.272
0.4765
1
f172
22.56
25.4
x
x
1
x
0.5
x
2.07
x
1.38
x
x
2.11
2.11
x
x
1.44
1.44
-40.74
-40.74
-40.74
-40.74
f170
-0.355
65.51
18.7
0.31
x
1
x
0.5
x
2.07
x
1.38
x
2.11
x
5.74
-40.74
-40.74
f168
-0.44
65.52
22.8
0.468
x
1
x
0.5
x
2.07
x
1.38
x
2.11
x
1.44
-40.74
-40.74
f165
-0.545
65.52
1
x
0.5
x
2.07
x
1.38
-0.695
-1.15
65.53
0.4265
0.5075
x
f161
21.18
16.59
x
1
x
0.5
x
2.07
x
1.38
x
x
2.11
2.11
x
x
2.87
2.87
-40.74
-40.74
-40.74
-40.74
65.55
20.05
0.42
0.5
0.5
1
x
2.18
x
x
1.38
2.06
x
1.99
x
-40.74
-40.74
f562
Appendix
318
DW = dry weight of sample.
TOC = Total organic carbon
‘Splits’ are aliquots of the original fraction which have been carried through for further processing.
Appendix III.b. Table of raw isoprenoidal GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4).
Sample ID
Depth / m
GDGT-1
GDGT-2
GDGT-3
GDGT-4' (cren. Isomer)
m/z [M+H]+ = 1302
m/z [M+H]+ = 1298
m/z [M+H]+ = 1296
m/z [M+H]+ = 1292
f536
20
6.5E+06 7.7E+05 7.6E+04 7.8E+07
4.4E+06
5.2E+05
4.4E+04
5.4E+07
2.2E+06 2.5E+05 2.1E+04 2.7E+07
2.2E+06 3.1E+05 2.8E+04 2.9E+07
f537
13.74
1.8E+07 1.4E+07 5.9E+05 4.6E+07
1.2E+07
8.5E+06
3.9E+05
3.0E+07
5.5E+06 4.2E+06 2.0E+05 1.4E+07
6.2E+06 4.4E+06 2.0E+05 1.6E+07
f538
10.84
2.3E+07 1.5E+07 3.4E+05 4.6E+07
1.4E+07
9.2E+06
1.9E+05
2.9E+07
7.1E+06 4.8E+06 9.6E+04 1.4E+07
7.3E+06 5.7E+06 9.9E+04 1.4E+07
f539
7.84
1.5E+07 2.5E+05 5.9E+04 1.2E+08
9.1E+06
1.5E+05
3.4E+04
7.8E+07
4.9E+06 7.7E+04 1.6E+04 3.9E+07
5.6E+06 7.3E+04 2.9E+04 3.8E+07
f541
4.11
3.7E+05 1.4E+07 2.9E+05 1.6E+06
2.2E+05
8.9E+06
1.6E+05
9.7E+05
9.9E+04 4.7E+06 8.9E+04 5.0E+05
1.3E+05 4.9E+06 9.0E+04 4.5E+05
f232
2.75
-
f218
1.55
-
f215
1.25
f213
f209
-
-
-
-
-
-
6.1E+04
3.5E+04
6.8E+06
-
5.1E+06 3.3E+05 1.3E+05 1.6E+07
3.8E+06
2.5E+05
9.5E+04
9.9E+06
7.9E+05 5.6E+04 2.1E+04 4.4E+06
6.9E+05 3.5E+04 1.6E+04 5.2E+06
1.05
0.75
9.1E+06 5.0E+05 1.7E+05 1.7E+07
7.1E+06
4.0E+05
1.3E+05
1.1E+07
1.1E+06 6.0E+04 2.0E+04 1.9E+06
4.3E+05 2.0E+04 1.0E+04 6.5E+05
4.8E+06 4.5E+06 1.4E+05 1.2E+07
3.4E+06
3.2E+06
1.0E+05
7.5E+06
5.9E+05 5.1E+05 1.3E+04 1.3E+06
2.6E+05 2.2E+05 6.5E+03 6.3E+05
f202
0.425
1.8E+06 1.2E+06
8.4E+06
1.2E+06
7.4E+05
-
4.8E+06
1.5E+05 9.5E+04
1.2E+05 7.8E+04
f199
0.275
6.9E+05 5.1E+05 3.0E+04 3.1E+06
3.9E+05
3.2E+05
1.8E+04
1.8E+06
1.3E+05 9.6E+04 3.7E+03 4.6E+05
1.2E+05 9.3E+04 6.1E+03 5.1E+05
f554
0.22
1.3E+05 1.0E+05 5.7E+04 2.5E+07
9.7E+04
7.0E+04
3.9E+04
1.9E+07
4.3E+04 2.8E+04 1.7E+04 8.8E+06
7.2E+04 5.7E+04 3.4E+04 1.2E+07
f197
0.19
-
-
-
-
8.9E+04 6.3E+04 1.0E+07
-
2.1E+05 1.7E+05
-
-
-
-
-
-
-
-
6.0E+06
1.8E+05
1.2E+05
-
4.1E+06
-
5.2E+04
4.8E+04
3.5E+05
-
5.7E+04 5.6E+04 4.7E+05
-
-
-
-
2.5E+04 9.6E+03 1.7E+06
-
8.6E+04 5.2E+04
-
5.6E+05
-
-
-
1.8E+06
-
-
-
-
2.8E+04 2.0E+04 1.2E+06
-
9.7E+04 8.2E+04
-
4.1E+05
-
-
-
2.3E+06
0.16
1.9E+06 1.4E+06 6.7E+04 2.0E+07
1.4E+06
1.1E+06
4.1E+04
1.2E+07
6.6E+05 5.5E+05 2.4E+04 6.2E+06
9.3E+05 5.9E+05 3.3E+04 6.0E+06
f558
0.1
5.4E+06 4.7E+06 7.9E+05 1.5E+07
4.2E+06
3.8E+06
6.0E+05
1.1E+07
1.9E+06 1.8E+06 2.7E+05 5.4E+06
2.5E+06 2.3E+06 4.0E+05 6.1E+06
f559
0.05
6.8E+06 2.8E+06 8.5E+04 1.8E+07
5.0E+06
2.2E+06
6.9E+04
1.4E+07
2.4E+06 1.0E+06 3.0E+04 6.2E+06
3.2E+06 1.3E+06 3.9E+04 8.9E+06
f560
0.005
7.5E+06 1.7E+05 1.2E+05 6.5E+06
5.7E+06
1.1E+05
8.7E+04
4.8E+06
2.7E+06 5.9E+04 3.8E+04 2.0E+06
3.1E+06 7.6E+04 5.0E+04 2.8E+06
f561
-0.07
2.9E+06 2.7E+06 4.4E+04 1.3E+07
2.2E+06
1.9E+06
3.3E+04
9.4E+06
9.1E+05 8.6E+05 1.4E+04 4.7E+06
1.3E+06 1.2E+06 2.2E+04 5.6E+06
f175
-0.18
8.6E+06 9.1E+06 1.9E+05
-
4.9E+06
5.5E+06
1.1E+05
-
2.6E+06 3.0E+06 5.7E+04
-
3.1E+06 3.2E+06 6.1E+04
-
f172
-0.27
-0.355
7.2E+06 7.3E+06 2.5E+05
-
4.2E+06
4.5E+06
1.6E+05
-
2.0E+06 2.2E+06 7.9E+04
-
2.7E+06 2.4E+06 8.2E+04
-
f170
6.3E+06 4.0E+06 1.8E+05
-
3.7E+06
2.7E+06
1.1E+05
-
2.0E+06 1.2E+06 5.6E+04
-
2.3E+06 1.5E+06 7.1E+04
-
f168
-0.44
4.6E+06 4.2E+06 3.2E+04
-
2.7E+06
2.6E+06
1.9E+04
-
1.3E+06 1.3E+06 5.4E+03
-
1.6E+06 1.4E+06 1.6E+04
-
f165
-0.545
4.6E+06 4.6E+06 8.2E+04
-
2.7E+06
2.7E+06
4.5E+04
-
1.5E+06 1.4E+06 2.6E+04
-
1.8E+06 1.6E+06 4.2E+04
-
f161
-0.70
5.6E+06 4.9E+06 5.0E+05
-
3.4E+06
3.3E+06
3.2E+05
-
1.7E+06 1.6E+06 1.6E+05
-
2.0E+06 1.3E+06 1.7E+05
f562
-1.15
-
-
1.9E+04 2.1E+04 2.2E+05
1.1E+06
-
-
-
3.1E+06
319
Appendix
-
-
-
f556
-
2.3E+04 1.6E+04 1.8E+05
-
Appendix III.c. Table of raw isoprenoidal GDGT peak areas (GDGT-0, and crenarchaeol), and raw TEX86 values.
Sample ID
Depth / m
crenarchaeol
GDGT-0
m/z [M+H]+ = 1292
m/z [M+H]+ = 1300
TEX86 / TEX86H
TEX86L
f536
20
6.2E+07 7.5E+06 7.2E+05 7.8E+08
3.2E+07
3.7E+06
3.7E+05
3.9E+08
0.574
0.585
0.550
0.584
0.334
0.337
0.311
0.338
f537
13.74
1.7E+08 1.3E+08 6.0E+06 4.5E+08
1.0E+08
7.2E+07
3.1E+06
2.4E+08
0.565
0.554
0.571
0.566
0.331
0.321
0.331
0.331
f538
10.84
2.1E+08 1.4E+08 3.2E+06 4.6E+08
1.3E+08
8.5E+07
1.9E+06
2.5E+08
f539
7.84
1.5E+08 2.6E+06 6.8E+05 1.3E+09
9.2E+07
1.4E+06
3.7E+05
6.9E+08
0.554
0.564
0.567
0.543
0.526
0.571
0.553
0.560
0.323
0.312
0.316
0.313
0.298
0.308
0.324
0.326
f541
4.11
3.6E+06 1.3E+08 2.8E+06 1.5E+07
2.1E+06
8.0E+07
1.6E+06
9.1E+06
-
-
-
0.525
0.318
-
0.321
-
0.317
-
0.287
-
0.562
-
0.551
2.75
0.545
-
0.532
f232
-
0.292
f218
1.55
2.0E+05 1.0E+06 6.3E+05 4.3E+07
2.3E+05
1.1E+06
6.7E+05
1.5E+08
-
0.563
0.508
0.489
-
0.348
0.328
0.365
f215
1.25
2.1E+07 1.4E+06 5.5E+05 1.7E+08
6.9E+07
4.5E+06
1.7E+06
1.8E+08
0.506
0.509
0.501
0.551
0.389
0.395
0.384
0.328
f213
1.5E+07 8.2E+05 2.8E+05 2.7E+07
1.2E+08
6.2E+06
2.0E+06
2.0E+08
0.489
0.488
0.484
0.451
0.411
0.414
0.404
0.377
f209
1.05
0.75
7.9E+06 7.2E+06 2.4E+05 1.8E+07
7.7E+07
7.2E+07
2.2E+06
2.0E+08
0.472
0.470
0.474
0.441
0.389
0.393
0.407
0.360
f202
0.425
3.7E+06 2.5E+06 3.8E+05 1.6E+07
4.2E+07
2.8E+07
4.9E+06
1.9E+08
0.445
0.429
-
0.408
0.375
0.361
-
0.350
f199
0.275
4.0E+06 3.1E+06 1.8E+05 1.7E+07
1.7E+07
1.3E+07
6.8E+05
7.1E+07
0.481
0.496
0.485
0.466
0.321
0.343
0.352
0.329
f554
0.22
1.4E+06 1.1E+06 5.8E+05 2.6E+08
6.0E+05
4.4E+05
2.4E+05
1.1E+08
0.612
0.607
0.614
0.608
0.354
0.354
0.347
0.353
3.8E+04 3.0E+04
4.4E+04
3.9E+04
-
-
-
-
-
-
-
-
-
-
2.1E+06 1.6E+06 4.1E+04 5.9E+07
2.3E+06
1.7E+06
4.2E+04
6.4E+07
0.639
0.603
0.576
0.385
0.348
-
0.342
5.1E+05 5.1E+05 4.9E+06
3.3E+05
2.9E+05
2.3E+06
-
1.8E+07 1.4E+07 6.8E+05 2.1E+08
8.8E+06
6.4E+06
3.0E+05
1.1E+08
0.621
0.608
0.602
0.617
0.616
0.597
0.554
0.395
0.352
0.398
0.356
0.349
0.313
0.322
f197
f556
0.19
0.16
-
-
-
-
-
-
f558
0.1
5.2E+07 4.7E+07 8.0E+06 1.5E+08
2.3E+07
2.0E+07
3.3E+06
6.2E+07
0.615
0.631
0.616
0.603
0.363
0.370
0.361
0.346
f559
0.05
6.6E+07 3.0E+07 8.8E+05 1.8E+08
2.8E+07
1.2E+07
3.4E+05
7.7E+07
0.613
0.618
0.617
0.616
0.353
0.367
0.376
0.364
f560
0.005
7.3E+07 1.8E+06 1.2E+06 6.6E+07
3.5E+07
7.9E+05
4.8E+05
3.1E+07
0.607
0.588
0.599
0.596
0.358
0.327
0.359
0.360
f561
-0.07
3.0E+07 2.9E+07 5.0E+05 1.2E+08
1.4E+07
1.3E+07
2.3E+05
5.4E+07
0.605
0.592
0.613
0.351
0.368
-0.18
8.8E+07 9.5E+07 1.9E+06
-
5.4E+07
5.7E+07
1.2E+06
-
7.3E+07 7.5E+07 2.7E+06
-
4.4E+07
4.5E+07
1.6E+06
-
0.551
0.560
-
0.303
0.314
0.315
0.318
0.313
0.325
f170
-0.27
-0.355
0.563
0.553
0.347
-
f172
0.551
0.554
0.604
-
0.370
f175
6.6E+07 4.3E+07 1.9E+06
-
4.2E+07
2.7E+07
1.1E+06
-
0.563
0.574
0.563
-
0.310
0.338
0.309
-
f168
-0.44
4.7E+07 4.6E+07 3.7E+05
-
3.0E+07
2.7E+07
2.2E+05
-
0.550
0.557
0.559
-
0.312
0.318
0.336
-
f165
-0.545
5.0E+07 4.9E+07 8.8E+05
-
3.0E+07
3.0E+07
6.0E+05
-
5.6E+07 5.1E+07 5.3E+06
-
3.4E+07
3.1E+07
3.0E+06
-
0.577
0.563
0.311
0.316
0.308
0.337
0.293
0.329
-
-0.70
0.551
0.560
-
f161
0.565
0.558
f562
-1.15
3.6E+07
7.5E+07
2.0E+07
-
-
3.6E+07
0.562
-
-
0.330
-
-
0.351
-
0.595
-
320
Appendix
-
-
-
Appendix III.d. Raw branched GDGT peak areas (bGDGT-Ia, bGDGT-Ib, bGDGT-Ic), and raw peak areas of crenarchaeol for calculation of BIT indices.
Sample ID
Depth / m
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.27
-0.355
-0.44
-0.545
-0.7
-1.15
Crenarchaeol
bGDGT-Ia
bGDGT-Ib
bGDGT-Ic
m/z [M+H]+ = 1292
m/z [M+H]+ = 1022
m/z [M+H]+ = 1020
m/z [M+H]+ = 1020
6.2E+07
1.7E+08
2.1E+08
1.5E+08
1.3E+08
2.1E+05
2.1E+07
1.5E+07
7.9E+06
3.7E+06
4.0E+06
1.4E+06
2.1E+06
1.8E+07
5.2E+07
6.6E+07
7.3E+07
3.0E+07
8.8E+07
7.3E+07
6.6E+07
4.7E+07
5.0E+07
5.6E+07
3.6E+07
7.5E+06
1.3E+08
1.4E+08
2.6E+06
3.6E+06
1.0E+06
1.4E+06
8.2E+05
7.2E+06
2.5E+06
3.1E+06
1.1E+06
1.6E+06
1.4E+07
4.7E+07
3.0E+07
1.8E+06
2.9E+07
9.5E+07
7.5E+07
4.3E+07
4.6E+07
4.9E+07
5.1E+07
-
7.8E+08
4.5E+08
4.6E+08
1.3E+09
1.5E+07
3.1E+08
4.4E+07
1.7E+08
2.7E+07
1.8E+07
1.6E+07
1.7E+07
2.6E+08
5.9E+07
2.1E+08
1.5E+08
1.8E+08
6.6E+07
1.2E+08
7.5E+07
2.4E+06
6.9E+06
7.9E+06
5.1E+06
4.9E+06
7.7E+05
5.4E+05
2.9E+05
1.1E+05
1.9E+05
7.2E+04
1.3E+05
1.1E+06
3.1E+06
3.6E+06
3.6E+06
1.6E+06
5.2E+06
4.8E+06
3.8E+06
2.8E+06
3.0E+06
3.3E+06
1.8E+06
2.7E+05
5.1E+06
5.3E+06
7.8E+04
1.2E+05
3.3E+04
5.6E+04
3.2E+04
2.7E+05
1.0E+05
1.4E+05
5.9E+04
8.5E+04
8.4E+05
2.8E+06
1.5E+06
8.4E+04
1.6E+06
5.9E+06
4.8E+06
2.3E+06
2.5E+06
3.0E+06
3.1E+06
-
4.5E+07
2.4E+07
2.5E+07
5.2E+07
7.1E+05
1.4E+07
2.2E+06
7.4E+06
1.3E+06
8.6E+05
8.4E+05
9.7E+05
2.0E+07
4.1E+06
1.4E+07
1.1E+07
1.4E+07
4.5E+06
9.9E+06
5.9E+06
4.9E+05
1.2E+06
1.5E+06
9.1E+05
1.1E+06
1.5E+05
6.0E+04
4.6E+04
1.9E+04
3.2E+04
1.3E+04
3.4E+04
2.0E+05
6.0E+05
7.2E+05
8.5E+05
3.1E+05
9.0E+05
8.6E+05
6.8E+05
5.1E+05
5.3E+05
5.3E+05
3.2E+05
5.9E+04
9.1E+05
1.0E+06
8.2E+03
2.5E+04
1.3E+04
4.1E+04
1.7E+04
8.3E+03
1.6E+04
1.5E+05
5.5E+05
2.9E+05
1.7E+04
2.9E+05
9.7E+05
8.3E+05
4.4E+05
4.3E+05
5.1E+05
5.2E+05
-
9.2E+06
3.7E+06
3.8E+06
7.5E+06
1.3E+05
2.6E+06
3.8E+05
1.4E+06
2.2E+05
1.2E+05
1.7E+05
1.5E+05
3.5E+06
7.1E+05
2.4E+06
2.0E+06
2.3E+06
7.4E+05
1.7E+06
1.0E+06
4.9E+05
1.2E+06
1.5E+06
9.1E+05
1.1E+06
1.5E+05
6.0E+04
4.6E+04
1.9E+04
3.2E+04
1.3E+04
3.4E+04
2.0E+05
6.0E+05
7.2E+05
8.5E+05
3.1E+05
9.0E+05
8.6E+05
6.8E+05
5.1E+05
5.3E+05
5.3E+05
3.2E+05
5.9E+04
9.1E+05
1.0E+06
8.2E+03
2.5E+04
1.3E+04
4.1E+04
1.7E+04
8.3E+03
1.6E+04
1.5E+05
5.5E+05
2.9E+05
1.7E+04
2.9E+05
9.7E+05
8.3E+05
4.4E+05
4.3E+05
5.1E+05
5.2E+05
-
9.2E+06
3.7E+06
3.8E+06
7.5E+06
1.3E+05
2.6E+06
3.8E+05
1.4E+06
2.2E+05
1.2E+05
1.7E+05
1.5E+05
3.5E+06
7.1E+05
2.4E+06
2.0E+06
2.3E+06
7.4E+05
1.7E+06
1.0E+06
Appendix
321
Appendix III.e. Raw branched GDGT peak areas (bGDGT-IIa, bGDGT-IIb, bGDGT-IIc, bGDGT-IIIa).
Sample ID
Depth / m
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.27
-0.355
-0.44
-0.545
-0.7
-1.15
bGDGT-IIa
m/z [M+H]+ = 1036
1.3E+06 1.8E+05 2.2E+07
4.4E+06 3.0E+06 1.4E+07
4.7E+06 3.9E+06 1.4E+07
3.3E+06 3.4E+04 3.2E+07
3.7E+06 5.6E+04 5.2E+05
8.8E+06
1.4E+04 9.7E+05
3.6E+05 2.6E+04 5.2E+06
3.1E+05 1.3E+04 6.5E+05
1.4E+05 1.6E+05 4.5E+05
5.1E+04 4.4E+04 3.5E+05
6.0E+04 4.8E+04 3.3E+05
3.1E+04 2.5E+04 6.9E+06
5.4E+04 3.2E+04 1.8E+06
5.2E+05 3.4E+05 5.6E+06
1.2E+06 1.2E+06 3.3E+06
1.6E+06 7.0E+05 4.7E+06
1.9E+06 4.2E+04 1.6E+06
7.7E+05 8.6E+05 3.2E+06
2.9E+06 3.1E+06
2.2E+06 2.6E+06
2.0E+06 1.3E+06
1.6E+06 1.2E+06
1.4E+06 1.4E+06
1.7E+06 1.6E+06
8.8E+05
2.6E+06
bGDGT-IIb
m/z [M+H]+ = 1034
5.2E+05 6.7E+04 8.5E+06
1.4E+06 1.0E+06 4.5E+06
1.7E+06 1.3E+06 4.9E+06
1.1E+06 9.9E+03 9.3E+06
1.2E+06 1.8E+04 1.5E+05
2.7E+06
3.0E+05
1.0E+05 6.7E+03 1.6E+06
8.7E+04
1.8E+05
4.4E+04 6.0E+04 1.2E+05
1.2E+04
8.5E+04
1.7E+04 1.9E+04 6.3E+04
5.5E+03 5.4E+03 2.7E+06
1.8E+04 8.4E+03 3.6E+05
1.4E+05 1.2E+05 1.7E+06
4.5E+05 4.1E+05 1.4E+06
5.4E+05 2.3E+05 1.9E+06
7.0E+05 9.7E+03 4.7E+05
2.5E+05 2.6E+05 1.1E+06
9.1E+05 1.1E+06
8.6E+05 8.7E+05
7.6E+05 4.3E+05
5.1E+05 4.6E+05
5.8E+05 5.4E+05
6.0E+05 5.6E+05
3.1E+05
8.4E+05
bGDGT-IIc
m/z [M+H]+ = 1032
9.1E+04 1.1E+04 1.1E+06
1.5E+05 1.8E+05 7.0E+05
2.6E+05 1.5E+05 5.9E+05
1.4E+05
1.4E+06
1.9E+05 4.1E+03 2.4E+04
4.0E+05
2.5E+04
2.2E+05
8.5E+03
1.7E+04
6.1E+03
2.3E+04
8.3E+03
1.0E+04
2.1E+04
5.5E+05
1.0E+05
3.3E+04 2.4E+04 3.9E+05
9.7E+04 7.7E+04 2.4E+05
9.1E+04 3.9E+04 2.2E+05
9.2E+04 2.5E+03 1.1E+05
6.0E+04 6.0E+04 2.1E+05
1.2E+05 2.0E+05
1.5E+05 1.6E+05
1.2E+05 8.0E+04
7.4E+04 7.5E+04
9.5E+04 9.7E+04
7.9E+04 1.1E+05
7.0E+04
1.2E+05
bGDGT-IIIa
m/z [M+H]+ = 1050
6.6E+05 7.2E+04 1.2E+07
2.1E+06 1.5E+06 6.2E+06
2.6E+06 1.8E+06 8.3E+06
1.5E+06 1.9E+04 1.5E+07
1.7E+06 4.6E+04 2.6E+05
4.1E+06
3.9E+03 4.4E+05
2.0E+05 1.6E+04 2.1E+06
1.4E+05 4.8E+03 3.9E+05
6.8E+04 7.7E+04 2.6E+05
2.3E+04 2.3E+04 1.1E+05
3.6E+04 2.6E+04 1.9E+05
7.1E+03 7.8E+03 3.1E+06
2.8E+04 1.5E+04 4.6E+05
2.0E+05 1.5E+05 2.0E+06
5.6E+05 4.6E+05 1.7E+06
7.2E+05 2.9E+05 1.5E+06
5.0E+05 1.6E+04 5.7E+05
3.0E+05 3.4E+05 1.1E+06
1.1E+06 1.3E+06
9.9E+05 1.0E+06
8.3E+05 5.3E+05
5.9E+05 5.6E+05
5.9E+05 6.1E+05
6.0E+05 6.4E+05
4.2E+05
7.5E+05
Appendix
322
Appendix III.f. Raw BIT indices, CBT and MBT values, pH and MAAT.
Sample
ID
Depth
/m
[I+II+III]/[I+II+III]+[IV]
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
0.067
0.072
0.067
0.062
0.074
0.000
0.060
0.061
0.059
0.047
0.067
0.072
0.092
0.089
0.084
0.082
0.077
0.082
0.095
0.099
0.092
0.095
0.091
0.091
0.081
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.27
-0.355
-0.44
-0.545
-0.7
-1.15
BIT Index
0.065
0.070
0.072
0.048
0.058
0.048
0.067
0.056
0.066
0.062
0.063
0.078
0.075
0.086
0.088
0.078
0.072
0.088
0.098
0.101
0.089
0.085
0.093
0.094
-
0.092
0.091
0.093
0.071
0.091
0.081
0.076
0.080
0.080
0.078
0.074
0.082
0.102
0.097
0.093
0.094
0.099
0.092
0.107
0.109
-Log ([Ib+IIb]/[Ia+IIa])
0.572
0.633
0.598
0.627
0.568
0.649
0.759
0.680
0.716
0.705
0.746
0.541
0.665
0.609
0.613
0.555
0.627
0.650
0.610
0.609
0.630
0.598
0.652
0.640
CBT
0.551
0.615
0.608
0.794
0.625
0.614
0.632
0.714
0.782
0.683
0.635
0.626
0.623
0.673
0.652
0.640
0.638
0.626
0.618
0.621
0.633
-
0.579
0.675
0.648
0.697
0.646
0.632
0.660
0.617
0.679
0.730
0.672
0.783
0.633
0.740
0.675
0.632
0.647
0.701
0.681
0.660
[Ia + Ib + Ic] / [ All
bGDGTs ]
MBT
0.548
0.516
0.568
0.521
0.528
0.536
0.521
0.486
0.525
0.513
0.579
0.526
0.486
0.564
0.489
0.523
0.606
0.588
0.607
0.507
0.538
0.561
0.581
0.530
0.549
0.594
0.662
0.662
0.633
0.669
0.675
0.640
0.652
0.614
0.646
0.650
0.607
0.624
0.642
0.631
0.622
0.674
0.605
0.603
0.676
0.599
0.604
0.666
0.594
0.569
0.686
0.562
0.561
0.591
0.564
0.562
0.551
0.559
0.568
0.579
0.587
0.577
0.570
0.576
0.628
(3.33 - CBT) / 0.38
7.26
7.10
7.19
7.11
7.27
7.06
6.77
6.97
6.88
6.91
6.80
7.34
7.01
7.16
7.15
7.30
7.11
7.05
7.16
7.16
7.11
7.19
7.05
7.08
pH
7.31
7.14
7.16
6.67
7.12
7.15
7.10
6.88
6.71
6.96
7.09
7.12
7.12
6.99
7.05
7.08
7.08
7.12
7.14
7.13
7.10
-
7.24
6.99
7.06
6.93
7.06
7.10
7.03
7.14
6.98
6.84
7.00
6.70
7.10
6.82
6.99
7.10
7.06
6.92
6.97
7.03
(MBT - 0.122 - 0.187*CBT) / 0.02
15.96
14.02
14.33
13.70
12.91
17.25
13.69
16.57
16.92
20.43
20.67
19.55
18.05
19.77
18.44
18.67
17.74
15.92
17.73
16.32
15.96
17.25
16.66
16.74
MAAT / °C
14.57
14.57
12.49
15.43
16.25
18.52
14.47
18.89
18.57
19.79
19.18
19.16
18.22
17.82
16.25
15.97
16.15
15.60
16.53
17.43
16.49
-
16.86
14.41
14.11
13.66
12.30
14.12
18.03
13.46
15.59
14.53
20.74
20.02
20.56
19.49
19.70
21.67
21.65
20.63
21.84
19.12
Appendix
323
Appendix III.g. Raw TEX86-derived SST estimates (Kim et al., 2008; Liu et al., 2009; Kim et al., 2010).
Sample ID
Depth / m
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
f197
0.19
f556
0.16
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
0.1
0.05
0.005
-0.07
-0.18
1.05
0.75
0.425
0.275
0.22
-0.27
-0.355
-0.44
-0.545
-0.7
-1.15
T
21.47
20.96
20.35
20.92
19.84
17.67
16.67
15.73
14.22
16.24
23.61
25.15
24.11
23.37
23.81
23.65
23.32
23.22
20.21
20.35
20.85
20.15
20.96
20.57
20.82
-10.78+56.2*TEX86
/ °C (Kim et al., 2008)
22.10
20.13
22.06
20.35
21.30
21.01
21.08
18.79
20.31
19.74
21.32
20.67
20.78
19.10
20.18
18.72
20.84
17.79
16.68
17.82
17.38
20.17
16.62
16.43
14.59
15.61
15.83
14.02
13.32
12.14
17.11
16.47
15.41
23.35
23.72
23.37
23.09
21.60
23.06
23.82
23.89
22.77
20.36
24.66
23.83
23.09
23.95
23.90
23.84
22.27
22.90
22.72
22.50
23.65
23.18
20.88
20.17
20.32
20.72
21.45
20.85
20.54
20.63
20.18
21.65
20.68
20.88
22.65
50.475-16.332*(1/TEX86)
T / °C (Liu et al., 2009)
22.02
22.56
20.78
22.53
21.56
20.99
21.86
21.60
20.99
21.66
19.43
20.95
21.52
20.40
21.88
21.29
20.50
21.40
19.76
20.83
19.36
21.45
18.35
17.06
18.22
18.38
17.88
20.81
17.04
16.98
16.75
14.30
15.85
15.70
15.99
13.46
13.76
12.39
10.43
16.50
17.57
16.79
15.42
23.79
23.58
23.87
23.60
24.93
23.37
22.13
24.17
23.35
23.95
23.59
24.00
23.12
21.00
23.94
24.58
23.96
23.37
23.82
24.05
24.01
23.97
23.56
22.71
23.22
23.07
23.48
22.89
23.82
23.45
20.86
21.49
20.81
20.99
20.96
21.33
21.45
22.00
21.45
20.80
21.16
21.25
21.56
20.83
22.17
21.19
21.30
21.49
21.43
23.02
68.4*Log(TEX86H)+38.6
T / °C (Kim et al., 2010, TEX86H)
22.10
22.67
20.84
22.64
21.63
21.05
21.94
21.67
21.05
21.74
19.52
21.01
21.59
20.46
21.96
21.36
20.56
21.46
19.83
20.89
19.46
21.51
18.50
17.33
18.38
18.53
18.07
20.88
17.32
17.26
17.06
14.97
16.28
16.15
16.40
14.29
14.53
13.45
11.95
16.84
17.79
17.09
15.91
24.01
23.79
24.11
23.80
25.31
23.56
22.22
24.44
23.53
24.19
23.80
24.25
23.27
21.06
24.18
24.90
24.20
23.56
24.05
24.30
24.26
24.21
23.76
22.83
23.39
23.23
23.67
23.03
24.05
23.64
20.92
21.56
20.87
21.05
21.02
21.40
21.52
22.08
21.52
20.86
21.23
21.32
21.63
20.89
22.27
21.26
21.36
21.55
21.50
23.17
67.5*Log(TEX86L)+46.9
T / °C
14.76
14.51
13.79
12.79
13.24
19.25
20.82
19.24
18.15
13.56
16.42
18.92
19.63
16.28
17.22
16.35
16.76
17.74
11.93
12.99
12.54
12.80
12.66
13.09
14.44
(Kim et al., 2010, TEX86L)
14.99
12.65
15.13
13.57
14.53
14.53
13.10
11.44
13.82
12.84
12.36
14.06
13.35
10.35
13.56
10.82
15.99
14.18
17.39
19.64
18.85
14.22
21.04
20.32
18.30
19.50
20.55
16.96
17.02
16.11
15.49
16.26
14.29
16.49
15.84
16.38
15.95
15.44
19.92
16.02
16.63
12.84
13.66
17.75
17.06
15.82
17.49
18.24
17.24
14.09
16.90
16.96
16.18
17.63
15.83
13.03
12.82
13.32
13.99
15.12
12.51
13.27
14.93
12.42
10.87
15.06
14.30
16.18
Appendix
324
Appendix III.h. Average TEX86 values, with statistical data for estimation of errors.
TEX86 / TEX86H
Sample
ID
Depth
/m
Age /
Ma
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
62.65
63.25
63.52
63.81
64.16
64.29
64.41
64.43
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
64.45
64.48
64.51
64.53
65.48
65.48
65.48
65.49
65.5
65.5
65.5
65.51
-0.27
-0.355
-0.44
-0.545
65.51
65.51
65.52
65.52
-0.7
-1.15
65.53
65.55
mean
SD
0.574 0.014
0.564 0.007
0.548 0.015
0.559 0.012
0.547 0.012
0.525
0.520 0.038
0.517 0.023
0.478 0.018
0.465 0.013
0.430 0.016
0.482 0.013
0.610 0.003
0.606 0.032
0.602 0.023
0.619 0.012
0.616 0.002
0.598 0.008
0.605 0.008
0.553 0.008
0.556 0.004
0.568 0.006
0.562 0.013
0.559 0.015
0.558 0.005
0.579 0.023
Sum
n
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
104
TEX86L
(n1)
(n1)*SD2
4
3
4
3
3
8.2E-04
1.5E-04
9.3E-04
4.3E-04
4.7E-04
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
78
4.4E-03
1.6E-03
9.5E-04
5.4E-04
7.7E-04
4.7E-04
3.1E-05
2.0E-03
3.1E-03
5.3E-04
1.6E-05
1.8E-04
2.5E-04
1.8E-04
3.1E-05
1.0E-04
5.3E-04
7.2E-04
6.2E-05
5.3E-04
0.020
mean
SD
0.329 0.012
0.329 0.005
0.315 0.010
0.315 0.008
0.311 0.016
0.292
0.347 0.019
0.374 0.031
0.401 0.017
0.384 0.018
0.366 0.013
0.336 0.014
0.352 0.004
0.358 0.023
0.355 0.033
0.364 0.021
0.365 0.010
0.351 0.016
0.354 0.015
0.307 0.009
0.319 0.006
0.330 0.026
0.309 0.028
0.305 0.009
0.326 0.009
0.341 0.014
Sum
n
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
104
1 / TEX86
(n1)
(n1)*SD2
4
3
4
3
3
0.0005
0.0001
0.0004
0.0002
0.0007
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
78
0.0011
0.0029
0.0008
0.0010
0.0005
0.0006
0.0000
0.0011
0.0064
0.0018
0.0003
0.0008
0.0009
0.0002
0.0001
0.0021
0.0024
0.0002
0.0003
0.0002
0.026
mean
SD
1.741 0.045
1.774 0.022
1.823 0.051
1.787 0.039
1.827 0.042
1.905
1.923 0.138
1.935 0.082
2.092 0.081
2.151 0.064
2.327 0.089
2.075 0.054
1.639 0.009
1.650 0.086
1.661 0.066
1.616 0.030
1.624 0.006
1.673 0.022
1.653 0.022
1.810 0.025
1.799 0.013
1.761 0.018
1.780 0.042
1.790 0.050
1.791 0.015
1.728 0.069
Sum
n
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
104
(n1)
(n-1)*SD2
4
3
4
3
3
0.0080
0.0015
0.0105
0.0045
0.0053
0.0000
0.0572
0.0203
0.0196
0.0124
0.0237
0.0089
0.0002
0.0148
0.0265
0.0037
0.0001
0.0014
0.0019
0.0019
0.0003
0.0010
0.0052
0.0074
0.0006
0.0047
0.242
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
78
0.016
Pooled SD
0.018
Pooled SD
0.056
mean SD
0.014
mean SD
0.015
mean SD
0.047
Appendix
325
Pooled SD
Appendix
Appendix III.i. Average TEX86-derived SST estimates (Kim et al., 2008; Liu et al., 2009) with statistical
data for estimation of errors.
T / °C (Kim et al., 2008)
Sample
ID
Depth
/m
Age /
Ma
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.7
10.8
7.84
4.11
2.75
1.55
1.25
62.6
63.2
63.5
63.8
64.2
64.3
64.4
64.4
1.05
0.75
0.43
0.28
0.22
0.19
0.16
0.1
0.05
0.01
-0.07
-0.18
64.5
64.5
64.5
64.5
65.5
65.5
65.5
65.5
65.5
65.5
65.5
65.5
-0.27
-0.36
-0.44
-0.55
65.5
65.5
65.5
65.5
-0.7
-1.15
65.5
65.5
T / °C (Liu et al., 2009)
mean
SD
n
(n1)
(n1)*SD2
mean
SD
n
(n1)
(n-1)*SD2
21.49
20.90
20.04
20.66
19.98
18.72
18.44
18.26
16.08
15.34
13.37
16.31
23.51
23.28
23.05
24.00
23.84
22.80
23.21
20.28
20.46
21.13
20.80
20.62
20.60
21.74
0.81
0.40
0.86
0.67
0.70
2.15
1.28
1.00
0.75
0.90
0.71
0.18
1.78
1.28
0.65
0.13
0.44
0.45
0.44
0.22
0.33
0.75
0.87
0.26
1.29
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
4
3
4
3
3
0
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
2.59
0.48
2.93
1.35
1.48
13.88
4.95
2.99
1.69
2.44
1.49
0.10
6.35
9.84
1.68
0.05
0.57
0.79
0.57
0.10
0.33
1.69
2.27
0.20
1.68
22.02
21.50
20.68
21.27
20.62
19.36
18.95
18.82
16.27
15.31
12.43
16.57
23.71
23.48
23.31
24.07
23.96
23.14
23.47
20.92
21.09
21.71
21.40
21.22
21.22
22.23
0.729
0.367
0.837
0.631
0.684
2.256
1.345
1.319
1.050
1.451
0.888
0.142
1.403
1.086
0.494
0.099
0.354
0.357
0.412
0.208
0.298
0.679
0.809
0.239
1.124
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
4
3
4
3
3
0
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
2.12
0.40
2.80
1.19
1.40
15.27
5.43
5.22
3.30
6.32
2.37
0.06
3.93
7.08
0.98
0.03
0.38
0.51
0.51
0.09
0.27
1.38
1.96
0.17
1.26
104
78
62.49
104
78
64.43
Sum
Sum
Pooled SD
0.895
Pooled SD
0.909
mean SD
0.772
mean SD
0.770
326
Appendix III.j. Average TEX86-derived SST estimates (Kim et al., 2010) and MAAT (Weijers et al., 2007b) with statistical data for estimation of errors.
T / °C (Kim et al., 2010, TEX86H)
Sample
ID
Depth
/m
Age /
Ma
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.7
10.8
7.84
4.11
2.75
1.55
1.25
62.6
63.2
63.5
63.8
64.2
64.3
64.4
64.4
1.05
0.75
0.43
0.28
0.22
0.19
0.16
0.1
0.05
0.01
-0.07
-0.18
64.5
64.5
64.5
64.5
65.5
65.5
65.5
65.5
65.5
65.5
65.5
65.5
-0.27
-0.36
-0.44
-0.55
65.5
65.5
65.5
65.5
-0.7
-1.15
65.5
65.5
T / °C (Kim et al., 2010, TEX86L)
MAAT
mean
SD
n
(n1)
(n1)*SD2
mean
SD
n
(n1)
(n1)*SD2
mean
SD
n
(n1)
(n-1)*SD2
22.12
21.57
20.75
21.34
20.69
19.46
19.12
18.96
16.65
15.83
13.50
16.91
23.93
23.70
23.51
24.34
24.20
23.30
23.66
20.98
21.16
21.79
21.47
21.30
21.29
22.34
0.751
0.375
0.830
0.638
0.679
2.158
1.288
1.125
0.871
1.121
0.776
0.157
1.549
1.156
0.554
0.111
0.385
0.391
0.416
0.210
0.308
0.699
0.823
0.242
1.183
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
4
3
4
3
3
0
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
2.25
0.42
2.75
1.22
1.38
13.97
4.98
3.79
2.27
3.77
1.81
0.07
4.80
8.01
1.23
0.04
0.44
0.61
0.52
0.09
0.29
1.47
2.03
0.18
1.40
14.27
14.29
13.02
13.01
12.63
10.82
15.85
17.99
20.12
18.85
17.43
14.90
16.28
16.77
16.43
17.25
17.33
16.18
16.43
12.24
13.43
14.37
12.35
12.13
14.07
15.31
1.040
0.478
0.968
0.730
1.524
1.608
2.535
1.247
1.391
1.068
1.207
0.296
1.879
2.683
0.950
0.781
1.394
1.265
0.843
0.509
2.319
2.784
0.841
0.825
1.234
5
4
5
4
4
1
4
4
4
4
4
4
4
3
7
5
4
4
5
4
3
4
4
4
4
2
4
3
4
3
3
0
3
3
3
3
3
3
3
2
6
4
3
3
4
3
2
3
3
3
3
1
4.33
0.68
3.75
1.60
6.96
0.00
7.76
19.28
4.67
5.80
3.42
4.37
0.26
7.07
43.19
3.61
1.83
5.83
6.40
2.13
0.52
16.13
23.25
2.12
2.04
1.52
15.80
14.33
13.65
14.27
13.82
14.12
18.03
16.41
14.64
15.19
18.83
19.78
19.93
19.61
18.98
20.20
19.43
19.04
18.61
15.95
16.94
15.96
16.24
17.34
16.58
17.93
1.15
0.28
1.00
1.01
2.12
2.63
1.35
1.20
2.70
0.80
1.18
0.16
0.85
1.31
1.92
1.44
2.90
0.03
1.12
0.51
0.40
0.13
0.12
1.68
3
3
3
3
3
1
1
3
2
3
2
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
0
0
2
1
2
1
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
2.67
0.16
2.01
2.03
9.03
13.89
1.82
2.87
7.29
1.28
2.79
0.05
1.44
3.44
7.37
4.15
16.77
0.00
1.26
0.26
0.16
0.02
0.01
2.82
104
78
59.81
104
78
178.55
Sum
Sum
Sum
39
83.58
0.876
Pooled SD
1.513
Pooled SD
1.464
mean SD
0.752
mean SD
1.296
mean SD
1.167
Appendix
327
Pooled SD
Appendix III.k. Average BIT indices, CBT and MBT ratios and pH, with statistical data for estimation of error.
BIT
Sample
ID
Depth
/m
Age /
Ma
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.27
-0.355
-0.44
-0.545
-0.7
-1.15
62.65
63.25
63.52
63.81
64.16
64.29
64.41
64.43
64.45
64.48
64.51
64.53
65.48
65.48
65.48
65.49
65.5
65.5
65.5
65.51
65.51
65.51
65.52
65.52
65.53
65.55
CBT
MBT
pH
mean
SD
n
n1
(n1)*SD2
mean
SD
n
n1
(n1)*SD2
mean
SD
n
n1
(n1)*SD2
mean
SD
n
n1
(n-1)*SD2
0.074
0.078
0.077
0.060
0.074
0.081
0.041
0.069
0.066
0.068
0.061
0.071
0.084
0.088
0.089
0.089
0.086
0.080
0.093
0.097
0.100
0.091
0.090
0.092
0.093
0.095
0.015
0.011
0.014
0.011
0.016
0.038
0.010
0.012
0.010
0.014
0.010
0.015
0.011
0.004
0.005
0.011
0.011
0.013
0.003
0.002
0.002
0.007
0.001
0.002
0.020
3
3
3
3
3
1
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
0
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
4.5E-04
2.6E-04
3.9E-04
2.6E-04
5.2E-04
0.0E+00
2.9E-03
2.0E-04
3.1E-04
1.9E-04
3.8E-04
2.0E-04
4.8E-04
2.6E-04
2.9E-05
4.5E-05
2.4E-04
2.3E-04
3.4E-04
6.4E-06
3.9E-06
4.8E-06
4.7E-05
1.9E-06
3.8E-06
4.0E-04
0.568
0.641
0.618
0.706
0.613
0.632
0.660
0.627
0.719
0.681
0.694
0.734
0.720
0.655
0.658
0.622
0.628
0.643
0.653
0.645
0.624
0.617
0.624
0.609
0.642
0.650
0.015
0.031
0.026
0.084
0.040
0.019
0.056
0.049
0.031
0.043
0.077
0.102
0.021
0.012
0.018
0.077
0.027
0.007
0.020
0.012
0.008
0.016
0.014
0.014
3
3
3
3
3
1
1
3
2
3
2
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
0
0
2
1
2
1
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
4.3E-04
1.9E-03
1.4E-03
1.4E-02
3.2E-03
0.0E+00
0.0E+00
7.5E-04
3.1E-03
4.8E-03
9.8E-04
3.6E-03
1.2E-02
2.1E-02
8.5E-04
2.8E-04
6.4E-04
1.2E-02
1.4E-03
4.9E-05
4.1E-04
1.5E-04
6.6E-05
2.6E-04
1.9E-04
2.0E-04
15.80
14.33
13.65
14.27
13.82
14.12
18.03
16.41
14.64
15.19
18.83
19.78
19.93
19.61
18.98
20.20
19.43
19.04
18.61
15.95
16.94
15.96
16.24
17.34
16.58
17.93
1.15
0.28
1.00
1.01
2.12
2.63
1.35
1.20
2.70
0.80
1.18
0.16
0.85
1.31
1.92
1.44
2.90
0.03
1.12
0.51
0.40
0.13
0.12
1.68
3
3
3
3
3
1
1
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
0
0
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
2.7
0.2
2.0
2.0
9.0
0.0
0.0
13.9
3.6
2.9
14.6
1.3
2.8
0.0
1.4
3.4
7.4
4.1
16.8
0.0
1.3
0.3
0.2
0.0
0.0
2.8
7.27
7.08
7.14
6.91
7.15
7.10
7.03
7.11
6.87
6.97
6.94
6.83
6.87
7.04
7.03
7.13
7.11
7.07
7.04
7.07
7.12
7.14
7.12
7.16
7.07
7.05
0.038
0.081
0.069
0.221
0.106
0.051
0.147
0.128
0.082
0.112
0.204
0.269
0.054
0.031
0.047
0.204
0.070
0.018
0.053
0.032
0.021
0.043
0.036
0.038
3
3
3
3
3
1
1
3
2
3
2
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
0
0
2
1
2
1
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
3.0E-03
1.3E-02
9.5E-03
9.7E-02
2.2E-02
0.0E+00
0.0E+00
5.2E-03
2.2E-02
3.3E-02
6.8E-03
2.5E-02
8.3E-02
1.4E-01
5.9E-03
2.0E-03
4.4E-03
8.3E-02
9.8E-03
3.4E-04
2.8E-03
1.0E-03
4.6E-04
1.8E-03
1.3E-03
1.4E-03
Sum
43
8.2E-03
Sum
39
8.4E-02
Sum
41
Sum
39
328
mean SD
0.014
0.011
Pooled
SD
mean SD
0.046
0.034
Pooled
SD
mean SD
92.7
1.504
1.167
Pooled
SD
mean SD
5.8E-01
0.122
0.090
Appendix
Pooled
SD
Appendix III.l. Calibration and measurement errors in TEX86-derived SST estimates.
Kim et al., 2008
Sample
ID
Depth
/m
Age /
Ma
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.7
10.8
7.84
4.11
2.75
1.55
1.25
62.6
63.2
63.5
63.8
64.2
64.3
64.4
64.4
1.05
0.75
0.43
0.28
0.22
0.19
0.16
0.1
0.05
0.01
-0.07
-0.18
64.5
64.5
64.5
64.5
65.5
65.5
65.5
65.5
65.5
65.5
65.5
65.5
-0.27
-0.36
-0.44
-0.55
65.5
65.5
65.5
65.5
-0.7
-1.15
65.5
65.5
calib.
err.
[+/-]
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
upper
meas.
err.
0.81
0.40
0.86
0.67
0.70
2.15
1.28
1.00
0.75
0.90
0.71
0.18
1.78
1.28
0.65
0.13
0.44
0.45
0.44
0.22
0.33
0.75
0.87
0.26
1.29
lower
meas.
err.
-0.81
-0.40
-0.86
-0.67
-0.70
-2.15
-1.28
-1.00
-0.75
-0.90
-0.71
-0.18
-1.78
-1.28
-0.65
-0.13
-0.44
-0.45
-0.44
-0.22
-0.33
-0.75
-0.87
-0.26
-1.29
Kim et al., 2010 [TEX86H]
Liu et al., 2009
calib.
err.
[+/-]
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
5.40
upper
meas.
err.
0.71
0.36
0.82
0.62
0.68
2.26
1.38
1.26
1.01
1.41
0.88
0.14
1.39
1.02
0.49
0.10
0.35
0.35
0.41
0.21
0.30
0.69
0.81
0.24
1.10
lower
meas.
err.
-0.71
-0.37
-0.83
-0.63
-0.69
-2.39
-1.42
-1.28
-1.02
-1.43
-0.89
-0.14
-1.44
-1.03
-0.49
-0.10
-0.36
-0.35
-0.42
-0.21
-0.30
-0.70
-0.82
-0.24
-1.15
calib.
err.
[+/-]
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
2.50
upper
meas.
err.
0.74
0.37
0.82
0.63
0.68
2.16
1.31
1.10
0.85
1.10
0.77
0.16
1.54
1.12
0.55
0.11
0.38
0.39
0.42
0.21
0.31
0.70
0.82
0.24
1.17
lower
meas.
err.
-0.74
-0.37
-0.83
-0.64
-0.68
-2.22
-1.32
-1.11
-0.86
-1.11
-0.78
-0.16
-1.57
-1.13
-0.55
-0.11
-0.39
-0.39
-0.42
-0.21
-0.31
-0.71
-0.83
-0.24
-1.19
Kim et al., 2010 [TEX86L]
calib.
err.
[+/-]
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
upper
meas.
err.
1.02
0.47
0.95
0.73
1.48
1.59
2.41
1.22
1.38
1.06
1.20
0.29
1.89
2.68
1.69
0.78
1.36
1.26
0.84
0.51
2.33
2.67
0.83
0.82
1.22
lower
meas.
err.
-1.03
-0.47
-0.96
-0.74
-1.49
-1.62
-2.46
-1.23
-1.39
-1.07
-1.21
-0.30
-1.93
-2.72
-1.77
-0.78
-1.37
-1.27
-0.84
-0.51
-2.38
-2.73
-0.83
-0.83
-1.25
329
Calibration errors are reproduced from the corresponding citations.
Appendix
meas. err. = measurement error, derived from the standard deviation; i.e. upper and lower measurement errors in TEX 86-derived SST were calculated by respectively adding and subtracting
the SD from the corresponding mean TEX86 value, and deriving SST estimates from those upper and lower values.
Appendix III.m. Propagated calibration and measurement errors.
Sample ID
Depth / m
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197b
f556b
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.2725
-0.355
-0.44
-0.545
-0.695
-1.15
Kim et al., 2008
Liu et al., 2009
Kim et al., 2010 [TEX86H]
Kim et al., 2010 [TEX86L]
[+]
[-]
[+]
[-]
[+]
[-]
[+]
[-]
1.88
1.75
1.90
1.83
1.84
1.70
2.74
2.13
1.97
1.86
1.92
1.84
1.71
2.46
2.13
1.82
1.70
1.75
1.76
1.76
1.71
1.73
1.86
1.91
1.72
2.14
-1.88
-1.75
-1.90
-1.83
-1.84
-1.70
-2.74
-2.13
-1.97
-1.86
-1.92
-1.84
-1.71
-2.46
-2.13
-1.82
-1.70
-1.75
-1.76
-1.76
-1.71
-1.73
-1.86
-1.91
-1.72
-2.14
5.45
5.41
5.46
5.44
5.44
5.40
5.86
5.57
5.55
5.49
5.58
5.47
5.40
5.58
5.50
5.42
5.40
5.41
5.41
5.42
5.40
5.41
5.44
5.46
5.41
5.51
-5.45
-5.41
-5.46
-5.44
-5.44
-5.40
-5.90
-5.58
-5.55
-5.49
-5.59
-5.47
-5.40
-5.59
-5.50
-5.42
-5.40
-5.41
-5.41
-5.42
-5.40
-5.41
-5.44
-5.46
-5.41
-5.52
2.61
2.53
2.63
2.58
2.59
2.50
3.31
2.82
2.73
2.64
2.73
2.62
2.50
2.94
2.74
2.56
2.50
2.53
2.53
2.53
2.51
2.52
2.60
2.63
2.51
2.76
-2.61
-2.53
-2.63
-2.58
-2.59
-2.50
-3.34
-2.83
-2.74
-2.64
-2.74
-2.62
-2.50
-2.95
-2.74
-2.56
-2.50
-2.53
-2.53
-2.53
-2.51
-2.52
-2.60
-2.63
-2.51
-2.77
4.13
4.03
4.11
4.07
4.26
4.00
4.30
4.67
4.18
4.23
4.14
4.18
4.01
4.42
4.81
4.34
4.07
4.22
4.19
4.09
4.03
4.63
4.81
4.08
4.08
4.18
-4.13
-4.03
-4.11
-4.07
-4.27
-4.00
-4.32
-4.69
-4.19
-4.24
-4.14
-4.18
-4.01
-4.44
-4.83
-4.37
-4.08
-4.23
-4.20
-4.09
-4.03
-4.65
-4.84
-4.09
-4.08
-4.19
[+] = upper error, [-] = lower error; the same error in measurement of TEX 86 may produce different upper and lower errors when applying a non-linear calibration.
330
Appendix
Propagation of calibration and measurement error is the ‘root sum of squares’ simple propagation method; i.e. calibration error and measurement error are squared, and the square-root of
the sum is taken as an overall estimation of error.
Appendix III.n. Raw GDGT peak areas used for quantification (including C46-GDGT internal standard).
Sample ID
Depth /
m
GDGT-1
GDGT-2
GDGT-3
GDGT-4'
GDGT-0
crenarchaeol
bGDGT-Ia
GDGT46 [I.S]
m/z [M+H]+ =
1298
4.4E+06 5.2E+05
1.2E+07 8.5E+06
1.4E+07 9.2E+06
9.1E+06 1.5E+05
m/z [M+H]+ =
1296
2.2E+06 2.5E+05
5.5E+06 4.2E+06
7.1E+06 4.8E+06
4.9E+06 7.7E+04
m/z [M+H]+ =
1292
2.2E+06 3.1E+05
6.2E+06 4.4E+06
7.3E+06 5.7E+06
5.6E+06 7.3E+04
m/z [M+H]+ =
1302
3.2E+07 3.7E+06
1.0E+08 7.2E+07
1.3E+08 8.5E+07
9.2E+07 1.4E+06
m/z [M+H]+ =
1292
6.2E+07 7.5E+06
1.7E+08 1.3E+08
2.1E+08 1.4E+08
1.5E+08 2.6E+06
m/z [M+H]+ =
1022
2.4E+06 2.7E+05
6.9E+06 5.1E+06
7.9E+06 5.3E+06
5.1E+06 7.8E+04
1.7E+08
3.7E+08
2.8E+08
1.9E+08
2.0E+07
2.6E+08
1.8E+08
3.3E+06
f536
f537
f538
f539
20
13.74
10.84
7.84
m/z [M+H]+ =
1300
6.5E+06 7.7E+05
1.8E+07 1.4E+07
2.3E+07 1.5E+07
1.5E+07 2.5E+05
f541
4.11
3.7E+05
1.4E+07
2.2E+05
8.9E+06
9.9E+04
4.7E+06
1.3E+05
4.9E+06
2.1E+06
8.0E+07
3.6E+06
1.3E+08
4.9E+06
1.2E+05
3.0E+06
1.2E+08
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
2.75
1.55
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.2725
-0.355
-0.44
-0.545
-0.695
-1.15
5.1E+06
9.1E+06
4.8E+06
1.8E+06
6.9E+05
1.3E+05
2.1E+05
1.9E+06
5.4E+06
6.8E+06
7.5E+06
2.9E+06
8.6E+06
7.2E+06
6.3E+06
4.6E+06
4.6E+06
5.6E+06
3.3E+06
8.9E+04
3.3E+05
5.0E+05
4.5E+06
1.2E+06
5.1E+05
1.0E+05
1.7E+05
1.4E+06
4.7E+06
2.8E+06
1.7E+05
2.7E+06
9.1E+06
7.3E+06
4.0E+06
4.2E+06
4.6E+06
4.9E+06
-
3.8E+06
7.1E+06
3.4E+06
1.2E+06
3.9E+05
9.7E+04
1.8E+05
1.4E+06
4.2E+06
5.0E+06
5.7E+06
2.2E+06
4.9E+06
4.2E+06
3.7E+06
2.7E+06
2.7E+06
3.4E+06
2.2E+06
6.1E+04
2.5E+05
4.0E+05
3.2E+06
7.4E+05
3.2E+05
7.0E+04
1.2E+05
1.1E+06
3.8E+06
2.2E+06
1.1E+05
1.9E+06
5.5E+06
4.5E+06
2.7E+06
2.6E+06
2.7E+06
3.3E+06
-
7.9E+05
1.1E+06
5.9E+05
1.5E+05
1.3E+05
4.3E+04
8.6E+04
6.6E+05
1.9E+06
2.4E+06
2.7E+06
9.1E+05
2.6E+06
2.0E+06
2.0E+06
1.3E+06
1.5E+06
1.7E+06
1.0E+06
2.5E+04
5.6E+04
6.0E+04
5.1E+05
9.5E+04
9.6E+04
2.8E+04
5.2E+04
5.5E+05
1.8E+06
1.0E+06
5.9E+04
8.6E+05
3.0E+06
2.2E+06
1.2E+06
1.3E+06
1.4E+06
1.6E+06
-
6.9E+05
4.3E+05
2.6E+05
1.2E+05
1.2E+05
7.2E+04
9.7E+04
9.3E+05
2.5E+06
3.2E+06
3.1E+06
1.3E+06
3.1E+06
2.7E+06
2.3E+06
1.6E+06
1.8E+06
2.0E+06
1.1E+06
2.8E+04
3.5E+04
2.0E+04
2.2E+05
7.8E+04
9.3E+04
5.7E+04
8.2E+04
5.9E+05
2.3E+06
1.3E+06
7.6E+04
1.2E+06
3.2E+06
2.4E+06
1.5E+06
1.4E+06
1.6E+06
1.3E+06
-
2.3E+05
6.9E+07
1.2E+08
7.7E+07
4.2E+07
1.7E+07
6.0E+05
2.3E+06
8.8E+06
2.3E+07
2.8E+07
3.5E+07
1.4E+07
5.4E+07
4.4E+07
4.2E+07
3.0E+07
3.0E+07
3.4E+07
2.0E+07
1.1E+06
4.5E+06
6.2E+06
7.2E+07
2.8E+07
1.3E+07
4.4E+05
1.7E+06
6.4E+06
2.0E+07
1.2E+07
7.9E+05
1.3E+07
5.7E+07
4.5E+07
2.7E+07
2.7E+07
3.0E+07
3.1E+07
-
2.0E+05
2.1E+07
1.5E+07
7.9E+06
3.7E+06
4.0E+06
1.4E+06
2.1E+06
1.8E+07
5.2E+07
6.6E+07
7.3E+07
3.0E+07
8.8E+07
7.3E+07
6.6E+07
4.7E+07
5.0E+07
5.6E+07
3.6E+07
1.0E+06
1.4E+06
8.2E+05
7.2E+06
2.5E+06
3.1E+06
1.1E+06
1.6E+06
1.4E+07
4.7E+07
3.0E+07
1.8E+06
2.9E+07
9.5E+07
7.5E+07
4.3E+07
4.6E+07
4.9E+07
5.1E+07
-
7.7E+05
5.4E+05
2.9E+05
1.1E+05
1.9E+05
7.2E+04
1.3E+05
1.1E+06
3.1E+06
3.6E+06
3.6E+06
1.6E+06
5.2E+06
4.8E+06
3.8E+06
2.8E+06
3.0E+06
3.3E+06
1.8E+06
3.3E+04
5.6E+04
3.2E+04
2.7E+05
1.0E+05
1.4E+05
5.9E+04
8.5E+04
8.4E+05
2.8E+06
1.5E+06
8.4E+04
1.6E+06
5.9E+06
4.8E+06
2.3E+06
2.5E+06
3.0E+06
3.1E+06
-
1.5E+06
2.5E+08
2.6E+08
4.0E+08
2.4E+08
2.6E+08
6.3E+06
4.3E+08
2.8E+08
2.9E+08
3.7E+08
1.7E+08
2.1E+08
2.0E+08
2.4E+08
2.6E+08
2.8E+08
2.6E+08
2.5E+08
8.4E+07
5.2E+06
1.8E+07
1.5E+07
3.7E+08
1.6E+08
2.0E+08
4.8E+06
4.1E+08
2.1E+08
2.6E+08
1.6E+08
3.7E+06
2.1E+08
2.2E+08
2.5E+08
1.7E+08
2.7E+08
2.6E+08
2.3E+08
3.5E+05
m/z [M+H]+ = 744
Appendix
331
Appendix III.o. Quantification of GDGTs, normalised to dry weight of sediment.
GDGT-1
GDGT-2
GDGT-3
GDGT-4'
GDGT-0
crenarchaeol
Sample ID
Depth / m
f536
f537
f538
f539
20
13.74
10.84
7.84
8.39
8.93
12.50
14.76
8.12
9.77
12.75
14.14
5.63
5.77
7.78
8.88
5.47
6.02
7.77
8.40
2.83
2.72
3.79
4.78
2.65
2.98
4.08
4.30
2.84
3.10
3.95
5.44
3.33
3.13
4.84
4.10
41.54
50.57
72.31
89.32
39.59
50.87
71.69
77.29
79.56
85.25
114.76
144.88
79.55
90.24
118.92
145.46
f541
4.11
7.60
7.42
4.59
4.59
2.04
2.40
2.58
2.52
42.44
41.22
74.90
67.03
f232
2.75
-
-
-
-
-
-
-
-
-
-
-
-
f218
f215
f213
f209
f202
f199
f554
f197b
f556b
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
1.55
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.2725
-0.355
-0.44
-0.545
-0.695
-1.15
3.87
2.59
3.69
2.33
2.05
0.75
2.33
0.22
0.60
2.47
2.27
2.95
1.36
2.66
1.60
1.77
1.01
1.14
1.84
5.49
4.14
2.36
3.54
2.32
2.10
0.72
2.27
0.18
0.54
2.37
2.19
3.25
1.28
2.52
1.63
1.74
0.93
1.16
1.79
-
2.65
1.90
2.89
1.67
1.33
0.42
1.68
0.19
0.43
1.92
1.69
2.25
1.05
1.51
0.94
1.05
0.59
0.68
1.11
3.55
2.32
1.80
2.80
1.67
1.28
0.45
1.59
0.13
0.42
1.93
1.74
2.11
0.91
1.54
0.99
1.16
0.57
0.67
1.21
-
1.09
0.40
0.46
0.29
0.17
0.14
0.74
0.09
0.20
0.90
0.82
1.08
0.43
0.82
0.45
0.57
0.29
0.36
0.56
1.71
0.63
0.40
0.42
0.27
0.16
0.13
0.63
0.06
0.22
0.92
0.82
1.10
0.40
0.83
0.50
0.54
0.29
0.35
0.58
-
1.24
0.35
0.17
0.13
0.14
0.13
1.26
0.10
0.29
1.14
1.09
1.22
0.60
0.94
0.60
0.66
0.35
0.44
0.65
1.78
1.32
0.25
0.14
0.11
0.13
0.13
1.29
0.09
0.24
1.19
0.99
1.43
0.55
0.89
0.53
0.63
0.32
0.41
0.49
-
35.46
35.11
46.75
37.31
48.52
18.48
10.36
2.45
2.70
10.54
9.44
13.73
6.76
16.67
9.89
11.75
6.42
7.46
11.19
32.43
47.99
31.93
43.55
37.39
47.98
18.07
10.02
1.90
2.58
10.38
9.58
14.92
6.35
15.89
9.90
11.53
6.12
7.54
11.21
-
44.02
10.51
6.11
3.86
4.22
4.34
24.44
2.17
5.63
24.04
22.27
28.67
14.10
27.10
16.32
18.44
10.19
12.28
18.63
58.57
41.67
9.82
5.81
3.75
4.38
4.42
24.32
1.78
5.64
23.71
23.35
34.39
13.66
26.38
16.57
18.61
10.19
12.25
18.67
-
-1
ng g / DW
-1
ng g / DW
-1
ng g / DW
-1
ng g / DW
-1
ng g / DW
-1
ng g / DW
bGDGT-Ia
ng g-1 / DW
3.14
3.44
4.27
4.92
2.54
2.85
3.62
4.45
4.39
2.56
-
-
0.39
0.22
0.14
0.12
0.21
1.25
0.20
0.33
1.41
1.20
1.43
0.76
1.61
1.08
1.07
0.60
0.74
1.10
3.02
0.81
0.40
0.22
0.14
0.18
0.20
1.33
0.17
0.34
1.43
1.19
1.57
0.75
1.65
1.07
1.01
0.55
0.76
1.13
-
Appendix
332
Appendix III.p. Quantification of GDGTs, normalised to total organic carbon.
GDGT-1
GDGT-2
GDGT-3
GDGT-4'
GDGT-0
crenarchaeol
Sample
ID
Depth /
m
f536
f537
f538
f539
20
13.74
10.84
7.84
1382.03
1774.36
2010.24
1984.06
1337.93
1941.98
2049.99
1900.07
927.10
1146.80
1251.40
1193.05
900.61
1197.11
1248.43
1128.58
466.04
540.52
610.02
642.08
436.56
592.58
656.69
577.65
468.05
615.51
634.47
731.50
548.91
621.60
777.57
551.58
6843.55
10053.50
11625.43
12005.64
6521.84
10114.12
11525.31
10388.87
13107.66
16949.01
18450.56
19473.26
13104.99
17941.13
19119.74
19550.85
f541
4.11
1062.30
1037.29
641.42
641.42
285.66
335.65
360.03
351.87
5931.53
5760.49
10467.70
f232
2.75
f218
1.55
1354.71
1447.21
928.02
812.90
381.16
221.52
433.32
462.16
12397.76
16778.99
f215
f213
f209
f202
f199
f554
f197b
f556b
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
1.25
1.05
0.75
0.425
0.275
0.22
0.19
0.16
0.1
0.05
0.005
-0.07
-0.18
-0.2725
-0.355
-0.44
-0.545
-0.695
-1.15
949.59
2047.52
1969.30
1624.71
622.26
725.37
112.34
190.59
1070.95
505.51
844.65
389.08
977.46
336.66
571.34
215.14
267.52
363.02
1306.18
867.57
1967.03
1954.72
1667.63
598.67
705.81
93.60
173.48
1023.85
487.43
931.20
365.80
928.12
342.00
560.49
199.61
272.49
353.18
698.97
1604.75
1409.79
1055.04
348.82
522.67
99.68
138.73
832.47
375.04
643.04
300.91
556.15
197.63
338.91
125.96
159.08
218.53
845.93
661.27
1555.24
1409.70
1014.94
369.94
495.09
65.72
134.53
834.53
387.11
604.33
259.82
566.08
208.08
375.53
121.40
157.78
238.01
146.52
254.10
243.06
133.48
116.67
230.39
46.85
65.02
387.80
182.93
310.30
123.64
299.91
94.18
183.99
62.01
84.99
110.99
408.05
146.74
235.88
225.59
129.92
111.48
196.03
29.54
69.83
397.48
181.33
315.19
115.31
303.55
104.23
174.41
61.32
81.24
114.10
128.39
96.67
105.79
113.14
110.56
390.80
52.58
91.34
493.84
241.72
350.37
171.39
345.88
126.22
212.36
75.27
103.08
128.30
424.35
90.82
80.24
95.41
107.03
108.54
400.44
46.68
75.05
515.76
220.06
410.30
155.94
328.14
111.36
203.73
68.47
95.19
97.00
12885.27
25971.53
31481.96
38510.07
15270.88
3223.14
1258.96
861.19
4564.34
2097.53
3927.82
1927.35
6130.43
2075.84
3790.05
1371.86
1748.21
2204.86
7721.15
11718.26
24191.70
31549.26
38075.42
14932.39
3117.39
977.90
823.14
4493.63
2129.16
4269.52
1812.38
5841.97
2077.05
3720.83
1307.84
1768.45
2209.79
ng g-1 / TOC
ng g-1 / TOC
ng g-1 / TOC
ng g-1 / TOC
ng g-1 / TOC
ng g-1 / TOC
bGDGT-Ia
ng g-1 / TOC
9368.71
516.76
684.13
686.78
660.74
355.47
469.24
720.42
714.66
589.46
357.37
15391.90
14571.21
-
297.39
3856.55
3395.88
3253.60
3352.94
3590.22
7600.50
1117.36
1797.30
10408.82
4949.03
8203.55
4022.10
9963.55
3424.78
5949.85
2177.60
2878.36
3671.16
13945.03
3605.31
3228.37
3166.08
3472.92
3651.42
7563.32
917.21
1800.62
10264.99
5188.10
9840.95
3897.11
9699.27
3477.91
6004.67
2177.84
2873.27
3679.01
142.53
121.12
118.56
97.65
170.14
387.35
103.50
104.83
610.64
265.78
410.07
215.55
590.86
226.73
346.33
128.76
173.24
217.31
718.08
145.71
123.82
120.58
139.43
161.20
414.57
89.86
107.02
620.58
264.47
449.35
214.65
607.60
224.41
324.89
117.41
178.26
222.50
-
-
Appendix
333
Appendix III.q. Average concentrations of GDGTs (1, 2, 3 ,4’), normalised to dry weight of sediment and total organic carbon, with statistical data for estimation of error.
Sample
ID
Depth /
m
GDGT-1
Mean μg g-1
% SD
(n-1)
(n-1)*SD
Mean μg g-1
% SD (n-1)
(n-1)*SD
Mean μg g-1
% SD
(n-1)
(n-1)*SD
Mean μg g-1
(n-1)
(n-1)*SD2
126.5
f536
20
2.3
1
5.3
2.0
1
4.2
4.6
1
21.3
DW
3.1
11.2
1
f537
13.74
9.3
1858.2
6.4
1
40.7
5.9
1172.0
3.0
1
9.2
2.8
566.5
6.5
1
42.2
3.1
618.6
0.7
1
0.5
f538
10.84
12.6
2030.1
1.4
1
1.9
7.8
1249.9
0.2
1
0.0
3.9
633.4
5.2
1
27.2
4.4
706.0
14.3
1
205.4
f539
7.84
14.4
1942.1
3.1
1
9.4
8.6
1160.8
3.9
1
15.4
4.5
609.9
7.5
1
55.8
4.8
641.5
19.8
1
393.3
f541
f232
f218
4.11
2.75
1.55
7.5
4.0
1049.8
1401.0
1.7
4.7
1
1
2.8
21.8
4.6
2.5
641.4
870.5
0.0
9.4
1
1
0.0
87.4
2.2
0.9
310.7
301.3
11.4
37.5
1
1
129.5
1403.2
2.5
1.3
356.0
447.7
1.6
4.6
1
1
2.6
20.7
f215
1.25
2.5
908.6
6.4
1
40.8
1.9
680.1
3.9
1
15.4
0.4
146.6
0.1
1
0.0
0.3
109.6
24.2
1
587.6
f213
3.6
2007.3
2.8
1
8.0
2.8
1580.0
2.2
1
4.9
0.4
245.0
5.3
1
27.6
0.2
88.5
13.1
1
172.5
f209
1.05
0.75
2.3
1962.0
0.5
1
0.3
1.7
1409.7
0.0
1
0.0
0.3
234.3
5.3
1
27.8
0.1
100.6
7.3
1
53.2
f202
0.425
2.1
1646.2
1.8
1
3.4
1.3
1035.0
2.7
1
7.5
0.2
131.7
1.9
1
3.7
0.1
110.1
3.9
1
15.4
f199
0.275
0.7
610.5
2.7
1
7.5
0.4
359.4
4.2
1
17.3
0.1
114.1
3.2
1
10.3
0.1
109.5
1.3
1
1.7
f554
0.22
2.3
715.6
1.9
1
3.7
1.6
508.9
3.8
1
14.7
0.7
213.2
11.4
1
129.8
1.3
395.6
1.7
1
3.0
f197
0.19
0.2
103.0
12.9
1
165.7
0.2
82.7
29.0
1
843.1
0.1
38.2
32.0
1
1026.5
0.1
49.6
8.4
1
70.7
f556
0.16
0.6
182.0
6.6
1
44.2
0.4
136.6
2.2
1
4.7
0.2
67.4
5.0
1
25.5
0.3
83.2
13.8
1
191.8
f558
0.1
2.4
1047.4
3.2
1
10.1
1.9
833.5
0.2
1
0.0
0.9
392.6
1.7
1
3.0
1.2
504.8
3.1
1
9.4
f559
0.05
2.2
496.5
2.6
1
6.6
1.7
381.1
2.2
1
5.0
0.8
182.1
0.6
1
0.4
1.0
230.9
6.6
1
44.0
f560
0.005
3.1
887.9
6.9
1
47.5
2.2
623.7
4.4
1
19.3
1.1
312.7
1.1
1
1.2
1.3
380.3
11.1
1
124.2
f561
-0.07
1.3
377.4
4.4
1
19.0
1.0
280.4
10.4
1
107.4
0.4
119.5
4.9
1
24.3
0.6
163.7
6.7
1
44.6
f175
-0.18
2.6
952.8
3.7
1
13.4
1.5
561.1
1.3
1
1.6
0.8
301.7
0.9
1
0.7
0.9
337.0
3.7
1
13.9
339.3
1.1
1
1.2
1.0
202.9
3.6
1
13.3
0.5
99.2
7.2
1
51.3
0.6
118.8
8.8
1
78.2
f170
-0.27
-0.355
1.6
1.8
565.9
1.4
1
1.8
1.1
357.2
7.3
1
52.6
0.6
179.2
3.8
1
14.3
0.6
208.0
2.9
1
8.6
f168
-0.44
1.0
207.4
5.3
1
28.0
0.6
123.7
2.6
1
6.8
0.3
61.7
0.8
1
0.6
0.3
71.9
6.7
1
44.8
f165
-0.545
1.2
270.0
1.3
1
1.7
0.7
158.4
0.6
1
0.3
0.4
83.1
3.2
1
10.2
0.4
99.1
5.6
1
31.6
-0.7
-1.15
1.8
358.1
1.9
1
3.8
1.2
228.3
6.0
1
36.4
0.6
112.5
2.0
1
3.8
0.6
112.6
19.6
1
386.0
5.5
1306.2
0.0
3.6
845.9
0.0
1.7
408.0
0.0
1.8
424.4
Sum
0
24
488.6
Sum
0
24
1266.5
Sum
0
24
3040.4
TOC
508.5
% SD
DW
2.7
f562
TOC
451.3
GDGT-4'
2
DW
5.5
f161
TOC
913.9
GDGT-3
2
DW
8.3
f172
TOC
1360.0
GDGT-2
2
Sum
0
0.0
24
2630.1
4.51
Pooled SD
7.26
Pooled SD
11.26
Pooled SD
10.47
mean SD
3.62
mean SD
4.38
mean SD
6.79
mean SD
8.38
Appendix
334
Pooled SD
Appendix III.r. Average concentrations of GDGTs (0, cren, bGDGT-1), normalised to dry weight of sediment and total organic carbon, with statistical data for estimation of error.
GDGT-0
Sample ID Depth / m
Mean μg g-1
% SD (n-1) (n-1)*SD
% SD (n-1)
(n-1)*SD
Mean μg g-1
TOC
493.0
% SD
(n-1)
(n-1)*SD2
f536
20
3.4
1
11.6
0.0
1
0.0
6.8
1
46.44
f537
13.74
50.7 10083.8
0.4
1
0.2
87.7
17445.1
4.0
1
16.2
3.5
702.3
3.7
1
13.35
f538
10.84
72.0 11575.4
0.6
1
0.4
116.8
18785.2
2.5
1
6.3
4.4
700.7
2.8
1
7.91
f539
7.84
83.3 11197.3
10.2
1
104.2
145.2
19512.1
0.3
1
0.1
4.7
625.1
8.1
1
65.02
f541
f232
f218
4.11
2.75
1.55
41.8 5846.0
41.7 14588.4
2.1
21.2
1
1
4.3
451.0
71.0
42.8
9918.2
14981.6
7.8
3.9
1
1
61.4
15.0
2.6
0.8
356.4
297.4
0.4
-
1
0
0.14
-
f215
1.25
33.5 12301.8
6.7
1
45.0
10.2
3730.9
4.8
1
22.7
0.4
144.1
1.6
1
2.43
f213
45.1 25081.6
5.0
1
25.2
6.0
3312.1
3.6
1
12.8
0.2
122.5
1.6
1
2.42
f209
1.05
0.75
37.3 31515.6
0.2
1
0.0
3.8
3209.8
1.9
1
3.7
0.1
119.6
1.2
1
1.42
f202
0.425
48.2 38292.7
0.8
1
0.6
4.3
3412.9
2.5
1
6.2
0.1
118.5
24.9
1
621.04
f199
0.275
18.3 15101.6
1.6
1
2.5
4.4
3620.8
1.2
1
1.4
0.2
165.7
3.8
1
14.56
f554
0.22
10.2
3170.3
2.4
1
5.6
24.4
7581.9
0.3
1
0.1
1.3
401.0
4.8
1
23.04
f197
0.19
2.2
1118.4
17.8
1
315.8
2.0
1017.3
13.9
1
193.5
0.2
96.7
10.0
1
99.60
f556
0.16
2.6
842.2
3.2
1
10.2
5.6
1799.0
0.1
1
0.0
0.3
105.9
1.5
1
2.14
f558
0.1
10.5
4529.0
1.1
1
1.2
23.9
10336.9
1.0
1
1.0
1.4
615.6
1.1
1
1.30
f559
0.05
9.5
2113.3
1.1
1
1.1
22.8
5068.6
3.3
1
11.1
1.2
265.1
0.3
1
0.12
f560
0.005
14.3
4098.7
5.9
1
34.8
31.5
9022.2
12.8
1
164.7
1.5
429.7
6.5
1
41.78
f561
-0.07
6.6
1869.9
4.3
1
18.9
13.9
3959.6
2.2
1
5.0
0.8
215.1
0.3
1
0.09
f175
-0.18
16.3
5986.2
3.4
1
11.6
26.7
9831.4
1.9
1
3.6
1.6
599.2
2.0
1
3.90
2076.4
0.0
1
0.0
16.4
3451.3
1.1
1
1.2
1.1
225.6
0.7
1
0.53
f170
-0.27
-0.355
9.9
11.6
3755.4
1.3
1
1.7
18.5
5977.3
0.6
1
0.4
1.0
335.6
4.5
1
20.40
f168
-0.44
6.3
1339.8
3.4
1
11.4
10.2
2177.7
0.0
1
0.0
0.6
123.1
6.5
1
42.51
f165
-0.545
7.5
1758.3
0.8
1
0.7
12.3
2875.8
0.1
1
0.0
0.7
175.8
2.0
1
4.07
-0.7
-1.15
11.2
2207.3
0.2
1
0.0
18.7
3675.1
0.2
1
0.0
1.1
219.9
1.7
1
2.78
32.4
7721.2
0
0.0
58.6
13945.0
0
0.0
3.0
718.1
-
0
-
Sum
24
1057.9
Sum
24
526.5
23
1017.0
f562
TOC
13106.3
bGDGT-I
2
DW
3.0
f161
TOC
6682.7
Mean μg g-1
DW
79.6
f172
DW
40.6
Crenarchaeol
2
Sum
-
6.64
Pooled SD
4.68
Pooled SD
6.65
mean SD
4.04
mean SD
2.92
mean SD
4.20
Appendix
335
Pooled SD
Appendix III.s. Quantification of polar compounds (sterols and hopanols), normalised to dry weight of sediment.
-1
ng g / DW
C30:0
22, 29,30trisnorhopan-21-one
30-norhopan-22one
25.64
32.35
22.75
1.28
13.11
7.32
17.94
10.95
0.00
20.78
0.00
4.97
13.97
7.61
47.82
2.17
9.82
25.44
45.46
32.92
125.55
11.69
16.90
63.73
0.00
1.08
2.12
27.63
13.62
2.66
16.54
10.01
27.03
5.65
5.74
4.30
2.76
15.46
25.46
48.72
21.24
17.33
5.26
6.98
40.01
83.53
30.37
64.27
18.33
21.71
8.71
6.79
24.44
51.81
114.88
95.40
179.56
161.14
346.69
50.86
94.02
45.95
94.25
50.37
88.42
2.02
3.39
5.50
16.43
42.91
2.15
32.73
53.53
17.88
11.57
11.75
16.26
41.21
45.05
29.11
25.33
24.53
9.94
8.31
8.38
2.41
11.77
f556
19.98
1.61
5.89
10.91
2.14
3.79
2.09
1.14
2.95
0.1
f558
0.05
f559
58.31
37.21
3.14
0.00
102.82
84.37
149.36
82.94
34.42
23.75
23.29
21.71
25.46
20.90
5.38
3.65
10.42
7.06
0.01
f560
42.55
0.11
142.14
68.69
0.00
40.01
0.00
1.17
3.98
-0.07
f561
85.40
0.00
0.00
25.24
8.86
2.77
5.50
1.32
3.01
-0.18
f175
267.30
0.00
0.00
24.59
10.50
6.29
19.48
2.26
4.62
-0.27
f172
37.84
0.00
0.00
37.22
7.00
3.35
4.01
1.08
2.51
-0.355
f170
48.72
0.00
31.31
18.19
3.90
3.17
5.13
2.01
3.65
-0.44
f168
64.13
0.00
28.07
8.39
4.98
0.00
3.24
1.87
3.83
-0.545
f165
92.27
0.00
22.15
10.95
0.00
0.00
0.00
2.61
5.11
-0.7
-1.15
f161
32.40
6.31
8.12
14.96
0.00
52.91
55.89
1.43
2.48
f562
68.29
0.00
170.59
500.97
54.91
283.31
107.57
2.62
5.82
Sample ID
Cholesterol
C27:0
C29:1
C29:0
C30:1
20
13.74
f536
f537
51.33
34.95
5.67
3.75
0.00
38.87
0.00
15.46
32.88
13.57
10.84
f538
66.74
3.60
41.32
18.11
7.84
f539
73.07
13.27
22.49
25.74
4.11
f541
213.14
7.91
28.14
2.75
f232
39.52
5.60
1.55
f218
11.99
56.99
1.25
f215
10.69
13.23
1.05
f213
0.75
f209
10.84
0.43
f202
0.28
f199
31.88
136.17
0.22
f554
0.19
f197
0.16
4-Me, 24-Et
Appendix
336
Dinosterol
Depth /m
Appendix III.t. Quantification of apolar compounds (low and mid-molecular weight n-alkanes), normalised to dry weight of sediment.
n-Alkanes ng g-1 / DW
Depth /m
Sample ID
C13
C14
C15
C16
C17
C18
C19
C20
C21
C22
C23
C24
20
13.74
f536
f537
0.30
0.36
0.00
0.09
0.06
0.22
0.00
0.42
0.12
0.63
1.08
3.29
2.19
5.75
2.69
7.81
2.50
5.87
2.96
4.99
3.01
4.90
2.70
3.92
10.84
f538
0.46
0.00
0.13
0.30
0.69
2.69
4.54
5.46
4.90
5.26
6.93
6.06
7.84
f539
0.11
0.00
0.03
0.03
0.29
1.07
1.17
1.33
1.35
1.45
1.55
1.26
4.11
f541
0.00
0.00
0.00
0.00
0.81
3.58
4.09
4.35
3.92
5.44
5.56
4.85
2.75
f232
0.08
0.01
0.33
14.51
118.40
161.33
56.96
16.62
5.35
4.10
3.76
3.24
1.55
f218
0.03
0.03
1.16
37.49
107.09
43.15
10.30
2.81
0.74
0.51
0.40
0.36
1.25
f215
0.34
0.21
1.41
88.38
589.20
557.11
170.91
40.47
11.06
11.31
6.74
4.04
1.05
f213
0.03
0.01
0.06
5.41
41.92
32.41
7.33
1.83
0.53
0.74
0.70
0.82
0.75
f209
0.00
0.00
1.03
40.84
96.74
56.96
16.36
11.15
1.85
1.01
0.95
0.88
0.43
f202
0.00
0.00
0.59
40.41
140.31
110.10
0.00
0.00
0.00
0.00
0.00
4.35
0.28
f199
0.00
0.00
0.00
5.31
47.60
58.38
26.55
22.60
6.55
5.37
2.96
3.07
0.22
f554
0.00
0.00
0.00
6.04
20.63
25.35
11.54
12.50
3.90
3.22
2.06
1.46
0.19
f197
0.08
0.41
20.58
272.28
453.80
245.58
57.47
22.93
7.71
8.19
5.14
4.41
0.16
f556
0.00
0.03
0.25
1.43
3.97
5.76
2.37
2.60
1.76
2.29
2.30
1.65
0.1
f558
0.03
0.01
0.02
0.22
0.87
2.05
1.33
1.49
0.60
0.71
0.32
0.30
0.05
f559
0.05
0.00
0.14
3.67
7.74
7.01
2.52
2.53
0.90
0.92
0.62
0.44
0.01
f560
0.24
0.08
0.43
0.47
9.52
16.41
15.81
25.08
21.07
24.23
18.21
14.73
-0.07
f561
0.00
0.00
0.00
0.00
0.89
4.63
6.50
7.87
7.90
10.48
11.64
8.73
-0.18
f175
0.00
0.29
19.40
99.24
155.66
94.84
28.00
5.02
1.00
0.78
1.02
0.98
-0.27
f172
0.00
0.00
0.00
8.19
42.54
55.14
46.35
20.29
2.82
1.11
0.59
0.53
-0.355
f170
0.00
0.65
32.48
148.02
190.88
116.30
51.40
33.11
21.83
18.03
14.87
11.91
-0.44
f168
0.00
0.52
10.34
69.33
144.00
71.60
37.75
19.18
8.14
5.09
3.80
2.76
-0.545
f165
0.00
0.32
11.87
78.11
117.18
49.75
7.16
2.38
0.78
0.82
0.57
0.33
-0.7
-1.15
f161
0.00
1.80
27.09
100.96
132.76
83.21
28.13
12.54
3.67
0.00
0.00
3.36
f562
0.00
0.00
1.58
5.39
20.37
27.20
9.98
10.09
7.04
11.26
13.26
10.59
Appendix
337
Appendix III.u. Quantification of apolar compounds (high-molecular weight n-alkanes, pristane and phytane, taraxer-14-ene), normalised to dry weight of sediment.
Alkanes ng g-1 / DW
Depth /m Sample ID
C25
C26
C27
C28
C29
C30
C31
C32
C33
C34
pristane
phytane
Taraxer-14-ene
f536
f537
3.08
4.14
1.91
2.91
3.99
5.15
2.40
2.84
6.28
7.11
2.05
2.45
5.36
5.34
0.92
1.47
1.63
1.79
0.00
0.86
0.00
0.00
3.19
5.16
5.69
0.89
10.84
f538
7.07
5.12
9.26
5.13
13.61
4.86
11.83
2.53
4.61
1.35
0.00
9.69
3.12
7.84
f539
1.59
1.07
1.97
1.03
2.71
0.87
1.93
0.49
0.68
0.15
1.78
7.85
0.65
4.11
f541
4.08
2.38
3.01
1.58
3.60
0.93
2.01
0.30
0.53
0.27
5.00
20.66
0.61
2.75
f232
2.62
1.13
1.48
0.63
1.25
0.43
0.81
0.25
0.33
0.12
201.59
316.78
0.17
1.55
f218
0.38
0.17
0.25
0.12
0.16
0.12
0.08
0.00
0.00
0.00
169.09
253.01
0.03
1.25
f215
4.23
3.35
4.43
3.19
4.12
2.25
3.37
0.00
3.58
0.00
201.59
307.67
0.12
1.05
f213
0.81
0.42
0.53
0.31
0.49
0.19
0.34
0.13
0.09
0.12
181.07
303.14
0.05
0.75
f209
0.74
0.61
0.53
0.50
0.58
0.38
0.48
0.35
0.39
0.34
444.28
446.80
0.00
0.43
f202
2.98
1.74
1.27
1.20
0.00
0.00
0.00
0.00
0.00
0.00
0.28
f199
2.21
1.77
1.42
1.20
2.16
1.18
1.88
1.42
1.89
1.49
148.13
85.28
221.23
249.47
0.00
0.00
0.22
f554
1.32
0.86
1.02
0.72
1.01
0.49
0.96
0.58
0.86
0.45
37.23
149.57
0.12
0.19
f197
5.29
2.29
4.03
1.88
4.09
1.98
3.16
1.54
0.00
0.00
445.42
596.96
0.14
0.16
f556
1.34
1.06
1.06
0.66
1.03
0.64
0.77
0.38
0.44
0.24
8.40
44.69
0.05
0.1
f558
0.21
0.11
0.11
0.06
0.12
0.05
0.09
0.05
0.07
0.04
0.05
f559
0.35
0.20
0.20
0.09
0.20
0.08
0.14
0.10
0.14
0.00
9.72
13.73
63.44
55.12
0.26
0.32
0.01
f560
9.75
4.78
3.51
1.83
4.02
1.76
4.02
1.22
2.58
0.00
7.04
50.65
0.17
-0.07
f561
6.84
4.44
5.63
3.49
5.44
1.87
3.44
0.69
2.12
0.00
3.47
35.07
0.89
-0.18
f175
1.33
0.67
1.14
0.54
1.12
0.34
0.79
0.19
0.27
0.00
148.48
240.02
0.04
-0.27
f172
0.41
0.45
0.80
0.66
1.02
0.47
0.81
0.32
0.27
0.00
47.05
120.01
0.04
-0.355
f170
8.40
5.11
4.59
1.87
3.74
1.11
2.35
0.27
1.08
0.00
312.13
374.61
0.19
-0.44
f168
2.55
1.95
2.60
1.12
2.81
0.78
1.95
0.00
0.96
0.00
203.87
289.51
0.08
-0.545
f165
0.38
0.21
0.51
0.20
0.74
0.27
0.52
0.21
0.26
0.00
184.74
242.95
0.03
-0.7
-1.15
f161
2.64
1.51
3.43
1.94
3.98
1.51
2.90
1.00
1.45
0.00
272.51
331.99
0.13
f562
7.01
3.73
4.52
2.15
5.28
1.58
3.62
0.66
1.42
0.00
36.06
169.87
0.58
Appendix
338
20
13.74
Appendix III.v. Quantification of acid compounds (low and mid-molecular weight n-alkanoic acids), normalised to dry weight of sediment.
n-alkanoic acids ng g-1 / DW
Depth /m Sample ID
C12
C13
C14
C15
C16
C17
C18
C19
C20
C21
C22
C23
C24
20
13.74
f536
f537
0.00
0.00
4.04
11.63
14.59
26.45
13.69
18.71
132.34
201.91
13.77
15.26
84.99
112.10
6.40
8.36
10.95
15.09
7.44
9.90
19.97
31.32
8.02
10.87
13.16
18.67
10.84
f538
0.00
3.53
13.86
13.98
257.07
14.88
155.30
9.06
17.86
11.23
38.06
12.46
23.39
7.84
f539
0.00
0.00
0.00
0.17
36.67
1.42
272.91
1.69
3.59
3.28
8.05
3.06
6.13
4.11
f541
0.00
0.00
0.00
0.53
11.89
1.78
8.45
1.80
3.22
2.63
4.95
3.20
6.95
2.75
f232
0.00
12.48
52.71
30.44
234.92
22.42
74.45
12.77
19.65
17.51
41.20
17.39
26.02
1.55
f218
0.00
0.12
4.48
4.94
127.57
6.26
47.09
3.80
5.40
4.11
4.85
3.38
4.64
1.25
f215
0.00
0.22
6.48
6.96
777.18
10.59
182.72
1.88
4.12
3.80
11.86
2.83
6.33
1.05
f213
0.00
0.04
3.12
4.22
187.85
6.16
60.00
2.05
3.97
4.06
8.02
2.44
3.40
0.75
f209
0.00
0.00
5.21
7.83
190.79
10.67
63.41
7.06
12.18
10.71
16.78
8.11
11.86
0.43
f202
0.00
2.21
49.95
34.83
698.83
23.49
349.36
11.51
20.88
19.21
33.99
14.97
21.34
0.28
f199
2.39
4.06
40.96
25.84
476.35
17.07
203.61
10.63
19.92
19.49
35.41
14.61
18.78
0.22
f554
0.00
0.00
1.09
1.93
462.41
3.03
357.59
2.44
4.41
4.29
9.54
3.69
6.81
0.19
f197
21.42
15.31
116.37
50.13
584.91
25.44
93.89
14.42
20.91
19.21
32.90
16.24
26.40
0.16
f556
0.00
0.00
0.00
0.00
1.70
0.42
2.50
0.50
0.99
0.88
1.63
1.19
2.64
0.1
f558
0.00
2.21
13.55
12.46
143.30
10.67
84.38
7.44
11.36
11.53
19.64
9.38
11.88
0.05
f559
0.00
0.68
4.81
4.50
44.18
4.07
28.73
2.90
4.70
4.96
8.28
3.92
5.28
f560
0.00
0.00
0.00
0.00
12.97
5.16
45.21
7.71
20.42
22.24
50.01
22.10
35.55
f561
0.00
0.00
1.22
1.80
33.91
2.47
26.86
1.59
2.26
2.43
3.27
2.12
2.53
-0.18
f175
0.00
0.00
1.55
2.85
40.98
8.85
69.92
7.38
16.30
5.17
14.18
1.99
3.25
-0.27
f172
0.00
0.00
0.00
0.00
4.74
1.68
10.33
1.84
4.31
2.55
7.76
4.02
10.25
-0.355
f170
0.00
0.00
0.25
0.54
12.19
1.10
9.77
0.56
1.34
0.40
1.35
0.25
0.46
-0.44
f168
0.00
0.00
0.00
0.00
0.06
0.04
0.17
0.03
0.06
0.04
0.09
0.04
0.07
-0.545
f165
0.00
0.00
0.00
0.00
1.69
0.92
6.87
0.00
2.18
0.89
1.87
1.12
2.98
-0.7
-1.15
f161
0.00
0.00
0.00
0.00
0.04
0.00
0.06
0.00
0.02
0.00
0.00
0.00
0.03
f562
0.00
0.00
0.00
0.00
3.99
0.81
5.11
1.15
2.06
2.22
5.04
2.53
6.45
Appendix
339
0.01
-0.07
Appendix III.w. Quantification of acid compounds (high-molecular weight n-alkanoic acids), normalised to dry weight of sediment.
Depth /m Sample ID
C25
C26
C27
C28
C29
C30
C31
C32
C33
C34
20
13.74
f536
f537
5.98
7.98
9.77
13.95
4.46
5.90
16.83
24.83
4.69
6.48
19.84
28.57
3.40
4.23
12.25
15.03
0.00
0.00
2.77
3.50
10.84
f538
9.61
21.88
8.67
31.85
7.93
34.80
5.38
18.45
0.00
4.26
7.84
f539
2.46
5.17
1.71
6.78
1.48
8.84
0.00
0.00
0.00
0.00
4.11
f541
2.91
5.27
1.84
4.48
1.11
4.15
0.54
1.53
0.00
0.00
2.75
f232
14.72
80.50
9.71
28.05
6.83
23.42
4.45
15.01
0.00
6.05
1.55
f218
2.43
2.46
1.55
1.81
1.01
1.16
0.42
0.50
0.00
0.12
1.25
f215
2.00
2.74
1.04
2.05
0.68
1.58
0.37
0.79
0.00
0.24
1.05
f213
1.11
1.11
0.52
0.62
0.29
0.33
0.13
0.12
0.00
0.03
0.75
f209
5.65
6.27
3.45
4.12
1.75
2.18
0.78
0.90
0.00
0.00
0.43
f202
9.76
13.99
5.37
7.66
2.45
3.30
0.82
1.07
0.00
0.00
0.28
f199
9.23
11.08
4.84
6.22
2.32
2.96
0.73
1.12
0.34
0.45
0.22
f554
2.43
4.02
1.52
3.24
0.96
2.42
0.50
1.11
0.10
0.22
0.19
f197
10.67
18.03
6.29
8.82
3.27
4.91
1.08
1.64
0.48
0.38
0.16
f556
1.01
1.52
0.50
0.89
0.27
0.65
0.11
0.25
0.04
0.03
0.1
f558
5.93
8.07
3.73
5.55
2.03
3.48
0.79
1.60
0.44
0.47
0.05
f559
2.38
3.36
1.39
2.26
0.66
1.41
0.28
0.49
0.13
0.09
0.01
f560
17.38
22.94
10.77
16.02
3.85
7.52
0.97
2.13
0.34
0.47
-0.07
f561
1.01
1.66
0.64
1.37
0.40
0.88
0.18
0.39
0.00
0.00
-0.18
f175
0.93
1.97
1.62
8.50
2.18
7.14
1.08
1.65
0.00
0.00
-0.27
f172
5.51
13.81
7.32
21.78
4.35
13.86
1.42
3.11
0.00
0.00
-0.355
f170
0.12
0.23
0.12
0.64
0.16
0.52
0.05
0.13
0.00
0.00
-0.44
f168
0.04
0.07
0.04
0.11
0.05
0.10
0.00
0.02
0.00
0.00
-0.545
f165
1.32
4.64
3.56
18.75
5.93
29.24
0.00
11.28
0.00
0.00
-0.7
-1.15
f161
0.00
0.03
0.00
0.05
0.00
0.05
0.00
0.00
0.00
0.00
f562
3.37
6.84
2.64
4.38
0.94
1.88
0.19
0.40
0.05
0.04
Appendix
340
Appendix III.x. Quantification of acid compounds (hopanoic acids), normalised to dry weight of sediment.
Hopanoic acids ng g-1 / DW
Depth /m Sample ID
C30 αβ
C30 ββ
C31 αβ
C31 βα
C31 ββ
C32 αβ
C32 βα
C32 ββ
C33 αβ
C33 βα
C33 ββ
C34 ββ
20
13.74
f536
f537
0.00
0.00
0.00
0.00
0.58
0.92
0.20
0.33
4.42
4.45
1.24
1.93
0.41
0.88
15.86
21.22
0.21
0.23
0.26
0.32
3.25
3.94
1.12
0.95
10.84
f538
0.00
0.00
0.92
0.23
7.88
2.11
1.04
23.57
0.29
0.36
4.51
1.22
7.84
f539
0.00
0.00
0.00
0.00
4.49
1.18
0.00
17.73
0.00
0.00
3.54
0.00
4.11
f541
0.00
0.00
0.15
0.12
0.65
0.20
0.16
2.20
0.00
0.00
0.45
0.00
2.75
f232
0.00
0.00
0.60
0.18
4.08
1.82
0.62
8.77
0.23
0.15
2.76
0.78
1.55
f218
0.00
0.00
0.20
0.08
1.35
0.33
0.11
3.59
0.06
0.04
0.70
0.25
1.25
f215
0.00
0.00
0.00
0.00
0.26
0.00
0.00
0.06
0.00
0.00
0.00
0.00
1.05
f213
0.00
0.00
0.00
0.00
1.20
0.15
0.03
4.13
0.00
0.00
0.38
0.00
0.75
f209
0.00
0.00
0.31
0.10
1.52
0.43
0.15
4.18
0.06
0.00
0.86
0.40
0.43
f202
0.00
0.00
0.23
0.09
1.24
0.33
0.17
3.51
0.06
0.04
0.90
0.41
0.28
f199
0.00
0.00
0.25
0.18
1.00
0.26
0.08
2.25
0.05
0.00
0.67
0.30
0.22
f554
0.00
0.00
0.54
0.00
2.09
0.80
0.00
5.56
0.00
0.00
1.35
0.22
0.19
f197
0.00
0.00
0.51
0.22
3.19
0.83
0.32
6.20
0.15
0.13
1.83
0.65
0.16
f556
0.00
0.00
0.09
0.00
0.21
0.09
0.00
0.43
0.00
0.00
0.11
0.00
0.1
f558
0.00
0.00
0.31
0.11
2.19
0.74
0.20
5.24
0.11
0.11
1.47
0.50
0.05
f559
0.00
0.00
0.11
0.03
0.91
0.21
0.09
1.86
0.05
0.03
0.58
0.31
0.01
f560
0.00
0.00
0.00
0.00
0.75
0.00
0.00
1.70
0.00
0.00
0.64
0.00
-0.07
f561
0.00
0.00
0.00
0.00
0.55
0.30
0.20
1.56
0.00
0.00
0.38
0.00
-0.18
f175
0.37
1.11
1.48
0.00
11.39
1.83
0.30
9.05
0.51
0.51
2.34
0.00
-0.27
f172
0.00
0.27
0.44
0.00
4.09
0.65
0.34
3.45
0.00
0.00
0.80
0.00
-0.355
f170
0.05
0.10
0.14
0.00
1.11
0.13
0.03
0.80
0.05
0.03
0.21
0.00
-0.44
f168
0.00
0.00
0.00
0.00
0.35
0.14
0.08
0.64
0.00
0.00
0.15
0.00
-0.545
f165
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-0.7
-1.15
f161
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
f562
0.00
0.00
0.00
0.00
0.15
0.00
0.00
0.22
0.00
0.00
0.03
0.00
Appendix
341
Appendix III.y. Raw δ13C values of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
δ13C n-alkanoic acids
Sample ID
C14
Depth / m
C15
C16
C17
C18
C19
C20
f536
20
-29.76
-28.89
-29.25
-29.29
-28.82
-28.87
-31.14
-30.95
-29.66
-29.74
-32.72
-32.09
-30.16
-30.62
f537
13.74
-29.17
-29.55
-28.96
-29.58
-29.09
-30.86
-29.94
-29.56
-29.32
-30.79
-30.65
-31.35
-30.99
-30.74
f538
10.84
-32.57
-32.49
-29.59
-28.93
-29.06
-28.92
-30.11
-30.33
-30.76
-30.59
-31.90
-31.25
-30.76
-30.34
f539
7.84
-
-
-28.64
-
-29.48
-29.09
-31.66
-30.72
-29.73
-29.82
-29.30
-31.94
-31.05
-30.58
f541
4.11
-
-
-
-
-28.64
-27.73
-
-
-27.20
-27.13
-
-
-29.97
-28.80
f232
2.75
-27.85
-27.51
-23.75
-25.14
-32.66
-33.32
-32.95
-31.06
-29.27
-29.24
-30.39
-32.00
-31.14
-32.10
f218
1.55
-29.51
-27.43
-29.26
-29.79
-32.17
-32.29
-31.36
-31.24
-30.03
-29.64
-32.44
-32.90
-30.04
-31.38
f215
1.25
-27.89
-29.61
-29.26
-31.59
-31.89
-32.21
-31.34
-31.66
-30.87
-28.93
-32.62
-
-30.60
-30.91
f213
1.05
-28.81
-28.71
-33.61
-29.42
-36.95
-34.65
-32.54
-33.08
-32.17
-30.48
-31.47
-31.86
-30.95
-32.07
-33.03
-27.35
-34.33
-30.68
-32.08
-32.23
-30.90
-30.92
-28.77
-31.02
-32.79
-32.06
-30.51
-30.12
-39.67
-
-31.98
-
-30.96
-
-31.06
-
-31.74
-
-30.07
-
f209
0.75
f202
0.43
-26.91
-26.83
-27.79
-27.37
-28.74
-29.12
-28.97
-28.47
-29.30
-30.57
-30.65
-32.14
-28.22
-26.77
f199
0.28
-26.59
-27.04
-27.53
-28.44
-30.09
-29.86
-29.48
-29.66
-29.99
-29.58
-32.23
-32.69
-32.07
-31.58
f554
0.22
-29.97
-28.71
-32.51
-28.37
-28.78
-28.70
-30.32
-29.63
-29.58
-29.44
-30.88
-31.08
-31.68
-31.51
f197
0.19
-29.03
-28.91
-30.31
-28.50
-32.31
-33.43
-29.48
-32.92
-29.06
-30.72
-32.37
-33.17
-31.63
-32.48
f556
0.16
-28.52
-28.54
-27.87
-27.97
-28.50
-28.34
-29.35
-29.58
-29.89
-28.99
-31.19
-31.00
-31.22
-31.08
f558
0.1
-29.37
-30.39
-29.66
-29.55
-28.91
-28.95
-29.46
-29.68
-29.55
-29.38
-32.06
-32.75
-31.42
-31.65
f559
0.05
-31.58
-29.52
-32.01
-32.46
-29.09
-28.98
-29.98
-29.28
-29.11
-29.11
-33.51
-32.77
-31.83
-31.76
f560
0.01
-
-
-26.58
-25.43
-
f561
-0.07
-27.28
-27.44
-25.95
-20.97
-28.87
-29.16
-30.57
-29.48
-30.06
-29.60
-32.31
-27.49
-30.40
-30.21
f175
-0.18
-22.01
-24.35
-27.39
-22.45
-25.41
-25.42
-28.82
-27.33
-26.99
-26.65
-29.51
-33.45
-31.08
-30.91
f172
-0.27
-
-
-
-
-25.08
-25.09
-
-
-24.30
-26.60
-
-
-
f170
-0.355
-
-
-
-
-28.26
-26.18
-
-
-29.05
-29.21
-
-
-29.03
-29.32
f168
-0.44
-
-
-
-
-27.72
-28.37
-27.78
-
-28.46
-27.39
-27.84
-27.75
-28.14
-26.92
f165
-0.545
-
-
-
-
-24.10
-28.36
-
-
-25.85
-26.37
-
-
-
-
f161
-0.7
-
-
-
-
-
-
-
-
-
-
-
-
-
-
f562
-1.15
-
-
-
-
-
-
-
-
-28.80
-29.29
-
-
-34.06
-29.53
-
-
-
-
-
-
-
-
-
-
342
Appendix
-32.83
Appendix III.z. Raw δ13C values of mid and high-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
δ13C n-alkanoic acids
Sample ID
C22
Depth / m
C24
C26
C28
C30
C32
C34
f536
20
-32.24
-31.94
-31.10
-30.72
-31.02
-30.41
-30.90
-31.01
-30.92
-30.69
-31.40
-31.13
-30.68
-31.25
f537
13.74
-31.97
-31.98
-31.07
-31.14
-31.01
-30.30
-31.01
-32.00
-31.21
-30.71
-31.44
-30.57
-30.72
-31.16
f538
10.84
-31.56
-31.41
-30.75
-31.05
-30.81
-30.50
-30.85
-31.03
-31.14
-30.69
-30.64
-30.90
-31.84
-31.60
f539
7.84
-33.08
-33.27
-30.69
-31.39
-29.20
-30.34
-29.38
-29.56
-30.37
-30.74
-30.80
-29.92
-30.45
-28.61
f541
4.11
-32.06
-29.82
-29.16
-28.63
-30.63
-30.00
-30.44
-30.06
-30.36
-31.74
-29.82
-30.76
-
-
f232
2.75
-34.10
-34.72
-32.83
-33.45
-32.24
-34.88
-30.89
-33.38
-31.14
-33.32
-30.92
-31.40
-33.53
-29.68
f218
1.55
-30.69
-31.35
-30.32
-30.38
-30.35
-30.04
-29.70
-29.35
-30.06
-30.66
-30.48
-30.75
-
-
f215
1.25
-31.76
-31.85
-30.76
-30.86
-30.79
-29.72
-28.74
-30.96
-30.05
-30.26
-30.08
-28.95
-30.34
f213
1.05
-31.75
-32.41
-31.34
-30.60
-30.22
-32.79
-30.29
-29.85
-29.82
-29.28
-28.65
-32.01
-
-
-32.48
-32.86
-29.68
-29.98
-34.99
-33.77
-30.22
-30.12
-28.08
-31.86
-29.49
-29.17
-
-
-33.30
-
-30.44
-
-31.88
-
-30.82
-
-30.70
-
-30.94
-
-
-
-
-
0.75
f202
0.43
-31.34
-31.80
-31.40
-32.12
-32.45
-32.46
-33.12
-33.41
-38.58
-34.62
-29.24
-30.76
f199
0.28
-34.09
-33.50
-32.78
-32.93
-32.32
-33.02
-32.96
-32.80
-34.57
-34.31
-30.79
-33.10
-
f554
0.22
-32.91
-32.75
-31.36
-31.24
-30.87
-30.57
-31.45
-29.65
-29.84
-30.01
-29.88
-29.93
-30.14
f197
0.19
-29.15
-30.01
-32.01
-32.53
-33.64
-33.69
-32.31
-32.66
-31.23
-31.86
-31.25
-30.69
-
-
f556
0.16
-31.43
-31.88
-30.60
-30.73
-30.46
-30.19
-30.04
-29.21
-29.08
-30.56
-28.94
-29.32
-30.16
-29.12
f558
0.1
-33.01
-33.28
-31.85
-32.07
-31.93
-31.78
-32.53
-32.43
-34.11
-30.30
-29.22
-27.31
-29.58
-31.80
f559
0.05
-32.86
-32.34
-
-
-31.83
-31.00
-30.89
-30.51
-30.98
-30.80
-28.42
-28.92
-28.48
-27.19
f560
0.01
-32.42
-32.43
-32.80
-29.79
-28.14
-32.64
-34.09
-31.86
-33.18
-32.54
-
-32.71
-
-
f561
-0.07
-
-
-29.49
-29.55
-29.03
-30.15
-28.98
-28.39
-28.92
-28.45
-26.93
-27.32
-
-
f175
-0.18
-31.81
-31.09
-32.90
-28.03
-26.28
-27.80
-29.65
-30.00
-29.96
-30.37
-30.18
-
-
-
f172
-0.27
-30.73
-30.22
-29.05
-30.78
-27.54
-28.26
-28.76
-28.84
-28.97
-27.82
-31.08
-31.19
-
-
f170
-0.355
-29.75
-
-
-32.25
-29.77
-30.86
-30.25
-29.02
-
-
f168
-0.44
-35.68
-33.61
-29.93
-29.29
-29.76
-29.41
-30.11
-30.23
-30.12
-29.97
-29.87
-30.27
-
-
f165
-0.545
-31.73
-30.44
-
-
-32.21
-29.15
-32.75
-29.94
-31.72
-30.25
-30.65
-30.21
-
-
f161
-0.7
-
-
-
-
-
-
-
-
-
-
-
-
-
-
f562
-1.15
-33.57
-32.73
-32.02
-31.14
-32.13
-32.42
-33.28
-33.17
-31.57
-31.39
-
-
-
-
-30.90
343
Appendix
f209
Appendix III.aa. Average δ13C values of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH. Standard deviations calculated for estimation of measurement error.
δ13C n-alkanoic acids
C14
C15
C16
C17
C18
C19
C20
Depth / m
mean
SD
0.62
0.03
0.04
mean
-31.05
0.13
mean
-29.70
0.05
mean
-32.40
SD
-29.32
mean
-28.85
mean
20
mean
-29.27
SD
f536
0.44
-30.39
0.33
f537
13.74
-29.36
0.27
-29.27
0.44
-29.98
1.25
-29.75
0.27
-30.05
1.04
-31.00
0.49
-30.86
0.17
f538
10.84
0.47
-28.99
0.09
-30.22
0.15
-30.68
0.12
-31.57
0.46
-30.55
0.30
7.84
0.06
-
-29.26
f539
-32.53
-
0.28
-31.19
0.06
-30.62
0.34
-
-
-
-28.18
0.64
-
-27.17
0.05
-
1.87
-
-30.81
4.11
0.67
-
-29.77
f541
-
-29.29
-29.38
0.83
f232
2.75
-27.68
0.24
-24.45
0.98
-32.99
0.46
-32.01
1.34
-29.25
0.02
-31.19
1.14
-31.62
0.68
f218
1.55
-29.90
0.27
1.37
-32.67
-31.50
0.08
0.23
-29.83
-32.05
0.08
0.23
-31.30
-30.42
0.37
1.65
-32.23
1.25
1.47
1.22
-29.53
f215
-28.47
-28.75
-32.62
0.33
-
-30.71
-30.76
0.95
0.21
f213
1.05
-28.76
0.07
-31.52
2.96
-35.80
1.63
-32.81
0.38
-31.33
1.20
-31.66
0.28
-31.51
0.79
f209
0.75
-29.97
2.87
-34.89
4.52
-32.10
0.13
-30.93
0.03
-30.28
1.31
-32.19
0.54
-30.23
0.24
f202
0.43
-26.87
0.06
-27.58
0.29
-28.93
0.27
-28.72
0.35
-29.94
0.90
-31.39
1.06
-27.50
1.03
f199
0.28
-26.81
0.32
-27.99
0.64
-29.98
0.17
-29.57
0.13
-29.78
0.29
-32.46
0.33
-31.82
0.35
f554
0.22
-29.34
0.89
-30.44
2.92
-28.74
0.05
-29.97
0.49
-29.51
0.10
-30.98
0.14
-31.59
0.12
f197
0.19
-28.97
0.08
-29.41
1.28
-32.87
0.79
-31.20
2.43
-29.89
1.18
-32.77
0.56
-32.06
0.61
f556
0.16
-28.53
0.02
-27.92
0.07
-28.42
0.11
-29.46
0.17
-29.44
0.63
-31.10
0.14
-31.15
0.10
f558
0.1
-29.88
0.72
-29.61
0.08
-28.93
0.03
-29.57
0.16
-29.47
0.12
-32.40
0.49
-31.54
0.16
f559
0.05
0.00
-33.14
0.05
-26.00
0.82
-
0.52
-
-31.80
-
0.49
-
-29.11
-
0.08
-
-29.63
-
0.32
-
-29.03
0.01
1.45
-
-32.24
f560
-30.55
-
-30.01
-
f561
-0.07
-27.36
0.12
-23.46
3.52
-29.01
0.21
-30.03
0.77
-29.83
0.33
-29.90
3.41
-30.30
0.13
f175
-0.18
1.65
-
0.01
-28.07
0.24
-31.48
-25.08
0.01
-
1.05
-
-26.82
-
3.49
-
-25.42
-0.27
-23.18
-
-24.92
f172
-25.45
1.62
-
2.79
-
-30.99
-
0.12
-
f170
-0.355
-
-
-
-
-27.22
1.47
-
-
-29.13
0.11
-
-
-29.17
0.21
f168
-0.44
-
-
-
-
-28.05
0.46
-27.78
-27.92
0.76
-27.79
f165
-0.545
-
-
-
-
-26.23
-
-
-26.11
-
0.86
-
-0.7
-
-
-
-
-
-
-
-
0.37
-
-27.53
-
f161
3.01
-
0.06
-
-
-
-
-
f562
-1.15
-
-
-
-
-
-
-
-
-29.05
0.34
-
-
-33.45
0.87
-28.64
SD
SD
SD
SD
344
Appendix
Sample ID
Appendix III.ab. Average δ13C values of mid and high-molecular weight n-alkanoic acids, corrected for BF3/MeOH. Standard deviations calculated for estimation of measurement error.
δ13C n-alkanoic acids
C22
C24
C26
C28
C30
C32
C34
Depth / m
mean
SD
mean
SD
mean
SD
mean
SD
mean
SD
mean
SD
mean
SD
f536
20
-32.09
0.21
-30.91
0.27
-30.71
0.43
-30.96
0.08
-30.80
0.16
-31.26
0.19
-30.97
0.40
f537
13.74
-31.97
0.01
-31.11
0.04
-30.65
0.51
-31.51
0.71
-30.96
0.35
-31.01
0.62
-30.94
0.31
f538
10.84
-31.48
0.10
-30.90
0.21
-30.65
0.22
-30.94
0.13
-30.92
0.32
-30.77
0.19
-31.72
0.17
f539
7.84
-33.17
0.13
-31.04
0.50
-29.77
0.81
-29.47
0.13
-30.56
0.26
-30.36
0.62
-29.53
1.31
f541
4.11
-30.94
1.58
-28.89
0.38
-30.31
0.44
-30.25
0.27
-31.05
0.98
-30.29
0.66
-
-
f232
2.75
-34.41
0.44
-33.14
0.44
-33.56
1.87
-32.13
1.76
-32.23
1.54
-31.16
0.34
-31.60
2.73
f218
1.55
1.25
-31.02
-31.81
0.46
0.06
-30.35
-30.81
0.04
0.07
-30.19
-30.26
0.22
0.76
-29.52
-29.85
0.25
1.57
-30.36
-30.15
0.42
0.15
-30.61
-29.51
0.19
0.80
-30.34
-
f215
f213
1.05
-32.08
0.47
-30.97
0.52
-31.50
1.82
-30.07
0.31
-29.55
0.38
-30.33
2.38
-
-
f209
0.75
-32.88
0.41
-30.03
0.38
-33.55
1.57
-30.39
0.38
-30.21
1.94
-29.87
0.95
-
-
f202
0.43
-31.57
0.33
-31.76
0.51
-32.46
0.01
-33.27
0.21
-36.60
2.80
-30.00
1.07
-
-
f199
0.28
-33.79
0.42
-32.85
0.11
-32.67
0.49
-32.88
0.11
-34.44
0.18
-31.95
1.63
-
-
f554
0.22
-32.83
0.11
-31.30
0.08
-30.72
0.22
-30.55
1.27
-29.92
0.12
-29.91
0.04
-30.14
f197
0.19
-29.58
0.61
-32.27
0.37
-33.67
0.03
-32.49
0.25
-31.54
0.44
-30.97
0.39
-
-
f556
0.16
-31.65
0.32
-30.66
0.09
-30.32
0.19
-29.62
0.59
-29.82
1.04
-29.13
0.27
-29.64
0.74
f558
0.1
-33.15
0.19
-31.96
0.16
-31.86
0.11
-32.48
0.07
-32.21
2.69
-28.27
1.35
-30.69
1.57
f559
0.05
-32.60
0.37
-
-
-31.41
0.59
-30.70
0.27
-30.89
0.13
-28.67
0.35
-27.84
0.92
f560
0.01
-32.43
0.01
-31.30
2.13
-30.39
3.18
-32.98
1.58
-32.86
0.45
-32.71
-
-
-
f561
-0.07
-
-
-29.52
0.04
-29.59
0.80
-28.69
0.41
-28.69
0.33
-27.12
0.28
-
-
f175
-0.18
-31.45
0.51
-30.46
3.44
-27.04
1.08
-29.83
0.25
-30.16
0.29
-30.18
-
-
-
f172
-0.27
-30.47
0.36
-29.92
1.23
-27.90
0.51
-28.80
0.06
-28.39
0.81
-31.13
0.08
-
-
f170
-0.355
-30.90
-29.75
-
-
-31.01
1.76
-30.56
0.43
-29.02
-
-
-
f168
-0.44
-34.64
1.46
-29.61
0.45
-29.59
0.25
-30.17
0.08
-30.04
0.11
-30.07
0.29
-
-
f165
-0.545
f161
-0.7
-31.08
-
0.91
-
-
-
-30.68
-
2.16
-
-31.35
-
1.99
-
-30.99
-
1.04
-
-30.43
-
0.31
-
-
-
f562
-1.15
-33.15
0.59
-31.58
0.63
-32.28
0.20
-33.23
0.08
-31.48
0.13
-
-
-
-
345
Appendix
Sample ID
Appendix III.ac. Raw peak areas for low molecular weight n-alkanoic acids, integrated from GC-C-IRMS chromatograms, for the purpose of weighting each compound in the calculation
of average δ13C value for a group of compounds.
n-alkanoic acid - peak areas [GC-C-IRMS]
Sample ID
Depth / m
C14
C15
C16
C17
C18
C19
C20
f536
20
0.981
1.239
1.332
1.71
17.371
22.364
1.802
2.289
13.185
17.097
0.876
1.127
1.944
2.472
f537
13.74
2.614
3.179
2.146
2.524
24.751
29.057
2.927
3.431
16.965
19.879
1.071
1.251
2.478
2.869
f538
10.84
2.514
2.404
2.209
2.22
33.784
33.257
3.053
2.941
26.918
26.58
1.532
1.514
3.613
3.571
f539
7.84
-
-
0.177
-
8.48
7.936
0.821
0.759
11.675
10.874
0.739
0.557
1.311
1.184
f541
4.11
-
-
0.961
0.921
-
-
0.678
0.656
-
-
0.399
0.399
2.75
15.034
-
f232
16.859
13.794
14.647
68.173
89.191
7.743
10.389
26.449
34.522
4.499
5.955
8.998
9.407
f218
1.55
1.017
1.079
2.058
2.006
50.262
51.436
3.555
3.549
26.009
26.588
2.084
2.063
3.818
3.7
f215
1.25
11.434
f213
1.05
2.319
4.161
2.79
8.625
2.575
5.022
3.659
117.683
59.133
101.284
57.575
6.943
4.414
5.779
4.171
28.052
17.941
24.269
16.395
2.958
2.802
2.702
4.999
3.994
4.37
3.588
0.623
0.432
1.272
0.93
45.487
30.094
2.595
1.69
19.281
11.877
2.062
1.137
0.409
-
0.689
-
30.237
-
1.724
-
11.926
-
1.168
2.371
-
1.79
21.432
27.168
0.916
2.155
2.076
1.575
2.744
2.562
2.713
2.397
5.286
4.703
14.536
1.192
1.257
1.693
1.792
18.99
18.547
1.567
1.526
2.789
2.724
27.324
2.25
2.004
4.697
4.672
-
27.46
0.339
0.368
-
-
-
0.193
0.306
0.32
3.51
3.61
0.155
0.16
0.37
0.378
4.341
2.324
3.247
7.375
5.786
0.666
0.467
1.965
1.312
0.618
0.466
-
-
0.432
0.392
-
-
-
-
6.608
7.219
-
-
4.082
4.281
-
-
0.353
0.618
-
1.56
1.311
0.226
1.982
1.616
0.268
0.234
0.446
0.387
-
0.591
-
0.783
-
-
-
0.416
-
-
-
-
-
-
-
-
-
-
0.424
0.551
0.528
-
-
0.277
0.261
0.75
f202
0.43
4.453
5.408
4.821
6.276
94.969
116.733
4.324
6.54
54.116
65.057
1.578
f199
0.28
2.633
2.53
2.244
2.128
41.47
40.011
1.916
1.826
21.766
20.817
0.945
f554
0.22
0.940
0.932
1.522
1.534
24.05
23.2
2.066
1.985
20.383
19.484
1.671
f197
0.19
16.802
4.847
20.183
5.53
100.803
81.126
6.067
7.795
20.982
15.362
f556
0.16
1.644
1.776
1.918
2.049
19.865
21.201
2.118
2.252
13.651
f558
0.1
2.153
2.049
2.229
2.074
27.25
26.523
2.265
2.203
f559
0.05
1.910
1.898
2.574
2.394
36.799
40.745
5.041
5.47
f560
0.01
-
-
-
-
-
-
f561
-0.07
0.290
0.278
0.321
0.327
4.937
4.895
f175
-0.18
0.265
0.22
0.194
0.237
5.594
f172
-0.27
-
-
-
-
f170
-0.355
-
-
-
-
f168
-0.44
-
-
-
f165
-0.545
f161
-0.7
-
-
-
f562
-1.15
-
-
-
Appendix
346
3.48
2.351
f209
Appendix III.ad. Raw peak areas for mid and high- molecular weight n-alkanoic acids, integrated from GC-C-IRMS chromatograms, for the purpose of weighting each compound in the
calculation of average δ13C value for a group of compounds.
n-alkanoic acid - peak areas [GC-C-IRMS]
Sample ID
Depth / m
C22
C24
C26
C28
C30
f536
20
3.636
4.769
2.659
3.37
2.21
2.759
f537
13.74
5.546
6.347
4.147
4.646
3.685
4.122
5.609
6.836
f538
10.84
8.149
8.06
6.498
6.264
7.939
8.066
10.026
12.165
f539
7.84
1.788
1.506
1.441
1.224
1.236
1.042
1.949
1.717
2.595
f541
4.11
0.406
0.461
0.728
0.744
0.662
0.68
0.724
0.739
f232
2.75
27.18
36.894
13.965
13.322
90.076
84.86
14.475
13.441
f218
1.55
3.485
3.547
3.673
3.534
1.677
1.557
1.569
f215
1.25
f213
1.05
7.607
4.943
6.462
4.263
5.852
3.648
4.797
3.142
3.743
2.361
2.808
1.819
4.804
1.794
f209
0.75
5.026
3.32
3.916
2.627
3.002
2.126
3.191
-
2.683
-
1.202
-
f202
0.43
7.388
8.39
4.65
5.356
2.654
f199
0.28
4.164
4.044
2.304
2.253
1.242
f554
0.22
4.303
3.843
3.697
3.29
f197
0.19
23.315
22.722
6.683
f556
0.16
2.186
2.361
2.731
f558
0.1
4.985
4.85
f559
0.05
9.244
9.425
f560
0.01
0.452
f561
-0.07
f175
5.655
5.748
C34
4.248
5.492
1.167
1.499
4.612
4.804
2.725
2.729
0.974
0.97
11.503
11.101
8.224
7.849
2.661
2.519
2.06
2.109
1.564
0.769
0.577
0.839
0.89
0.518
0.557
-
-
5.644
4.909
2.655
3.138
0.84
0.722
1.323
1.318
1.033
0.378
0.486
-
-
3.822
1.043
2.991
1.474
1.714
0.776
1.91
0.714
0.872
0.453
0.953
-
-
1.601
0.985
1.416
0.683
0.513
0.334
-
-
1.055
-
0.738
-
0.31
-
-
-
3.055
1.739
2.221
0.791
0.959
0.333
0.357
-
-
1.19
0.781
0.759
0.446
0.443
0.249
0.247
-
-
2.258
2.012
2.085
1.755
2.054
1.641
0.993
0.638
0.412
6.875
4.268
6.983
3.202
3.263
2.196
2.191
1.11
1.121
-
-
2.935
2.358
2.585
2.319
2.552
2.194
2.55
1.413
1.637
0.426
0.494
3.371
3.29
2.142
2.109
1.518
1.491
1.252
1.174
0.596
0.585
0.287
0.274
-
-
3.988
5.305
2.652
2.458
2.318
2.328
0.825
1.13
0.549
0.522
0.193
0.381
0.423
0.265
0.301
0.213
0.242
0.133
0.155
-
0.155
-
-
-
-
0.532
0.546
0.481
0.489
0.607
0.627
0.52
0.545
0.318
0.33
-
-
-0.18
1.751
1.165
0.314
0.222
0.383
0.223
1.908
1.081
2.003
0.95
1.092
-
-
-
f172
-0.27
0.218
0.211
0.315
0.305
0.476
0.468
0.947
0.945
0.773
0.779
0.266
0.254
-
-
f170
-0.355
0.175
-
-
0.329
0.379
0.347
0.386
-
0.236
-
-
f168
-0.44
0.726
0.649
0.811
0.691
1.353
1.189
3.634
3.113
0.822
3.8
2.384
1.974
-
-
f165
-0.545
f161
-0.7
0.637
-
0.669
-
-
-
0.227
-
0.278
-
0.901
-
1.017
-
1.923
-
1.79
-
1.251
-
1.108
-
-
-
f562
-1.15
0.691
0.614
0.936
0.916
1.027
1.018
0.726
0.735
0.413
0.433
-
-
-
-
Appendix
347
7.179
0.445
4.428
C32
Appendix III.ae. Table of n-1 values for n-alkanoic acid δ13C measurements.
n-alkanoic acid (n-1)
Sample ID
Depth / m
C14
C15
C16
C17
C18
C19
C20
C22
C24
C26
C28
C30
C32
C34
f536
20
1
1
1
1
1
1
1
1
1
1
1
1
1
1
f537
13.74
1
1
1
1
1
1
1
1
1
1
1
1
1
1
f538
10.84
1
1
1
1
1
1
1
1
1
1
1
1
1
1
f539
7.84
-
-
1
1
1
1
1
1
1
1
1
1
1
1
f541
4.11
-
-
1
-
1
-
1
1
1
1
1
1
1
-
f232
2.75
1
1
1
1
1
1
1
1
1
1
1
1
1
1
f218
1.55
1
1
1
1
1
1
1
1
1
1
1
1
1
-
f215
1.25
f213
1.05
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
-
f209
0.75
1
1
1
1
1
1
1
1
1
1
1
1
1
-
f202
0.43
2
2
2
2
2
2
2
2
2
2
2
2
2
-
f199
0.28
1
1
1
1
1
1
1
1
1
1
1
1
1
-
f554
0.22
1
1
1
1
1
1
1
1
1
1
1
1
1
-
f197
0.19
1
1
1
1
1
1
1
1
1
1
1
1
1
-
f556
0.16
1
1
1
1
1
1
1
1
1
1
1
1
1
1
f558
0.1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
f559
0.05
1
1
1
1
1
1
1
1
-
1
1
1
1
1
f560
0.01
-
-
-
-
1
-
-
1
1
1
1
1
-
-
f561
-0.07
1
1
1
1
1
1
1
-
1
1
1
1
1
-
f175
-0.18
1
1
1
1
1
1
1
1
1
1
1
1
-
-
f172
-0.27
-
-
1
-
1
-
-
1
1
1
1
1
1
-
f170
-0.355
-
-
1
-
1
-
1
-
-
-
1
1
-
-
f168
-0.44
-
-
1
-
1
1
1
1
1
1
1
1
1
-
f165
-0.545
-
-
1
-
1
-
-
1
-
1
1
1
1
-
f161
-0.7
f562
-1.15
-
-
-
-
1
-
1
1
1
1
1
1
-
Appendix
348
n = number of measurements made for calculation of mean δ13C value and standard deviation; i.e. if a measurement was made in duplicate, n = 2.
n-1 is used in the calculation of pooled standard deviation (pooled variance).
Appendix III.af. Table of (n-1)*SD2 values for n-alkanoic acid δ13C measurements.
n-alkanoic acid (n-1)*SD2
Sample ID
Depth / m
C14
C15
C16
C17
C18
C19
C20
C22
C24
C26
C28
C30
C32
C34
20
0.38
0.00
0.00
0.02
0.00
0.20
0.11
0.04
0.07
0.19
0.01
0.03
0.04
0.16
f537
13.74
0.07
0.19
1.57
0.07
1.08
0.24
0.03
0.00
0.00
0.26
0.50
0.12
0.38
0.09
f538
10.84
0.00
0.22
0.01
0.02
0.02
0.21
0.09
0.01
0.04
0.05
0.02
0.10
0.04
0.03
f539
7.84
0.00
0.00
0.08
0.44
0.00
3.48
0.11
0.02
0.25
0.65
0.02
0.07
0.39
1.71
f541
4.11
0.00
0.00
0.41
0.00
0.00
0.00
0.68
2.50
0.15
0.19
0.07
0.95
0.44
0.00
f232
2.75
0.06
0.96
0.21
1.80
0.00
1.31
0.46
0.19
0.20
3.49
3.10
2.37
0.12
7.44
f218
1.55
2.15
0.14
0.01
0.01
0.07
0.11
0.91
0.21
0.00
0.05
0.06
0.18
0.04
0.00
f215
1.25
f213
1.05
1.48
0.01
2.72
8.75
0.05
2.67
0.05
0.15
1.88
1.44
0.00
0.08
0.05
0.63
0.00
0.22
0.01
0.27
0.57
3.31
2.47
0.10
0.02
0.15
0.64
5.66
0.00
0.00
f209
0.75
8.21
20.42
0.02
0.00
1.71
0.29
0.06
0.17
0.15
2.45
0.14
3.76
0.89
0.00
f202
0.43
0.01
0.17
0.14
0.25
1.60
2.25
2.10
0.22
0.52
0.00
0.08
15.64
2.29
0.00
f199
0.28
0.10
0.41
0.03
0.02
0.09
0.11
0.12
0.18
0.01
0.24
0.01
0.03
2.67
0.00
f554
0.22
0.79
8.55
0.00
0.24
0.01
0.02
0.01
0.01
0.01
0.05
1.61
0.01
0.00
0.00
f197
0.19
0.01
1.63
0.63
5.91
1.39
0.32
0.37
0.37
0.13
0.00
0.06
0.19
0.15
0.00
f556
0.16
0.00
0.00
0.01
0.03
0.40
0.02
0.01
0.10
0.01
0.04
0.35
1.08
0.07
0.55
f558
0.1
0.52
0.01
0.00
0.02
0.02
0.24
0.03
0.04
0.03
0.01
0.01
7.24
1.82
2.47
f559
0.05
2.12
0.10
0.01
0.24
0.00
0.27
0.00
0.14
0.00
0.34
0.07
0.02
0.12
0.84
f560
0.01
0.00
0.00
0.00
0.00
0.67
0.00
0.00
0.00
4.53
10.11
2.48
0.20
0.00
0.00
f561
-0.07
0.01
12.37
0.04
0.59
0.11
11.61
0.02
0.00
0.00
0.63
0.17
0.11
0.08
0.00
f175
-0.18
2.73
12.16
0.00
1.11
0.06
7.79
0.01
0.26
11.86
1.17
0.06
0.09
0.00
0.00
f172
-0.27
0.00
0.00
0.00
0.00
2.64
0.00
0.00
0.13
1.51
0.26
0.00
0.66
0.01
0.00
f170
-0.355
0.00
0.00
2.17
0.00
0.01
0.00
0.04
0.00
0.00
0.00
3.09
0.18
0.00
0.00
f168
-0.44
0.00
0.00
0.21
0.00
0.57
0.00
0.74
2.13
0.20
0.06
0.01
0.01
0.08
0.00
f165
-0.545
0.00
0.00
9.08
0.00
0.14
0.00
0.00
0.83
0.00
4.67
3.95
1.08
0.10
0.00
f161
-0.7
-
-
-
-
-
-
-
-
-
-
-
-
-
-
f562
-1.15
0.00
0.00
0.00
0.00
0.12
0.00
0.76
0.35
0.39
0.04
0.01
0.02
0.00
0.00
349
SD = standard deviation
(n-1)*SD2 is used as a parameter in the calculation of pooled variance
Appendix
f536
III.ag. Weighted mean average δ13C values for groups of n-alkanoic acids : low molecular weight (δ13CLMW), mid-molecular weight (δ13CMMW) and high-molecular weight (δ13CMMW).
Estimate of measurement error for each group is given as the pooled standard deviation.
δ13C n-alkanoic acid groups : weighted mean
Sample ID
Depth / m
δ13CLMW (C14-C18)
δ13C
f536
f537
f538
f539
f541
f232
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
20
13.74
10.84
7.84
4.11
2.75
1.55
1.25
1.05
0.75
0.43
0.28
0.22
0.19
0.16
0.1
0.05
0.01
-0.07
-0.18
-0.27
-0.355
-0.44
-0.545
-29.22
-30.03
-29.85
-29.57
-27.77
-31.43
-31.37
-31.46
-34.61
-31.48
-29.26
-29.79
-29.10
-32.00
-28.81
-29.18
-29.11
-25.98
-29.29
-26.48
-25.22
-27.91
-28.00
-26.37
n
6
6
6
4
4
6
6
6
6
9
6
6
6
6
6
6
6
2
6
6
4
4
4
4
δ13CHMW (C26-C34)
Pooled SD
0.36
0.95
0.10
0.20
0.46
0.30
0.86
1.07
1.17
1.82
0.54
0.27
0.52
0.82
0.37
0.42
0.84
0.82
0.23
0.96
1.15
1.05
0.63
2.15
δ13C
-30.94
-31.10
-30.90
-30.06
-30.53
-33.20
-30.07
-30.00
-30.49
-31.82
-33.16
-32.95
-30.37
-32.73
-29.79
-31.68
-30.70
-31.95
-28.65
-29.72
-28.74
-30.49
-30.02
-30.88
n
10
10
10
10
8
10
8
9
8
12
8
8
9
8
10
10
10
7
8
7
8
5
8
8
δ13CMMW (C20-C24)
Pooled SD
0.29
0.52
0.21
0.75
0.64
1.82
0.29
0.96
1.52
1.35
1.50
0.86
0.65
0.32
0.65
1.52
0.53
2.07
0.50
0.66
0.48
1.28
0.20
1.57
f161
-0.7
-
-
-
-
-
-
f562
-1.15
-29.04
2
0.34
-32.44
6
0.15
δ13C
-31.30
-31.45
-31.09
-31.80
-29.56
-33.65
-30.69
-31.20
-31.57
-31.19
-28.89
-33.05
-31.99
-30.45
-31.12
-32.38
-32.33
-31.55
-29.84
-31.22
-30.14
-29.74
-31.05
-31.07
n
6
6
6
6
6
6
6
6
6
9
6
6
6
6
6
6
4
5
4
6
4
4
6
2
Pooled SD
0.27
0.10
0.22
0.36
1.05
0.53
0.61
0.14
0.61
0.35
0.69
0.32
0.11
0.54
0.20
0.17
0.26
1.50
0.10
2.01
0.91
0.21
1.01
0.91
-32.42
6
0.71
n = number of measurements which are used in the calculation of the weighted mean average value. Pooled SD = pooled standard deviation: the standard deviations calculated for each
compound measurement is pooled to provide an estimate of the total precision associated with the compound group weighted mean average δ13C value.
Appendix
350
Appendix
Appendix IV
Mid-Waipara River Column 2 (Paleocene) : Geochemical Data and
Statistical Information
List of Tables:
IV.a.
Sample preparation information.
IV.b.
Raw δ13C values and peak areas (from GC-C-IRMS chromatograms) of low-molecular
weight n-alkanoic acids, corrected for BF3/MeOH.
IV.c.
Raw δ13C values and peak areas (from GC-C-IRMS chromatograms) of mid and highmolecular weight n-alkanoic acids, corrected for BF3/MeOH.
IV.d.
Raw δ13C values and peak areas (from GC-C-IRMS chromatograms) of hopanoic acids,
corrected for BF3/MeOH.
IV.e.
Average δ13C values of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
Standard deviations calculated for estimation of measurement error.
IV.f.
Average δ13C values of mid and high-molecular weight n-alkanoic acids, corrected for
BF3/MeOH. Standard deviations calculated for estimation of measurement error.
IV.g.
Average δ13C values of hopanoic acids, corrected for BF3/MeOH. Standard deviations
calculated for estimation of measurement error.
IV.h.
Statistical information for low-molecular weight n-alkanoic acid δ13C measurements : (n-1)
and (n-1)*SD2, for calculation of pooled standard deviation.
IV.i.
Statistical information for mid and high-molecular weight n-alkanoic acid δ13C
measurements : (n-1) and (n-1)*SD2, for calculation of pooled standard deviation.
IV.j.
Statistical information for hopanoic acid δ13C measurements : (n-1) and (n-1)*SD2, for
calculation of pooled standard deviation.
IV.k.
Weighted mean average δ13C values for groups of n-alkanoic acids : low molecular weight
(δ13CLMW), mid-molecular weight (δ13CMMW) and high-molecular weight (δ13CMMW).
Estimate of measurement error for each group is given as the pooled standard deviation.
IV.l.
Table of raw isoprenoidal GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4,
crenarchaeol, GDGT-0)
IV.m.
Raw and mean TEX86 values, presented with standard deviations and other statistical
information (e.g. pooled standard deviation for datasets)
IV.n.
Raw and meanTEX86-derived SST estimates, presented with standard deviations and other
statistical information (e.g. pooled standard deviation for datasets)
IV.o.
Raw branched GDGT and crenarchaeol peak areas (separate crenarchaeol measurement for
BIT index calculation).
IV.p.
BIT indices, CBT and MBT ratios, pH and MAAT estimates.
351
Appendix IV.a. Sample preparation information.
Sample ID
Depth / m
Age / Ma
DW/g
TLE Fraction
androstane / μg
Hexadecanol / μg
n-C19 / μg
δ13C BF3MeOH
MW49
132.54
55.75
15.13
1
1.95
2.17
2.06
-43.32
MW48
132.07
55.78
15.34
1
1.95
2.17
2.06
-43.32
MW46
131.11
58.02
20.11
1
1.95
2.17
2.06
-43.32
MW 45
130.66
58.04
20.54
0.20
1.95
2.17
2.06
-43.32
MW43
129.53
58.10
15.45
0.20
1.95
2.17
2.06
-43.32
MW42
129.26
58.11
8.01
0.25
1.95
2.17
2.06
-43.32
MW40
128.38
58.16
15.10
0.33
1.95
2.17
2.06
-43.32
MW39
126.39
58.26
15.72
0.33
1.95
2.17
2.06
-43.32
MW38
125.24
58.31
15.65
1
1.95
2.17
2.06
-43.32
MW37
123.52
58.40
20.01
1
1.95
2.17
2.06
-43.32
MW35
121.15
58.52
20.44
1
1.95
2.17
2.06
-43.32
MW34
119.63
58.59
15.40
0.5
1.95
2.17
2.06
-43.32
MW33
117.93
58.68
15.03
1
1.95
2.17
2.06
-43.32
MW31
114.89
58.83
20.67
1
1.95
2.17
2.06
-43.32
MW29
110.08
59.07
20.11
1
1.95
2.17
2.06
-43.32
MW52
101.17
59.52
15.00
1
1.95
2.17
2.06
-43.32
1
1.95
2.17
2.06
-43.32
93.70
59.89
MW56
79.66
60.59
20.49
1
1.95
2.17
2.06
-43.32
MW57
70.42
61.05
14.95
1
1.95
2.17
2.06
-43.32
MW58
64.81
61.33
20.23
1
1.95
2.17
2.06
-43.32
MW60
62.23
61.46
15.29
1
1.95
2.17
2.06
-43.32
MW62
58.32
61.90
20.59
1
1.95
2.17
2.06
-43.32
352
Appendix
MW53
20.92
Appendix IV.b. Raw δ13C values and peak areas (from GC-C-IRMS chromatograms) of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
δ13C n-alkanoic acid
C14
Depth / m
Sample ID
Peak Area
MW63
58.32
MW62
62.23
MW60
64.81
MW58
70.42
MW57
79.66
MW56
93.70
MW53
101.17
MW52
110.08
MW29
114.89
MW31
117.93
MW33
C16
C17
C18
C19
C20
δ13C
Peak Area
δ13C
Peak Area
δ13C
Peak Area
δ13C
Peak Area
δ13C
Peak Area
δ13C
Peak Area
δ13C
-
-
0.70
-32.87
5.09
-29.34
1.42
-31.43
2.83
-29.15
0.80
-32.56
1.70
-30.96
0.15
-33.47
0.75
-33.72
5.69
-29.45
1.57
-31.35
3.13
-28.54
0.89
-31.73
1.89
-31.45
-
-
0.65
-36.79
5.30
-31.53
1.73
-33.10
3.31
-31.21
3.78
-34.95
3.88
-33.85
-
-
0.56
-36.77
4.70
-32.19
1.64
-33.79
3.51
-31.28
3.56
-34.54
3.67
-33.96
-
-
-
-
0.76
-30.81
0.28
-35.46
0.77
-29.62
0.30
-32.65
0.54
-31.75
-
-
-
-
0.59
-31.70
0.19
-39.50
0.60
-30.07
0.21
-31.83
0.36
-31.36
-
-
0.39
-33.06
4.23
-29.50
0.99
-31.35
3.18
-29.43
1.32
-32.65
3.04
-32.47
-
-
-
-
1.65
-29.14
0.39
-30.78
1.24
-29.60
0.53
-32.64
1.19
-32.38
-
-
-
-
0.27
-30.50
-
-
0.54
-29.60
-
-
0.57
-32.20
-
-
-
-
0.27
-32.82
-
-
0.52
-31.64
-
-
0.56
-33.23
-
-
0.91
-35.80
16.19
-35.10
2.88
-34.82
5.20
-32.57
1.35
-31.23
2.47
-33.01
-
-
0.83
-35.56
16.00
-35.36
2.89
-34.44
5.24
-32.66
1.33
-32.16
2.46
-32.58
-
-
0.29
-35.38
1.96
-30.68
0.65
-31.69
1.24
-29.52
0.36
-30.04
0.61
-31.59
-
-
0.29
-37.53
1.92
-31.16
0.64
-32.41
1.23
-28.50
0.35
-30.46
0.59
-30.80
-
-
0.33
-35.85
3.84
-32.16
1.11
-34.04
2.53
-30.88
1.01
-30.97
1.81
-32.89
-
-
0.29
-38.26
3.70
-32.33
1.07
-33.83
2.43
-30.47
1.04
-31.62
1.73
-32.56
-
-
-
-
0.58
-27.61
0.33
-30.19
1.05
-28.88
0.41
-27.86
0.90
-28.58
-
-
-
-
0.58
-28.11
0.33
-31.08
1.02
-27.69
0.41
-26.76
0.86
-27.59
-
-
-
-
1.05
-30.34
-
-
1.79
-27.93
0.88
-30.26
1.57
-30.14
-
-
-
-
1.02
-29.28
-
-
1.71
-28.09
0.77
-30.69
1.51
-29.81
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
353
Appendix
53.82
C15
119.63
MW34
121.15
MW35
123.52
MW37
125.24
MW38
126.39
MW39
128.38
MW40
129.26
MW42
129.53
MW43
130.66
MW45
131.11
MW46
132.07
MW48
132.54
MW49
-
-
-
-
0.47
-28.15
0.18
-26.62
0.50
-27.64
0.19
-28.93
0.39
-
-
-
-
0.69
-26.77
0.26
-27.71
0.75
-29.33
0.29
-28.59
0.62
-
-
-
-
0.43
-28.81
-
-
0.63
-28.93
-
-
-
-
0.53
-28.75
-
-
0.79
-30.84
0.20
-29.97
0.50
-
-
-
-
1.63
-25.99
0.39
-26.79
1.35
-27.14
0.50
-26.14
0.98
-
-
-
-
2.00
-26.18
0.48
-25.10
1.67
-27.18
0.61
-25.67
1.22
0.22
-28.08
0.28
-26.78
0.84
-28.68
0.42
-29.16
0.89
-27.60
0.43
-27.60
0.79
0.25
-26.81
0.32
-27.31
0.95
-28.98
0.50
-28.35
1.00
-27.41
0.48
-25.85
0.90
-
-
-
-
0.43
-30.97
-
-
0.70
-28.16
-
-
0.40
-
-
-
-
0.42
-26.51
-
-
0.57
-29.73
-
-
0.35
-
-
-
-
-
-
-
-
0.73
-24.92
0.36
-22.45
0.80
-
-
-
-
-
-
-
-
0.86
-26.38
0.42
-20.06
0.95
-
-
-
-
0.19
-22.28
-
-
0.63
-28.22
-
-
0.38
-
-
-
-
0.24
-28.66
-
-
0.69
-27.19
-
-
0.40
-
-
-
-
0.50
-26.53
-
-
0.39
-
-
-
-
0.84
-27.35
0.27
-22.73
0.53
-
-
-
-
1.32
-27.24
-
-
-
-
-
-
1.76
-
-
-
-
0.37
-25.16
-
-
-
-
-
-
0.56
-
-
-
-
-
-
-
-
0.24
-26.38
-
-
-
-
-
-
-
-
-
-
-
0.16
-28.91
-
-
-
0.23
-28.95
0.22
-30.76
4.15
-30.56
1.20
-30.75
3.90
-31.01
0.72
-31.33
1.70
0.15
-25.09
0.13
-32.83
2.84
-28.96
0.86
-30.69
2.61
-29.20
0.48
-30.23
1.13
-
-
-
-
-
-
-
-
0.40
-27.66
-
-
-
-
-
-
-
-
-
-
-
0.38
-29.15
-
-
-
-
-
-
-
-
-
-
-
0.49
-27.44
-
-
0.39
-
-
-
-
-
-
-
-
0.43
-28.88
-
-
0.34
0.36
Appendix
354
Appendix IV.c. Raw δ13C values and peak areas (from GC-C-IRMS chromatograms) of mid and high-molecular weight n-alkanoic acids, corrected for BF3/MeOH.
δ13C n-alkanoic acid
Depth /
m
Sample
ID
53.82
C22
C24
C26
C28
C30
C32
C34
Peak
Area
δ13C
Peak
Area
δ13C
Peak
Area
δ13C
Peak
Area
δ13C
Peak
Area
δ13C
Peak
Area
δ13C
Peak
Area
δ13C
MW63
2.33
2.56
-32.18
-31.91
2.16
2.40
-31.67
-31.09
1.40
1.57
-30.78
-31.44
0.91
1.03
-31.24
-30.23
-
-
-
-
-
-
58.32
MW62
7.40
6.96
-33.70
-33.32
4.73
4.43
-33.18
-33.47
3.34
3.12
-33.66
-33.65
2.48
2.32
-33.41
-33.12
-
-
-
-
-
-
62.23
MW60
0.87
0.67
-32.68
-32.65
0.60
0.47
-29.89
-30.26
0.35
0.27
-31.09
-32.17
0.27
0.21
-32.13
-32.75
-
-
-
-
-
-
64.81
MW58
8.48
3.33
-32.69
-32.43
8.18
3.25
-31.81
-31.85
7.15
2.86
-32.23
-32.11
4.55
1.80
-32.69
-32.23
2.69
0.99
-31.88
-31.35
1.37
0.53
-31.82
-31.48
-
-
70.42
MW57
1.52
1.50
-34.08
-33.28
1.07
1.07
-33.20
-32.83
0.82
0.81
-33.70
-32.78
0.84
0.84
-32.73
-31.23
0.41
0.41
-33.91
-33.55
-
-
-
-
79.66
MW56
4.64
4.64
-32.48
-32.38
4.06
4.06
-31.79
-31.88
3.12
3.08
-32.23
-32.68
2.27
2.21
-32.07
-32.90
1.33
1.29
-31.09
-32.03
0.74
0.69
-30.93
-31.23
-
-
93.70
MW53
1.01
0.98
-32.61
-32.44
0.75
0.73
-31.55
-31.46
0.57
0.56
-30.77
-31.69
0.39
0.38
-31.74
-31.19
0.24
0.23
-29.72
-32.72
-
-
-
-
101.17
MW52
3.75
3.60
-33.79
-33.56
2.10
2.02
-33.10
-33.41
1.54
1.48
-34.00
-33.97
1.19
1.15
-33.59
-33.02
0.56
0.54
-33.27
-34.31
0.25
0.25
-33.23
-32.75
-
-
110.08
MW29
1.04
1.00
-30.37
-30.41
1.12
1.05
-28.10
-27.54
1.24
1.19
-28.14
-29.03
1.73
1.66
-28.77
-28.76
1.86
1.78
-29.37
-29.66
-
-
0.36
0.35
-30.35
-29.90
114.89
MW31
3.36
3.23
-32.32
-32.27
3.59
3.45
-31.41
-31.32
3.25
3.09
-31.48
-31.48
2.48
2.35
-30.65
-30.71
2.08
1.98
-30.77
-30.45
1.64
1.62
-30.83
-30.96
0.66
0.62
-29.03
-30.03
17.93
MW33
-
-
-
-
-
-
-
-
-
-
-
-
-
Appendix
355
119.63
MW34
121.15
MW35
123.52
MW37
125.24
MW38
126.39
MW39
128.38
MW40
129.26
MW42
129.53
MW43
130.66
MW45
131.11
MW46
132.07
MW48
132.54
MW49
0.66
-30.16
0.65
-28.65
0.54
-29.74
0.55
-28.09
0.67
-29.72
0.35
-30.89
-
-
0.99
-31.26
0.98
-28.93
0.84
-30.08
0.84
-28.45
1.01
-29.02
0.56
-29.95
-
-
0.68
-30.68
0.75
-30.03
0.70
-30.66
0.57
-30.62
0.34
-30.69
0.36
-30.05
-
-
0.90
-31.69
0.96
-30.76
0.90
-31.83
0.73
-30.77
0.43
-30.71
0.47
-29.86
-
-
1.45
-28.79
1.46
-26.41
0.90
-26.70
0.80
-29.57
0.55
-30.01
0.39
-29.26
-
-
1.83
-28.06
1.83
-26.81
1.14
-26.97
1.01
-29.16
0.69
-30.36
0.49
-29.50
-
-
1.63
-30.06
1.55
-29.29
1.41
-29.71
1.08
-30.30
0.54
-32.40
0.46
-28.79
-
-
1.91
-29.91
1.77
-28.95
1.65
-29.74
1.28
-31.83
0.73
-30.08
0.55
-29.22
-
-
0.73
-31.31
1.18
-30.44
1.14
-30.86
0.60
-28.09
0.50
-29.10
-
-
-
-
0.63
-30.12
1.02
-30.93
0.99
-30.14
0.53
-28.91
0.45
-28.93
-
-
-
-
1.35
-22.09
1.86
-21.20
1.73
-24.15
2.06
-27.06
2.71
-28.45
2.15
-29.92
0.60
-28.59
1.61
-22.38
2.29
-21.63
2.20
-23.81
2.59
-27.29
3.56
-28.29
2.70
-29.44
0.75
-28.47
0.64
-30.81
0.54
-29.09
0.42
-31.11
0.32
-31.46
0.27
-28.53
0.26
-29.63
-
-
0.86
-30.99
0.68
-28.79
0.51
-29.78
0.40
-28.22
0.34
-29.67
0.32
-30.95
-
-
0.56
-27.72
0.65
-26.85
0.61
-27.89
0.54
-25.94
0.95
-28.01
0.46
-29.02
-
-
0.97
-27.10
1.12
-26.39
1.04
-28.67
0.91
-27.95
0.55
-27.80
0.81
-29.51
-
-
2.99
-28.27
3.37
-25.78
3.22
-28.46
2.73
-27.49
3.06
-28.28
2.68
-29.27
-
-
0.91
-28.01
1.06
-27.13
0.98
-28.73
0.91
-28.05
0.89
-29.27
0.71
-28.79
-
-
0.22
-28.60
0.34
-29.43
0.38
-30.39
0.49
-25.55
0.49
-28.19
0.50
-27.03
-
-
-
-
0.22
-28.81
0.25
-26.63
0.32
-28.03
0.31
-26.99
0.32
-30.27
-
-
1.43
-33.66
1.09
-33.79
0.69
-32.24
0.90
-33.62
1.16
-33.25
1.17
-34.55
-
-
0.88
-30.43
0.73
-29.86
0.45
-28.01
0.62
-29.24
0.74
-30.41
0.77
-31.52
-
-
0.27
-34.24
0.22
-31.18
-
-
-
-
-
-
-
-
-
-
0.25
-32.81
0.21
-33.77
-
-
-
-
-
-
-
-
-
-
0.56
-31.80
0.45
-32.59
0.34
-31.22
0.67
-28.81
0.34
-30.71
0.37
-28.52
-
-
0.48
-33.36
0.37
-29.92
0.27
-29.84
0.59
-28.17
0.30
-31.59
0.33
-28.09
-
-
Appendix
356
Appendix
Appendix IV.d. Raw δ13C values and peak areas (from GC-C-IRMS chromatograms) of hopanoic acids,
corrected for BF3/MeOH.
δ13C Hopanoic acids
Depth / m Sample ID
53.82
MW63
58.32
MW62
62.23
MW60
64.81
MW58
70.42
MW57
79.66
MW56
93.70
MW53
101.17
MW52
110.08
MW29
114.89
MW31
117.93
MW33
119.63
MW34
121.15
MW35
123.52
MW37
125.24
MW38
126.39
MW39
128.38
MW40
129.26
MW42
129.53
130.66
MW43
MW45
131.11
MW46
132.07
MW48
132.54
MW49
C30 ββ
C31 ββ
C32 ββ
Peak Area
0.72
δ13C
-31.92
Peak Area
4.17
δ13C
-29.91
Peak Area
0.95
δ13C
-33.34
0.80
-30.97
4.60
-29.90
1.04
-33.24
0.56
-33.17
3.48
-30.80
0.68
-31.62
0.20
-31.25
3.50
-30.98
0.63
-31.70
0.36
-31.24
0.86
-30.32
0.13
-30.52
0.29
-32.41
0.67
-29.90
0.01
-31.18
1.41
-30.94
5.10
-29.94
1.43
-30.31
0.55
-30.31
1.99
-29.61
0.55
-30.29
0.21
-30.87
0.46
-29.62
0.01
-28.91
0.21
-29.47
0.46
-28.35
0.01
-28.38
0.76
-31.37
2.42
-30.92
0.72
-29.22
0.75
-29.42
2.42
-30.33
0.71
-28.98
0.37
-28.32
1.11
-28.34
0.37
-31.06
0.37
-28.92
1.09
-28.53
0.36
-28.48
0.26
-30.34
0.56
-28.70
0.01
-28.97
0.24
-29.51
0.55
-29.04
0.01
-28.92
0.73
-29.96
2.27
-28.57
0.49
-31.06
0.63
-31.63
2.09
-28.63
0.45
-29.54
1.04
-30.63
3.10
-28.97
0.81
-30.22
1.00
-30.15
2.98
-29.09
0.78
-28.85
-
-
-
-
-
-
0.41
-31.50
1.49
-28.11
0.33
-29.73
0.61
-30.21
2.19
-28.42
0.47
-29.77
0.65
-29.07
2.05
-28.47
0.57
-30.65
0.85
-29.55
2.63
-28.21
0.73
-28.13
1.39
-31.64
3.77
-26.64
1.07
-27.49
1.70
-28.25
4.59
-27.32
1.29
-27.32
1.36
-27.03
4.58
-25.96
1.22
-26.35
1.59
-26.97
5.14
-26.23
1.37
-26.03
0.43
-25.51
1.31
-26.92
0.30
-29.14
0.37
-29.34
1.21
-26.82
0.26
-25.54
1.27
-26.29
3.43
-24.58
0.85
-25.83
1.61
-25.94
4.10
-24.80
1.00
-25.71
0.25
-26.97
0.74
-24.25
0.15
-24.49
0.33
-27.90
1.08
-24.47
0.23
-27.58
0.28
-25.52
0.85
-25.82
0.18
-26.91
0.48
0.82
-27.63
-28.82
1.58
5.24
-26.90
-25.67
0.37
1.34
-26.70
-25.97
0.45
-28.71
1.45
-25.56
0.36
-27.76
-
-
-
-
-
-
-
-
-
-
-
-
0.26
-31.06
2.18
-32.22
0.42
-34.79
0.21
-35.69
1.48
-29.23
0.29
-29.08
-
-
-
-
-
-
-
-
-
-
-
-
0.37
0.33
-28.12
-26.67
0.34
0.30
-30.46
-31.88
-
-
357
Appendix IV.e. Average δ13C values of low-molecular weight n-alkanoic acids, corrected for BF3/MeOH. Standard deviations calculated for estimation of measurement error.
δ13C n-alkanoic acids
Sample ID
Depth / m
MW63
C14
Mean
53.82
-33.47
MW62
58.32
MW60
C15
SD
Mean
-
-33.30
-
-
62.23
-
MW58
64.81
MW57
C16
SD
Mean
0.60
-29.39
-36.78
0.01
-
-
-
-
70.42
-
MW56
79.66
MW53
C17
SD
Mean
0.08
-31.39
-31.86
0.47
-
-31.26
-33.06
-
-
-
-
-
93.7
-
MW52
101.17
MW29
C18
SD
Mean
0.06
-28.84
-33.44
0.49
0.63
-37.48
-29.32
0.26
-
-31.66
-35.68
0.17
-
-36.46
-
-
110.08
-
MW31
114.89
MW34
C19
SD
Mean
0.43
-32.15
-31.24
0.05
2.85
-29.84
-31.06
0.40
1.64
-
-35.23
0.19
1.52
-30.92
-37.05
1.70
-
-
-
-
119.63
-
MW35
121.15
MW37
123.52
MW38
C20
SD
0.07
-31.20
0.35
-34.74
0.16
-33.91
0.07
0.31
-32.24
0.06
-31.55
0.28
-29.52
0.12
-32.64
0.56
-32.42
0.06
-
-30.62
1.44
-
-
-32.71
0.73
-34.63
0.27
-32.62
0.06
-31.70
0.01
-32.79
0.30
0.34
-32.05
0.51
-29.01
0.72
-30.25
0.00
-31.20
0.56
-32.24
0.12
-33.93
0.15
-30.67
0.29
-31.30
0.02
-32.73
0.23
-
-27.86
0.36
-30.63
0.62
-28.29
0.84
-27.31
0.00
-28.08
0.70
-
-
-29.81
0.75
-
-
-28.01
0.11
-30.47
0.08
-29.97
0.23
-
-
-
-27.46
0.97
-27.17
0.77
-28.49
1.19
-28.76
0.07
-28.40
0.89
-
-
-
-
-28.78
0.04
-
-
-29.89
1.35
-29.97
-
-30.25
0.70
-
-
-
-
-26.09
0.13
-25.95
1.19
-27.16
0.03
-25.91
0.08
-26.24
0.30
125.24
-27.44
0.89
-27.05
0.37
-28.83
0.21
-28.76
0.57
-27.51
0.14
-26.72
0.04
-27.36
0.87
MW39
126.39
-
-
-
-
-28.74
3.15
-
-
-28.94
1.12
-
-
-28.17
0.41
MW40
128.38
-
-
-
-
-
-
-
-
-25.65
1.03
-21.26
0.04
-22.31
0.18
MW42
129.26
-
-
-
-
-25.47
4.52
-
-
-27.70
0.73
-
-
-28.53
1.01
MW43r
129.53
-
-
-
-
-26.20
1.47
-
-
-26.93
0.48
-22.73
-
-26.78
0.71
MW45
130.66
-
-
-
-
-
-
-
-
-27.64
1.79
-
-
-
-
MW46
131.11
-27.02
2.73
-31.79
1.47
-29.76
1.13
-30.72
0.04
-30.11
1.28
-30.78
0.17
-29.40
1.93
MW48
132.07
-
-
-
-
-
-
-
-
-28.41
1.06
-
-
-
-
MW49
132.54
-
-
-
-
-
-
-
-
-28.16
1.02
-
-
-30.96
0.24
Appendix
358
SD
Mean
Appendix IV.f. Average δ13C values of mid and high-molecular weight n-alkanoic acids, corrected for BF3/MeOH. Standard deviations calculated for estimation of measurement error.
δ13C n-alkanoic acids
Sample ID Depth / m
C22
C24
C26
C28
C30
C32
C34
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
53.82
-32.05
0.19
-31.38
0.41
-31.11
0.47
-30.73
0.72
-
-
-
-
-
-
MW62
58.32
-33.51
0.27
-33.33
0.20
-33.65
0.00
-33.27
0.21
-
-
-
-
-
-
MW60
62.23
-32.67
0.02
-30.08
0.26
-31.63
0.76
-32.44
0.44
-
-
-
-
-
-
MW58
64.81
-32.56
0.18
-31.83
0.03
-32.17
0.09
-32.46
0.32
-31.61
0.37
-31.65
0.24
-
-
MW57
70.42
-33.68
0.57
-33.01
0.26
-33.24
0.65
-31.98
1.06
-33.73
0.25
-
-
-
-
MW56
79.66
-32.43
0.07
-31.83
0.06
-32.45
0.32
-32.48
0.59
-31.56
0.66
-31.08
0.21
-
-
MW53
93.7
-32.53
0.12
-31.51
0.06
-31.23
0.65
-31.46
0.39
-31.22
2.12
-
-
-
-
MW52
101.17
-33.67
0.16
-33.26
0.22
-33.99
0.02
-33.30
0.40
-33.79
0.74
-32.99
0.34
-
-
MW29
110.08
-30.39
0.03
-27.82
0.39
-28.59
0.63
-28.77
0.01
-29.51
0.20
-
-
-30.13
0.32
MW31
114.89
-32.29
0.04
-31.36
0.07
-31.48
0.00
-30.68
0.04
-30.61
0.22
-30.90
0.09
-29.53
0.70
MW34
119.63
-30.71
0.78
-28.79
0.20
-29.91
0.24
-28.27
0.25
-29.37
0.49
-30.42
0.67
-
-
MW35
121.15
-31.19
0.71
-30.40
0.52
-31.25
0.83
-30.70
0.11
-30.70
0.02
-29.96
0.13
-
-
MW37
123.52
-28.43
0.52
-26.61
0.28
-26.84
0.19
-29.36
0.29
-30.19
0.25
-29.38
0.16
-
-
MW38
125.24
-29.98
0.11
-29.12
0.25
-29.73
0.02
-31.06
1.08
-31.24
1.65
-29.01
0.31
-
-
MW39
126.39
-30.72
0.84
-30.68
0.34
-30.50
0.51
-28.50
0.58
-29.02
0.12
-
-
-
-
MW40
128.38
-22.23
0.21
-21.42
0.30
-23.98
0.25
-27.18
0.17
-28.37
0.12
-29.68
0.34
-28.53
0.08
MW42
129.26
-30.90
0.13
-28.94
0.21
-30.45
0.94
-29.84
2.29
-29.10
0.80
-30.29
0.93
-
-
MW43r
129.53
-27.78
0.50
-26.54
0.59
-28.44
0.38
-27.36
0.98
-27.91
0.65
-29.15
0.31
-
-
MW45
130.66
-28.60
-29.12
0.44
-28.51
2.66
-26.79
1.75
-27.59
0.85
-28.65
2.29
-
-
MW46
131.11
-32.04
2.28
-31.82
2.78
-30.12
2.99
-31.43
3.10
-31.83
2.01
-33.04
2.15
-
-
MW48
132.07
-33.52
1.01
-32.47
1.83
-
-
-
-
-
-
-
-
-
-
MW49
132.54
-32.58
1.10
-31.26
1.89
-30.53
0.98
-28.49
0.45
-31.15
0.62
-28.31
0.30
-
-
359
Appendix
Mean
MW63
Appendix
Appendix IV.g. Average δ13C values of hopanoic acids, corrected for BF3/MeOH. Standard deviations
calculated for estimation of measurement error.
δ13C Hopanoic acids
C30 ββ
C31 ββ
C32 ββ
Sample ID
Depth / m
Mean
SD
Mean
SD
Mean
SD
MW63
53.82
-31.441833
0.67
-29.903226
0.01
-33.287484
0.07
MW62
58.32
-32.210633
1.36
-30.890581
0.12
-31.659141
0.05
MW60
62.23
-31.826233
0.83
-30.111226
0.29
-30.850125
0.47
MW58
64.81
-30.62705
0.45
-29.774194
0.24
-30.297891
0.01
MW57
70.42
-30.1667
0.99
-28.983484
0.90
-28.644797
0.37
MW56
79.66
-30.395583
1.38
-30.627871
0.42
-29.103188
0.17
MW53
93.7
-28.6198
0.43
-28.436903
0.14
-29.766797
1.82
MW52
101.17
-29.9249
0.58
-28.869935
0.24
-28.944891
0.04
MW29
110.08
-30.794967
1.18
-28.601032
0.04
-30.299953
1.08
MW31
114.89
-30.38835
0.34
-29.026839
0.09
-29.534766
0.97
MW34
119.63
-30.852833
0.91
-28.261419
0.22
-29.750297
0.02
MW35
121.15
-29.308
0.34
-28.340903
0.19
-29.388844
1.78
MW37
123.52
-29.947117
2.40
-26.980387
0.48
-27.407297
0.12
MW38
125.24
-27.00005
0.04
-26.093161
0.19
-26.188875
0.23
MW39
126.39
-27.423717
2.71
-26.869419
0.06
-27.339234
2.54
MW40
128.38
-26.115
0.25
-24.690839
0.16
-25.769156
0.08
MW42
129.26
-27.43715
0.66
-24.363097
0.15
-26.034188
2.19
MW43r
129.53
-27.673783
1.53
-25.988387
0.62
-26.833922
0.74
MW45
130.66
-
-
-
-
-
-
MW46
131.11
-33.377267
3.27
-30.723871
2.11
-31.935
4.04
MW48
132.07
-
-
-
-
-
-
MW49
132.54
-27.39065
1.03
-31.170839
1.00
-
-
360
Appendix IV.h. Statistical information for low-molecular weight n-alkanoic acid δ13C measurements : (n-1) and (n-1)*SD2, for calculation of pooled standard deviation.
δ13C n-alkanoic acids
Sample ID
Depth / m
MW63
C14
C15
2
C16
2
C17
2
C18
2
C19
C20
(n-1)*SD
(n-1)
(n-1)*SD2
0.18
1
0.00
1
0.12
1
0.00
1
0.03
1
0.01
8.15
1
0.10
1
0.00
1
0.08
1
0.16
1
0.01
1
0.32
1
0.00
2.70
-
-
1
2.07
-1
-
1
0.54
1
0.03
1
0.07
1
0.00
1
0.00
1
0.09
2.32
1
0.11
1
0.26
1
0.52
1
0.00
1
0.31
1
2.90
1
0.01
1
0.02
1
0.08
1
0.00
1
0.05
-
-
1
0.13
1
0.39
1
0.71
1
0.00
1
0.49
-
-
-
1
0.56
-
-
1
0.01
1
0.01
1
0.06
-
-
-
-
1
0.95
1
0.60
1
1.42
1
0.01
1
0.79
121.15
-
-
-
-
1
0.00
-
-
1
1.82
-
-
1
0.49
MW37
123.52
-
-
-
-
1
0.02
1
1.43
1
0.00
1
0.01
1
0.09
MW38
125.24
1
0.80
1
0.14
1
0.04
1
0.33
1
0.02
1
0.00
1
0.76
MW39
126.39
-
-
-
-
1
9.92
-
-
1
1.25
-
-
1
0.17
MW40
128.38
-
-
-
-
-
-
-
-
1
1.06
1
0.00
1
0.03
MW42
129.26
-
-
-
-
1
20.39
-
-
1
0.53
-
-
1
1.03
MW43r
129.53
-
-
-
-
1
2.16
-
-
3
0.69
-
-
3
1.53
MW45
130.66
-
-
-
-
-
-
-
-
1
3.19
-
-
-
-
MW46
131.11
1
7.46
1
2.15
1
1.29
1
0.00
1
1.63
1
0.03
1
3.74
MW48
132.07
-
-
-
-
-
-
-
-
1
1.12
-
-
-
-
MW49
132.54
-
-
-
-
-
-
-
-
1.03
-
-
1
0.06
(n-1)*SD
(n-1)
(n-1)*SD
(n-1)
(n-1)*SD
(n-1)
(n-1)*SD
(n-1)
(n-1)*SD
53.82
-
-
1
0.36
1
0.01
1
0.00
1
MW62
58.32
-
-
1
0.00
1
0.22
1
0.24
MW60
62.23
-
-
-
-
1
0.39
1
MW58
64.81
-
-
-
-
1
0.07
MW57
70.42
-
-
-
-
1
MW56
79.66
-
-
1
0.03
MW53
93.7
-
-
1
MW52
101.17
-
-
MW29
110.08
-
-
MW31
114.89
-
MW34
119.63
MW35
1
2
Appendix
361
(n-1)
(n-1)
2
Appendix IV.i. Statistical information for mid and high-molecular weight n-alkanoic acid δ13C measurements : (n-1) and (n-1)*SD2, for calculation of pooled standard deviation.
δ13C n-alkanoic acids
Sample ID Depth / m
C22
C24
C26
C28
C30
C32
C34
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
MW63
53.82
1
0.04
1
0.17
1
0.22
1
0.52
-
-
-
-
-
-
MW62
58.32
1
0.07
1
0.04
1
0.00
1
0.04
-
-
-
-
-
-
MW60
62.23
1
0.00
1
0.07
1
0.58
1
0.19
-
-
-
-
-
-
MW58
64.81
1
0.03
1
0.00
1
0.01
1
0.11
1
0.14
1
0.06
-
-
MW57
70.42
1
0.32
1
0.07
1
0.42
1
1.13
1
0.06
-
-
-
-
MW56
79.66
1
0.01
1
0.00
1
0.10
1
0.34
1
0.44
1
0.04
-
-
MW53
93.7
1
0.02
1
0.00
1
0.43
1
0.15
1
4.50
-
-
-
-
MW52
101.17
1
0.03
1
0.05
1
0.00
1
0.16
1
0.54
1
0.12
-
-
MW29
110.08
1
0.00
1
0.16
1
0.40
1
0.00
1
0.04
-
-
1
0.10
MW31
114.89
1
0.00
1
0.00
1
0.00
1
0.00
1
0.05
1
0.01
1
0.49
MW34
119.63
1
0.61
1
0.04
1
0.06
1
0.06
1
0.24
1
0.44
-
-
MW35
121.15
1
0.51
1
0.27
1
0.68
1
0.01
1
0.00
1
0.02
-
-
MW37
123.52
1
0.27
1
0.08
1
0.04
1
0.08
1
0.06
1
0.03
-
-
MW38
125.24
1
0.01
1
0.06
1
0.00
1
1.17
1
2.71
1
0.09
-
-
MW39
126.39
1
0.70
1
0.12
1
0.26
1
0.34
1
0.01
-1
0.00
-
-
MW40
128.38
1
0.04
1
0.09
1
0.06
1
0.03
1
0.01
1
0.12
1
0.01
MW42
129.26
1
0.02
1
0.04
1
0.89
1
5.25
1
0.64
1
0.87
-
-
MW43r
129.53
3
0.76
3
1.04
3
0.44
3
2.86
3
1.27
3
0.29
-
-
MW45
130.66
-
-
1
0.19
1
7.07
1
3.08
1
0.72
1
5.25
-
-
MW46
131.11
1
5.21
1
7.71
1
8.91
1
9.60
1
4.05
1
4.60
-
-
MW48
132.07
1
1.03
1
3.34
-
-
-
-
-
-
-
-
-
-
MW49
132.54
0.09
-
-
1
1.22
1
3.57
1
0.95
1
0.21
1
0.39
1
Appendix
362
Appendix
Appendix IV.j. Statistical information for hopanoic acid δ13C measurements : (n-1) and (n-1)*SD2, for
calculation of pooled standard deviation.
δ13C Hopanoic acids
Sample ID
Depth / m
MW63
C30 ββ
C31 ββ
C32 ββ
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
(n-1)
(n-1)*SD2
53.82
1
0.45
1
0.00
1
0.00
MW62
58.32
1
1.85
1
0.01
1
0.00
MW60
62.23
1
0.68
1
0.09
1
0.22
MW58
64.81
1
0.20
1
0.06
1
0.00
MW57
70.42
1
0.98
1
0.82
1
0.14
MW56
79.66
1
1.89
1
0.17
1
0.03
MW53
93.7
1
0.18
1
0.02
1
3.32
MW52
101.17
1
0.34
1
0.06
1
0.00
MW29
110.08
1
1.40
1
0.00
1
1.17
MW31
114.89
1
0.12
1
0.01
1
0.94
MW34
119.63
1
0.83
1
0.05
1
0.00
MW35
121.15
1
0.12
1
0.04
1
3.17
MW37
123.52
1
5.74
1
0.23
1
0.01
MW38
125.24
1
0.00
1
0.04
1
0.05
MW39
126.39
1
7.35
1
0.00
1
6.45
MW40
128.38
1
0.06
1
0.02
1
0.01
MW42
129.26
1
0.43
1
0.02
1
4.78
MW43r
129.53
3
7.02
3
1.15
3
1.64
MW45
130.66
-
-
-
-
-
-
MW46
131.11
1
10.72
1
4.47
1
16.33
MW48
132.07
-
-
-
-
-
-
1.00
-
-
MW49
132.54
1
1.05
1
363
Appendix IV.k. Weighted mean average δ13C values for groups of n-alkanoic acids : low molecular weight (δ13CLMW), mid-molecular weight (δ13CMMW) and high-molecular weight
(δ13CMMW). Estimate of measurement error for each group is given as the pooled standard deviation.
δ13C n-alkanoic acid groups : weighted mean
13
Sample ID
Depth / m
δ CLMW (C14-C18)
13
δ C
Pooled SD
0.37
δ13CMMW (C20-C24)
δ13CHMW (C26-C34)
13
13
δ C
-31.58
n
6
Pooled SD
0.33
δ C
δ13CHopanoic acid
13
δ C
MW63
53.82
-29.81
n
9
-30.96
n
4
Pooled SD
0.61
-30.64
n
6
Pooled SD
0.39
MW62
58.32
-32.18
8
0.34
-33.55
6
0.20
-33.49
4
0.15
-31.15
6
0.79
MW60
62.23
-31.47
6
1.70
-31.60
6
0.22
-31.92
4
0.62
-30.62
6
0.58
MW58
64.81
7
0.28
-32.26
6
0.11
-32.18
8
0.28
-30.09
6
0.29
MW57
70.42
-29.75
-30.96
4
1.55
-33.28
6
0.56
-32.83
6
0.73
-29.35
6
0.80
MW56
MW53
79.66
93.7
-34.63
-30.91
8
8
0.19
0.90
-32.29
-31.86
6
6
0.18
0.33
-32.17
-31.30
8
6
0.48
1.30
-30.30
-28.74
6
6
0.84
1.08
MW52
101.17
-32.17
8
0.87
-33.34
6
0.21
-33.66
8
0.45
-29.20
6
0.36
MW29
110.08
-28.57
6
0.64
-28.78
6
0.47
-29.08
8
0.37
-29.28
6
0.92
MW31
114.89
4
0.54
-31.48
6
0.14
-30.88
10
0.33
-29.40
6
0.60
MW34
119.63
-28.68
-27.90
6
0.99
-29.45
6
0.69
-29.38
8
0.45
-28.95
6
0.54
MW35
MW37
121.15
123.52
-29.50
-26.50
4
6
0.95
0.69
-30.73
-27.19
6
6
0.65
0.38
-30.78
-28.68
8
8
0.42
0.23
-28.69
-27.70
6
6
1.05
1.41
MW38
125.24
-28.07
10
0.51
-29.13
6
0.53
-30.28
8
1.00
-26.29
6
0.18
MW39
126.39
-28.82
4
2.36
-30.27
6
0.57
-29.64
6
0.55
-27.04
6
2.15
MW40
128.38
2
1.03
-21.88
6
0.23
-27.59
10
0.21
-25.19
6
0.18
MW42
129.26
-25.71
-27.23
4
3.23
-29.69
6
0.60
-29.94
8
1.38
-25.31
6
1.32
MW43r
MW45
129.53
130.66
-27.04
0.84
1.79
-27.03
-29.02
12
3
0.61
0.44
-28.37
-27.80
16
8
0.64
2.01
-26.31
12
1.04
-27.41
6
2
MW46
131.11
-30.14
10
1.58
-31.25
6
2.36
-32.16
8
2.61
-31.43
3
3.24
MW48
132.07
-28.39
2
1.06
-33.05
4
1.48
MW49
132.54
-28.12
2
1.02
-31.72
6
1.27
-29.39
8
0.64
-29.18
4
1.01
Appendix
364
Appendix IV.l. Table of raw isoprenoidal GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4, crenarchaeol, GDGT-0)
Sample Depth /
ID
m
GDGT-1
GDGT-2
GDGT-3
GDGT-4' (cren isomer)
GDGT-0
crenarchaeol
m/z [M+H]+ = 1300
m/z [M+H]+ = 1298
m/z [M+H]+ = 1296
m/z [M+H]+ = 1292'
m/z [M+H]+ = 1302
m/z [M+H]+ = 1292
MW49
132.54
2.7E+05
1.3E+05
5.1E+05
2.6E+05
2.0E+05
9.4E+04
9.0E+05
4.3E+05
9.0E+05
4.4E+05
5.1E+06
2.5E+06
MW48
132.07
6.6E+04
3.7E+04
1.1E+05
4.1E+04
2.3E+04
1.5E+05
7.9E+04
2.1E+05
1.1E+05
9.2E+05
5.0E+05
MW46
MW45
131.11
130.66
1.3E+06
2.3E+06
1.1E+06
1.0E+06
1.4E+06
5.6E+04
-
2.8E+05
6.1E+05
6.8E+05
3.2E+05
5.7E+05
5.8E+05
2.8E+05
6.8E+06
1.6E+07
7.9E+06
1.0E+07
1.7E+07
8.1E+06
MW43
129.53
1.6E+06
8.5E+05
9.4E+05
5.0E+05
3.9E+05
2.1E+05
4.0E+05
2.2E+05
1.1E+07
5.7E+06
1.3E+07
6.8E+06
MW42
129.26
2.0E+06
8.8E+05
1.1E+06
4.5E+05
2.1E+05
1.4E+07
6.5E+06
1.5E+07
6.7E+06
128.38
2.0E+06
-
1.1E+06
4.4E+05
-
4.3E+05
4.4E+05
2.0E+05
MW40
4.9E+05
-
-
1.6E+07
-
1.8E+07
-
MW39
126.39
8.5E+05
4.4E+05
5.8E+05
3.0E+05
2.1E+05
1.1E+05
2.7E+05
1.4E+05
5.0E+06
2.6E+06
5.9E+06
3.0E+06
MW38
MW37
125.24
123.52
2.2E+06
2.7E+06
1.1E+06
-
1.4E+06
1.7E+06
7.0E+05
-
5.8E+05
6.8E+05
3.0E+05
-
6.1E+05
8.7E+05
3.1E+05
-
1.3E+07
1.5E+07
7.0E+06
-
1.8E+07
2.1E+07
9.2E+06
-
MW35
121.15
1.5E+06
7.2E+05
1.0E+06
4.7E+05
4.0E+05
1.9E+05
4.5E+05
2.1E+05
8.8E+06
4.2E+06
1.2E+07
5.8E+06
MW34
119.63
2.5E+06
1.2E+06
1.6E+06
6.7E+05
3.2E+05
1.4E+07
6.8E+06
2.0E+07
9.1E+06
117.93
9.7E+05
5.3E+05
7.0E+05
2.9E+05
1.6E+05
7.2E+05
4.0E+05
3.3E+05
MW33
7.5E+05
3.8E+05
2.2E+05
5.2E+06
2.9E+06
8.9E+06
4.9E+06
MW31
114.89
1.1E+06
5.8E+05
7.3E+05
3.0E+05
1.5E+05
3.6E+05
1.8E+05
6.5E+06
3.4E+06
9.4E+06
4.9E+06
MW29
MW52
110.08
101.17
2.5E+06
9.3E+05
4.2E+05
1.6E+06
6.3E+05
3.7E+05
-
1.2E+05
6.8E+05
2.8E+05
6.7E+05
2.6E+05
3.1E+05
1.3E+05
1.6E+07
5.5E+06
2.5E+06
2.1E+07
8.1E+06
3.6E+06
MW53
93.70
1.4E+06
6.7E+05
9.6E+05
4.6E+05
4.4E+05
2.1E+05
5.0E+05
2.4E+05
7.5E+06
3.7E+06
1.3E+07
6.2E+06
MW56
79.66
7.6E+05
3.8E+05
5.6E+05
2.4E+05
1.2E+05
3.7E+06
1.9E+06
7.0E+06
3.5E+06
70.42
6.4E+05
3.6E+05
4.7E+05
2.0E+05
1.1E+05
3.3E+05
2.7E+05
1.7E+05
MW57
2.8E+05
2.5E+05
1.5E+05
3.4E+06
1.9E+06
6.1E+06
3.3E+06
MW58
64.81
1.1E+06
4.9E+05
7.1E+05
3.2E+05
3.3E+05
1.5E+05
3.6E+05
1.6E+05
6.0E+06
2.8E+06
1.0E+07
4.6E+06
MW60
MW62
62.23
58.32
1.0E+06
1.9E+06
4.9E+05
1.0E+06
7.2E+05
1.6E+06
3.4E+05
1.6E+05
3.6E+05
3.7E+05
8.1E+05
3.2E+05
7.0E+05
9.8E+05
1.8E+05
4.9E+05
5.4E+06
8.2E+06
2.6E+06
4.3E+06
9.6E+06
1.9E+07
4.7E+06
9.6E+06
MW63
53.82
1.8E+06
8.5E+05
1.3E+06
6.1E+05
5.6E+05
2.6E+05
7.1E+05
3.4E+05
8.2E+06
3.9E+06
1.6E+07
7.9E+06
Appendix
365
Appendix
Appendix IV.m. Raw and mean TEX86 values, presented with standard deviations and other statistical
information (e.g. pooled standard deviation for datasets)
TEX86 / TEX86H
Sample
ID
Depth / m
MW49
132.54
0.86
MW48
132.07
MW46
raw
TEX86L
1 / TEX86
Mean
SD
Mean
SD
Mean
SD
0.85
0.85
0.003
1.17
1.17
1.17
0.004
0.52
0.53
0.53
0.003
0.81
0.81
0.81
0.003
1.23
1.23
1.23
0.004
0.49
0.48
0.49
0.007
131.11
0.59
-
0.59
-
1.70
-
1.70
-
0.38
-
0.38
-
MW45
130.66
0.52
0.52
0.52
0.001
1.92
1.92
1.92
0.003
0.32
0.32
0.32
0.000
MW43
129.53
0.52
0.52
0.52
0.001
1.93
1.92
1.93
0.005
0.32
0.32
0.32
0.000
MW42
129.26
0.50
0.51
0.50
0.004
2.00
1.98
1.99
0.016
0.31
0.31
0.31
0.001
MW40
128.38
0.50
-
0.50
-
2.01
-
2.01
-
0.31
-
0.31
-
MW39
126.39
0.55
0.55
0.55
0.000
1.80
1.80
1.80
0.001
0.35
0.35
0.35
0.000
MW38
125.24
0.54
0.53
0.54
0.005
1.85
1.88
1.87
0.018
0.33
0.33
0.33
0.004
MW37
123.52
0.55
-
0.55
-
1.82
-
1.82
-
0.34
-
0.34
-
MW35
121.15
0.55
0.55
0.55
0.003
1.81
1.83
1.82
0.010
0.34
0.34
0.34
0.002
MW34
119.63
0.55
0.55
0.55
0.003
1.82
1.83
1.83
0.009
0.34
0.34
0.34
0.003
MW33
117.93
0.59
0.59
0.59
0.001
1.70
1.71
1.70
0.003
0.36
0.35
0.35
0.002
MW31
114.89
0.55
0.55
0.55
0.002
1.81
1.82
1.82
0.006
0.34
0.34
0.34
0.002
MW29
110.08
0.54
-
0.54
-
1.84
-
1.84
-
0.34
-
0.34
-
MW52
101.17
0.56
0.56
0.56
0.002
1.78
1.79
1.79
0.006
0.34
0.34
0.34
0.000
MW53
93.70
0.58
0.57
0.58
0.002
1.73
1.74
1.74
0.005
0.34
0.34
0.34
0.002
MW56
79.66
0.60
0.60
0.60
0.001
1.67
1.67
1.67
0.004
0.36
0.36
0.36
0.001
MW57
70.42
0.59
0.58
0.59
0.005
1.69
1.71
1.70
0.015
0.36
0.35
0.35
0.004
MW58
64.81
0.56
0.56
0.56
0.000
1.78
1.78
1.78
0.000
0.34
0.34
0.34
0.001
MW60
62.23
0.58
0.58
0.58
0.003
1.71
1.73
1.72
0.009
0.35
0.34
0.35
0.004
MW62
58.32
0.63
0.62
0.63
0.003
1.59
1.60
1.60
0.007
0.38
0.37
0.37
0.002
MW63
53.82
0.58
0.59
0.59
0.003
1.71
1.70
1.71
0.008
0.35
0.36
0.35
0.002
sum (n-1)
19
sum (n-1)
19
sum (n-1)
19
sum (n-1)*SD2
Pooled SD
1.4E-04
0.0027
raw
sum (n-1)*SD2
Pooled SD
1.4E-03
0.0084
raw
sum (n-1)*SD2
Pooled SD
1.3E-04
0.0027
366
Appendix IV.n. Raw and meanTEX86-derived SST estimates, presented with standard deviations and other statistical information (e.g. pooled standard deviation for datasets)
SST / °C
Kim et al., 2008
Sample
ID
Depth / m
MW49
132.54
37.38
MW48
132.07
35.02
MW46
131.11
MW45
MW43
raw
Kim et al., 2010 : TEX86H
Liu et al., 2009
Mean
SD
Mean
SD
Mean
SD
Mean
SD
37.16
37.27
0.16
31.42
34.82
34.92
0.14
30.43
31.33
31.37
0.06
34.01
30.34
30.39
0.06
32.52
33.88
33.94
0.10
27.99
32.39
32.45
0.09
26.22
28.21
28.10
0.16
25.65
25.94
22.36
-
22.36
-
22.78
-
22.78
-
22.91
-
22.91
-
0.40
18.22
-
18.22
-
130.66
18.53
18.46
18.49
129.53
18.36
18.46
18.41
0.05
19.16
19.08
19.12
0.07
18.98
19.09
19.03
0.05
19.26
19.19
19.22
0.08
19.09
19.19
19.14
0.05
13.92
13.91
13.92
0.01
0.07
13.37
13.31
13.34
MW42
129.26
17.34
17.65
17.50
0.22
17.84
18.19
18.01
0.25
18.03
18.36
0.04
18.20
0.23
12.69
12.77
12.73
MW40
128.38
17.16
-
17.16
-
17.63
-
17.63
-
17.84
0.05
-
17.84
-
12.64
-
12.64
MW39
126.39
20.39
20.36
20.38
0.02
21.03
21.00
21.02
0.02
-
21.09
21.06
21.08
0.02
16.24
16.22
16.23
0.02
MW38
MW37
125.24
19.56
19.14
19.35
123.52
20.11
-
20.11
0.29
20.22
19.80
20.01
-
20.76
-
20.76
0.30
20.28
19.87
20.08
0.29
14.54
14.04
14.29
0.36
-
20.82
-
20.82
-
15.05
-
15.05
MW35
121.15
20.25
20.01
20.13
0.17
20.89
20.67
-
20.78
0.16
20.95
20.73
20.84
0.16
15.55
15.26
15.41
0.20
MW34
119.63
20.08
MW33
117.93
22.26
19.85
19.97
0.16
20.73
22.17
22.21
0.06
22.69
20.51
20.62
0.15
20.79
20.57
20.68
0.15
15.35
15.02
15.19
0.23
22.62
22.66
0.05
22.82
22.74
22.78
0.06
16.63
16.43
16.53
0.14
MW31
114.89
MW29
110.08
20.23
20.10
20.16
0.10
19.81
-
19.81
-
20.88
20.75
20.81
0.09
20.94
20.81
20.87
0.09
15.16
14.96
15.06
0.14
20.47
-
20.47
-
20.54
-
20.54
-
15.38
-
15.38
MW52
101.17
20.77
20.63
20.70
-
0.10
21.38
21.25
21.32
0.09
21.45
21.31
21.38
0.09
15.69
15.68
15.69
0.01
MW53
93.70
21.64
21.51
MW56
79.66
22.77
22.88
21.57
0.09
22.16
22.05
22.10
0.08
22.26
22.14
22.20
0.09
15.60
15.32
15.46
0.19
22.83
0.08
23.12
23.21
23.16
0.06
23.28
23.37
23.33
0.07
16.87
16.99
16.93
MW57
70.42
22.48
0.09
22.07
22.28
0.29
22.88
22.54
22.71
0.24
23.02
22.65
22.84
0.26
16.63
16.16
16.39
0.33
MW58
64.81
MW60
62.23
20.86
20.86
20.86
0.00
21.46
21.47
21.46
0.00
21.53
21.53
21.53
0.00
14.87
14.97
14.92
0.07
22.01
21.77
21.89
0.17
22.49
22.28
22.38
0.15
22.60
22.38
22.49
0.15
16.14
15.63
15.88
MW62
0.37
58.32
24.52
24.31
24.41
0.15
24.47
24.32
24.39
0.11
24.78
24.61
24.70
0.12
18.19
18.00
18.09
MW63
0.13
53.82
22.00
22.23
22.11
0.16
22.47
22.67
22.57
0.14
22.58
22.79
22.69
0.15
16.39
16.57
16.48
0.13
sum (n-1)
19
sum (n-1)
19
sum (n-1)
19
sum (n-1)
19
sum (n-1)*SD2
Pooled SD
4.4E-01
0.152
raw
sum (n-1)*SD2
Pooled SD
3.6E-01
0.138
raw
Kim et al., 2010 : TEX86L
sum (n-1)*SD2
Pooled SD
3.7E-01
0.140
raw
sum (n-1)*SD2
Pooled SD
7.8E-01
0.202
Appendix
367
Appendix IV.o. Raw branched GDGT and crenarchaeol peak areas (separate crenarchaeol measurement for BIT index calculation).
crenarchaeol
bGDGT-IIIa
Sample
ID
Depth / m
m/z [M+H]+
1292
m/z [M+H]+ m/z [M+H]+ m/z [M+H]+ m/z [M+H]+ m/z [M+H]+ m/z [M+H]+ m/z [M+H]+ m/z [M+H]+ m/z [M+H]+
1050
1048
1046
1036
1034
1032
1022
1020
1018
MW49
132.54
5.5E+06
MW48
132.07
1.0E+06
MW46
131.11
1.2E+07
MW45
130.66
1.8E+07
MW43
129.53
MW42
2.1E+04
bGDGT-IIIb
bGDGT-IIIc
bGDGT-IIa
bGDGT-IIb
bGDGT-IIc
bGDGT-Ia
bGDGT-Ib
bGDGT-Ic
-
-
4.2E+04
1.8E+04
5.6E+03
1.5E+05
3.5E+04
2.8E+04
-
-
1.4E+04
5.8E+03
2.5E+03
7.2E+04
1.3E+04
1.7E+04
1.8E+05
-
-
2.7E+05
8.5E+04
2.0E+04
4.6E+05
5.7E+04
2.7E+04
4.4E+05
-
-
4.5E+05
1.4E+05
2.1E+04
7.9E+05
6.2E+04
2.7E+04
1.4E+07
3.5E+05
-
-
4.1E+05
1.3E+05
1.9E+04
6.7E+05
6.7E+04
2.6E+04
129.26
1.6E+07
4.7E+05
-
-
4.5E+05
1.5E+05
1.9E+04
8.3E+05
7.0E+04
2.8E+04
MW40
128.38
2.0E+07
3.9E+05
-
-
3.7E+05
1.6E+05
1.5E+04
1.0E+06
6.7E+04
2.9E+04
MW39
126.39
6.4E+06
1.3E+05
-
-
1.5E+05
6.3E+04
9.7E+03
3.0E+05
3.3E+04
1.4E+04
MW38
125.24
1.9E+07
3.9E+05
-
-
4.3E+05
1.8E+05
2.4E+04
7.3E+05
8.9E+04
3.7E+04
MW37
123.52
2.3E+07
3.4E+05
-
-
4.6E+05
1.9E+05
2.7E+04
8.7E+05
1.0E+05
4.6E+04
MW35
121.15
1.3E+07
2.0E+05
-
-
2.7E+05
9.8E+04
1.6E+04
4.6E+05
5.7E+04
2.6E+04
MW34
119.63
2.2E+07
4.5E+05
-
-
4.8E+05
1.8E+05
3.1E+04
8.0E+05
1.0E+05
4.8E+04
MW33
117.93
9.8E+06
1.1E+05
-
-
1.7E+05
6.6E+04
1.1E+04
3.1E+05
4.5E+04
2.0E+04
MW31
114.89
1.0E+07
1.2E+05
-
-
1.7E+05
6.8E+04
1.2E+04
3.2E+05
4.6E+04
2.1E+04
MW29
110.08
2.5E+07
2.4E+05
-
-
3.9E+05
1.4E+05
2.2E+04
7.3E+05
1.0E+05
4.6E+04
MW52
101.17
9.0E+06
1.0E+05
-
-
1.6E+05
6.2E+04
1.2E+04
3.4E+05
4.6E+04
2.1E+04
MW53
93.70
1.4E+07
1.1E+05
-
-
1.7E+05
7.4E+04
1.5E+04
3.7E+05
5.5E+04
2.6E+04
MW56
79.66
7.9E+06
6.8E+04
-
-
1.0E+05
4.3E+04
7.5E+03
2.1E+05
3.1E+04
1.4E+04
MW57
70.42
6.7E+06
6.8E+04
-
-
1.0E+05
4.2E+04
9.3E+03
2.2E+05
3.4E+04
1.6E+04
MW58
64.81
1.1E+07
1.3E+05
-
-
1.9E+05
8.0E+04
1.5E+04
4.4E+05
6.2E+04
2.9E+04
MW60
62.23
1.1E+07
1.1E+05
-
-
1.8E+05
8.2E+04
1.6E+04
3.5E+05
6.4E+04
3.0E+04
MW62
58.32
2.0E+07
1.9E+05
-
-
3.4E+05
1.6E+05
3.3E+04
7.6E+05
1.4E+05
7.0E+04
MW63
53.82
1.8E+07
1.6E+05
-
-
2.9E+05
1.3E+05
2.7E+04
4.9E+05
1.0E+05
4.8E+04
Appendix
368
Appendix IV.p. BIT indices, CBT and MBT ratios, pH and MAAT estimates.
Sample
ID
Depth / m
BIT Index
CBT
MBT
pH
MAAT / °C
MW49
132.54
0.037
0.554
0.710
7.304
24.234
MW48
132.07
0.076
0.651
0.823
7.050
28.976
MW46
131.11
0.072
0.709
0.495
6.897
12.007
MW45
130.66
0.085
0.793
0.457
6.676
9.325
MW43
129.53
0.091
0.747
0.460
6.797
9.938
MW42
129.26
0.096
0.762
0.460
6.759
9.790
MW40
128.38
0.082
0.794
0.545
6.674
13.738
MW39
126.39
0.084
0.676
0.497
6.985
12.418
MW38
125.24
0.076
0.644
0.456
7.070
10.692
MW37
123.52
0.068
0.666
0.501
7.009
12.738
MW35
121.15
0.065
0.673
0.478
6.993
11.510
MW34
119.63
0.074
0.666
0.454
7.010
10.382
MW33
117.93
0.056
0.629
0.515
7.108
13.762
MW31
114.89
0.056
0.633
0.514
7.097
13.703
MW29
110.08
0.052
0.658
0.526
7.032
14.027
MW52
101.17
0.045
0.621
0.533
7.129
14.722
MW53
93.70
0.062
0.660
0.545
7.026
14.976
MW56
79.66
0.046
0.625
0.547
7.118
15.399
MW57
70.42
0.063
0.649
0.559
7.056
15.797
MW58
64.81
0.056
0.633
0.551
7.098
15.534
MW60
62.23
0.058
0.563
0.533
7.281
15.296
MW62
58.32
0.059
0.564
0.577
7.279
17.455
MW63
53.82
0.050
0.519
0.518
7.398
14.959
Appendix
369
Appendix
Appendix V
ODP Site 1121 : Geochemical Data and Statistical Information
List of Tables:
V.a.
Table of raw GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4, crenarchaeol,
GDGT-0, bGDGT-Ia)
V.b.
Average TEX86 values, with statistical data for estimation of errors. BIT’ is related to BIT,
but uses the only quantifiable branched GDGT (bGDGT-I) for calculation of the index,
thus is analogous to, but not identical to, the BIT index.
V.c.
Average TEX86-derived SST estimates (Kim et al., 2008; Liu et al., 2009; Kim et al.,
2010), with statistical data for estimation of errors.
370
Appendix
Appendix V.a. Table of raw GDGT peak areas (GDGT-1, GDGT-2, GDGT-3, GDGT-4, crenarchaeol,
GDGT-0, bGDGT-Ia)
Sample Depth
ID
mbsf / m
CP12
56.97
Age /
Ma
58.27
GDGT-0
GDGT-1
GDGT-2
GDGT-3
GDGT-4'
crenarchaeol
bGDGT-Ia
m/z
[M+H]+ =
1302
m/z
[M+H]+ =
1300
m/z [M+H]+
= 1298
m/z
[M+H]+ =
1296
m/z
[M+H]+ =
1292
m/z [M+H]+
= 1292
m/z
[M+H]+ =
1022
3.82E+06
5.88E+05
4.63E+05
9.31E+04
2.70E+05
4.74E+06
2.18E+05
3.86E+07
7.62E+06
5.76E+06
1.16E+06
3.07E+06
4.82E+07
3.54E+06
3.74E+07
7.36E+06
5.64E+06
1.23E+06
3.04E+06
4.80E+07
3.49E+06
4.59E+06
9.04E+05
6.58E+05
1.74E+05
3.81E+05
5.37E+06
4.18E+05
CP17
64.975
58.53
8.14E+06
1.11E+06
6.68E+05
9.22E+04
3.25E+05
4.39E+06
2.80E+06
CP19
66.565
58.58
2.86E+07
4.97E+06
4.08E+06
8.81E+05
2.13E+06
2.74E+07
5.21E+06
CP20
68.065
58.63
6.33E+06
4.59E+06
6.39E+05
9.71E+05
6.33E+06
4.59E+06
2.94E+06
1.31E+06
9.84E+05
1.81E+05
2.25E+05
1.31E+06
9.84E+05
7.84E+05
CP21
69.565
58.68
7.13E+05
1.76E+05
1.34E+05
4.96E+04
8.20E+04
8.18E+05
1.20E+05
CP22
71.735
58.75
7.34E+07
1.30E+07
9.33E+06
2.05E+06
5.15E+06
8.26E+07
1.30E+07
CP24
72.815
58.79
2.34E+07
3.57E+06
2.70E+06
4.02E+05
1.36E+06
1.82E+07
4.34E+06
CP25
74.665
58.85
3.54E+06
6.04E+05
5.04E+05
1.09E+05
2.07E+05
2.32E+06
7.45E+05
1.75E+06
3.49E+05
2.92E+05
3.47E+04
1.34E+05
1.68E+06
1.98E+05
3.30E+07
6.53E+06
5.96E+06
9.44E+05
2.80E+06
3.48E+07
3.76E+06
2.61E+07
5.38E+06
4.68E+06
7.66E+05
2.29E+06
2.79E+07
3.05E+06
2.58E+06
4.87E+05
4.47E+05
6.37E+04
1.84E+05
2.42E+06
2.73E+05
1.75E+07
3.25E+06
2.88E+06
6.30E+05
1.98E+06
2.16E+07
2.17E+06
2.18E+07
4.01E+06
3.34E+06
9.10E+05
2.18E+06
2.85E+07
3.00E+06
1.21E+07
2.28E+06
1.94E+06
3.58E+05
1.19E+06
1.66E+07
1.61E+06
1.37E+06
2.72E+05
2.19E+05
4.02E+04
1.25E+05
1.80E+06
2.07E+05
CP26
CP29
76.035
84.365
58.89
59.16
CP30
84.875
59.18
8.17E+07
1.04E+07
9.34E+06
2.02E+06
6.44E+06
7.93E+07
1.38E+07
CP31
85.865
59.21
4.72E+07
7.10E+06
6.16E+06
1.35E+06
3.35E+06
4.78E+07
5.19E+06
CP33
90.965
59.37
3.33E+08
6.83E+07
6.25E+07
1.34E+07
3.66E+07
5.02E+08
2.21E+07
CP35
92.965
59.44
7.52E+07
8.77E+06
1.02E+07
2.21E+06
4.82E+06
5.37E+07
8.98E+06
3.88E+07
7.70E+06
6.87E+06
1.31E+06
4.06E+06
4.58E+07
3.08E+06
CP36
94.045
59.47
2.15E+07
3.94E+06
3.70E+06
7.21E+05
2.11E+06
2.61E+07
1.88E+06
4.73E+07
8.63E+06
7.86E+06
1.34E+06
4.54E+06
5.58E+07
4.14E+06
5.40E+07
7.68E+06
3.55E+06
7.72E+05
2.49E+06
3.20E+07
1.07E+07
8.50E+07
1.19E+07
5.95E+06
1.27E+06
3.93E+06
5.07E+07
1.77E+07
CP37
119.65
60.30
371
Appendix V.b. Average TEX86 values, with statistical data for estimation of errors. BIT’ is related to BIT, but uses the only quantifiable branched GDGT (bGDGT-I) for
calculation of the index, thus is analogous to, but not identical to, the BIT index.
TEX86 / TEX86H
Sample Depth
ID
mbsf / m
TEX86L
1 / TEX86
BIT' [Ia / cren + Ia]
Age /
Ma
Mean
SD
Mean
SD
Mean
SD
Mean
SD
CP12
56.97
58.27
0.575
7.02E-03
1.741
2.11E-02
0.394
1.09E-02
0.063
1.29E-02
CP17
64.975
58.53
0.494
-
2.025
-
0.357
-
0.389
-
CP19
66.565
58.58
0.588
-
1.701
-
0.411
-
0.160
-
CP20
68.065
58.63
0.635
1.54E-03
1.575
3.83E-03
0.117
1.91E-02
0.417
3.74E-02
CP21
69.565
58.68
0.601
-
1.663
-
0.373
-
0.128
-
CP22
71.735
58.75
0.559
-
1.789
-
0.382
-
0.136
-
CP24
72.815
58.79
0.555
-
1.801
-
0.405
-
0.192
-
CP25
74.665
58.85
0.576
-
1.737
-
0.414
-
0.243
-
CP26
76.035
58.89
0.586
1.22E-02
1.707
3.60E-02
0.439
8.09E-03
0.101
3.67E-03
CP29
84.365
59.16
0.608
1.82E-02
1.645
4.95E-02
0.416
1.02E-02
0.095
6.45E-03
CP30
84.875
59.18
0.630
-
1.587
-
0.428
-
0.148
-
CP31
85.865
59.21
0.605
-
1.653
-
0.422
-
0.098
-
CP33
90.965
59.37
0.622
-
1.607
-
0.433
-
0.042
-
CP35
92.965
59.44
0.662
-
1.510
-
0.481
-
0.143
-
CP36
94.045
59.47
0.617
5.62E-03
1.620
1.47E-02
0.439
5.21E-03
0.066
3.08E-03
CP37
119.65
60.30
0.477
9.92E-03
2.096
4.35E-02
0.304
1.09E-02
0.255
6.17E-03
sum (n-1)
13
sum (n-1)
13
sum (n-1)
13
5.4E-02
13
sum (n-1)*SD2
1.7E-01
sum (n-1)*SD2
6.4E-02
sum (n-1)*SD2
7.0E-02
Pooled SD
4.2E-03
Pooled SD
1.3E-02
Pooled SD
5.0E-03
Pooled SD
5.4E-03
372
Appendix
sum (n-1)
sum (n-1)*SD2
Appendix V.c. Average TEX86-derived SST estimates (Kim et al., 2008; Liu et al., 2009; Kim et al., 2010), with statistical data for estimation of errors.
Kim et al., 2008
Sample Depth
ID
mbsf / m
Kim et al., 2010: TEX86H
Liu et al., 2009
Kim et al., 2010: TEX86L
Age /
Ma
Mean
SD
Mean
SD
Mean
SD
Mean
SD
CP12
56.97
58.27
21.51
0.39
22.05
0.35
22.14
0.36
19.59
0.82
CP17
64.975
58.53
16.97
-
17.40
-
17.63
-
16.66
-
CP19
66.565
58.58
22.26
1.80
22.70
1.69
22.82
1.71
20.82
1.99
CP20
68.065
58.63
20.46
-
21.04
-
21.13
-
18.82
-
CP21
69.565
58.68
23.02
-
23.32
-
23.49
-
17.96
-
CP22
71.735
58.75
20.63
-
21.26
-
21.32
-
18.68
-
CP24
72.815
58.79
20.43
-
21.07
-
21.13
-
20.38
-
CP25
74.665
58.85
21.58
-
22.11
-
22.21
-
21.05
-
CP26
76.035
58.89
22.16
0.69
22.60
0.59
22.73
0.62
22.77
0.54
CP29
84.365
59.16
23.41
1.02
23.61
0.81
23.83
0.89
21.21
0.72
CP30
84.875
59.18
24.64
-
24.56
-
24.89
-
22.04
-
CP31
85.865
59.21
23.21
-
23.47
-
23.66
-
21.59
-
CP33
90.965
59.37
24.19
-
24.23
-
24.51
-
22.38
-
CP35
92.965
59.44
26.44
-
25.82
-
26.36
-
25.42
-
CP36
94.045
59.47
23.91
0.32
24.01
0.24
24.26
0.27
22.73
0.35
CP37
119.65
60.30
16.04
0.56
16.25
0.71
16.63
0.62
11.96
1.05
sum (n-1)
sum (n-1)
13
sum (n-1)
13
sum (n-1)
13
8.75
2
6.85
2
7.39
2
9.75
Pooled SD
0.67
Pooled SD
0.53
Pooled SD
0.57
Pooled SD
0.75
sum (n-1)*SD
sum (n-1)*SD
sum (n-1)*SD
sum (n-1)*SD
373
Appendix
13
2
Appendix
Appendix VI
Geological, Lithological and Extended Sample Information
VI.a.
Schematic diagram of Cretaceous-Cenozoic New Zealand sediment succession.
VI.b.
Canterbury Basin chronostratigraphic chart.
VI.c.
Mid-Waipara K/Pg Section sample collection information.
VI.d.
Mid-Waipara River Column 2 sample collection details.
VI.e.
Mid-Waipara Column 2 lithologic column.
VI.f.
Photographs of mid-Waipara Column 2 sample collection.
VI.g.
Recovery, gamma-ray, cumulative percent lithology, biostratigraphy and sequence
boundary location of Paleocene strata at Bass River, New Jersey.
VI.h.
Distribution of Paleocene sediments on the New Jersey Coastal Plain.
VIi.
Carbonate carbon isotope correlation between ODP Sites 1121. 1124 and DSDP Site 577
374
Appendix
Appendix VI.a. Schematic diagram showing generalised depositional patterns, unconformities and important
tectonic and oceanographic events set within the broad framework of the 1st order tectonic megacycle
represented by supra-basement Cretaceous-Cenozoic sedimentary successions from New Zealand (from King
et al.1999).
375
Appendix
Appendix VI.b. Canterbury Basin chronostratigraphic chart showing different rock units and their time of
deposition, from on-shore Canturbury progressing south east to off-shore Canturbury Basin. Note midWaipara River Section at far North-West onshore Canterbury. (Samuel, unpublished Master’s thesis, 2009)
376
Appendix
Appendix VI.c. Mid-Waipara K/Pg Section sample collection information: condensed from table of
integrated collection of 187 samples compiled by C.J. Hollis (Morgans et al., 2005). The collections included
were taken by Hollis et al. in 1999 (M34/f535-f562) and Strong and Edwards in 1982 (M34/f158-f256). The
Fossil Record Number (FRF), field number, NZMS 260 M34 grid reference, GNS foraminiferal curation
number (F), stratigraphic position (from the Fossil Record File), formation, and microfossil and geochemical
analyses completed are given.
NZFR
M34/
f536
f537
f538
f539
f541
f218
f215
f213
f209
f202
f199
f554
f197
f556
f558
f559
f560
f561
f175
f172
f170
f168
f165
f161
f562
Field
no.
GNS F# NZMS 260
M34/
MW7
MW6
MW5
MW4
MW2
76059402
76059402
76059402
76059402
76059402
76059402
76059402
76059402
76059402
76059402
76059402
F36109 76059402
MW16
76059402
76059402
F36107 76059402
MW15
76059402
MW14
76059402
MW13
76059402
MW12
76059402
F36128
F36125
F36123
F36119
MW17
MW18
76059402
76059402
76059402
76059402
76059402
76059402
76059402
76059402
Depth (m ± K/Pg)
Formation /
Base Top
Mean
Lithology
102.00 top Waipara Greensand
43.00 base Waipara Greensand
20.000 Loburn
13.740 Loburn
10.840 Loburn
7.74 7.94
7.840 Loburn
4.06 4.16
4.110 Loburn
4.000 base Loburn Fm
2.300 lowest concretionary band based on f120
1.50 1.60
1.550 "glc sst"
1.20 1.30
1.250 "glc sst"
1.00 1.10
1.050 "glc sst"
0.70 0.80
0.750 "glc sst"
0.40 0.45
0.425 "glc sst"
0.25 0.30
0.275 "glc sst"
0.20 0.24
0.220 "glc sst"
0.20 0.20
0.200 jarositic bed
0.18 0.20
0.190 "glc sst"
0.12 0.20
0.160 "glc sst"
0.08 0.12
0.100 "glc sst"
0.02 0.08
0.050 "glc sst"
0.00 0.01
0.005 "glc sst"
0.000 KTB zone
-0.10 -0.04 -0.070 Conway
-0.20 -0.16 -0.180 Conway
-0.29 -0.26 -0.273 Conway
-0.38 -0.33 -0.355 Conway
-0.46 -0.42 -0.440 Conway
-0.57 -0.53 -0.545 Conway
-0.73 -0.66 -0.695 Conway
-1.20 -1.10 -1.150 Conway
377
Appendix
Appendix VI.d. Mid-Waipara River Column 2 sample collection, adapted from Morgans et al., (2005)
detailing GNS 2003 collection suite, taken by H.E.G. Morgans, E.M. Crouch, B.D. Field, J.I Raine and C.P.
Strong. Suite included 265 samples (M34/f610 to f874) which were collected and are located on six
lithologic columns (Columns 1 to 6), based on their geographic and stratigraphic position. Detailed here are
23 samples from mid-Waipara Column 2. The Fossil Record Number (FRF), field number, GNS
foraminiferal curation number (F), NZMS 260 M34 grid reference and stratigraphic position of the samples
are given.
Fossil Record
File Number
Field number
Sample ID
(this study)
GNS Science
Curation
Number
Grid Ref.
NZMS 260
M34/
M34/f678
MW16/02/03-49
MW49
F37006
7706 9420
132.54
132.53
132.54
M34/f677
MW16/02/03-48
MW48
F37005
7706 9420
132.07
132.06
132.07
Strat. Strat. Strat
base (m) top (m) mid (m)
Possible Ashley Mudstone (Slumped) or Unconformity
M34/f675
MW16/02/03-46
MW46
F37003
7706 9420
131.11
131.10
131.11
M34/f674
MW16/02/03-45
MW45
F37002
7706 9419
130.66
130.65
130.66
M34/f671
MW16/02/03-42
MW42
F36999
7705 9419
129.26
129.25
129.26
M34/f669
MW16/02/03-40
MW40
F36997
7705 9419
128.38
128.37
128.38
M34/f668
MW16/02/03-39
MW39
F36996
7704 9420
126.39
126.38
126.39
M34/f667
MW16/02/03-38
MW38
F36995
7703 9420
125.24
125.23
125.24
M34/f666
MW16/02/03-37
MW37
F36994
7703 9420
123.52
123.51
123.52
M34/f665
MW16/02/03-35
MW35
F36993
7703 9421
121.15
121.14
121.15
M34/f664
MW16/02/03-34
MW34
F36992
7702 9421
119.63
119.62
119.63
M34/f662
MW16/02/03-33
MW33
F36990
7702 9422
117.93
117.92
117.93
M34/f660
MW16/02/03-31
MW32
F36988
7702 9422
114.89
114.88
114.89
M34/f658
MW16/02/03-29
MW30
F36986
7701 9424
110.08
110.07
110.08
M34/f657
MW16/02/03-52
MW52
F36985
7698 9427
101.17
101.16
101.17
M34/f656
MW16/02/03-53
MW53
F36984
7697 9427
93.70
93.69
93.70
M34/f653
MW16/02/03-56
MW56
F36981
7693 9428
79.66
79.65
79.66
M34/f652
MW16/02/03-57
MW57
F36980
7690 9429
70.42
70.41
70.42
M34/f651
MW16/02/03-58
MW58
F36979
7688 9429
64.81
64.80
64.81
62.23
Base Waipara Greensand
M34/f649
MW16/02/03-60
MW60
F36977
7686 9429
62.23
64.50
62.22
M34/f647
MW16/02/03-62
MW62
F36975
7685 9429
58.32
58.31
58.32
M34/f646
MW16/02/03-63
MW63
F36974
7683 9429
53.82
53.81
53.82
Lowest Exposed Loburn Formation
39.80
378
Appendix
Appendix VI.e. mid-Waipara Column 2 lithologic column, from Morgans et al., (2005), showing the
position of tape and compass survey points, lithological descriptions and formations. Column location is west
side of the “horseshoe bend” (GR M34/7677 9441 to M34/7706 9420). The Fossil Record Number (FRF),
field number (MW16/02/03-#), GNS foraminiferal curation number (FRF) and NZMS 260 M34 grid
reference are given.
379
Appendix
380
Appendix
Appendix VI.f. Photographs of mid-Waipara Column 2 sample collection (taken from Morgans et al., 2005).
381
Appendix
382
Appendix
Appendix VI.g. Recovery, gamma-ray, cumulative percent lithology, biostratigraphy and sequence boundary
location of Paleocene strata at Bass River, NJ, with palaeodepth curve derived from benthic foraminiferal
biofacies palaeoslope modeling, percent planktonic foraminifera, and lithology. Horizontal gray lines across
figure represent sequence boundary location. N, nannoplankton Zone and P, Planktonic foraminifera Zone.
Taken from Harris et al., (2010).
383
Appendix
Appendix VI.h. Distribution of Paleocene sediments on the New Jersey Coastal Plain calibrated to the
Berggren et al. (1995) time scale with backstripped record of Kominz et al. (2008). Paleocene hiatuses
correlate to the benthic foraminifera d18O record of Berggren et al. (2000) at DSDP Site 318, and sea level
records of Haq et al. (1987), Hardenbol et al. (1998), Luning et al. (1998) (East Sinai), and Guasti et al.
(2005) (El Kef, Tunisia). New Jersey core holes arranged based on paleoslope model projections. Gray
rectangles with wavy lines represent sediments deposition, white areas show time not represented, and
hatched areas are uncertainty in sequence boundary pick. Lower case “g” in sediments represents glauconite.
Thick gray lines on the δ18O record represent the increases in δ18O that correlate to New Jersey hiatuses.
Taken from Harris et al., (2010).
384
Appendix
Appendix VI.i. From Wei et al., (2005); correlation between ODP Site 1121B, ODP Site 1124C and DSDP
Site 577 based upon δ13C of bulk carbonate. The δ13C of bulk carbonates are from Zachos et al. (1985) and
Shackleton et al. (1985). A total of six chemostratigraphic correlation lines are assigned.
385
Dedication
This thesis is dedicated
icated to Alan, Gail and Ricky Taylor, and Sioned
ioned Mair Roberts.