PALEOCEANOGRAPHY, VOL.
VOL. 12,
12, NO.
NO.2,
PALEOCEANOGRAPHY,
2, PAGES
PAGES175-190,
175-190,APRIL
APRIL 1997
1997
Comparison of
of Imbrie-Kipp
Imbrie-Kipp transfer
transfer function
Comparison
function and
and modern
modern
analog
using sediment
sediment trap
trap and
analog temperature
temperature estimates
estimates using
and core
core
top foraminiferal
top
foraminiferal faunas
faunas
J. D.
D. Ortiz'
Ortiz • and
and A. C.
C. Mix
Mix
College of
of Oceanic
Oceanic and
and Atmospheric
Sciences, Oregon
Oregon State
State University,
University, Corvallis
Corvallis
College
Atmospheric
Sciences,
Abstract. We
estimates
of
(SST)
Abstract.
Weevaluate
evaluatethe
thereliability
reliabilityof
ofstatistical
statistical
estimates
of sea
seasurface
surfacetemperature
temperature
(SST) derived
derived
from
planktonic
foraminiferal
faunas
using
the
modern
analog
method
and
the
Imbrie-Kipp
method.
from planktonicforaminiferalfaunasusingthe modem analogmethodand the Imbrie-Kippmethod.
Global core
core top
provide aa calibration
data set,
set, while
modern sediment
sediment trap
trap faunas
faunas are
are used
used for
for
Global
top faunas
faunasprovide
calibrationdata
while modem
validation. Linear
of
SST generated
generated slopes
slopes close
close to
to one
one
validation.
Linearregression
regression
of core
coretop
toppredicted
predictedSST
SST against
againstatlas
atlasSST
for both
However,
the
transfer
function
temperature
estimates
had
for
bothmethods.
methods.
However,
theJmbrie-Kipp
Imbrie-Kipp
transfer
function
temperature
estimates
hadan
anintercept
intercept
13°C
warmer
than
modern
analog
estimates
and
1.7°C
warmer
than
recorded
atlas
SST.
The
RMS error
error
1.3øCwarmerthanmodemanalogestimates
and1.7øCwarmerthanrecordedatlasSST. The RMS
for the
for
the core
coretop
topdata
dataset
setusing
usingthe
themodern
modemanalog
analogmethod
method(1.5°C)
(1.5øC)was
wassmaller
smallerthan
thanthat
thatof
ofthe
theJmbrieImbrieKipp method
method (1.9øC).
(1.9°C). SST
trap
different
Kipp
SSTerrors
errorsfor
forthe
thesediment
sediment
trapfaunas
faunaswere
werenot
notstatistically
statistically
differentfrom
fromthose
those
of the
functions for
for limited
limited
of
the core
coretop
top data
dataset,
set,regardless
regardlessof
of method.
method.Developing
DevelopingImbrie-Kipp
Imbrie-Kipptransfer
transferfunctions
regions
residual
not
regionsreduced
reducedthe
theRMS
RMS variability
variabilitybut
butintroduced
introduced
residualstructure
structure
notpresent
presentin
inthe
theglobal
globalImbrieImbrieKipp transfer
transfer function.
function. Dissolution
Kipp
Dissolutionsimulations
simulationswith
with the
thesediment
sedimenttrap
trapsample
samplewhich
whichgenerated
generatedthe
the
warmest SST
SST residual
residual for
for both
methods suggests
suggests that
that the
the loss
loss of
water foraminifera
from
warmest
bothmethods
of delicate
delicatewarm
warm water
foraminiferafrom
midlatitude
sediments
may
be
the
cause
of
this
thermal
error.
We
conclude
that
(1)
the
faunal
structure
of
midlatitudesedimentsmay be the causeof this thermalerror. We concludethat (1) the fauna]structure
of
sediment trap
trap and
are
estimate SST
SST reliably
reliably for
for modem
modern
sediment
and core
coretop
topassemblages
assemblages
are similar;
similar;(2)
(2) both
bothmethods
methodsestimate
foraminiferal flux
flux assemblages,
assemblages, but
but the
the modem
modern analog
analog method
method exhibits
exhibits less
less bias;
bias; and
and (3)
(3) both
both methods
methods
foraminifera]
are
relatively robust
are relatively
robustto
to samples
sampleswith
with low
low communality
communalitybut
butsensitive
sensitiveto
toselective
selectivefaunal
faunaldissolution.
dissolution.
than
thanmodern.
modem. This
This 2°-3°C
2ø-3øCcooling
cooling was
wasindicated
indicatedby
by several
several
types of
types
of microfossils
microfossils[Molfino
[Molfino et
et al.
al. 1982].
1982].
Broecker
[1986] compared
compared these
these findings
findings with
with planktonic
planktonic
Broecker[1986]
Because sea
sea surface
surfacetemperature
temperature(SST)
(SST)provides
providesan
an important
important
Because
foraminiferal8180
6'O and concluded
the 8180
6'°O data
data was also
concluded the
also
climate diagnostic
diagnosticon
on aa variety
variety of
of spatial
spatial and
scales, foraminiferal
climate
and temporal
temporal scales,
Stott and
reasonably consistent
with
cooling.
we
assess the
reconstructions
consistent
withaa2°-3°C
2ø-3øC
cooling. Stott
andTang
Tang
we assess
the reliability
reliability of
ofpaleotemperature
paleotemperature
reconstructions reasonably
reached aa similar
similar conclusion
conclusion in
in their
their study
The two
derived from
[1996] reached
studyof
of tropical
tropical
derived
from planktonic
planktonic foraminiferal
foraminifera] faunas.
faunas. The
two [1996]
techniques
most
commonly
used
to
estimate
paleotemperature
8180
measurements.
The
recent
study
of
Broccoli
and
Marciniak
techniquesmost commonly usedto estimate paleotemperature 8180measurements.
The recentstudy BroccoliandMarciniak
from
these microfossils
microfossils are
are the
the transfer
function method
method of
of [1996]
from these
transfer function
[1996] suggests
suggests that
that point
point by
of
by point
pointcomparisons
comparisons
of climate
climate
Imbrie and
awl Kipp
Kipp [1971]
[1971] and
Imbrie
and the
the modern
modern analog
analog method
method of
of model
output
and
observations
reduces
some
of
the
low-latitude
modeloutputandobservations
reduces
someof the low-latitude
Huison [1980]
[1980] as
by Prell
Hutson
as modified
modified by
Prell [1985].
[1985]. Do
Do these
thesetwo
two SST
Unfortunately, they
they could
could not
not make
SSTdiscrepancy.
discrepancy.Unfortunately,
makeaa clear
clear
provide
consistent,
unbiased
paleotemperature
methods
methods provide consistent, unbiased paleotemperature determination
as to
over
determination
as
to the
thevalidity
validityof
of one
oneapproach
approach
overthe
theother.
other.
estimates?
estimates?
coral SrjCa
In
In contrast,
contrast, results
results derived
derived from
from coral
St/Ca paleopaleoA
potential problem
thermometry [e.g.,
[e.g., Beck
Becket
et al.
al. 1992;
1992; Guilderson
et al.
A potential
problem is
is most
mostevident
evidentin
inthe
thetemperature
temperature thermometry
Guilderson
et
al. 1994]
1994]
dilemma
of the
last glacial
ocean and
and a
a variety
variety of
based methods
methods [e.g.,
[e.g., Rind
Rind and
and Peteet,
Peteet,
dilemmaof
the low-latitude
low-latitudelast
glacialmaximum
maximum(LGM)
(LGM) ocean
of terrestrial
terrestrial
based
where
paleotemperature reconstructions
reconstructions differ
may have
have been
been as
as
wheremicrofossil
microfossilpaleotemperature
differ from
from 1985]
1985] suggest
suggestthat
thatlow-latitude
low-latitudeglacial
glacialSST
SSTmay
other
methods by
by as
and are
are inconsistent
inconsistent with
cooler than
than modern.
modem. Because
of this
othermethods
asmuch
muchas
as2°-3°C
2ø-3øCand
with much
much as
as 5°-6°C
5ø-6øCcooler
Becauseof
this apparent
apparent
some
climate model
model results
results [Rind
[Rindand
andPeteet,
Peteet,1985].
1985]. Statistical
Statistical discrepancy,
some climate
discrepancy,we
wereevaluate
reevaluatethe
thereliability
reliability of
of statistically
statistically based
based
reconstructions
planktonic
microfossil SST
reconstructionsbased
basedon
on microfossils
microfossils [e.g.,
[e.g., CLIMAP,
CLIMAP, 1976,
1976, microfossil
SST estimates
estimates derived
derived from
from planktonic
1981]
suggest that
that low
low -- latitude
latitude SST
SSTwas
wasat
at most
most 2ø-3øC
2°-3°C cooler
cooler foraminiferal
foraminiferal faunas
faunasusing
using the
the transfer
transfer function
function method
method of
1981] suggest
of
Introduction
Introduction
Imbrie and
and Kipp
Kipp [1971]
[1971] and
lmbrie
and the
the modern
modernanalog
analogmethod
methodof
of
Hutson [1980]
as modified
modified by
byPrell
Prell [1985].
[1985]. Our
Hutson
[1980] as
Ouranalysis
analysisdiffers
differs
'Now at
Earth
Observatosy
of
University,
previous sediment
based studies
studies in
in that
SST
1Now
atLamosn-Doherty
Lamont-Doherty
Earth
Observatory
ofColumbia
Columbia
University, from
fromprevious
sedimentbased
thatwe
weestimate
estimate
SST
Palisades, New York.
Palisades,
for
trap assemblages
assemblages caught
caught in
in the
for sediment
sedimenttrap
thewater
watercolumn
columnas
as
to
whether
well
well as
asfor
for core
coretops.
tops. This
This test
testis
isdesigned
designed
to assess
assess
whether
Copyright
1997
Geophysical
Union.
Copyright
1997by
bythe
theAmerican
American
Geophysical
Union.
smoothing
modification involved
involved with
with the
the generation
of
smoothingand
andmodification
generation
of
faunal
SST
the
fossil
record
induces
bias
in
foraminiferal
the
fossil
record
induces
bias
in
foraminiferal
faunal
SST
Paper
Papernumber
number96PA02878.
96PA02878.
estimates.
estimates.
O883-83O5/976PA-O2878$l2.00
0883-8305/97/96PA-02878512.00
175
175
ORTIZ AND
AND MIX:
MIX: SEDIMENT
SEDIMENT TRAP-CORE
TRAP-CORE TOP
TOP COMPARISON
COMPARISON
ORTIZ
176
those
thosefrom
from PrelI
Prell [1985]
[1985] and
andselected
selectedsamples
samplesfrom
from Parker
Parkerand
and
Berger
[1971],
Coulbourn
Ct
al.
[1980],
and
Thompson
Berger [1971], Coulbournet al. [1980], and Thompson[1981].
[1981].
Core Top
Top and
Trap Data
Samples
to
Core
and Sediment
Sediment Trap
Data Sets
Sets
Samplesin
in these
thesedata
datasets
setswere
werescreened
screened
toexclude
excludeduplicates
duplicates
and
samples
with
erroneous
locations
(A.
E.
Morey
and
samples
with
erroneous
locations
(A.
E.
Moreyand
andA.
A. C.
C.
Prell
of Hutson
Prell [1985]
[1985] tested
tested the
the modem
modem analog
analog method
method of
Hutson
To
account
communication,
1996).
for
Mix,
personal
Mix,
personal
communication,
1996).
To
account
for
[1980] and
and demonstrated
that with
[1980]
demonstrated
that
with slight
slightmodification,
modification,it
it yields
yields
in the
the taxonomy
used by
by various
differencesin
taxonomy used
various workers,
workers, we
we
function differences
essentially
identical SST
essentially identical
SST results
results to
to the
the transfer
transfer function
employed
a
subset
of
27
taxonomic
species
and
lumped
some
approach of Imbrie and Kipp [1971]. These tests were employeda subsetof 27 taxonomicspeciesand lumpedsome
Methods
Methods
approach of lmbrie and Kipp [1971].
These tests were taxonomically similar species into morphologic groups. The
taxonomically similar speciesinto morphologic groups. The
four
four morphologic
morphologicgroups
groupswe
we employed
employedare
are (1)
(1) G.
G. ruber
ruber(total),
(total),
which
includes
both
the
pink
and
white
varieties;
(2) G.
which includesboth the pink arid white varieties; (2)
G.
sacculifer
(total),
which
includes
G.
trilobus
and
G.
sacculifer;
sacculifer(total), which includesG. trilobus andG. sacculifer;
(3) G. menardii (total), which includes G. menardii, G. menardii
stratigraphic sampling
(2) dissolution
errors, (3)
stratigraphic
sampling errors,
errors, (2)
dissolution errors,
(3) (3) G. menardii (total), which includesG. menardii, G. menardii
flexuosa (=neoflexuosa),
and G.
G. tumida;
and (4)
fiexuosa
(=neofiexuosa),and
turnida;and
(4) N.
N. dutertrei
dutertrei
bioturbation
which
mixes
together
foraminiferal
shells
from
bioturbation which mixes together forarniniferalshells from
(which
the
"Neogloboquadrina
pachyderma
includes
(which
includes
the
"Neogloboquadrina
pachyderma
-different
times,
and
(4)
the
possibility
that
the
statistical
different times, and (4) the possibility that the statistical
Neogloboquadrina
dutertrei
(P-D)
intergrade"
category
of
Kipp
correlation
to SST
SST observed
observedinin the
the core
core top
top faunas
is not
correlation to
faunas is
not Neogloboquadrinadutertrei(P-D)intergrade" categoryof Kipp
[1976]). We believe the P-D intergrade category to be
present in
in the
is aa secondary
present
the living
living faunas
faunasbut
but rather
rather is
secondaryartifact,
artifact, [1976]). We believe the P-D intergrade category to be
conspecific
with
based on
conspecific
with N.
N. dutertrei
dutertreibased
on our
ourplankton
planktontow
towand
and
caused,
for
example,
by
the
correlation
of
SST
with
other
caused,for example, by the correlation of SST with other
sediment trap
trap studies
sediment
studies[Ortiz
[Ortiz and
andMix,
Mix, 1992;
1992;Ortiz
Ortiz et
etal.
al.1995].
1995].
environmental variables.
environmental
variables.
The sediment
The
first three
three problems
problems may
as
The
sedimenttrap
trap data
data are
are of
of known
knownmodem
modemage
ageand
and
The first
may be
be expressed
expressed
aseither
eitherrandom
random
essentially
free
of
dissolution.
Table
1
provides
information
or
in the
or systematic
systematicerrors
errorsin
the SST
SSTestimates
estimatesderived
derivedfrom
from either
either essentially free of dissolution. Table 1 provides information
the locations
locations of
of the
method. We
error by
by calculating
error regarding
regardingthe
the sediment
sedimenttrap
trapfaunas
faunasand
andtheir
their
method.
We assess
assessrandom
randomerror
calculatingthe
the RMS
RMS error
sources,
while
Table
2
lists
the
flux-weighted
foraminiferal
for
each
method.
We
assess
systematic
bias
in
each
method
by
sources,
while
Table
2
lists
the
flux-weighted
foraminiferal
for eachmethod. We assesssystematicbias in eachmethodby
trap samples
determining
the slope
faunasfrom
from these
theselocations.
locations. The
The sediment
sedimenttrap
sampleshave
have
determiningthe
slopeand
andintercept
interceptof
of actual
actualversus
versusestimated
estimated faunas
the
disadvantage
of
short
integration
times,
ranging
residuals for
SST
and by
from
SST regressions
regressions and
by testing
testing residuals
for statistically
statistically the disadvantageof short integration times, ranging from
months to
to 66 years.
we several
trends.
To address
significant
several months
years. Poorly
Poorly resolved
resolvedinterannual
interannual
significant trends.
To
address the
the fourth
fourth problem,
problem, we
variation may
To assess
effect, the
assembled
a validation
validation data
data set
set of
assembled a
of foraminiferal
foraminiferal faunas
faunas from
from 13
13
variation
may affect
affect the
the results.
results. To
assessthis
this effect,
the
modem analog
analog method
sediment
trap locations
locations (Figure
including our
ourthree
three sites
sites at
methodand
andQ-mode
Q-modefactor
factoranalysis
analysisprovide
provide
sedimenttrap
(Figure 1)
1) including
at modem
estimates of
of how
how different
different the
the sediment
sediment trap
trap faunas
42°N
in the
quantitative
estimates
faunas
42øN in
the California
California Current
Currentand
andaapreviously
previouslyunpublished
unpublished quantitative
are
from
the
sedimentary
faunas.
data
set
from
a
site
in
the
equatorial
Pacific,
Manganese
Nodule
faunas.
datasetfrom a sitein the equatorialPacific, ManganeseNodule are from the sedimentary
Unlike
the core
core top
top data
data set,
set, the
the sediment
counts
Project (MANOP)
Unlikethe
sedimenttrap
trapfaunal
faunalcounts
Project
(MANOP) Site
SiteC.
C.
We compare
comparethe
the sediment
sedimenttrap
trap validation
validationdata
data set
set with
not all
all based
based on
on the
the >150
>150 g.rn
im size
We
with aa are
arenot
sizefraction.
fraction. Ideally,
Ideally, the
the
calibration
sediment trap
trap samples
in
calibrationdata
dataset
set of
of 1121
1121 core
coretops
tops(Figure
(Figure2)
2) composed
composedof
of sediment
samplesshould
shouldbe
beprocessed
processed
in aamanner
mannerwhich
whichis
is
conducted
using core
core top
top foraminiferal
conductedusing
foraminiferal faunas
faunasfrom
from the
the three
three
of
major
basins.
Unfortunately,
major ocean
ocean basins.
Unfortunately, validation
validation of
paleotemperature
proxy
methods
based
on
core
top
data
alone
palcotemperature
proxy methodsbasedon core top data alone
has several
These include
has
several potential
potential sources
sourcesof
of bias.
bias. These
include (1)
(1)
90
9O
o0
30
30
60
60
90
90
120
120
150
150
180
180
150
150
120
120
90
90
60
60
30
30
0
0
90
9O
60
6O
60
60
+
4
30
w
i,i
30
:::)
0
C3
+
30
30
+
.7 5
,",• 8
+
10
+
9'
0
30
30
30
30
60
'11 12 13, 60
60
90
90
0
0
I
30
50
I
I
I
60
60
90
90
120
120
I
I
I
I
I
150
150
I
I
II
I
I
180
180 150
150 120
120
•i•
I
I
I
90
90
60
60
30
30
0
60
90
90
LONG 1U DE
LONGITUDE
FIgure
of the
usedin
in the
the paper.
paper. Numbers
next to
to each
each trap
trap location
location
Figure 1.
1. Locations
Locationsof
the13
13sediment
sedimenttrap
trapfaunas
faunasused
Numbersnext
correspond
to map
map indices
in Table
Table 1.
for
sample
correspond
to
indicesin
1. References
References
foreach
eachpublished
published
sampleare
arelisted
listedin
in Table
Table1.
1.
177
ORTIZ AND MIX: SEDIMENT
TRAP-CORE TOP
TOP COMPARISON
COMPARISON
SEDIMENT TRAP-CORE
30
3O
0
90
9O
60
60
90
90
120
120
150
150
180
180
150
150
120
120
90
90
60
30
30
0
0
90
9O
60
6O
6O
30
3O
3O
w
aD
0
30
3O
+
+
60
6O
90
9O
0
0
30
60
90
120
150
180
150 120
90
60
30
LONGITUDE
LONGITUDE
FIgure 2.
for
in
Figure
2.Locations
Locations
forthe
the1121
1121core
coretop
topsamples
samples
inthe
theglobal
globalcore
coretop
topdata
dataset.
set.
identical
to that
identicalto
that of
of the
thecore
coretop
topsediments.
sediments.In
In our
ourstudies
studieswe
we
have
both the
the 125-150
>150 [lxn
p.m size
size fractions.
fractions.
have measured
measured
both
125-150 and
and>150
contributions
from each
each of
of the
the 27
27 taxa
taxa (see
(see Table
Table3).
3). A
contributions
from
A varimax
varimax
rotation is
is applied
assemblages
rotation
appliedto
to Fct
Fctso
sothat
thatthe
theresulting
resulting
assemblages
remain close
closeto
to the
the centroid
centroid of
of the
the sample
sample data.
data. This
This
us to
to easily
our samples
samples to
to >150
Thisrotation
rotation
This allows
allows us
easily compare
compareour
>150 pm
[lxn remain
has the
advantage
of producing
producing orthogonal
orthogonal assemblages
with
has
the
advantage
of
assemblages
with
sediments
or
>125
pm
sediment
trap
samples.
We
recommend
sedimentsor >125 •m sedimenttrap samples. We recommend
generally
positive coefficients
that
are
more
easily
interpreted
generally
positive
coefficients
that
are
more
easily
interpreted
that
future
sediment
trap
and
plankton
tow
studies
follow
this
that futuresedimenttrap andplankton tow studiesfollow this than an unrotated solution.
elements of
of Bet
Bct describe
the
thananunrotated
solution.The
Theelements
describe
the
fraction. While
procedure
focuson
on the
the >150
procedureororfocus
>150 pm
[lxnsize
size fraction.
While
relative
contribution
of
each
variinax
assemblage
to
each
core
relative
contribution
of
each
varimax
assemblage
to
each
core
variations
in
sieve
size
introduce
some
uncertainty
in
the
variations in sieve size introduce some uncertainty in the
top
sample. The
described by
by its
its communality
(the
topsample.
Themodel
modelfit
fit is
is described
communality
(the
sediment trap
trap to
to core
core top
sediment
top comparison,
comparison,the
theresidual
residualerrors
errorswe
we sum
of
squares
of Bct
or the
normalized
vector
length),
which
is
sum
of
squares
of
Bet
or
the
normalized
vector
length),
which
is
obtained are
are not
not correlated
correlated with
with sieve
sievesize
sizevariations.
variations. Any
Any bias
bias
obtained
a linear
measureofof the
the fraction
linear measure
fraction of information
information retained
retained from
from
introduced
by this
this source
source of
of error
error is
is thus
thus not
not systematic.
introducedby
systematic. These
These
each
sample
[Imbrie
and
Kipp,
1971].
A
perfect
model
fit is
is
each
sample
[Imbrie
and
Kipp,
1971].
A
perfect
model
fit
potential
sources
of
error
will
be
evaluated
further
in
the
potential sourcesof error will be evaluatedfurther in the
achieved
when
communality
goes
to
1,
and
Ect=O.
achieved
whencommunality
goesto 1, andEct=0.
discussion to follow.
discussion
follow.
We use
use the
the transpose
of the
We
transpose
of
thecore
coretop
topfactor
factorscore
scorematrix
matrix
(FTct)
to
evaluate
the
structure
of
the
sediment
trap
data
matrix
(F?ct)
to
evaluate
the
structure
of
the
sediment
trap
datamatrix
Q-Mode
Factor Analysis
Q-Mode Factor
Analysis and
and Imbrle-Kipp
Imbrie-Kipp Transfer
Transfer
(Ust)
by
determining
a
factor
loading
matrix
(Bst)
for
the
(Ust)
by
determining
a
factor
loading
matrix
(Bst)
for
the
Functions
Functions
sediment trap
sediment
trapdata
dataset:
set:
As
first step
As aa first
step in
in the
thecomparison
comparisonof
of core
core top
top and
andsediment
sediment
U5
(2)
Bst ++Est
Et
trap
we calculated
calculatedaa Q-mode
Q-modefactor
factormodel
modelfor
for the
the global
global
UstFTct
FTct= Bst
(2)
trapfaunas,
faunas,we
core
top
database
following
Imbrie
and
Kipp
[1971].
Q-mode
core top databasefollowing Imbrie andKipp [1971]. Q-mode This assumes that the structure of the core top assemblages
that the structure
of the coretop assemblages
factor
means of
of This assumes
factor analysis
analysisprovides
providesan
an objective,
objective,quantitative
quantitativemeans
apply
to
the
sediment
trap
faunas.
if
is not
apply
to
the
sediment
trap
faunas.
ff this
this assumption
assumptionis
not
is accomplished
accomplished by
by
simplifying complex
simplifying
complex data
datasets.
sets. This
This is
correct,
the
resulting
sample
communality
will
be
low,
and
the
correct,
the
resulting
sample
communality
will
be
low,
and
the
decomposing
the
core
top
data
matrix
(Uct)
into
a
factor
score
decomposing
the core top datamatrix (Uct) into a factor score elements of Est will be nonzero. If the distribution of the core
elementsof Est will be nonzero. If the distributionof the core
matrix
loading matrix
matrix (Bct),
(Bct), and
matrix
matrix(Fat).
(Fct), aa factor
factorloading
andan
an error
errormatrix
top assemblages
are controlled
controlled by
by their
their environment,
environment, then
top
assemblages
are
then Bstt
(Eci:
(Ect):
should
produce
distinct
patterns
shouldproducedistinct patterns when
whenplotted
plotted against
against aa
controlling environmental
(1) controlling
environmentalvariable
variable such
suchas
as SST
SST [Imbrie
[Imbrie and
and
Ect
Uct == Bt
BetFct
Fct + Ect
(1)
Kipp, 1971].
structure of
of the
Kipp,
1971]. However,
However, ifif the
the fundamental
fundamentalstructure
the
the core
core top
top percent
percent abundance
abundancedata,
data,is
is based
based on
on counts
counts sediment trap faunas differs from that of the core top faunas,
Uct, the
sedimenttrapfaunasdiffersfromthat of the coretop faunas,
then the
pattern of
of B5t
with respect
respect to
to SST
SST will
will not
not
of n=27
121 coretops.
thedistribution
distribution
pattern
Bst with
of
n=27 planktonic
planktonicforaminiferal
foraminiferaltaxa
taxa in
in N=1
N=1121
coretops. then
Each core
core top
topfauna
faunain
inUct
Uctisisrow
rownormalized
normalizedso
sothat
thatits
its sum
sum of
of match
match that
that of
of Bet.
Each
Bct.
squares is
isunity.
unity. The
The elements
elements of
of the
the factor
matrix, Fct,
The core
core top
top factor
factor loadings
loadings in
in Bct
against
squares
factorscore
scorematrix,
F ct,
The
Bct were
wereregressed
regressed
against
describe
m
varimax
rotated
assemblages
composed
of
weighted
SST
to
develop
a
stepwise
least
squares
transfer
function.
describem varimaxrotatedassemblagescomposedof weighted SST to developa stepwiseleast squarestransferfunction.
ORTIZ AND MIX:
TRAP-CORE TOP COMPARISON
MIX: SEDIMENT TRAP-CORE
178
Following
and
FollowingImbrie
lmbrieand
andKipp
Kipp[1971],
[1971],we
weinclude
includesquared
squared
andcross
cross
These
product
tenns for
factor in
in the
the stepwise
stepwise regression.
productterms
for each
eachfactor
regression. These
tms are
included
ininthe
if their
terms
are
included
thefinal
finalregression
regressionif
their partial
partialFF value
value
0\
00
0
.
. ,
,
j";l
exceeds the
the critical
exceeds
critical 5%
5% significance
significancethreshold.
threshold.Squared
Squaredand
and
cross
terms are
are included
includedso
so that
that our
crossproduct
productterms
our results
results can
can be
be
compared with
with equations
equations of
of the
compared
the type
typedeveloped
developedfor
forCLIMAP
CLIMAP
[1976,
because each
eachfactor
factormay
mayexhibit
exhibit nonlinear,
nonlinear,
[1976, 1981]
1981] and
and because
parabolic
responses
to
temperature
and/or
interactive
parabolic responsesto temperatureand/or interactiveeffects
effects
[Imbrie
and Kipp,
Kipp, 1971].
1971]. The
[lmbrie and
The regression
regressioncoefficients
coefficientsfrom
from the
the
global Imbrie-Kipp
Imbrie-Kipp transfer
transfer function
function are
are used
used with
with the
global
the sediment
sediment
trap factor
trap
factor loadings
loadings in
in B5t
Bst to
to determine
determine Imbrie-Kipp
Imbrie-Kipp
temperature
estimates
for
each
of
the
sediment
trap faunas.
faunas.
temperatureestimatesfor eachof the sedimenttrap
The
transfer
function
SST
is
compared
with
The transfer function SST is comparedwith seasonally
seasonally
weighted SST
SST from
from each
each trap
trap location
weighted
location obtained
obtainedfrom
from Levitus
Levitus
[1982].
for each
is
[1982]. The
The SST
SSTweighting
weighting for
each trap
trap temperature
temperatureis
detennined from
from its
its duration
determined
durationand
anddeployment
deploymentseason.
season. This
This
procedureisis necessary
necessary because
becausesome
someofof the
the sediment
procedure
sediment trap
trap
deployments
did not
not sample
samplethe
theentire
entireannual
annualcycle.
cycle. Assigning
Assigning
deploymentsdid
an
forarniniferal
an annual
annual average
averagetemperature
temperatureto
to aasubannual
subannual
foraminiferal
fauna
would introduce
introducean
an unrealistic
unrealistic temperature
temperaturebias
bias to
to our
fauna would
our
comparisons.
comparisons.
jU
.
'nO
00 In In 00 CV) In
N In in In N N C C N In N N
The
The Modern
Modern Analog
Analog Method
Method
AAAAAAAAAAAAA
AAAAAAAAAAAAA
o o 00000 N 0 In 00 m
NNNNNN
0%'n N
.'Cl
NN cfl N
We
calculate modern
modernanalog
analog SST
SST from
from the
the sediment
We calculate
sedimenttrap
trap
faunasusing
usingthe
thecore
coretops
topsas
asthe
thecalibration
calibrationdata
dataset.
set. We
then
faunas
We then
compare
these SST
SST
comparethese
SST estimates
estimateswith
withmeasured
measured
SSTvalues
valuesfrom
from
Levitus
[1982] at
at the
the sediment
sedimenttrap
traplocations.
locations. As
As aa final
final test
test of
of
Levitus[1982]
the
modern
analog
method,
we
estimated
modern
analog
SST
for
the modem analogmethod,we estimatedmodemanalogSST for
each
core top
top in
each core
in the
thedatabase
databaseby
by comparison
comparisonagainst
againstevery
every
other
This global
other core
core cop
top in
in the
thedatabase.
database. This
global calculation
calculation is
is
similar to
to the
the separate
separate ocean
ocean basin
basin calculations
calculationsof
ofPrell
Prell [[1985].
similar
1985].
000000000%00%N00 IO
It
the level
level of
of variation
variation in
in the
It allows
allows us to evaluate
evaluate the
the sediment
sediment
trap
versus
core
top
comparison
against
the
level
of
variation
trapversuscore top comparisonagainstthe level of variation
observed
observedin
in the
thecore
coretop
topdata
dataset.
set.
The
compares planktonic
method compares
planktonic
The modem
modem analog
analog method
foraminiferal
assemblages
in
samples
with
unknown
foraminiferal assemblages in samples with unknown
environmental
conditions (SST
(SSTin
in this
this application)
application) with
environmentalconditions
with core
core
tops from
tops
from locations
locations with
with known
known environmental
environmental conditions.
conditions.
The
two basic
basic assumptions
analog method
The two
assumptionsfor
for the
the modern
modernanalog
methodare
are
similar
to
those
of
the
Imbrie-Kipp
transfer
function.
first
similar to thoseof the Imbrie-Kipp transferfunction. The
The first
ON 00
NO in N 0000 c %D ifl
C N In 0 In N 000000 N Ifl
NN
in in vi N 00
O 0' 0%
C
In
00 In N In ON '
In C Cfl In C C C)
0%
c,cn--
I
6
.
u
U
u
v-i '0 N 000% 0N m
I
J
assumption is
is that
that similar
faunal assemblages
are
assumption
similarforaminiferal
foraminiferalfaunal
assemblages
are
produced
by similar
similar suites
suites of
l:noduced
by
of environmental
environmentalconditions.
conditions. The
The
second
assumption is
is that
that SST
SST is
is the
secondassumption
the environmental
environmentalvariable
variable
which
determines
variation
in
foraminiferal
or
which determinesvariation in foraminiferalassemblages
assemblages
or is
is
correlated with
with environmental
variables which
which determine
determine
environmental
variables
foraminiferal variation.
foraminiferal
variation.
The
holds well
well for
formost
mostof
of the world
world ocean.
ocean.
The first
farstasswnpcion
assumption
holds
One
notable
exception
to
the
rule
occurs
at
very
high
northern
Onenotableexception
to the ruleoccursat very high northern
and southern
climatic extremes,
extremes, the
the
and
southern latitudes.
latitudes. At
At these
these climatic
foraminiferal fauna
fauna becomes
becomes essentially
essentially monospecific,
foraminiferal
monospecific,
dominated
by left-coiling
However, high
high
dominatedby
left-coilingN.
N.pachyderma.
pachyderma. However,
southern
latitudes
are
cooler
by
l°-2°C
than
high
northern
southernlatitudesare cooler by 1ø-2øCthan high northern
foraminiferal
latitudes.
faunas attain
latitudes. Because
Because
foraminiferalfaunas
attain essentially
essentially
monospecific
status well
well before
before extremely
extremely cold
cold southern
southern ocean
ocean
monospecific
status
SST
values are
arereached,
reached,use
useofofaa global
global data
SSTvalues
dataset
setto
topredict
predict
modem
analog SST
modemanalog
SST at
at extremely
extremelyhigh
high latitudes
latitudescan
can give
give
erroneous
resultsdue
ckntoto the
the averaging
of SST
erroneousresults
averaging of
SST from
from both
both
hemispheres.
hemispheres.To
To avoid
avoidthis
thisproblem,
problem,we
wefollow
followthe
thestandard
standard
.g
0.0
0.0
6.7
6.7
21.9
0.0
0.0
1.8
27.4
14.2
17.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
58.2
,• 4 c:5c:5c5 d d d d c:5d c5 c:5•
•
c:5c• d c:5d N d d c:5•
d d
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d d
10.8
dd
1.8
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dd
8.6
0.0
6.7
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0.0
dd,4c•
1.8
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dd
0.0
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o.o
0.7
24.1
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17.5
4.9
d •: dK
0.0
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dd
dd
0.0
0.0
0.0
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oo
d•
0.0
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d •: d N dd,4d
0.0
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d d d d d d •
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11.8
d,-4
6.0
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d N d d
1.4
d d d d c5 •:c5 d d d d d N cSK
17.0
0.0
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0.0
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0.1
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0.8
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03
1.5
0.0
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5.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
6.4
3.6
23.5
0.8
23.5
0.0
0.0
0.0
0.0
0.0
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0.3
1.3
0.3
0.0
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27.2
1.9
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0.0
0.0
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2.0
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8.2
0.0
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0.0
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6.5
1.5
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13.3
0.3
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0.0
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21.6
10
10.0
38.4
0.0
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1.8
d•dddd••dd•dKNdddddddd•dK
13.0
9
8
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11
0.0
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92.0
6.3
0.0
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13
12
ooooooooo.
16.2
15.2
4.8
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N •
1.8
2.7
2.0
14.8
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5.2
0.0
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0.9
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7
o
0.0
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33.4
0.0
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dd
0.0
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0.0
0.0
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0.0
2.9
,4 d 'dddd,4c•dd4•:Kdddddddd4d,4
0.0
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0.0
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,4 d•
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00
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o. o.o.
o.o.o.o.o.o.o.o.o.o.o.o.o.o.o.
d•
aSome rare species that were reported in the original sources are omitted here from the flux weighted percents because these taxa were not unifornily reported
by all workers. These categories were essentialy treated as unidentified.
bG. ruber (total) = G. ruber (white) and G. ruber (pink); G. saccu1fer (total) = G. sacculjfer and G. trilobus; G. nwnardii (total) = G. menardii, G. tumida, and
G. menardii neoflexuosa.
0. wziversa
G. conqlobatus
G. ruber (total)"
G. tenelus
G. sacculifer (total)"
S. dehiscens
G. aequilaierahs
G. calida
G. builoides
G. faclonensis
G.digilata
G. rubescer,.s
G. quinqueloba
Left-coiling N. pachyderma
Right-coiling N. pachyderma
N. dutertrei
G. conglo,nerata
G. hexagona
P. obliquiloculata
G. inflata
Left-coiling G. truncatulinoides
Right-coiling G. truncatu1iroides
G. crassaformis
G. hi,yuta
G. scitiila
G. menardii (total)"
G. glutinata
5
•:
1
Map Locations
Table 2. Flux-Weighted Percent Abundance for the Sediment Trap Foraminiferal Faunas as Numbered in Table 1
7
9
ORTIZ AND MIX: SEDIMENT TRAP-CORE TOP COMPARISON
179
ORTIZ
ORTIZ AND MIX:
MIX: SEDIMENT
SEDIMENT TRAP-CORE
TRAP-CORE TOP
TOP COMPARESON
COMPARISON
180
Table
Varimax
Factor Model
Model Based
Based on
on 1121
1121 Core
Core Tops
Tops
Table 3.
3. Factor
FactorScores
Scoresfor
forthe
theSeven-Factor,
Seven-Factor,
VarimaxRotated,Q-Mode
Rotated,Q-Mode Factor
Factor
Factor1,
1,
Taxon
Taxon
0. w&iversa
O.
universa
G.rub.T.I
G. rub. T./
Gsac. T.
G•vac.
T.
G. conglobatuSo
conglobahts
G.
0.02
0.02
0.05
0.05
G. tenelus
tenalus
G.
0.04
0.04
G. sacculiœer
sacculifer (total)
G.
(total)
ø
0.31'
0.31'
G. ruber
rube, (total)
G.
(total)
S. dehiscens
dehircens
S.
aequiloieralLc
G. aequilateralis
G. calma
caliihi
G.
G. bulloides
bulloides
G.
G.facloneans
G. faclonensis
digitata
G. di•#ata
G.
G. rubescerss
rubescerts
G. ½uincueloba
quinqueloba
Left-coiling
N. pachyderma
pachyderma
Left-coiling N.
Right-coiling
N. pachwlerma
pachwie,,na
Ri•at-coiling N.
N. dutertrei
duterirci
N.
G.
G. conglomerala
conl•lomerata
G.
G. hexagona
hexagona
P. obli•uiloculata
obliquioculata
P.
G.inflata
G. i.n//ata
Left-coilingG. truncatulinoides
truncatulinoides
Right-coilingG.
Right-coilingG.truncalulinoides
truncatulinoides
G. crassaformis
crassaformis
G.hirsuta
G. hirsuta
G.sciwia
G. scitula
G.
(total)
G.,nanardii
menardii
(total)
ø
G. •lut/nata
glutinata
G.
Infonnation
per Factoff
Factot
Informationper
0.90'
0.00
0.00
0.10
0.05
-0.03
-0.03
0.05
0.05
0.01
0.01
0.03
-0.01
0.02
0.02
-0.04
0.02
0.02
0.01
0.02
0.01
-0.02
0.02
0.02
0.02
0.
02
0.01
0.01
0.01
0.01
0.01
0.05
0.05
0.26
0.26
27.4%
27.4%
Factor
Factor2.
2,
G. men.
G.
men.T.
T.
Factor
Factor3.
3,
N.pac.L
N. pac. L.
0.00
0.00
0.01
0.01
-0.05
-0.01
-0.01
0.07
0.07
0.03
0.03
0.01
0.01
-0.01
0.06
0.06
-001
-0.01
0.02
-0.01
-0.01
-0.01
-0.01
-0.00
-0.00
-0.09
0.03
0.03
0.04
0.01
0.12
0.03
0.01
0.01
0.01
0.01
0.00
0.00
-0.00
-0.00
0.01
0.01
-0.01
-0.01
0.03
0.03
0.00
0.00
-0.01
-0.01
-0.01
0.17
0.17
-0.04
-0.04
0.00
-0.01
-0.01
0.12
0.97'
0.97'
0.04
0.04
0.02
0.02
0.00
-0.00
-0.00
0.03
0.03
-0.02
-0.02
-0.01
001
0.01
0.00
0.00
0.00
0.00
-0.01
-0.01
-0.00
-0.00
0.97'
0.97'
-0.14
12.1 %
12.1%
Factor
Factor4.
4,
G.inf.
G.
inf.
Factor 5,
Factor
5,
N.dul.
N. dut.
0.00
0.00
-0.00
-0.00
-0.05
-0.00
-0.00
0.04
0.04
-0.00
-0.00
0.03
0.03
0.00
0.00
0.06
-0.00
-0.00
-0.02
-0.02
0.00
0.00
-0.00
0.01
0.01
0.13
0.13
0.13
0.13
0.01
0.01
-0.01
-0.01
0.01
0.01
-0.03
-0.03
0.26
0.26
0.08
0.08
-0.01
-0.01
0.03
0.03
0.92'
0.92'
0.09
0.09
0.10
0.10
0.01
0.01
-0.06
-0.06
-0.03
-0.03
.0.00
-0.00
-0.00
-0.00
0.01
0.01
-0.01
-0.01
0.10
0.98'
0.98'
0.01
0.01
0.01
-0.04
-009
-0.09
-0.02
-0.02
-0.03
-0.03
0.00
0.00
0.02
0.02
0.05
-0.01
-0.01
0.03
0.03
0.00
-0.03
-0.03
-0.04
-0.04
-0.12
-0.12
-0.12
-0.12
12.5%
12.5%
-0.01
-0.01
0.05
0.05
14.6%
14.6%
8.4%
8.4%
Factor
Factor6,
6,
G.
G. bulIJ
bull./
G.glut.
G. glut.
0.01
0.01
0.00
0.00
Factor
Factor7.
7,
P.obliq.
P.
obliq.
0.01
0.04
0.04
-0.11
-0.11
-0.11
-0.11
0.02
0.02
0.00
0.00
-0.08
-0.08
-0.00
-0.00
0.02
0.02
0.02
0.02
0.01
0.01
0.11
0.11
0.00
0.00
0.06
0.06
-0.16
-0.16
-0.02
-0.02
-0.00
-0.00
0.02
0.02
0.06
0.06
-0.07
-0.07
0.05
0.05
-0.01
0.04
0.04
0.04
0.01
0.81'
0.81'
0.05
0.05
0.01
0.00
0.02
-0.03
-0.07
-0.07
0.00
0.01
0.01
-0.01
-0.01
-0.01
-0.01
0.02
0.04
0.04
0.55'
0.55'
11.5%
11.5%
0.01
0.00
0.00
0.03
0.03
-0.01
0.93'
0.93'
0.03
0.03
-0.03
-0.03
-0.02
-0.00
-0.00
-0.01
-0.01
-0.00
-0.07
-0.07
0.27
0.27
5.1%
5.1%
Dnninant species.
•Dominant
species.
G.
(pink);
G.
(total)
==G.G.saculjfer
and
G.G.trilobMs;
G.
G. rube,
ruber(total)
(total)== G.
G.rube,
ruber(white)
(white)and
andG.
G.rube,
tuber
(pink);
G.saccu1fer
sacculifer
(total)
saculifer
and
trilobus;
G. menardii
menardii(Total)
(Total)==
G. menardii,
,nenardii, G.
G.
G. twnida,
turnida,and
andG.
G. menardii
menardiineoflexuosa.
neoflexuosa.
1ota1
explained:
91.5%.
•Fotalinformation
information
explained:
91.5%.
procedureof
ofPrell
Preli [1985]
[1985] and
and compare
compare high-latitude
high-latitude (northern)
(northern)
procedure
southern
hemisphere trap
trap samples
samples against
against (northern)
southernhemisphere
(northern)southern
southern
hemisphere core
core top
hemisphere
top samples
samplesonly.
only.
Assessment
of the
the second
Assessment
of
secondassumption
assumptionis
is more
moreproblematic.
problematic.
For
relatively
small
spatial
scales
and
short
For relatively small spatial scales and short timescales,
timescales,
absolute
foraminifera
absoluteabundance
abundanceassemblages
assemblagesof
of planktonic
planktonic foraminifera
from plankton
plankton tow
from
tow and
andseasonal
seasonalsediment
sedimenttraps
trapsdemonstrate
demonstrate
factors (food
greater control
control by
and
greater
by biological
biological factors
(foodavailability
availability and
light)
than
temperature
[Fairbanks
and
Wiebe,
1980;
Watkins
light) than temperature[Fairbanlcsand Wiebe, 1980; Watkins
et al.
al. 1996;
Mix, 1992;
Here we
et
1996; Ortiz
Ortiz and
and Mix,
1992; Ortiz
Ortiz et
et al.
al. 1995].
1995]. Here
focus on
on the
the relative
relative abundance
abundance of
of foraminiferal
foraminiferalassemblages
assemblages at
at
focus
large
spatial
scales,
integrated
over
time
scales
of
generally
large spatial scales, integratedover time scalesof generally
longer than
than the
the annual
cycle.
Under
longer
annual cycle.
Under such
such conditions,
conditions,
foraminiferal core
core top
top assemblages
exhibit relatively
relatively strong
foraminiferal
assemblages
exhibit
strong
relationships
to SST
1971; PrelI,
relationships to
SST [e.g.,
[e.g., Imbrie
lmbrie and
andKipp,
Kipp, 1971;
Prell,
angle [Prentice,
[Prentice, 1980;
1980; Overpeck
Overpecket
etal.
al. 1985].
1985]. The
angle
Theuse
useof
of the
the
squaredchord
chorddistance
distancetends
tends to
to increase
increase the
of
squared
theimportance
importance
ofrare
rare
species and
decreasethe
the importance
importanceof
of abundant
abundantones
ones so
so that
species
anddecrease
that
differences in
in the
the abundant
abundant species
species alone
alone do
do not
not dominate
dominate the
the
differences
Prell
[1985]
demonstrated
that
the
dissimilarity
estimate.
dissimilarity estimate. Prell [1985] demonstratedthat the
squaredchord
chorddistance
distanceworked
workedwell
well with
with foraminiferal
squared
foraminiferalfaunas.
faunas.
Accordingly, we
we use
use the
chord distance
distance between
Accordingly,
the squared
squaredchord
betweenthe
the
target sample
sample and
and each
each core
coretop
top in
in the
the database
as
of
target
database
asaameasure
measure
of
intersample
dissimilarity:
intersampledissimilarity:
rn
m
1/22
d=[p
it
diJ
_ 1/2•2
= • [Pill/2
--pit
PjI•
1
1t2
k=1
I
(3)
(3)
k=l
In this
d11 is the squared chord distance between the ith
In
thisnotation,
notation,
dijis thesquared
chorddistance
between
theith
and jth samples, while p. and p.1 represent the fractional
andjth samples,
whilePikandPjk represent
thefractional
of the
species in
in samples
samples ii and
andj.j. The
1985].
whetherthe
the correlation
correlation to
to SST
is percentages
1985]. We
We wish
wish to
to determine
determinewhether
SST is
percentagesof
the kth
kth species
The 27
27
taxonomic categories
also present
in the
the squared
squared chord
also
present in
the global
globaldata
dataset
setofoftemporally
temporallyaveraged
averaged taxonomic
categoriesused
usedto
to calculate
calculatethe
chord
sediment trap
sediment
trapfaunas.
faunas.
Temperature
estimates based
based on
on the
the modem
modern analog
analog method
Temperatureestimates
method
depend
on
averages
of
sample-by-sample
comparisons.
dependon averagesof sample-by-sample
comparisons.Hutson
Hutson
[1980]
[1980] used
used the
the cosine
cosine theta
theta angle
angle as
as aa measure
measureof
of the
the
multivariate distance
distance (i.e.,
between two
multivariate
(i.e., dissimilarity)
dissimilarity) between
two
distance
are the
the same
distance are
same as
as those
thoseused
usedin
in the
theQ-mode
Q-modefactor
factor
analysis described
above
Just as
analysis
described
above(Table
(Table3).
3). Just
asthe
thecommunality
communality
provides
of how
provides aa quantitative
quantitative estimate
estimate of
how well
well aa foraminiferal
foraminiferal
fauna
is
explained
by
a
factor
model,
the
sample
faunais explainedby a factormodel, theaverage
average
sample
dissimilarity
provides aa quantitative
estimate of
of the
the similarity
dissimilarity
provides
quantitative
estimate
similarity
foraminiferal faunas.
faunas. Empirical
pollen studies
studies suggest
suggest that
that the
the between
foraminiferal
Empiricalpollen
betweenaa target
targetfauna
faunaand
andits
its closest
closestanalogs.
analogs. Empirical
Empirical
squared
chord
distance
provides
more
reliable
results
than
suggest that
that values
of dij
d, <
squaredchord distanceprovides more reliable results than studies
studies
suggest
valuesof
< 0.25
0.25yield
yieldreliable
reliableanalogs
analogs
several other
other dissimilarity
dissimilarity measures
measures including
including the
the cosine
cosine theta
theta (W.
communication, 1996).
1996). We
several
(W. Prell,
Prell, personal
personalcommunication,
We tested
testedthis
this rule
role
0khZ AND
ORTIZ
ANDM1X
MIX:SEDIMENT
SEDIMENT TRAP-CORE
TRAP-CORE TOP
TOP COMPARISON
COMPARISON
bO
0
0
I-
0
rJ
Factor 22 (G.
men. T.'
T.: 12.1%)
Factor
(G. men.
12.1%)
Factor 11 (G.
Factor
(G. rub.
rub. T.,
T., G.
G. sac:
sac' 27.4%)
27.4%)
1.001.00
0.750.75
0.500.50
1.001.•
C
0.75 .E
0.75
0.50-0o 0.50
0.25 I¸
•
0.00ri..
• 0.00
-0.25
-0.25 -
0250.25
-5
-5
I
I
I
I
I
I
0
5
10
15
20
20
25
r2• cl• :•'
:c••
•-0.25
t
0000.00
-0.25
-0.25 -
30
-5
-5
bfJ
Factor
Factor33 (N.
(N. pac.
pac.Left:
Left' 8.4%)
8.4%)
I
i
I
i
I
i
II
I
I
II
I
5
10
15
20
20
25
25
30
30
Factor4(G.
Factor4 (G. inf.:
inf.' 12.5%)
12.5%)
ß
1.00-
bO
0.75
1
0.500.50
I-
0.25
0.25 -
.
•2>:. -:-•, t"
ß
0.75 -
0
0.50-
0
-":.?'*::"::::"'"::•i•'i•
-5
-5
I
I
I
I
I
I
I
0
5
10
15
20
20
25
30
1.00
C
I-
• ,.'•<'..,
.::•'•
g•.!?...-.
0000.00
-0.25
-0.25 -,
.. -
0.25 -
0.25
0.00-0.25-,
-0.25
-5
-5
0
,
,
10
1.001.oo
0
0.500.50
0.250.25
0.00
0.00-
I.-
0
-0.25
-0.25
'
•.;•gY'-')2'
'"."?.':,'::'i
bf
C
•._ ..'..•7::•
.......
f
0.75 -
0.75
0.50-
,.•:gg.;5.':.q
C_._"•:
-")--'r••--::...?•
......
':•:'
-•
0.00.::
......
ß::.:,.!.•
....,:::.....•!:'•'_:•.•i?:•iii,,•,,i:"•::::•.':;•iiiii!'
ß :.,y,...
I
0
.., _.:.......:::::::::--:.:•',: .•:'.:::•:..:.: ::.:.:.'...•,•,.:
I
5
I
I
20
20
I
10
10
15
I
25
25
-5
30
30
00
,
,
5
10
10
•
g
•
-0.25
-O.25 -5
-•"--o:'•,'-3'"
ß
ß
•
- y,.
¾,:/.
%.... :'....::::'.'5,.
.i-..iff: i:::;:i::
..........
:'::i:-:i:"'
.:.i:i:•i:•i!•?:.:.::•
.........
......
.- •.
I
I
I
I
I
I
I
0
5
10
15
20
20
25
30
30
:%.
=
0.75 - h
0.75
.
:::::::::::::::::::::::::::::::::::::::::::::::::::::::::
.::::
......
•
,
20
20
25
25
30
30
25
25
30
30
Communality
Communality
1.00-
• .::-?;.f"..
•;.•.
-
.... -.'":: $::.•:..:.
-:•':5
:i!•i
•;•::•+,,
,
15
SST
SST (°C)
(øC)
Factor
Factor77 (P.
(P. obliq.:
obliq.' 5.1%)
5.1%)
0.500.50
0.250.25
0.000.00
-.;..:j..'
:!!.!...,::.
':i
l
-0.25 ,I I i i i I*
-0.25-,
I
1.00
1.00
I•
30
30
'*•5
:-'"'-:""• ;' -•"
.....
"
SST
SST (°C)
(øC)
o
0
25
25
Factor
bull., G.
Factor6
6 (G.
(G. bull.,
G. glut.:
glut.' 11.5%)
11.5%)
•,
.•<'-•;-..!
-..-:::,
i.:'•:
....•
.'.'.'"..,,:.!:.;:;.-.
•
•...'
,•,,. :.:
:•.:..
..::;. :
'{•
•"•.:
...... '.•...:.
-',.:•'
.. .-.:'.•i::•:,-.-..::::?.,
-,
0.75
0.75 -
20
20
1.001.00
'•."•'•'
'-•
'•.:':•..'.i:::::...•.i.:i•
0.25-
-5
-5
C
.E
,
15
15
SST
SST (°C)
(øC)
Factor 55 (N.
Factor
(N. dut.:
dut.' 14.6%)
14.6%)
0.75
0.75 - e
.•;:: .:.:'q-..':
5
SST (°C)
(øC)
C
-.'-'-...'..:' :....'i¾:'
SST
SST (°C)
(øC)
0.75 -
0
.
0
SST
SST (°C)
(øC)
1.001.00
181
E
E
0
L)
½::...,:.
0.50-
0.50
0.25 -
0.25
1
0.00-,
0.00
-5
-5
I
I
I
I
I
0
0
5
10
10
15
20
20
SST
SST (°C)
(øC)
SST (°C)
(øC)
I
Sediment
SedimentTraps
Traps
C Core
CoreTops
Tops
Figure
loadings
andand
communalities
versus
sea
surface
temperature
for
Figure 3.3.Factor
Factor
loadings
communalities
versus
sea
surface
temperature
for the
theglobal
globalQ-mode
Q-modefactor
factor
model described
describedin
in the
the text.
text. Core
Core tops
tops are
while sediment
sedimenttraps
traps are
are large
large solid
model
are small
small open
opensquares,
squares,while
solid squares.
squares.
Abbreviated
names list
list the
the dominant
species for
for each
each factor.
Figures 3a-3g
3a-3g correspond
correspond to
to factors
factors 1-7.
1-7. Figure
Figure 3h
3h
Abbreviatednames
dominantspecies
factor.Figures
displays
displayssample
samplecommunalities.
communalities.
that is
is <0.20
of thumb
thumb by
by calculating
calculatingddofor
for each
each sample
sample in
in the
the core
top data
analogsthat
<0.20 and
andthat
that 99%
99% of
of the
thefaunas
faunashave
haveaverage
average
of
coretop
data analogs
<0.26. W.
communication,
1996)
set
with all
are not
not dd0 values
values<0.26.
W.L.
L.Prell
Prell(personal
(personal
communication,
1996)
setin
in comparison
comparison
with
all others.
others.While
Whilevalues
valuesof
of du
do are
normal in
in distribution,
natural log
log transformed
values of
of ddoßare
normal
distribution,
natural
transformed
values
are
approximately
log
normal.
We
note
that
97%
of
the
faunas
in
approximately
log normal.We notethat97% of the faunasin
value
for
their
top
five
d.,
tho
core
top
data
set
have
an
average
thecoretopdatasethaveanaverage
d0 valuefor theirtop five
reports
similar experience
experiencewith
with applications
applications of
of this
this method
to
reportssimilar
methodto
foraminiferal
faunas. We
We thus
thus choose
choose0.20
0.20 as
foraminiferal faunas.
as aa conservative
conservative
cutoff
cutoff limit.
limit.
182
182
ORTIZ
SEDIMENT TRAP-CORE
TRAP-CORE TOP COMPARISON
COMPARISON
ORTIZ AND
AND MDC:
MIX: SEDIMENT
Using the
the SST
Using
thevalues
valuesof
of dij as
asthe
theselection
selectioncTiteria,
criteria,the
SST
values
from
the
five
core
tops
least
dissimilar
to
the
values from the five core tops least dissimilar to the target
target
Table
for
Table4.
4.Coefficients
Coefficients
forthe
theGlobal
GlobalImbrie-Kipp
Imbrie-Kipp
Transfer
Transfer Function
Function
sample
for that
sampleare
areaveraged
averagedto
to estimate
estimatethe
the modern
modernanalog
analogSST
SST for
that
sample.
rather than
sample. We
Weuse
usearithmetic,
arithmetic, rather
than weighted
weightedaverages,
averages,
when calculating
Tests we
when
calculating analog
analog SST
SSTestimates.
estimates. Tests
we have
have
conducted
demonstrate
that
SST
averages
weighted
by the
conducteddemonstratethat SST averages weighted by
the
individual dissimilarity
individual
dissimilarity estimates
estimates as
as proposed
proposed by
by Hiason
Hutson
[1980]
are not
not significantly
different from
from arithmetic
arithmetic averages.
[1980] are
significantlydifferent
averages.
We
not experiment
We did
did not
experiment with
with more
more sophisticated
sophisticatedgeographic
geographic
weighting methods
methods [e.g.,
[e.g., Pfiaumann
Pflaumann et
weighting
et al.
al. 1996].
1996].
Results
Results
Q-Mode
Q-Mode Factor
Factor Analysis
Analysis
Term
Term
Intercept
Intercept
Factor 3
Factor
4
Factor 4
Factor
Factor 33 squared
squared
Factor
Factor 4
4 squared
squared
Factor
Factor 5
5 squared
squared
Factor
Factor 6
6 squared
squared
Factor
Factor 7
7 squared
squared
Factor 1I x factor 3
Factor 1I x factor
factor 44
Factor 1I x factor
factor 66
Factor 2 x factor 3
Factor 2 x factor
factor 44
Factor
factor 66
Factor 2
2x
x factor
Factor 2 x factor 7
Factor 3 x factor 4
Factor 3 x factor 5
Factor 3 x factor
factor 66
Factor
Factor 4 x factor
factor 66
Factor 4 x factor 7
Factor 5 c• factor 6
Coefficient
Coefficient
27.6
-46.2
-46.2
-26.2
-26.2
21.2
21.2
18.6
18.6
-1.1
-1.1
-3.3
3.0
72.8
72.8
4.5
5.4
55.9
Seven factor
factor assemblages
assemblages together
together account
account for
for 91.5%
91.5% of
of the
the
13.4
Seven
9.3
information
in
the
global
core
top
data
set.
The
addition
of
informationin the globalcoretop data set. The additionof an
an
-3.8
eighth
would
the total
total
eighth factor
factorassemblage
assemblage
wouldhave
have increased
increasedthe
21.4
information
by only
Models with
informationexplained
explainedby
only 2.4%
2.4% to
to93.9%.
93.9%. Models
with
20.0
few
assemblages
generated
groupings
that
were
ecologically
10.6
few assemblages
generated
groupings
that wereecologically
less
-3.1
Table 33 lists
lists the
less distinct.
distinct. Table
the factor
factor scores
scores for
for the
the seven
seven
19.7
19.7
assemblages
we
chose
to
retain.
The
seven
factors
group
assemblages
we choseto retain. The sevenfactorsgroup
-6.0
-6.0
species
which
specieswith
withsimilar
similardistributions
distributionsinto
into assemblages
assemblages
which
individually
accountfor
for5-27%
5-27%ofofthe
thetotal
totalinformation.
information. These
individuallyaccount
These
assemblages
correspond
roughly
to
oceanographic
assemblages
correspond roughly
to oceanographic
environments.
For
by
environments.
Forexample,
example,factor
factor1,
1, which
whichis
isdominated
dominated
by
G.
G. sacculifer,
sacculifer, is
is important
important in
oligotrophic
G. rube,
ruberand
andG.
in warm,
warm,oligotrophic
Global Imbrie-KIpp Transfer Function
regions,
while factor
3, composed
left-coiling N. Global Imbrie-Kipp Transfer Function
regions, while
factor 3,
composedof
of left-coiling
pachyderina, isisindicative
extremes.
A
significant SST
SST transfer
pachyderma,
indicativeof
ofcold,
cold,high-latitude
high-latitude
extremes.
A statistically
statistically significant
transfer function
function was
was
To
the sediment
trap and
and core
core top
developed using
usingthe
thecore
coretop
topdata
dataset.
set.The
Theterms
termsfor
forthis
this global
global
To compare
comparethe
sedimenttrap
top foraminiferal
foraminiferal developed
faunas,
we apply
apply the
the core
core top
top factor
factorscores
scoresto
to the
the sediment
sediment trap
trap Imbrie-Kipp
lmbrie-Kipp transfer
transfer function
function are
are listed
listed in
in Table
This
faunas,
we
Table 4.
4. This
data
extract factor
factor loadings
loadings for
for each
each sample.
sample. Plots
regression, based
based on
on 1121
1121 samples,
samples, is
is significant
significant at
dataand
andextract
Plotsof
of factor
factor regression,
at p<0.Ol,
p<<0.01,
loading
against S•F
SST from
from Levitus
Levitus [1982]
[1982] serve
serve as
as aa useful
has an
an r:
r2of
of 0.93,
0.93, and
and an
anRMS
RMSerror
errorof
of1.9øC.
1.9°C. The
The core
loading against
useful has
coretop
topSST
SST
indication
of
sample
environments
(Figure
3).
estimates
have
a
slope
of
0.93±0.02
In
general,
and
an
intercept
indicationof sampleenvironments
(Figure3). In general, estimateshave a slope of 0.93+0.02 and an interceptof
of
factor
loadings from
fromthe
the two
two data
data sets
sets have
have similar
similar trends
trends with
with 1.7±0.4
factorloadings
1.7+0.4 at
at the
the 95%
95% confidence
confidencelimit
limit with
with respect
respectto
toLevitus
Levitus
respect
to SST.
SST (Figure
(Figure4a).
4a).The
Theslope
slopeofofthe
thecore
coretop
top regression
regression is
is
respectto
SST. This
Thisis
ismost
mostclear
clearfor
for factors
factors 1, 3, 5,
5, and
and66 [1982]
[1982]SST
(Figure
3).
significantly different
one (with
confidence), given
given
(Figure 3).
significantly
differentfrom
fromone
(with 95%
95% confidence),
the sample
sample size
size of
Potential differences between
betweenthe
thetwo
two data
datasets
setsdo
doexist.
exist. The
The the
of 1121
1121 core
coretops.
tops.
To
compare the
the core
core top
top and
sediment trap
trap assemblages,
we
amplitude
of the
the factor
factorloadings
loadingsfor
forfactors
factors2,2,4,4, and
amplitudeof
and 7
7 are
are
To compare
andsediment
assemblages,
we
applied the
the core
core top
function
trap
diminished in
in the
the sediment
trap assemblages
relative to
to the
diminished
sedimenttrap
assemblages
relative
the applied
toptransfer
transfer
functionto
tothe
thesediment
sediment
trapfactor
factor
4, Table
When the
the transfer
is
core top
top assemblages.
species in
in these
loadings(Figure
(Figure 4,
Table 5).
5). When
transferfunction
function is
core
assemblages.The
The dominant
dominantspecies
thesefactors
factors loadings
are
relatively
rare
in
the
sediment
traps
and
abundant
in
some
of
applied
to
the
sediment
trap
samples,
the
SST
estimates
follow
arerelativelyrarein the sediment
trapsandabundant
in someof appliedto the sedimenttrap samples,the SSTestimatesfollow
slope of
the core
core top
top sediments.
This could
couldbe
beaa sampling
sampling problem
problem or
or aa slope
at the
of 0.92±0.16
0.92+0.16 and
andan
anintercept
interceptof
of 4.2±2.8
4.2+2.8 at
the 95%
95%
the
sediments.This
limit with
respect to
to the
Levitus [1982]
may
a bias
bias in
in the
the sediments.
sediments. All
of the
the species
confidence
limit
with respect
theLevitus
[1982] SST
SSTvalues.
values.
may reflect
reflecta
All of
speciesinvolved
involved confidence
have
shells, suggesting
RMS error
errorfor
forthe
the sediment
sediment trap
trap SST
SST estimates
estimates with
with this
this
have heavily
heavily calcified
calcifiedshells,
suggestingthat
that dissolution
dissolutionmay
may The
The RMS
enrich them
them inin the
the sediments
sediments relative
relative to
to their
their abundance
in the
the method
was
2.6°C.
The
slope
of
the
sediment
trap
relationship
enrich
abundance in
methodwas2.6øC.Theslopeof thesediment
traprelationship
overlying
(0.92±0.16)
is not
not significantly
different from
that of
(0.92.•.16) is
significantlydifferent
from that
of the
thecore
core
overlyingwater
watercolumn.
column.
or from
from one.
one. However,
as was
was the
the case
case for
for the
the core
core tops,
tops,
The
measureshow
how much
much of
the tops,
The model
model communality
communality measures
of the
tops,or
However,as
interval
information content
content of
of the
the foraminiferal
foraminiferalfaunas
faunasisis explained
explained by
by the
information
the 95%
95%confidence
confidence
interval on
on the
the regression
regressionintercept
intercept
the
factor
model
(Figure
3h).
For
both
core
top
and
sediment
indicates
a
warm
bias
in
the
sediment
trap
SST
(Figure
the factor model (Figure3h). For both core top and sediment indicates
a warmbiasin thesediment
trapSSTestimates
estimates
(Figure
trap
4b). AAtwo-sided
t-test
Imbrie
amounts of
of 4b).
trap faunas
faunasthe
the factor
factormodel
modelexplains
explains adequate
adequateamounts
two-sided
t-testof
ofthe
the3.0°C
3.0øCaverage
average
ImbrieKipp-SST
Kipp-SST
sample information
information at
or >20°C)
sediment trap
trap residual
residual demonstrates
demonstratesthat
thatthis
thisbias
bias is
is significant
significant
sample
at latitudinal
latitudinalextremes
extremes(SST
(SST <9°C
<9øCor
•20øC) sediment
but
of freedom
=12, RMSE=2.6°C,
but explains
explainslittle
little information
informationin
in the
themidlatitude
midlatitudefaunas
faunasat
atSST
SST at
at psO.Ol
p<<0.01 (degrees
(degreesof
freedom(4t)
(dr)=12,
RMSE=2.6øC,ttfrom 9ø-15øC.
9°-15°C. Note,
Note, however,
however, that
that this
this pattern
pattern is
is seen
in the
value=4.18 >> t-crit@0.01=3.055).
from
seenin
the value--4.18
t-crit•0.01=3.055). The
The sediment
sedimenttrap
trapSST
SST
communalities
of both
both the
trap faunas,
estimates also
also appear
appear to
to exhibit
exhibit aa residual
residualtrend
trendas
asaa function
function of
of
communalitiesof
the core
coretop
top and
andsediment
sedimenttrap
faunas, estimates
suggesting
that aa similar
similar process
process contributes
contributes to
to the
the effect
in the
the factor
model communality.
communality. However,
it is
that this
this
suggestingthat
effect in
factormodel
However,it
is unlikely
unlikelythat
both
data sets.
sets. We
featureis
is statistically
statistically significant:
significant: The
Thetrend
trendisisnot
not present
present in
in
bothdata
We explore
explorehow
howlow
low sample
samplecommunality
communalitymay
may feature
affect the
the SST
the core
top
SST
residuals
and
occurs
only
at
very
low
affect
SST estimates
estimatesderived
derivedfrom
from the
theImbrie-Kipp
lmbrie-Kippand
and the
core top SST residualsand occursonly at very low
modem
section.
communality
in the
trap
(Figure
modernanalog
analogmethods
methodsin
in the
thediscussion
discussion
section.
communality
in
thesediment
sediment
trapresiduals
residuals
(Figure4c).
4c).
183
183
ORTIZ
MIX: SEDIMENT
SEDIMElff ThAP-CORE
ORTIZ AND MIX:
TRAP-CORETOP
TOPCOMPARISON
COMPARISON
3434
3030-
a Imbrie-Kipp
a
Imbrie-Kipp
•,
•.:.,.
.•,•--•;-•,
-" -•.,7.[?
2626--
0
22-
22-
1818-
:i:?.' •... - ß
1D
-C
0
14141010'...-'
ß
6622-
•.'.."•&-2
-%'
3434
303026262222-
aModem
Anal.•,g...
••"••
,......,_•,...
ß.•::•'•
•':• ....-.ff:'..{•
ß
181814141010-
622-
...
,--,•.,.,,.•:...,.• ,,,'
....
.....
r.'.'•.=.,$•'
.., - 7-.,":'""
•'"
..L,:•;a .4 '?"•
6-
-2 e
-2-,
I
2
I
6
.---•
-2-,
-2
,
,
,
,
,
,
-2
14141822263034
18 22 26 30 34
-2 22 6 61010
I,
I
I
I
I
I
I
10 14 1822263034
-2 2 6 10 14 18 22 26 30 34
-2
.4:•-v•
I
I
I
I
I
I
I
Levitus SST
Levims
SST (°C)
(øC)
Levitus
Levims SST (°C)
(øC)
1515
15-
10
•
ß-
..,•
,.% f":::
. ;.'".',.
•.• (¾.,...:...•?:..-:}
5-
0=5-
<"="
'ø:'""
•'"""'"'•""
""
•••''':- ."'
' .'ß.d..,
L".O
;;., .....
,:.,.,
....
,:0
-5-
o
-10-
-15
-10I
I
I
I
I
I
I
-15-,
I
-2 22 6 610101414181822263034
22 26 30 34
-2
I
I
I
I
I
I
I
I
I
-2 2 6 10 14 18 22 26 30 34
Levitus
Levims SST
SST (°C)
(øC)
Levitus
Levims SST
SST (°C)
(øC)
15-
1515
1010
&•
.....
.,.:, '"•'
['
10-
55 ?•:"'%,..,
'-"-:.•:
0,-...--•:....
-•,..:-._'•.
-.•,
:.-.....
-5-5 <'..•:5..•.•..,:.,
.,...-'
"o'o o o
-10-10
15
- 1.0
•-1.0
E
•
•
0.0
0.6
0.6 0.4
0.4 0.2
0.2 0.0
Communality
Communality
o Core
Sediment
Traps
CoreTops
Tops
SedimentTraps
0.8
0.8
-10
-15-,
15
•
I.
I.
I.
I
0.2 0.3
0.0 0.1
0.1 0.2
0.3 0.4
0.4 0.5
0.5 0.6
0.6
0.0
Dissimilarity
Dissimilarity
.i
IU Sediment Traps
Core Tops
Tops
Sediment
Traps .•:•
Core
Results of
of the
Figure
4.
Figure 4.
Results
the global
global Imbrie-Kipp
Imbrie-Kipp transfer
transfer
(SST)
(a) Levitus [1982]
function.
function. (a)Lev/tus
[1982] sea
seasurface
surfacetemperature
temperature
(SST)
Results of
of the
Figure 5.
versus
predictedSST.
SST. Diagonal
Diagonal lines
lines mark
mark aa 1:1
1:1 relationship
relationship Figure
5. Results
theglobal
globalmodem
modemanalog
analogmethod.
method.
versuspredicted
Dashed
and
solid
lines
are
as
defmed
in
Figure
4. (a)
(long
dashed
line),
and
least
squares
regressions
for
the
core
top
Dashed
and
solid
lines
are
as
defined
Figure
(a) Levitus
Levitus
(longdashedline), andleastsquares
regressions
for thecoretop
SST. (b)
(solid line)
line) and
sediment trap
trap (short
(short dashed
dashedline)
line) samples.
samples. (b)
(b) [1982]
[1982] SST
SST versus
versuspredicted
predictedSST.
(b) Levitus
LevimsSST
SSTversus
versus
(solid
andsediment
average sample
SST. (c) Residual
Levitus SST
SST versus
versusresidual
residual SST.
SST. (e)
(c) Residual
Residual SST
SSTversus
versus factor
factor residual
residual SST.
Residual SST
SST versus
versus average
sample
Levims
denotes less
less similar
Greater dissimilarity
Lower eommunalities
communalities denote
model
dissimilarity. Greater
dissimilarity denotes
similar
modelcommunality.
communality. Lower
denoteweaker
weaker dissimilarity.
samples.
factor model
model fit.
fit. Note
factor
Notereversed
reversedcommunality
communalityaxis.
axis.
samples.
184
184
ORTIZ
TOP COMPARISON
COMPARISON
ORTIZ AND
AND MIX:
MIX: SEDIMENT
SEDIMENT TRAP-CORE
TRAP-CORE TOP
Table
Estimates
for
Table5.
$.Global
GlobalImbrie-Kipp
lmbrie-Kippand
andModern
ModemAnalog
AnalogTemperature
Temperature
Estimates
for the
theSediment
SedimentTrap
Trap Faunas
Faunas
Average
Average
Site
Site
Gulf
Gulf of Alaska
Alaska
Nearshore
Nearshore
Midway
Gyre
Gvre
San Pedm
Pedro Basin
Sargasso
Sar•assoSea
Sea
Central
Central Pacific
Pacific
Troica1
Tropical Atlantic
Atlantic
Panama Basin
MANOP
MANOP Site
Site C
King
King George
GeorgeBasin
Basin
North
North Weddell
Weddell Sea
Mend
Maud Rise
Rise
Sample
Actual
Sample
Actual
Dissimilarity
Communality
Temperature
Dissimilarity Communality
Temperature
0.34
0.34
0.34
0.34
0.22
0.22
0.58
0.58
0.23
0.23
0.27
0.27
0.34
0.34
0.13
0.16
0.16
0.70
0.70
8.5
12.4
13.4
13.4
14.4
14.4
15.5
15.5
23.1
23.1
26.3
26.3
0.63
0.63
0.23
0.23
0.61
0.61
0.83
0.83
0.39
0.39
0.94
0.94
0.97
0.97
0.97
0.97
0.94
0.95
0.95
0.96
0.96
0.11
0.11
0.06
0.06
0.08
0.08
0.04
0.04
0.05
0.05
Modem
Modem
Analog
Analog
Residual
Residual
Modem
Modem
Analog
Analog
Temperature
Temperature
9.5
1.0
12.7
14.0
14.0
18.5
11.7
03
0.3
26.8
26.8
26.9
26.9
26.3
26.3
-0.6
-0.9
-0.9
-0.5
-0.5
12.9
13.8
16.2
16.2
23.7
23.7
15.4
26.6
2&6
29.5
29.6
24.6
24.6
28.9
28.9
2.9
2.9
3.3
3.4
0.6
0.6
4.2
4.2
-3.8
-3.8
0.4
0.4
2.2
23.4
23.4
28.5
28.5
26.7
27.5
27.5
-0.1
0.6
28.1
2.0
2.0
2.0
1.8
2.6
2.9
2.9
1.7
2.2
hnbrie-Kipp
Imbrie-Kii•
Temperature
Temperature
Imbrie-Kipp
Imbrie-Kipp
Residual
Residual
4.4
4.4
1.4
2.7
2.7
9.3
9.3
-0.1
-0.1
3.6
3.6
3.1
2.8
2.8
-2.3
-2.3
2.6
2.6
3.5
4.2
4.2
3.9
3.9
Modern
Modern Analog
Analog Results
Results
Modem analog
analog SST
SST residuals
residualsdisplayed
displayedno
nosignificant
significant trends
trends as
as
Modem
a
function
of
Levitus
SST
(Figure
Sb)
or
average
modern
analog
a
function
of
Levims
SST
(Figure
5b)
or
average
modem
analog
bias in
We assessed
potential
We
assessed
potential bias
in the
themodern
modernanalog
analogSST
SST dissimilarity (Figure 5c). l'his was true for both the core top
estimates in
in the
the same
manner as
as with
estimates
samemanner
with the
the Imbrie-Kipp
Imbrie-Kipp transfer
transfer dissimilarity (Figure 5c). This wastrue for both the core top
and sediment
sedimenttrap
trapmodem
modemanalog
analogSST
SSTestimates.
estimates.
function. The modem analog SST estimates for the sediment and
function. The modernanalogSSTestimatesfor the sediment
modem
trap
listed in
trap samples
samplesare
are fisted
in Table
Table5.
5. We
We determined
determined
modem
analog
for every
every sample
sample in
in the
by
analogSST
SST for
the core
coretop
topdatabase
database
by Discussion
Discussion
comparing each
each sample
sample against
against all
all other
other samples
samples in
in the
the data
data set
set
comparing
(Figure
5a). These
have
(Figure5a).
Thesecore
coretop
topMAT
MATSST
SSTestimates
estimates
havean
anRMS
RMS
error
of 1.5°C.
core top
top SST
SST estimates
estimates have
have
errorof
1.5øC. The
The modem
modernanalog
analogcore
aa slope
of
0.98±0.01
and
an
intercept
of
0.4±0.3
relative
slope of 0.98+0.01 andan interceptof 0.4+0.3 relativeto
to
Levitus [1982]
Levitus
[1982] SST.
SST.
When
core tops
tops are
are used
used to
to estimate
estimate MAT SgI'
SST values
values for
for
Whenthe
thecore
each
of the
eachof
the sediment
sedimenttrap
trap faunas,
faunas,the
the resulting
resultingestimates
estimateshave
have
an
errorof
of2.2øC
2.2°Cand
andfollow
followaaslope
slope of
of 0.95+0.15
0.95±0.15 and
an RMS
RMS error
andan
an
intercept
of 1.9±2.5
interceptof
1.9•_2.5relative
relativeto
to Levitus
Levitus[1982].
[1982]. The
The modem
modem
analog method
analog
methodproduced
producedslopes
slopes and
and intercepts
intercepts with
with no
no
statistically
significant
difference
between
the
core
top and
statisticallysignificantdifferencebetweenthe core top
and
sediment
trap data
data sets.
sets. The
sedimenttrap
Theintercepts
interceptsfor
forthe
themodem
modernanalog
analog
SST estimates
estimates were
weresmaller
smallerthan
thanthose
those for
for the
the global
SST
global ImbrieImbriethe result
Kipp transfer
Kipp
transferfunction
function(Fable
(Table6).
6). Unlike
Unlike the
resultusing
usingthe
the
Imbrie-Kipp
method,
a
two-sided
t-test
of
the
1.2°C
Imbrie-Kipp method,a two-sidedt-test of the 1.2øCaverage
average
MAT
trap residual
residual demonstrates
demonstratesthat
thatthis
this offset
offset is
is
MAT SST
SST sediment
sedimenttrap
not
= 2.2øC,
2.2°C, tnot statistically
statisticallydifferent
differentfrom
fromzero
zero(df-12,
(df=12,RMSE
RMSE =
tvalue=1.89
t-critt)0.05=2.179). Using
the core
core top
set,
value=l.89 << t-orit•0.05=2.179).
Using the
top data
dataset,
the slope
slope for
for the
was closer
closer to
to unity
the
the modem
modernanalog
analog method
methodwas
unity
than the
than
the slope
slopefor
forthe
theglobal
globalImbrie-Kipp
Imbrie-Kipptransfer
transferfunction.
function.
These
of estimating
estimating paleoceanographic
These two
two methods
methods of
paleoceanographic
temperature
have
received
considerable
scrutinyover
overthe
the past
past
temperaturehave receivedconsiderablescrutiny
two decades.
decades. However,
not all
all of
of these
these studies
studies have
have reached
reached the
the
two
However, not
same conclusions
conclusions regarding
regardingthe
the relative
relative applicability
applicability of
of the
same
the
two methods.
methods. PreIl
two
Prell [1985]
[1985] compared
comparedthe
the two
two methods
methodsusing
using
core top
top and
core
andglacial
glacial maximum
maximum samples
samples from
from the
the Atlantic,
Atlantic,
Indian,
concluded that
that they
Indian, and
andPacific
Pacific basins.
basins. He
He concluded
they provided
provided
similar results
results within
within each
basin and
similar
each basin
and that
that transfer
transfer functions
functions
calibrated
for aa specific
specificbasin
basin worked
workedbest
best in
in that
that basin.
calibratedfor
basin. Prell
Prell
[1985] did
did not
not present
presentresults
results for
for aa global
global comparison,
comparison, nor
[1985]
nor did
did
his
include any
any modem
modemsediment
sedimenttrap
trapsamples.
samples. Anderson
his work
work include
Anderson
at
of the
the two
et al.
al. [1989]
[ 1989]made
madedowncore
downcorecomparisons
comparisons
of
two methods
methodsin
in
the
Coral
Sea
and
also
concluded
the
two
methods
the Coral Sea and also concludedthe two methodsprovided
provided
similar results.
the
similar
results. Their
Their findings
findingsaccentuated
accentuated
the discrepancies
discrepancies
between
marine SST
SST estimates
estimateswhich
whichsuggest
suggestlittle
little cooling
cooling of
betweenmarine
of
the LGM
Pacific and
terrestrial temperature
temperature
the
LGM low-latitude
low-latitude Pacific
and terrestrial
estimates
estimates which
which imply
imply aa much
muchlarger
largerlow-latitude
low-latitudethermal
thermal
decrease.
decrease.
Working
with a
a calibration
data set
set composed
composed of
of 499
499 Pacific
Working with
calibrationdata
Pacific
Table
of the
Table 6.
6. Statistical
StatisticalComparison
Comparisonof
theTwo
Two Methods
Methods
Core top
top Faunal
Core
Faun• Comparison
Comp•iso• (N=1121)
(N= 1121)
Analysis
Type
Analysis
Type
Global
Global Jmb,ie-Kipp
Imbrie-Kipp
Transfer
Transfer function
function
Modem analog
analogmethod
method
Temperature
Temperatureestimate
estimate
Mean
Mean
Residual
Residual
RMS
RMS
Error
Error
Slope
Slope
Intercept
Intercept
Sediment
(N=13)
SedimentTrap
TrapFaunal
FaunalComparison
Comparison
(N= 13)
Mean
Mean
Residual
Residual
R
RMS
Error
Error
Slope
Slope
Intercept
Intercept
0.0
1.9
1.9
0.93±0A2'
0.93_+0.02'
1.7±0.4
1.7_+0.4'
3.0"
3.0•
2.6
0.92±0.16
0.92__+0.16
4.2±2.8k
4.2+__2.8'
0.0
1.5
1.5
0.98±0.01
0.98_+0.01
0.4±0.3
0.4_+0.3
1.2
2.2
2.2
0.95±0.15
0.95__+0.15
1.9±2.5
1.9+__2.5
'Signifrant
difference
from
and
from zero
zero for
for intercepts
interceptsat
atpp <
<0.05.
'Significant
difference
from11for
forslopes
slopes
andfrom
0.05.
"Significant
differencefrom
fmmzero
zeroatatp
bSignificant
difference
p <<0.01.
<< 0.01.
ORTIZ AND
AND MIX: SEDIMENr
SEDIMENT TRAP-CORE
TRAP-CORE TOP
TOP COMPARISON
COMPARISON
ORTIZ
core tops,
tops, Le
Le [1992]
compared these
these methods
methodsat
attwo
twosites
sitesin
in the
the
core
[1992]compared
western
Pacific.
The
primary
conclusion
of
I.e
[1992]
was
that
westernPacific. The primaryconclusionof Le [1992] wasthat
the
the Imbrie-Kipp
Imbrie-Kippmethod
methodprovided
providedconsistent,
consistent,reliable
reliableSST
$ST
did not.
estimates
estimates and
and that
that the
the modem
modemanalog
analog method
method did
not.
Methodological differences
differences between
between the
the study
study of
of Le [[1992]
Methodological
1992] and
and
Le
those
of
PrelI
[1985]
and
our
study
must
be
addressed.
those of Prell [1985] and our study must be addressed. Le
[1992] compared
comparedthe
thetwo
twomethods
methodsusing
using 18
18 and
and 33
33 species
species for
for
[1992]
modem
analogcalculations
calculationsand
andaa subset
subset of
of 24
24 species
modemanalog
speciesfor
for
a second
This
transfer
transfer function
function calculations.
calculations.
This introduces a
second
variable
making
ifif
variableinto
intothe
thecomparison,
comparison,
makingit
it difficult
difficultto
todetermine
determine
the obtained
obtained results
results are
are fundamental
or potentially
potentially related
related to
to
the
fundamentalor
differences
in the
the species
species lists.
lists. Le
use of
of aa smaller
differences
in
Le [1992]
[ 1992]made
madeuse
smaller
calibration
data set
calibrationdata
setthan
thanPrell
Prell [1985]
[ 1985]or
orthis
thisstudy
studyand
andevaluated
evaluated
the methods
by comparing
SST estimates
estimates from
the
methodsby
comparingdowncore
downcoreSST
from two
two
cores
first of
coresin
in aa relatively
relatively small,
small,low-latitude
low-latituderegion.
region. The
The first
of
these factors
decreases the
the range
these
factors decr•es
range of
of hydrographic
hydrographicvariation
variation
included in
in the
the calibration
calibration data
set, while
included
data set,
while the
the second
seconddecreases
decreases
the range
range of
of temperature
variation over
over which
the
temperaturevariation
which the
the two
two methods
methods
were assessed.
assessed. While
While evaluating
evaluating the
the temporal
response of
of the
were
temporalresponse
the
two methods
methodsprovides
providesindications
indicationsof
of their
their precision,
precision, itit cannot
two
cannot
assess their
assess
their accuracy
accuracyat
atreconstructing
reconstructing true
true SS1'
SST variation
variation
185
185
intercept
of 4.2_-t:2.8,
4.2±2.8, and
and an
an RMS
RMSerror
errorof
of2.6øC.
2.6°C. The
The statistics
statistics
intercept
of
for
the
modem
analog
method
using
the
sediment
trap
for themodernanalogmethodusingthe sedimenttrapdata
dataset
set
were aa slope
slope of
of 0.95+0.15,
0.95±0.15, an
were
anintercept
interceptof
of 1.9±2.5.
1.9+2.5,and
andan
an
RidS error
RMS
error of
of 2.2°C
2.2øC(Table
(Table 6).
6). The
The confidence
confidenceintervals
intervals
associated
with
the
much
smaller
sediment
trap data
data set
set (N=13)
associated
with the muchsmallersedimenttrap
(N= 13)
are
wider than
than those
those of
arewider
of the
thelarger,
larger,coretop
coretopdata
dataset
set(N=1
(N=I 121).
121).
As aa result,
result, using
using the
produced
As
the sediment
sedimenttraps,
traps,both
bothmethods
methods
produced
SST
estimates with
with slopes
slopes that
that were
werenot
not significantly
significantly different
SST estimates
different
from
SST
from unity
unity relative
relativeto
toobserved
observed
SST(with
(with95%
95%confidence).
confidence).
two-sided f-test,
However,
However,using
using the
the small
small sample
sample two-sided
t-test, we
we
demonstrate
that the
demonstratethat
themean
meanresidual
residualvalue
valueof
of the
thelmbrie-Kipp
Imbrie-Kipp
method
different from
(with 99%
method was
wassignificantly
significantly different
from zero
zero (with
99%
confidence),
while the
the mean
by the
confidence),while
mean residual
residualvalue
value produced
producedby
the
modern
analog method
different from
modem analog
method was
was not
not significantly
significantly different
from
zero. This
for the
zero.
This was
wasthe
the same
samepattern
patternobserved
observedfor
the regression
regression
intercepts
with the
interceptswith
the much
muchlarger
largercore
coretop
topdata
dataset.
set.
The
The greatest
greatestpotential
potential systematic
systematicbias
biaswe
weobserved
observedusing
using
either
was related
related to
to the
either the
the core
core top
top or
or sediment
sedimenttrap
trap data
data was
the
differences
in the
the intercepts
intercepts of
differencesin
of the
theactual
actualversus
versusestimated
estimatedSST
SST
regressions
for the
the two
two methods.
methods. Using
set,
regressionsfor
Using the
the core
core top
top data
dataset,
the Imbrie-Kipp
Imbrie-Kipp method
method generated
generated an
an intercept
intercept of
of 1.7±0.4°C
the
1.7+0.4øC
Levitus [1982]
SST. This
becauseofofthe
the lack
lack of
of aa priori
knowledge of
of the
true relative
relative to
to Levitus
[1982] SST.
Thisvalue
valueis
is1.3°C
1.3øCwarmer
warmerthan
than
because
priori knowledge
the true
the 0.4øC+0.3
0.4°C±0.3 intercept
intercept of
of the
analog method
method for
for the
For these
these reasons,
employ global
global data
paleotemperatures. For
the modern
modemanalog
the
paleotemperatures.
reasons,we
we employ
data the
sets of
of coretop
coretopdata
data set
set(Table
(Table 6).
6).
sets
coretopand
and sediment
sedimenttrap
trap faunas
faunasas
as aa means
meansof
of assessing
assessing coretop
Because
Imbcie-Kipp transfer
transfer functions
functions are
both the
andprecision
precisionof
of the
the two
two methods
methods over
over the
both
the accuracy
accuracyand
the
Because
Imbrie-Kipp
areoften
oftendeveloped
developed
for
specific
oceanic
regions,
we
generated
two
additional
observed
global
SST
range.
for specificoceanicregions,we generatedtwo additionalfactor
factor
observedglobal SST range.
models
using (1)
modelsand
andImbrie-Kipp
Imbrie-Kipp transfer
transferfunctions
functions using
(1) only
only
Comparisons of
of Both
Comparisons
Both Methods
Methods
To
with the
To evaluate
evaluate the
the temperature
temperaturebiases
biases associated
associatedwith
the
modem
analog and
modem analog
and global
global hnbrie-Kipp
Imbrie-Kipp SST
SST estimates,
estimates,we
we
calculated simple
simple linear
of actual
calculated
linear regressions
regressions of
actual SST
SST against
against
samples
from sites
sites >8°C
samples from
>8øC and
and (2)
(2) only
only samples
samplesfrom
from sites
sites
>20°C.
>20øC. The
TheRMS
RMS error
errorin
in the
the>8°C
>8øCequation
equationwas
was 1.9°C,
1.9øC,while
while
that
for
the
>20°C
equation
was
1.3°C.
Despite
that for the >20øC equationwas 1.3øC. DespiteRMS
RMS errors
errors
smaller or
or equal
to the
smaller
equal to
the global
globalImbrie-Kipp
Imbrie-Kipp equation,
equation, both
both
regional
had more
more significant,
significant, systematic
systematic
regional equations
equations had
temperaturebias
biasthan
thanthe
theglobal
globalrelationship
relationship (Figure
(Figure6).
6). This
This
temperature
fmding
suggests
the
need
for
great
caution
when
regional
finding suggeststhe need for great caution when regional
lmbrie-Kipp
Extreme SST
Imbrie-Kipp transfer
transferfunctions
functionsare
areemployed.
employed. Extreme
SST
errors
foraminiferal
fauna
errorscan
canoccur
occurif
if aa downcore
downcore
foraminiferal
faunawas
wasgenerated
generated
when the
was outside
when
the true
truepaleotemperature
paleotemperaturewas
outside the
the calibration
calibration
range
of the
range of
the data
data set
set(i.e.,
(i.e., during
during "no-analog"
"no-analog" situations).
situations).
offset in
to the
if the
Temperature
estimates within
within the
the thermal
thermal bounds
bounds of
of the
the data
offset
in the
the SST
SST estimates
estimates relative
relative to
the actual
actual SST
SST if
the
Temperatureestimates
dataset
set
slope
due
residual
slope of
of the
the regression
regressionis
isnot
notsignificantly
significantly different
different from
from may
may also
alsobe
bequestionable
questionable
dueto
tothe
thesystematic
systematic
residualbias.
bias.
RMS errors
errors indicate
indicate greater
greater random
random error
error in
in the
The
Table 5, and
and Table 6 indicate
indicate that
that the
unity.
The results
resultsin Figure
Figure5, Table
the
unity. Larger
LargerRMS
the
modem
analog
method
provides
relatively
unbiased
estimates
Thus
minimal
temperature
bias
is
displayed
SST
estimates.
modern
analog
method
provides
relatively
unbiased
estimates
SST estimates. Thus minimal temperaturebias is displayed
of SST
SST over
overaarange
rangeofofalmost
almost30øC.
30°C. This
This result
result is
is particularly
when
slopes are
when slopes
are close
closeto
to 1,
1, intercepts
interceptsare
are close
close to
to zero,
zero, and
and of
particularly
impressive when
when one
one considers
considersthe
the relatively
relatively poor
poor quality
of
RMS
RMS errors
errors are small.
small.
impressive
quality of
Temperature
estimates
derived
from
the
coretop
data
set
the
core
top
analogs
which
were
identified
for
many
of
the
Temperatureestimates derived from the coretop data set the core top analogs which were identifiedfor many of the
(N=1 121)using
usingthe
themodern
modemanalog
analogmethod
methodcame
cameclosest
closestto
to this
this sediment
sediment trap
(N=1121)
trapassemblages.
assemblages.In
In 77 of
of the
the13
13 cases,
cases,the
theaverage
average
ideal,
withaaslope
slope of
of 0.98+0.01,
0.98±0.01, an
of 0.4+0.3,
0.4±0.3, and
dissimilarity coefficient
ideal,with
an intercept
interceptof
and dissimilarity
coefficientwas
was>0.20,
>0.20, the
the critical
critical threshold
thresholdwe
we
an RMS
RMS error
error of
of 1.5°C
discuss in
in the
the methods
methods section.
section. While
While we
we do not
not recommend
recommend
an
1.5øC (Table
(Table 6).
6). The
The variability
variability associated
associated discuss
with
the slope
slope and
intercept of
of the
the regression
within the
the relaxing
relaxing this
this constraint
in downcore
studies, the
the robustness
robustness of
of
with the
and intercept
regressionare
are within
constraintin
downcorestudies,
95%
confidence interval
interval of
of the
Using the
method
is
demonstrated
by
the
fact
that
even
when
pushed
95% confidence
the statistic.
statistic. Using
the same
samecore
core the
themethodis demonstrated
by the fact that evenwhenpushed
top data
set but
but estimating
beyond the
the scope
scope of
of its
top
dataset
estimatingSST
SST with
with the
theglobal
globalImbrie-Kipp
Imbrie-Kipp well
well beyond
its geologic
geologicapplication
applicationparameters,
parameters,
transfer function
function method
method resulted
resulted in
in greater
bias. it
values for
for most
most of
of the
transfer
greatertemperature
temperaturebias.
it still
still provided
providedrelatively
relativelyaccurate
accurateSSI'
SST values
the
sediment
trap
localities.
This
can
be
seen
by
comparing
the
coretop
statistics
down
each
This can be seenby comparingthe coretopstatisticsdown each sedimenttrap localities.
The two
two most
column in
in Table
Table 6.
6. The
for
in the
column
Thestatistics
statistics
forthe
thecoretop
coretopglobal
globalImbrieImbrieThe
mostsevere
severeSST
SSTerrors
errors in
the sediment
sedimenttrap
trap
comparison occurred
for traps
traps in
in the
Basin (-3.8°C)
Kipp transfer
transferfunction
functionyield
yieldaaslope
slope of
of 0.93+0.02,
0.93±0.02, which
which is
is comparison
occurredfor
theSan
SanPedro
PedroBasin
(-3.8øC)
Kipp
significantly different
different from
from one,
one, an
which
at the
the Multitracers
MultitracersGyre
Gyresite
site (+4.2øC).
(-i-4.2°C).Both
Bothof
ofthese
these sites
sites
andat
significantly
an intercept
interceptof
of 1.7±0.4,
1.7_+0.4,
which and
is
significantly
different
from
zero,
and
an
RMS
error
of
1.9°C,
are
located
in
the
California
Current
region
where
coretops
is significantlydifferentfrom zero,and an RMS errorof 1.9øC, arelocatedin the California Currentregion wherecoretopsare
are
almost 0.5øC
0.5°C larger
larger than
than the
the RMS
error for
for the
the modern
modem analog
analog relatively
relatively scarce
scarce and
and calcite
calcite dissolution
dissolutionis
isheavy.
heavy. At
almost
RMS error
At least
leastsome
some
method (Table
(Table 6).
of the
error associated
associatedwith
with these
these two
two traps
method
6).
of
the temperature
temperature
error
trapsmust
must
Temperature bias
bias in
in the
method for
from inadequacy
inadequacy of
of the
the coretop
coretopcalibration
calibrationdata
dataset.
set. While
While
Temperature
theImbrie-Kipp
Imbrie-Kippmethod
for the
thesediment
sediment arise
arisefrom
trap faunas
faunas was
was expressed
expressedas
asaaslope
slopeof
of0.92+0.16,
0.92±0.16, aa nonzero
both of
are serious,
of the
the errors
errors described
describedabove
above are
serious, similar
trap
nonzero both
estimatedSST
SSTfor
forboth
both the
the coretop
coretop and
Irap data
sets
estimated
andsediment
sedimenttrap
datasets
(Figures
4
and
5).
Four
regression
statistics
(slope,
intercept,
(Figures4 and 5). Four regressionstatistics(slope, intercept,
RMS error,
error, and
and mean
mean residual
residual value)
value) are
are summarized
summarized in
in Table
Table 6.
RMS
6.
A
slope significantly
significantly different
A slope
differentfrom
from 11 indicates
indicatesresidual
residualtrends
trends
in
estimates. A
in the
the SST
SST estimates.
A regression
regressionintercept
interceptor
or aa mean
meanresidual
residual
value
significantly
different
from
zero
indicates
value significantly different from zero indicates a
a constant
constant
186
MIX: SEDIM•
SEDIMENT TRAP-CORE
ThAP-CORE TOP
TOP COMPARISON
COMPARISON
ORTIZ AND MIX:
•
q
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3434
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rI
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3030J._
b
Imbrie-Kipp,
S >20øC.
:1
2622-
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I
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d
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ß•':,.,,,,':'-b,•:'""
,.-4'-.
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-5-
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'½',,•!•,•0
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ß
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Levitus SST
SST (øC)
(°C)
Levitus
Levitus SST
SST (°C)
Levi•s
(øC)
E-
I
/
? 4'"*"'
ß-t-'4-
00
,4.
-10-
-15
-15-i
I,
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-2
,I
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I,
10 14
22 26 30
10
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1822263034
-10-,
34
Levitus
LevitusSST
SST (°C)
(øC)
Levitus SST (°C)
Levitus
(øC)
1515
30
30
10lO
Fca 20
:20-
5
5-
i:.'
-....
0
::.-'t.,""•,•:
:•'
,
,
-2 2 6 10 14 18 22 26 30 34
f
I
S
S
S o e
oo
.•
-..:,.-.
0
::,
-15
1.0
1.0
-10
0.8
0.6 0.4
0.2
0.8
0.6
0.4
0.2
Communality
Communality
oo
+
0.0
0.0
1.0
0.8
0.6
0.6
0.4
0.4
0.2
0.2
•.•
0.0
Communality
Communality
Sediment
Traps
range)
Sediment
Traps(in
(in calibration
calibration
range)
Sediment
Traps
(outside
calibration
range)
SedimentTraps(outsidecalibrationrange)
Core Tops
Tops (in
calibration range)
range)
Core
(in calibration
Figure
ofofthe
culled
Imbrie-Kipp
transfer
functions.
Dashed
and
in Figure
Figure6.6.Results
Results
the
culled
Imbrie-Kipp
transfer
functions.
Dashed
andsolid
solidlines
linesare
areas
asdefmed
defined
in
Figure
6a,
6e
function
based on
on all core
core tops
tops >8øC.
>8°C. Figures
6b, 6d.
4. Figures
Figures
6a,6c,
6c,and
and
6eshow
showtransfer
transfer
function
based
Figures
6b,
6d,and
and6f show
show
transfer function
based on
on all
communality
axis.
transfer
function
based
all core
coretops
tops>20°C.
>20øC.Note
Notereversed
reversed
communality
axis.
ORTIZ AND MIX:
MIX: SEDIMENT TRAP-CORE TOP COMPARISON
AssessingPotential
PotentialBias
Bias inin the
Assessing
the Sediment
Sediment Trap
Trap
12
Data Set
Set
Data
a
10-
We observed
observed that
that the
the basic
basic structure
structure of
of the
the sediment
sediment trap
We
trapand
and
core
top
faunas
relative
to
SST
were
comparable
by
applying
core top faunasrelative to SST were comparableby applying
the
coretop factor
to the
The
the coretop
factor model
model to
thesediment
sedimenttrap
trapdata
dataset.
set. The
greatest differences
between the
the two
two data
in
greatest
differencesbetween
data sets
sets occurred
occurredin
I
I
II
11
2
2
3
II
I
I
4
5
6
Trap deployment
deployment duration
Trap
duration(years)
(years)
7
12
12
b
10101
8-
<
44
•
22
overall
exhibit smaller
smaller error
error than
than most
most of
of the
overall duration
durationexhibit
the >125
> 125 jim
gm
and
>150 Ilm
pm sieved
sievedsamples.
samples. One
One explanation
explanation for
for this
this curious
and>150
curious
result
is that
sediment traps
traps
result is
that these
thesesamples
sampleswere
werecollected
collectedfrom
from sediment
deployed
in tropical
regions where
where small
small species
species are
are relatively
relatively
deployedin
tropicalregions
uncommon
1959]. AA second
uncommon[e.g.,
[e.g., Bradshaw,
Bradshaw,1959].
secondexample
example serves
serves
to
to illustrate
illustrate this
this point
point further.
further.Small
Smallspecies,
species,particularly
particularlyG.
G.
00
-2
-2
I
0
midlathude faunas
and
midlatitude
faunaswhich
whichhad
hadrelatively
relativelypoor
poorcoznmunalities
communalities
and
large
modern
analog
dissimilarities
relative
to
coretops
(Table
largemodemanalogdissimilaritiesrelative to coretops(Table
5). These
betweenthe
the two
two data
data sets
5).
Thesedifferences
differencesbetween
setsmay
mayoccur
occur
because (1)
(1) the
the global
global factor
factor model
model does
does not
not adequately
resolve
because
adequatelyresolve
forazniniferal faunal
faunal variability
variability in
in the
the midlatitudes,
midlatitudes, (2)
(2) delicate,
foraminiferal
delicate,
soluble
individuals
in
the
sediment
trap
faunas
are
unlikely to
to
solubleindividualsin the sedimenttrap faunasare unlikely
be weli
preserved in
in the
the geologic
be
well preserved
geologic record,
record, or
or (3)
(3) the
thedifference
difference
between the
the sediment
sediment trap
trap and
andcoretop
coretopdata
dataset
setisisdue
duetotosieving
sieving
between
artifacts
and/or
the
duration
of
trap
deployment.
artifactsand/orthe durationof trap deployment.
We
the third
third point
point before
before dealing
dealing with
with the
the other
We will
will address
addressthe
other
two
between the
the two
two data
two possibilities.
possibilities. If
If the
the difference
differencebetween
data sets
sets
were
artifact alone,
that the
the absolute
absolute
were due
due to
to artifact
alone, we
we predict
predict that
magnitude
of the
trap residuals
residuals would
would increase
increase as
as sieve
sieve
magnitudeof
thesediment
sedimenttrap
size
moved
farther
from
the
standard
>150
pm
sieve
size
size moved farther from the standard>150 !lm sieve size and
and
would
increasing trap
Perhaps
trap duration.
duration.
would decrease
decreasewith
with increasing
Perhaps
surprisingly,
surprisingly,the
the absolute
absoluteSST
SSTresiduals
residualsfrom
from both
both the
theImbrieImbrieany
Kipp
Kipp and
and modern
modem analog
analog methods
methods do
do not
not indicate
indicate any
systematic
on sieve
sieve size
systematic dependence
dependenceon
size (Figure
(Figure 7).
7). Indeed
Indeed the
the
>100
sieved samples
samples that
for the
>100 jim
pxnsieved
that were
were deployed
deployed for
the shortest
shortest
Slope
-0.4°C/year explains
Slopeof
of-0.4øC/year
explains45%
45%
of
of the
the>125
>125 jim
!xmerror
errorvariance.
variance.
6[-
187
187
I
I
I
I
2
4
5
6
3
Trap
deployment
duration
(years)
Trapdeployment
duration(years)
11
0
7
100
m sieve
100 gm
sieve
125
pmsieve
125 gm
sieve
oo
150
150 j.tm
gm sieve
sieve
magnitudeof
of the
the sediment
Figure
Figure 7. Absolute
Absolutemagnitude
sedimenttrap
trapSST
SST
residuals for
for (a)
residuals
(a) the
the hnbrie-Kipp
Imbrie-Kipp method
methodand
and(b)
(b) the
themodem
modem
analog
as aa function
analogmethod
methodas
functionof
of the
thesediment
sedimenttrap
trapdeployment
deployment
duration
andseive
seivesize.
size. Slope
Slope in
in Figure
Figure7b
lb is
durationand
is based
basedon
on aa least
least
squares
regression
of
only.
squares
regression
of the
the>125
>125jim
!xmsamples
samples
only.
situations are
situations
areavoidable
avoidablein
in downcore
downcoreapplications
applicationsby
bycareful
careful
attention
by
attentionto
to the
thequality
qualityof
of the
themodem
modemanalogs
analogsas
asindicated
indicatedby
the
magnitude
of
the
dissimilarity
coefficient.
In
a
sediment
the magnitudeof the dissimilarity coefficient. In a sediment
application,
erroneous SST
SST estimates
estimates such
such as
as those
those at
application,erroneous
atGyre
Gyreand
and
the
Basin would
wouldnot
not be
be predicted
the San
San Pedro
PedroBasin
predictedifif aa critical
critical
dissimilarity threshold
threshold of
of 0.20
0.20 were
were used
used as
as aa cutoff
dissimilarity
cutoff criteria.
criteria.
are present
present in
in high
high relative
relative abundance
abundance in
in the
the >125
quinqueloba,
quinqueloba,are
> 125
pm
sediment trap
trap samples
samples from
from the
the Gulf
of Alaska
lira integrated
integratedsediment
Gulf of
Alaska
and the
the San
San Pedro
Pedro basin.
basin. This
This accounts
accountsin
inlarge
largepart
part for
for the
the low
and
low
communality and
andhigh
high dissimilarities
dissimilarities of
of these
communality
thesetwo
two integrated
integrated
sediment trap
While the
extreme
sediment
trap samples
samples (Fable
(Table 5).
5).
While
the extreme
dissimilarity and
and low
low communality
communalityfor
for the
the Gulf
Gulf of
of Alaska
dissimilarity
Alaska
sample might
might indicate
sample
indicateits
its temperature
temperatureestimate
estimateshould
shouldbe
be very
very
poor, itit actually
produces aa temperature
temperatureestimate
estimatewith
with less
less error
error
poor,
actuallyproduces
than the
the San
San Pedro
Pedrotrap
trapsample.
sample. The
The observation
observation that
that coretops
than
coretops
from
the
vicinity
of
the
Gulf
of
Alaska
core
are
somewhat
more
from the vicinity of the Gulf of Alaska core are somewhatmore
common than
than those
those from
from the
the San
San Pedro
PedroBasin
Basin in
in the
common
the coretop
coretop
data set
set provides
provides aa plausible
plausible explanation.
data
explanation. In
In short,
short, sieve
sieve size
size
does not
not appear
to exhibit
exhibit any
effects on
on the
does
appearto
any systematic
systematiceffects
the SST
SST
residuals in
in the
residuals
the sediment
sedimenttrap
trapdata
dataset.
set.
Three
points can
with respect
respect to
Three key
key points
canbe
be made
madewith
to sediment
sedimenttrap
trap
duration.
First,
the
Imbrie-Kipp
method
produced
residuals that
that
duration. First, theImbrie-Kippmethodproducedresiduals
were independent
independent of
of sediment
sediment trap
trap duration
This
were
duration(Figure
(Figure7a).
7a). This
result seems
as the
result
seemsplausible,
plausible, as
the errors
errors in
in the
the Imbrie-Kipp
Imbrie-Kipp
temperature
regression
are
largely
a
function of
of the
temperatureregressionare largely a function
thestructure
structureof
of
the
coretop
faunas
that
determine
the
terms
in
the
the coretop farinasthat determine the terms in the transfer
transfer
function. Additionally,
the use
use of
of factor
factor analysis
analysis acts
acts to
to filter
function.
Additionally,the
filter
the sediment
the
sediment trap
trap observations
observationsof
of random
randomvariations.
variations. In
In
contrast, modem
contrast,
modem analog
analogSST
SST residuals
residualstend
tend to
to decrease
decreasewith
with
longer trap
trap •eployments
teployments (Figure
(Figure 7b).
7b). Again,
longer
Again,such
suchaa trend
trendseems
seems
plausible. Longer
integration times
times should
should result
result in
in samples
plausible.
Longerintegration
samples
with increasing
similarity to
to fossil
fossil faunas.
with
increasingsimilarity
faunas.The
Thetrend
trendaccounts
accounts
for
roughly 45%
45% of
of the
the error
error variance
variance in
in the
the seven
for roughly
seven>125
>125 pm
sieved
samples.
Interestingly,
errors
that
are
not
statistically
sievedsamples. Interestingly,errorsthat arenot statistically
188
188
ORTIZ AND
AND MIX:
MIX: SEDIMENT
SEDIMENT TRAP-CORE
TRAP-CORE TOP
TOP COMPARISON
COMPARISON
ORTIZ
different
by the
the two
two sediment
differentfrom
from zero
zeroare
areachieved
achievedby
sedimenttrap
trapfaunas
faunas
with
with deployment
deploymentduration
durationof
of 4-6
4-6 years.
years.
21
This
casts doubt
on the
wisdom
that
This result
result casts
doubt on
the conventional
conventional
wisdom that
argues sediment
sedimenttraps
traps are
are not
not directly
directly comparable
comparable to
to core
core tops
tops
argues
because
of their
their differences
differencesinin integration
integration time
time (months
becauseof
(months to
to
years
decadesto
to millennia
millennia in
in core
years in
in sediment
sedimenttraps
traps versus
versusdecades
core
tops). One
to explain
tops).
One way
way to
explain this
this result
result is
is that
that variance
varianceat
at an
an
foraminiferal
assemblages,
annual
cycle
dominates
living
annual cycle dominates living foraminiferal assemblages,
while variance
while
variance at
at interannual
interannualtime
time scales
scales is
is significantly
significantly
smaller. If
trap
would
smaller.
If so,
so,aafew
fewyears
yearsof
ofsediment
sediment
trapdeployment
deployment
would
with
sufficient
capture
the
long-term
mean
assemblage
capture the long-term mean assemblage with sufficient
precision for
data collected
collected over
over
precision
for calibration
calibrationwith
with temperature
temperaturedata
the
last few
few decades,
decades,or
or for
for comparison
comparison with
with geologic
geologic samples
the last
samples
that
that accumulated
accumulatedin
in the
thelast
lastfew
few thousand
thousandyears.
years.
To
summarize,
sieve
size
does
not appear
appear to
toplay
play aa dominant
dominant
To summarize,sievesize doesnot
factor
in determining
factor in
determiningthe
themagnitude
magnitudeof
of the
theSST
SSTerrors
errorsrecorded
recorded
by
sediment trap
trap faunas.
faunas. Sediment
trap duration
does not
not
by these
thesesediment
Sedimenttrap
durationdoes
appear
to the
appear to
to contribute
contributesignificantly
significantly to
theImbrie-Kipp
Imbrie-Kipp SST
SST
errors
but could
could account
accountfor
forup
uptoto45%
45%ofof the
the variance
variance in
in the
errorsbut
the
modem
temperature estimates.
estimates. Sediment
Sediment trap
trap records
records of
of
modem analog
analogtemperature
more
4 years
years duration
duration appear
appear sufficient
sufficient to
to provide
more than
than4
provideaverage
average
assemblages analogous
analogousto
to those
those in
in geologic
geologic samples.
samples. Because
assemblages
Because
significant
sources
of
error
between
the
sediment
trap and
core
significantsourcesof error betweenthe sedimenttrap
andcore
top sediments
remain, we
we explore
explore the
top
sedimentsremain,
the two
two remaining
remainingalternative
alternative
hypotheses:
hypotheses:(1)
(1) the
theglobal
globalfactor
factormodel
modeldoes
doesnot
notadequately
adequately
resolve
variability in
resolveforaminiferal
foraminiferalfaunal
faunalvariability
in the
themidlatitudes
midlatitudesand
and
(2) delicate,
delicate, soluble
soluble individuals
individuals in
in the
the sediment
(2)
sedimenttrap
trap faunas
faunasare
are
unlikely to
unlikely
to be
be well
well preserved
preservedin
in the
thegeologic
geologicrecord.
record.
The first
The
first possibility
possibilityseems
seemsunlikely.
unlikely. For
For example,
example,several
several
of
the
factors
exhibit
high
factor
loadings
in
of the factorsexhibit high factor loadings in the
themidlatitude
midlatitude
temperature range
range (Figure
temperature
(Figure 3),
3), suggesting
suggestingmodel
model terms
terms of
of
significance
Dismissing
significanceto
to these
theseregions
regionshave
havebeen
beenisolated.
isolated. Dismissing
us to
the
the first
first possibility
possibility leads
leads us
to conclude
concludethat
that the
the second
second
possibility,
dissolution,
may
play
a
role
in
the
sediment
possibility, dissolution,may play a role in the sedimenttrap
trap
the results
versus core
versus
core top
top differences.
differences. Although
Although the
results were
were
considerably noisy,
noisy, the
the sediments
appear to
to be
be enriched
considerably
sedimentsappear
enrichedin
in
robust species
after the
the dissolution
robust
species which
which remain
remain after
dissolution of
of more
more
fragile
fragile species
speciesfrom
from the
the sediment
sedimenttrap
trapfaunas.
faunas. Despite
Despite these
these
differences,
the
coretop
calibration
data
set
estimated
differences,the coretopcalibration dataset estimatedaccurate
accurate
SST
for most
mostof
ofthe
thesediment
sedimenttrap
trapfaunas.
faunas.In
In the
the final
final section,
section,
SST for
we
explore the
the error
error at
at Gyre
Gyreinin closer
closerdetail
detailas
as aa means
means of
of
we explore
evaluating
this
potential
dissolution
bias
in
the
sediment
evaluating this potential dissolution bias in the sediment
record.
record.
Assessing Potential
Potential Dissolution
Assessing
Dissolution Bias
Bias in
in the
the Core
Core
Top Data
Top
Data Set
Set
The Gyre
Gyre sediment
sedimenttrap
trap is
is located
located in
in the
The
the California
CaliforniaCurrent,
Current,
650
off the
the southern
southern Oregon
Oregoncoast.
coast. On
650 km
km off
On aa seasonal
seasonalbasis,
basis,
this site
fauna
this
siteshifts
shiftsfrom
from aasummer/fall
summer/fallsubtropical
subtropical
faunadominated
dominated
by O.
0. wziversa
G. ruber
ruber to
winter/springfauna
fauna rich
rich
by
universaand
andG.
to aa diverse
diversewinter/spring
in right-coiling
pachyderma,N.
N.dutertrei,
dutertrei,G.
G.glutinata,
gltainaa, G.
in
right-coiling N.
N. pachyderrna,
G.
quinqueloba, G.
and G.
G. falconensis.
falconensis. The
quinqueloba,
G. bulloides,
bulloides,and
The remainder
remainderof
of
the
G. calida,
calida, T.
T. humilis,
humilis, and
the species
speciesin
in this
thisfauna
faunainclude
includeG.
and G.
G.
scitula [Ortiz
scitula
[Ortiz and
and Mix,
Mix, 1992].
1992]. The
The resulting
resultingflux-weighted
flux-weighted
annual
average fauna
fauna is
is composed
composedof
of 37%
37% O.
0. universa
annualaverage
universaand
and13%
13%
G.
G. rube,'.
ruber.
of the
In the
In
the underlying
underlying core
core top
top sediments
sedimentsof
the northeast
northeast
Pacific, O.
0. universa
and G.
G. ruber
ruber accounts
accountsfor
for 0-5%
0-5% of
of the
the
Pacific,
universa and
18
'.... '....
ß,.
'...
ß....
ß..
•
-..,
15
-...
ß..
%
•'**
,,o
12
9
134
0O
iI
I
I
I
132
130
128
126
124
Longitude (°W)
Longitude
(øW)
Levitus SST
Levitus
SST (°C)
(øC)
Predicted SST
0% simulated
simulated dissolution
dissolution
........1 ........ Predicted
SST for
for 0%
Predicted SST
dissolution
........& ........ Predicted
SST for
for 50%
50% simulated
simulated dissolution
Predicted SST
dissolution
0O ........ Predicted
........
SST for
for 75%
75% simulated
simulated dissolution
Predicted SST
dissolution
........• ........ Predicted
SST for
for 90%
90% simulated
simulated dissolution
Figure 8.
8. Effects
Figure
Effectsofofnumerical
numericaldissolution
dissolution scenarios
scenarios on
on
modem analog
analog temperature
modem
temperatureestimates
estimates from
from the
theMultitracers
Multitracers
sedimenttraps.
traps. Error
Error bars
bars of
of +1.5øC
±1.5°C apply
apply in
in all
all cases
sediment
casesbut
but for
for
clarity are
text
clarity
are shown
shownonly
only for
for0%
0% and
and75%
75% simulations.
simulations. See
See text
for further
for
further details.
details.
expectations
for its
its relative
relative abundance
abundance in
in the
the underlying
expectationsfor
underlyingrecent
recent
sediments
by at
at least
for
sedimentsby
least32%.
32%. Moreover,
Moreover,the
the37%
37%abundance
abundance
for
0.
the maximum
abundance for
for this
this species
O. universa
universaexceeds
exceedsthe
maximumabundance
species
recordedininthe
theentire
entireglobal
globalcoretop
coretopdata
database
baseby
by 19%.
19%. The
recorded
The
13% abundance
abundance for
for G.
G. ruber
ruber exceeds
for its
13%
exceedsexpectations
expectations
for
its relative
relative
abundance
in the
the underlying
underlying sediments
sedimentsby
byat
at least
least 8%.
8%. Because
abundance
in
Because
these
these two
two species
speciesare
are indicative
indicative of
of warmer
warmer waters
waters than
than the
the
remainder of
of the
in the
and both
remainder
the species
species in
the Gyre
Gyre fauna,
fauna, and
both are
are
relatively sensitive
relatively
sensitive to
to dissolution,
dissolution, it
it seems
seems likely
likely they
they
contribute heavily
heavily to
to the
temperaturebias
bias at
at the
the
contribute
the 4.2°C
4.2øC warm
warm temperature
Gyre site.
Gyre
site.
To
the contribution
of these
these two
To evaluate
evaluatethe
contributionof
two species
speciesto
to this
this
problem, we
modernanalog
analog SST
SSTfor
for the
the three
problem,
we recalculated
recalculatedmodem
three
sediment traps
traps in
in the
sediment
theMultitracers
Multitracerstransect
transectafter
after"numerically
"numerically
dissolving"
the
sediment
trap
faunas
(Figure
We
dissolving" the sediment trap faunas (Figure 8).
8).
We
accomplished
this by
by making
makingvery
very simple
simple assumptions
assumptions of
accomplished
this
of how
how
dissolution might
might affect
affect these
these samples.
samples. These
are
dissolution
Theseassumptions
assumptions
are
that
0. universa
G. ruber
ruber would
would be
be removed
removed at
at equal
rates at
thatO.
universaand
andG.
equalrates
at
all
sites and
that no
no dissolution
all three
threesites
andthat
dissolutionof
of other
otherspecies
specieswould
would
occur. This
very simple
occur.
Thisprovides
providesaa very
simplescenario
scenariofor
for evaluating
evaluatingthe
the
impact
of these
these two
two species
species on
on estimated
estimatedSST
SST while
while holding
holding all
all
impactof
other variables
other
variablesconstant.
constant. Sensitivity
Sensitivitystudies
studieswere
werecarried
cardedout
out
foraminiferal
assemblage [Coulbourn
[Coulbournet
etal.
al. 1980].
1980]. An
An annually
annually
foraminiferalassemblage
on faunas
faunas with
with 50%,
50%, 75%,
75%, and
and 90%
90%of
of the
the individuals
individuals of
of these
these
universa exceeds
averaged
averaged abundance
abundance of
of 37%
37% for
for 0.
O. universa
exceeds on
ORTIZ
TOP
ORTIZAND
ANDMIX:
MIX: SEDIMENT
SEDIMENTTRAP-CORE
TRAP-CORE
TOPCOMPARISON
COMPARISON
189
189
species
from the
the faunal
was provided
by a
a grant
speciesremoved
removedfrom
faunallist.
list. The
The various
variousspecies
species OSU
OSUwas
provided
by
grantfrom
fromthe
theNSF.
NSF.This
ThisisisLamont-Doherty
Lamont-Doherty
percentages were
were recalculated
recalculated following
following each
each "dissolution"
"dissolution" step
step Earth
contribution
5598.
EarthObservatosy
Observatory
contribution
5598.
percentages
to preserve
preserve percent
percent abundance
abundanceclosure,
closure, and
and then
then modern
modern analog
analog
to
SST
estimates
were
generated
for
the
new
fauna.
SST estimates
weregenerated
for thenew fauna.
References
References
Removal
Removalof
of up
up to
to 50%
50% of
of the
theindividuals
individualsof
of these
thesetwo
twospecies
species
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D.M., W.L
W.L Prell,
of sea
results
in
SST
estimates
which
overlap
within
errors
with
the
Prell, and
and NJ.
N.J.Barratt,
Barratt,Estimates
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seasurface
surface
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coral sea
sea at
at the
in
the
temperature
initial
modem
analog
SST
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in
the
coral
the
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initial modernanalog SST estimatesfor thesethree samples Paleoceanography, 4, 615-627, 1989.
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(Figure 8).
8). Thus
is quite
robust to
to Beck,
(Figure
Thusthe
themodem
modernanalog
analogmethod
methodis
quiterobust
J.W.,R.L
R.L Edwards,
Beck,LW.,
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75% of
of the
moderate
moderate dissolution.
dissolution.
Removal of
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individuals of
of
Joanno
and
temperature
$oannot,
andC.
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Heinin,Sea-surface
Sea-surface
temperaturefrom
from coral
coralskeletal
skeletal
these
two
species
from
the
Gyre
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resulted
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SST
estimates
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257,644-647,
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ratios,Science,
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644-647,1992.
1992.
thesetwospecies
fromtheGyrefaunaresultedin SSTestimates stronsiwn/calcium
Bradshaw,L,
I., Ecology
Ecologyof
ofliving
livingplanktonic
planktonicforaminifera
foraminiferain
inthe
the north
north and
and
which
were similar
similar to
to the
the historically
historically recorded
recorded SST
SST at
at that
that site.
site. Bradshaw,
whichwere
equatorial
Pacific
Oceans,
Contrib.
Cushman
Found.,
Foraminfera1
equatorial
Pacific
Oceans,
Coatrib.
Cushman
Found.,
Foraminiferal
In
the
more
coastal
sites,
removing
greater
than
50%
of
these
In the more coastalsites, removinggreaterthan 50% of these
Rat.,
Res.,10,25-64,
10, 25-64,1959.
1959.
This Broccoli,
two
of
two species
speciesresulted
resultedin
in SST
SSTunderestimates
underestimates
of l°-3°C.
1ø-3øC. This
AJ., and
glacial climate
climate
Broccoli,A.J.,
andE.P.
E.P.Marciniak,
Marciniak,Comparing
Comparingsimulated
simulatedglacial
result suggests
suggests the
the Gyre
Gyre site
site thermal
thermalbias
biasderives
derivesfrom
fromthe
thehigh
high
and
A
Paleoceanography,
11,
result
andpaleodata:
palcodata:
A reexamination,
re.
examination,
Paleoceanography,
11,3-14,
3-14,1996.
1996.
surface ocean
ocean
Broecker, W.S.,
on surface
relative abundance
abundance of
of O.
0. isniversa
G. ruber
in the sediment
relative
universa and G.
ruber in
sediment
Broecker,
W.S., Oxygen
Oxygenisotope
isotope constraints
constraintson
temperatures,
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temperatures,
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121-134,1986.
1986.
Climate: Long-Range
Long-Range Investigation,
Investigation, Prediction,
Prediction, and
and Mapping
Climate:
Mapping(CLIMAP)
(CLIMAP)
Project
Members,The
The surface
surface of
of the
ProjectMembers,
the ice
ice age
ageEarth,
Earth,Science,
Science,191,
191,
dissolution of
of these
these fragile
fragile species
speciesfrom
fromthe
thefossil
fossil assemblage.
assemblage.
1131-1137,
dissolution
1131-1137,1976.
1976.
CLIMAP Project
Project Members,
Unfortunately,
simply culling
Members,Seasonal
Seasonalreconstructions
reconstructionsof
of the
the earth's
earth's
Unfortunately,simply
cullingthese
thesespecies
speciesfrom
fromthe
thelist
listused
used CLIMAP
susface at
the
last
glacial
maximum,
Geol.
Soc.
Am.
Map Chart
surface
at
the
last
glacial
maximum,
Geol.
Soc.
Am.
Map
Chart Ser..
Ser.,
in
the
calculation
of
sample
dissimilarities
does
not
solve
this
in the calculationof sampledissimilaritiesdoesnot solve this
MC-36,
MC-36, 1-18,
1-18, 1981.
1981.
preservation problem.
problem. We
additional experiments
experiments in
in Coulbown,
preservation
We conducted
conducted
additional
W.T.,F.L.,
FL, Parker,
Coulboum,W.T.,
Parker, and
and W.H.
W.H. Berger,
Berger, Faunal
Faunaland
andsolution
solution
which
we excluded
excludedthese
thesetwo
twospecies
speciesfrom
fromthe
the taxonomic
taxonomic list
which we
list
patterns
of planktcnic
of
pauemsof
planktonicforaminifera
foraminiferain
in surface
surfacesediments
sediments
of the
theNorth
North
and
modern analog
Pacific, Mar. Micropaleontol..
5,
andthen
thenrecalculated
recalculated
modern
analogSST.
SST. In
In the
theabsence
absenceof
of
Pacific,
Micropaleontol.,
5, 329-399,
329-399,1980.
1980.
Deuser, W.G.,
W.G., Seasonal
Seasonal variation
variation in
in isotopic
isotopic composition
compositionand
and deep-water
deep-water
these
the dissimilarity
dissimilarity function
matrix, analogs
thesespecies
speciesfrom
from the
function matrix,
analogs I)euser,
fluxes
of the
abundant
planktonic
foraminifera of
of
fluxesof
the tests
testsci
ofperennially
Perennially
abundant
planktonicforaminifera
are selected,
and the
for
for slightly
slightly more
morenorthern
northern latitudes
latitudes are
selected, and
the
the
Sargasso
Sea:
Results
from
sediment-trap
collections and
and their
the
Sargasso
Sea:
Results
from
sediment-trap
collections
their
resulting modern
the true
true SST.
resulting
modemanalog
analogSST
SSTunderestimates
underestimates
the
SST.
significance,
I. Foraminferal
14-27,
paleoceanographic
paleoceanographic
significance,J.
ForaminiferalRes.,
Res.,17,
17, 14-27,
1987.
1987.
Deuser, W.G.,
W.G., and
planktomc
Deuser,
and E.H.
E.H. Ross,
Ross,C.,
C., Seasonally
Seasonallyabundant
abundant
planktonic
Conclusions
Conclusions
foraminifera of
of the
Sea:
deep-water
foraminifera
the Sargasso
Sargasso
Sea:succession,
succession,
deep-waterfluxes,
fluxes,
isotopic compositions,
isotopic
compositions,and
and paleoceanographic
paleoceanographicimplications,
implications,I.
J.
We
reassessed
the
utility
of
the
Imbrie-Kipp
and
modem
We reassessed
the utility of the Imbrie-Kipp and modem
Foranwsjferal
Ram.,
19, 268-293.
Foraminiferal
Res.,19,
268-293,1989.
1989.
from Donner,
of estimating
estimating paleotemperature
analog methods
B., and
and G.
of
analog
methods of
palcotemperature from
Donner, B.,
G. Wefer,
Wefer, Flux
Flux and
andstable
stableisotopic
isotopiccomposition
compositionof
!'leogloboquad.rina
pachydermaand
and other
other planktonic
Our approach
foraminiferal
Neogloboquadrina
pachyderma
planktonicforaminifers
foraminifersin
in
foraminiferalfaunas.
faunas. Om
approachdiffers
differs from
from previous
previous
the Southern
Ocean (Ariantic
(Atlantic sector),
sector),Deep
DeepSea
SeaRes.,
Res.,Part
Pan I,1, 41,
41, 1733the
SouthernOcean
1733sediment based
based calibration
calibration studies
because we
weuse
use global
global core
sediment
studiesbecause
core
1743, 1994.
1994.
for Fairbanks
faunas for
calibration and
top faunas
top
faunasfor
for calibration
andsediment
sedimenttrap
trap faunas
R., and
and P.H.
and chlorophyll
FairbanksR.,
P.H. Wiebe,
Wiebe,Fomaminiferal
Foraminiferaland
chlorophyllmaximum:
maximum:
validation. Our
Our results
results can be summarized
validation.
summarized as
as follows.
follows.
Vertical
seasonal succession,
and paleoceanographic
Vertical distribution,
distribution,seasonal
succession,and
paleoceanographic
significance,
Science,
209,
the sediment
sediment trap
trap and
and coretop
coretop faunal
1. The
The basic
basicstructure
structureof the
faunal
significance,
Science,
209,1524-1526,
1524-1526,1980.
1980.
T.,
Rubenstone, Tropical
Guilderson,
R.G.
Fairbanks, and
and J.L.
Guilderson,
T.,
R.G.
Fairbanks,
J.L. Rubenstone,
Tropical
assemblages
are
comparable.
The
greatest
difference
occurs
in
assemblages
arecomparable.
Thegreatest
difference
occursin
variations
since
20,000
years
ago:
temperature
temperature
variations
since
20,000
years
ago: Modulating
Modulating
midlatitude faunas
faunas where
midlatitude
where the
the sediment
sediment traps
traps have
have poor
poor
interhemnispheric
climate change,
change. Science,
Science, 263,
263, 663-665,
interhemispheric
climate
663-665,1994.
1994.
comxnunalities
relative to
to coretops.
communalitiesrelative
coretops. These
Thesedifferences
differencesmay
may Hutaon,
Analysis
Hutson,W.H.,
W.H., The
The Aguihas
AgulhasCurrent
Currentduring
duringthe
theLate
LatePleistocene:
Pleistocene:
Analysis
arise
from
the
scarcity
of
coretops
in
midlatitude
regions
as
of
Science,
arisefrom the scarcityof coretopsin midlatituderegionsas
of modem
modemfaunal
faunalanalogs,
analogs,
Science,207,
207,64-66,
64-66,1980.
1980.
and N.G.
method
well as
as the
the presence
presence of
of delicate,
delicate, soluble
soluble forms
forms in
in the
Imbrie, 1.,
J., and
N.G. Kipp,
Kipp, A
A new
newmicmpaleontological
micropaleontological
methodfor
for
well
thesediment
sediment Imbrie,
quantitative
Application
to aa Late
Late Pleistocene
Pleistocene
quantitativepaleoclimatology:
paleoclimatology:
Applicationto
traps which
unlikely to
in
traps
whichare
areunlikely
to be
bewell
wellpreserved
preserved
in sediments.
sediments. Caribbean
core, in
Glacial Ages,
Ages, edited
edited by
by K.
Caribbean core,
in The
The Late
Late Cenozoic
CenozoicGlacial
K.
Despite these
these differences,
the coretop
Despite
differences,
the
coretopcalibration
calibrationdata
data set
set
Turekian,
Turekian,pp.
pp.71-181,
71-181,Yale
YaleUniv.
Univ.Press,
Press,New
New Haven,
Haven,Conn.,
Conn.,1971.
1971.
effectively
estimated
SST
for
most
of
the
sediment
trap
faunas.
effectively
estimated
SSTformostof thesediment
trapfaunas. Kipp,
Kipp, N.G.,
N.G., New
New transfer
transferfunction
function for
for estimating
estimatingpast
pastseasurface
seasurface
modem analog
analog method
method exhibited
exhibited less
and
conditions
from sea
sea level
level distribution
distributionof
of planktonic
planktonic foraminifera
foraminifera in
2. The
The modern
lesssystematic
systematic
and
conditions
from
in the
the
North
random bias
bias than
than the
method over
over the
the full
full range
range of
NorthAtlantic,
Atlantic,Geol.
Geol.Soc.
Soc.Am.
Am.Me,n.,v.
Mem.,v.18,
18, 3-41,
3-41, 1976.
1976.
random
theImbrie-Kipp
Imbrie-Kippmethod
of
Le, J.,
estimation
Sensitivitytest
test on
on two
Le,
J.,Palaeotemperature
Palaeotemperature
estimationmethods:
methods:Sensitivity
two
global
globalSST.
SST.
western
westernequatorial
equatorialpacific
pacific cores,
cores,Quaternary
QuaternaryScience
ScienceReviews,
Reviews,11,
Regional
Imbne-Kipp
transfer
functions
exhibited
greater
3. RegionalImbrie-Kipptransferfunctions
exhibitedgreater 801-820, 1992.
1992.
systematic
bias and
and equal
equal or
or smaller
smaller random
randombias
bias than
than the
Levitus, S.,
S., Climatological
Climatological atlas
the world
NOAAProf.
Prof. Pap.
Pap. 13,
systematic
bias
the Levitus,
ariasof
of the
world ocean.
ocean,NOAA
13,
173
pp. US.
D.C.
global
function
173Pp.
U.S.Ckwi.
Govt.Print.
Print.Off.,
Off.,Washington,
Washington,
D.C.1982.
1982.
globalImbrie-Kipp
Imbrie-Kipptransfer
transfer
functionwe
wedeveloped.
developed.
Molfino, B.,
B., N.G.
N.G. Kipp,
of
Molfino,
Kipp, and
and J.
J.Morley,
Morley,Comparison
Comparison
of foraminiferal,
foraminiferal,
Coccolithophorid,
Coocotithophorid,and
and Radiolarian
Radiolarian paleotemperature
paleotemperatureequations:
equations:
Acknowledgments.
We
thank
the
captain
and
crew
of
R/V
Wecoma
Acknowledgments.
We thankthecaptain
andcrewof R/V Wecoma Assemblage
coherency and
and estimate
estimate concordancy,
concordancy, Quat.
Qua:. Res.,
Res., 17,
17, 279279Assemblagecoherency
and the
sedimenttrap
trap group
group for
for their
their efforts
efforts during
the
and
theMuhutracers
Multitracerssediment
duringthe
313,
1982.
313, 1982.
of
Muhitracers sediment
trap
J.D., and
and
succession
Multitracers
sediment
trapcroises.
cruises.Early
Earlyversions
versions
of the
themanuscript
manuscript Ortiz,
Ortiz, LD.,
andA.C.
A.C. Mix,
Mix, The
Thespatial
spatialdistribution
distribution
andseasonal
seasonal
succession
of
in the
off Oregon,
were
improved by
by comments
commentsfrom
fromN.
N.Pisias,
Pisias,P.
P.Wheeler,
Wheeler, M.
M. Abbott,
Abbott, and
and
of planktonic
planktonicforaminifera
foraminiferain
the California
CaliforniaCurrent
Currentoff
Oregon,
wereimproved
September
19871988, in
in Upwelling
Upwelling Systems:
Systemr: Evolution
Evolution Since
Since the
the Early
Early
September
1987-1988,
D.
D. Birkes.
Birkes. We
We thank
thankW.
W.Prell,
Prell,D.
D.Andreasen,
Andreasen,and
andtwo
twoanonymous
anonymous
Miocene, edited
edited by
by C.P.
C.P. Summerhayes,
Summerhayes,W.L.
W.L Prell,
Prell, and
and K.C.
Emeis,
Miocene,
K.C.
Emeis,
for this
reviewers
for their
reviewersfor
theirhelpful
helpfulreviews.
reviews. Funding
Fundingfor
thisproject
projectwas
was
197-213,
Geol. Soc.
PubI.. 64,
197-213,Geol.
Soc.Spec.
Spec.Publ.,
64, 1992.
1992.
provided by
by a
a NASA
NASA Graduate
Graduatestudent
studentfellowship
fellowshipto
tothe
thefirst
first author
author and
and Ortiz, J.D., A.C. Mix, and R.W. Collier, Environmental control of living
provided
Ortiz, LD., A.C. Mix, and R.W. Collier, Environmentalcontrolof living
Curation of
of the
by
to the
the Multitracers
project.
and asymbiotic
planktonic foraminifera
foraminifera in
in the
symbioticand
asymbioticplanktonic
theCalifornia
California
byNSF
NSFfunding
funding
to
Multitracers
project.Curation
theMultitracers
Multitracers symbiotic
Current,
Paleoceanography, 10,
987-1009,
1995.
Current,
Paleoceanography,
10,
987-1009,
1995.
sediment
trap
samples
at
the
NORCOR
Marine
Geological
Repositosy
at
sediment
trapsamples
attheNORCORMarineGeological
Repository
at
a no-analog
condition in
in the
traps
traps at
at the
the Gyre
Gyresite,
site, a
no-analog condition
the traps
traps
relative to
relative
to the
theregional
regionalcoretops
coretopsdue
dueto
to the
the removal
removal by
by
190
190
ORTIZ
TRAP-CORE
TOP COMPARISON
COMPARISON
ORTIZ AND
AND MIX:
MIX: SEDIMENT
SEDIM•
TRAP-CORE TOP
Overpeck. J.T.,
J.T., T.
T. Webb,
Webb, and
and I.C.
I.C. Prentice,
Prentice, Quantitative
Quantitative interpretation
interpretationof
of
Overpeck,
fossil pollen
pollen spectra:
spectra: Dissimilarity
Dissimilaritycoefficients
coefficientsand
andthe
the method
method of
of
fossil
modem analogs,
Re:., 23,
modem
analogs,Qual.
Quat.Res.,
23, 87-108,
87-108,1985.
1985.
Parker,
F.L, and
pauerns of
Parker,F.L•,
andW.L
W.L.Berger,
Berger,Faunal
Faunaland
andsolution
solutionpatterns
of planktonic
planktonic
foraminifera in
in surface
surface sediments
sediments of
of the
the South
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