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PALEOCEANOGRAPHY, VOL. 23, PA1216, doi:10.1029/2007PA001433, 2008
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Effects of surface ocean conditions on deep-sea calcite dissolution
proxies in the tropical Pacific
Figen Mekik1 and Lisa Raterink2
Received 14 February 2007; revised 23 October 2007; accepted 8 November 2007; published 26 March 2008.
[1] Finding the ideal deep-sea CaCO3 dissolution proxy is essential for quantifying the role of the marine
carbonate system in regulating atmospheric pCO2 over millennia. We explore the potential of using the
Globorotalia menardii fragmentation index (MFI) and size-normalized foraminifer shell weight (SNSW) as
complementary indicators of deep-sea CaCO3 dissolution. MFI has strong correlations with bottom water
[CO2
3 ], modeled estimates of percent CaCO3 dissolved, and Mg/Ca in Pulleniatina obliquiloculata in core top
samples along a depth transect on the Ontong Java Plateau (OJP) where surface ocean temperature variation is
minimal. SNSW of P. obliquiloculata and Neogloboquadrina dutertrei have weak correlations with MFI-based
percent dissolved, Mg/Ca in P. obliquiloculata shells and bottom water [CO2
3 ] on the OJP. In core top samples
from the eastern equatorial Pacific (EEP), SNSW of P. obliquiloculata has moderate to strong correlations
with both MFI-based percent CaCO3 dissolved estimates and surface ocean environmental parameters. SNSW
of N. dutertrei shells shows a latitudinal distribution in the EEP and a moderately strong correlation with
MFI-based percent dissolved estimates when samples from the equatorial part of the region are excluded. Our
results suggest that there may potentially be multiple genotypes of N. dutertrei in the EEP which may be
reflected in their shell weight. MFI-based percent CaCO3 dissolved estimates have no quantifiable relationship
with any surface ocean environmental parameter in the EEP. Thus MFI acts as a reliable quantitative CaCO3
dissolution proxy insensitive to environmental biases within calcification waters of foraminifers.
Citation: Mekik, F., and L. Raterink (2008), Effects of surface ocean conditions on deep-sea calcite dissolution proxies in the tropical
Pacific, Paleoceanography, 23, PA1216, doi:10.1029/2007PA001433.
1. Introduction
[2] Accurately quantifying deep marine CaCO3 dissolution has been a challenging oceanographic problem for
many decades [e.g., Arrhenius, 1952; Berger, 1973;
Broecker, 1982; Archer and Maier-Reimer, 1994; Mekik
and François, 2006]. Calcite preservation is a major component of the marine carbonate system (others include the
influx of ions into the ocean as weathering products from
land, the air-sea exchange of CO2, the marine biological
pump, and the rain ratio, which is the ratio of organic carbon
to calcite flux at the seabed); and developing a reliable
CaCO3 preservation proxy is important because the dissolution of carbonates in deep-sea sediments is an integral
part of the global carbon cycle in regulating atmospheric
pCO2 over thousands of years [Broecker, 1971; Archer and
Maier-Reimer, 1994; Archer et al., 2000].
[3] Most CaCO3 dissolution indicators are based, at least
in part, on the preservation state of foraminifer shells. Some
of the ways this preservation state has been defined are (1)
the ratio of the number of foraminifer test fragments for a
given species to the number of whole shells from that
species [e.g., Peterson and Prell, 1985a, 1985b; Le and
1
Department of Geology, Grand Valley State University, Allendale,
Michigan, USA.
2
Department of Earth and Environmental Sciences, Wright State
University, Dayton, Ohio, USA.
Copyright 2008 by the American Geophysical Union.
0883-8305/08/2007PA001433$12.00
Shackleton, 1992; Mekik et al., 2002]; (2) dissolutioninduced loss in size-normalized whole foraminifer shell
weight [Lohmann, 1995; Broecker and Clark, 2001a,
2001b]; and (3) changes in the Mg/Ca ratio of foraminifer
shells through dissolution [Brown and Elderfield, 1996;
Rosenthal et al., 2000; Dekens et al., 2002; Rosenthal and
Lohmann, 2002; Mekik and François, 2006; Mekik et al.,
2007a]. Most proxies anchor dissolution-induced changes in
foraminifer shells to the [CO2
3 ] of bottom waters [e.g.,
Broecker and Clark, 2001a, 2001b; Dekens et al., 2002;
Marchitto et al., 2005]. Instead, Mekik et al. [2002] related
the fragmentation trend of Globorotalia menardii shells to
model derived estimates of percent CaCO3 dissolved in
deep-sea sediments. Their percent CaCO3 dissolved estimates take into account both the CO2
3 undersaturation of
bottom waters and respiratory CaCO3 dissolution within
sediments driven by fluxes of organic carbon reaching the
seabed [Emerson and Bender, 1981].
[4] The ideal CaCO3 dissolution proxy would be (1) timeefficient (short analysis time per sample); (2) based on
species (and/or their fragments) which are easy to identify
even by nonspecialists, if dependent on biogenic components; (3) without biological/ecological bias, or at least
have a bias that is quantifiable and accurately predictable;
(4) sensitive to a wide range of dissolution (ideally from 0 to
100% calcite dissolved); (5) calibrated against an independent and quantitative estimate of percent CaCO3 dissolved;
and (6) reliably applicable in areas with strong gradients to
surface ocean conditions like temperature, [CO2
3 ], nutrient
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
availability, productivity, and even in areas where there is
large variation to both organic carbon and calcite fluxes
reaching the seabed.
[5] We assume uniformity among foraminifer shells when
developing CaCO3 dissolution proxies, yet no two foraminifers are exactly alike because vital processes may affect
shell composition, thickness and therefore weight. The best
means for quantifying deep-sea CaCO3 dissolution may be
using a multiproxy approach within the same sediment
samples [e.g., Mekik and François, 2006; Naik and Naidu,
2007; Ni et al., 2007]. We will focus on two dissolution
proxies, size normalized whole foraminifer shell weight
(SNSW) [Broecker and Clark, 2001a; 2001b, 2003] and
the G. menardii fragmentation index (MFI) [Mekik et al.,
2002], with some independent corroboration from foraminifer Mg/Ca. We undertake the following research questions:
[6] 1. Intuitively, loss in foraminifer shell weight would
precede fragmentation as dissolution progresses. Is there
such a sequential relationship between SNSW and MFI with
increasing CaCO3 dissolution in the sediments and decreasing bottom water [CO2
3 ]? Or does shell weight loss happen
simultaneously with fragmentation under similar degrees of
undersaturation and organic carbon
bottom water CO2
3
degradation in sediment pore waters?
[7] 2. How sensitive are SNSW and MFI to environmental
influences within foraminifers’ calcification waters, such as
temperature, [CO2
3 ], nutrient availability and apparent oxygen utilization (AOU)? Mg/Ca in foraminifer shells is predominantly governed by calcification temperature [e.g.,
Nürnberg, 1995; Elderfield and Ganssen, 2000; Lea et al.,
2000; Anand et al., 2003]; is this also true of SNSW and MFI?
2. Background
2.1. Globorotalia menardii Fragmentation Index
[8] The G. menardii fragmentation index is the ratio of
the number of damaged G. menardii specimens (D) to the
number of whole plus damaged specimens of this species
within a sediment aliquot. Damaged specimens are grouped
into categories as whole specimens with small holes (holes),
pieces greater than half intact (>half), pieces less than half
intact (<half) and keels:
D ¼ number with holes þ number > half
þ ðnumber < half =3Þ þ ðnumber keels=5Þ
ð1Þ
[9] Mekik et al. [2002] based MFI on Ku and Oba’s
[1978] laboratory experiments, which showed that dissolution damage in G. menardii shells is quantifiable. The
available MFI transfer function relates the fragmentation
trend of G. menardii shells in core tops of deep Pacific
sediments to model-derived estimates of percent CaCO3
dissolved (R2 = 0.88) with the following calibration equation [Mekik et al., 2002]:
percent CaCO3 dissolved ¼ 5:111 þ ðMFI*160:491Þ
MFI2 *79:636
ð2Þ
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[10] By percent CaCO3 dissolved, we mean the fraction of
the vertical calcite flux that has been lost to dissolution in
any one spot on the sea bottom. Mekik et al. [2002] used the
biogeochemical model Muds [Archer et al., 2002] to calculate the percent CaCO3 dissolved for sample locations along
two depth transects in the Pacific Ocean: on the Ontong
Java Plateau (OJP), and on the East Pacific Rise outside of
the equatorial upwelling region (1900 – 4441 m depth).
These values were then used to calibrate MFI. Both bottom
2
water DCO2
3 (which is the [CO3 ] of in situ waters less
2
[CO3 ] at saturation) and organic carbon fluxes reaching
the sediments were included both in the model [Archer et
al., 2002] and in calculations of percent CaCO3 dissolved
[Mekik et al., 2002]. This is because CaCO3 dissolution on
the seafloor is in part driven by organic carbon degradation
in the top meter of sediment.
[11] All calibration samples experienced some bottom
undersaturation (DCO2
ranges between
water CO 2
3
3
0.32 and 28.98 mmol/kg). Estimates of DCO2
3 for each
sample location in MFI’s calibration sample set are from
Archer’s [1996, personal communication, 2001] global
gridded database. Organic carbon flux estimates used to
calibrate MFI are from (1) satellite-based surface ocean
productivity estimates from Behrenfeld and Falkowski
[1997]; (2) surface ocean productivity compilations of
Berger et al. [1987] and Berger [1989] and the attenuation
of organic carbon with water depth using Berger et al.’s
[1987] equation; and (3) Jahnke’s [1996] global gridded
database for benthic oxygen fluxes. Details regarding the
equation, calibration and modeling of MFI are discussed by
Mekik et al. [2002].
[12] Mekik and François [2006] provided independent
corroboration for MFI as a dissolution proxy using Mg/Ca
and Mg/Sr in shells of P. obliquiloculata and G. menardii in
samples from the OJP where surface ocean temperature
variation is minimal but where there is a steep gradient to
of bottom waters. Mg/Ca in P. obliquiloculata
DCO2
3
shells strongly correlates with MFI (R2 = 0.94) and with
MFI-based percent dissolved (R2 = 0.84) on the OJP [Mekik
and François, 2006] where Mg/Ca decreases with increasing MFI-based percent calcite dissolved. Subsequently,
Mekik et al. [2007a] used MFI for dissolution correction
of Mg/Ca paleothermometry. Mekik et al. [2002, 2007b]
expanded MFI’s applicability to core top samples in the
eastern equatorial Pacific (EEP) where both surface ocean
productivity and the rain ratio reaching the seabed are
highly variable. Also, Loubere et al. [2004] and Richaud
et al. [2007] applied MFI in down core work for estimating
CaCO3 fluxes to the deep sea.
[13] In summary, MFI is unique among available dissolution proxies because (1) G. menardiis provide a quantifiable fragmentation trend with increasing dissolution where
other species tend to stay intact until a threshold value of
DCO2
3 is reached, and then fall to pieces randomly below
this threshold (F. Mekik, unpublished data, 2000); (2) it is
the only dissolution proxy anchored against model-derived
estimates of percent CaCO3 dissolved per sample location
[Mekik et al., 2002]; (3) it is efficient (20– 30 minutes per
sample); (4) it uses a species whose fragments are easy to
identify; (5) it works at least in one region (EEP) where the
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
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surface ocean has a strong productivity gradient [Mekik et
al., 2002, 2007a, 2007b]; and (6) as explained above, there
is some independent corroboration for MFI as a dissolution
proxy from Mg/Ca and Mg/Sr in multiple species of
planktonic foraminifers [Mekik and François, 2006]. However, neither the relationship between MFI and SNSW, nor
SNSW’s application in an upwelling region like the EEP
has previously been explored. That is our goal herein.
2.2. Size-Normalized Foraminifer Shell Weight
[ 14 ] The size-normalized foraminifer shell weight
(SNSW) method is founded on the assumption that foraminifer test weight loss within a specified size range is
driven solely by dissolution of foraminifer shells in sediments [Lohmann, 1995; Broecker and Clark, 2001a,
2001b]. This has been well established for several species
of planktonic foraminifers including Neogloboquadrina
dutertrei, Pulleniatina obliquiloculata and Globigerinoides
ruber [e.g., Broecker and Clark, 2001a, 2001b, 2003].
Broecker and Clark [2001a] relate shell mass loss to depth
normalized bottom water [CO2
3 ] which they define as
* ¼ CO2
CO2
þ 20ð4 zÞ
3
3
ð3Þ
2
where [CO2
3 ]* represents depth normalized [CO3 ] and z
2
is water depth in kilometers. [CO3 ] values in their work
are extrapolated from GEOSECS data. They report an
average size normalized foraminifer weight loss slope of
0.30 ± 0.05 mg per 1 mmol/kg decrease in depth normalized
[CO2
3 ].
[15] It seems that SNSW and MFI may potentially serve
to expand and complement one another since, intuitively,
foraminifer shell mass loss should precede fragmentation.
We explore this issue as well as potential environmental
effects on each proxy.
2.3. Eastern Equatorial Pacific
[16] Unlike surface waters above the Ontong Java Plateau, the EEP is an expansive region of both coastal and
equatorial upwelling with high pCO2 in its surface waters
[Tans et al., 1990]. The South Equatorial Current (SEqC) is
driven by trade winds and marks the northern branch of the
South Pacific subtropical gyre [Pennington et al., 2006]
where it feeds a major open ocean upwelling system in the
EEP. The SEqC seems to originate from the SW Antarctic
Pacific [Toggweiler et al., 1991; Kessler, 2006]. The EEP
cold tongue results from the divergence of flow along the
equator and generally spans between 3°N and 3°S though it
is not usually symmetrical about the equator [Wyrtki, 1981;
Fiedler and Talley, 2006]. This cold upwelling process
brings macronutrients to the euphotic zone [Chavez and
Barber, 1987] and the deep chlorophyll maximum is shallow in this region of the EEP [Fiedler and Talley, 2006;
Kessler, 2006] where phytoplankton in the equatorial undercurrent display only weak seasonality [Pennington et al.,
2006]. The EEP is generally a region of weak seasonality
[Chavez and Toggweiler, 1995; Loubere, 1998; Loubere
and Fariduddin, 1999] and high-nitrate low-chlorophyll
concentration [Behrenfeld and Kolber, 1999; Pennington
et al., 2006]. This means that upwelled nutrients are never
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fully utilized by the plankton [Chavez and Barber, 1991]
because of iron and silica limitation [Dugdale et al., 1995,
2002; Dugdale and Wilkerson, 1998]. The Costa Rica Dome
is an oceanic upwelling center in the EEP along the coasts of
Nicaragua and Costa Rica where the thermocline approaches
very near the sea surface [Fiedler and Talley, 2006].
[17] Because the EEP is a major upwelling zone, all
surface ocean parameters we consider herein have steep
gradients across the region. This makes the area an ideal
study site for the effects of environmental factors on
sedimentary CaCO3 dissolution proxies using tropical
planktonic foraminifers. However, precisely because it is
an upwelling zone, all surface ocean parameters in this
region tend to covary (Table 1) which makes distinguishing
the effect of one parameter (e.g., temperature) from another
(e.g., [NO
3 ]) challenging.
3. Methods
3.1. Samples
[18] We used whole tests from P. obliquiloculata and
N. dutertrei for SNSW because those two species are most
commonly used in dissolution work [e.g., Broecker and
Clark, 2001a, 2001b; Dekens et al., 2002; Mekik and
François, 2006; Naik and Naidu, 2007]. Because there is
a steep gradient to temperature between 50 and 150 m water
depth in the EEP, it is important to identify more precise
depth habitats for each of our species. All of our species are
thermocline dwellers [Bé, 1960; Hilbrecht, 1996; Anand et
al., 2003; Farmer et al., 2007]; however, P. obliquiloculata
prefer living at 50 m water depth [Farmer et al., 2007] and
Mekik et al. [2007a] found the best relationship between
Mg/Ca in shells of this species and water temperatures at
50 m. G. menardii prefer 75 m water depth [Farmer et al.,
2007] while N. dutertrei are known to live in the deep
chlorophyll maximum (DCM) [Fairbanks et al., 1982;
Fairbanks and Wiebe, 1980; Loubere, 2001]. We used
Loubere’s [2001] habitat depth estimates for N. dutertreis
based on isotope equilibrium depths calculated using a
combination of d 13C and d18O from N. dutertrei shells in
EEP core tops. For samples beyond Loubere’s [2001] data
set (those from the OJP and some samples from the EEP),
we used the average value of the environmental parameter
of interest between 50 and 75 m because this is the mean
value of habitat depth in Loubere’s [2001] work and this
depth is also in keeping with independent DCM depth
estimates for the EEP [Fiedler and Talley, 2006; Kessler,
2006; Pennington et al., 2006].
[19] We picked N. dutertrei shells from the 355– 415 mm
size range as described by Broecker and Clark [2001a,
2001b], and P. obliquiloculata’s from the 420 – 520 mm size
range because smaller P. obliquiloculata shells are not
abundant in our samples from the EEP. Many studies have
illustrated that using larger foraminifers improves analytical
accuracy because larger foraminifer size minimizes ontogenetic effects [Kroon and Darling, 1995] and provides more
consistent results among samples [Oppo and Fairbanks,
1989]. Even in Mg/Ca work on planktonic foraminifer
shells, Elderfield et al. [2002] established that geochemical
data from larger foraminifers yield results which are more
consistent with temperatures in foraminifer habitat waters.
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Table 1. Correlations Between Variables in the EEPa
Temperature
Nitrate
CO32
AOU
R
Water
Depth, m
DCO32
Calcite
Dissolved, %
50 m
75 m
DCM
50 m
75 m
DCM
50 m
75 m
100 m
50 m
75 m
100 m
Water depth
DCO3
Percent dissolved
T 50 m
T 75 m
T DCM
Nitrate 50 m
Nitrate 75 m
Nitrate DCM
AOU 50 m
AOU 75 m
AOU DCM
CO32 50 m
CO32 75 m
CO32 DCM
1
0.33
0.04
0.09
0.07
0
0.06
0.06
0.01
0.12
0.1
0.05
0.08
0.06
0.01
0.33
1
0.18
0.01
0.01
0.05
0.02
0
0.06
0.1
0
0.02
0.02
0.03
0.11
0.04
0.18
1
0.18
0.29
0.3
0.28
0.36
0.52
0.21
0.28
0.38
0.25
0.36
0.48
0.09
0.01
0.18
1
0.79
0.5
0.6
0.44
0.43
0.82
0.64
0.54
0.85
0.68
0.58
0.07
0.01
0.24
0.79
1
0.61
0.75
0.72
0.75
0.82
0.83
0.78
0.86
0.88
0.81
0
0.05
0.3
0.5
0.61
1
0.58
0.54
0.78
0.5
0.52
0.84
0.56
0.58
0.93
0.06
0.02
0.28
0.6
0.75
0.58
1
0.82
0.78
0.75
0.76
0.73
0.86
0.86
0.84
0.06
0
0.36
0.44
0.72
0.54
0.82
1
0.92
0.66
0.87
0.85
0.67
0.88
0.83
0.01
0.06
0.52
0.43
0.75
0.78
0.78
0.92
1
0.58
0.81
0.9
0.6
0.84
0.9
0.12
0.01
0.21
0.82
0.82
0.5
0.75
0.66
0.58
1
0.83
0.71
0.89
0.83
0.68
0.1
0
0.28
0.64
0.83
0.52
0.76
0.87
0.81
0.83
1
0.87
0.8
0.93
0.79
0.05
0.2
0.38
0.54
0.78
0.84
0.73
0.85
0.9
0.71
0.87
1
0.68
0.83
0.91
0.08
0.02
0.25
0.85
0.86
0.56
0.86
0.67
0.6
0.89
0.8
0.68
1
0.87
0.75
0.06
0.03
0.36
0.68
0.88
0.58
0.86
0.88
0.84
0.83
0.93
0.83
0.87
1
0.87
0.01
0.11
0.48
0.58
0.81
0.93
0.84
0.83
0.9
0.68
0.79
0.91
0.75
0.87
1
2
a
T is temperature; DCM stands for deep chlorophyll maximum.
Furthermore, J. Bijma’s (personal communication, 2006)
unpublished SNSW data from Globigerinoides sacculifer
tests also supports the assertion that analytical accuracy
improves with increasing foraminifer size.
[20] We ascertain that our core tops are Holocene in
several ways. First, Loubere [2001] provided d 13C and
d 18O measurements from N. dutertrei shells in core tops
from the EEP which are consistent with Holocene d13C and
d 18O values. Some of the core tops we are using herein
overlap with a subset of Loubere’s [2001] samples, and the
geographic distribution of his core tops is broad enough to
allow for a regional assessment of age distribution in the
EEP. In addition to Loubere’s [2001] data set, Mekik et al.
[2007b] generated d 18O data from foraminifers in samples
from very deep core tops where chemical erosion may have
obliterated Holocene sediments and they excluded samples
with values inconsistent with those for the Holocene. We
also excluded those samples herein. Second, Mekik et al.’s
[2007b] EEP rain ratio maps generated from a subset of
samples used herein fit well with chlorophyll-based estimates of Recent surface ocean productivity in the EEP [after
Behrenfeld and Falkowski, 1997]. Last, Mekik et al.’s
[2007a] Mg/Ca data from planktonic foraminifers from
the same core tops as those used herein show consistent
patterns with Recent sea surface temperatures in the habitat
waters of each species.
3.2. Sample Preparation
[21] We followed methods outlined by Mekik et al. [2002]
for generating MFI data, and used procedures described by
Lohmann [1995] and Broecker and Clark [2001a] for
SNSW measurements with three modifications in order to
improve data quality. First, foraminifers were picked individually within given size ranges instead of trapping foraminifers between two sieves; and all the picking was done
by the same person (F. Mekik). This ensures that size
measurements for each foraminifer are made on the shortest
diameter and improves the consistency of foraminifer size
within each range. Second, a wet picking technique was
used because wet foraminifers are more transparent. This
facilitates picking the cleanest specimens because using an
ultrasonicator or other cleaning methods on foraminifers
generally damages shells and distorts weight data. Third, we
weighed two separately picked, size-normalized populations
for each species from each sample in order to compare
replicate measurements of species-specific mean weight
from each sediment sample. Replicate mean weight measurements for all samples are not available, however, because
of the low abundance of clean foraminifers in given size
ranges in some samples.
[22] We aimed for 50 or more whole shells for weighing
from each sediment sample. However, in some samples,
especially those from high-dissolution areas, we had to base
our mean weight on fewer foraminifers. Our data set for
MFI (Figure 1) is larger than that for SNSW because
fragments of G. menardii are far more abundant than clean
whole foraminifer shells in tight size ranges.
3.3. Analytical Method
[23] Mekik et al. [2002] estimated MFI’s error margin at
10– 15%. It is customary to count 300 or more G. menardii
whole shells and fragments per sample to obtain statistically
robust results. Counts in some high-dissolution samples fell
below 300 because of lack of shell matter.
[24] There are three main sources of uncertainty in SNSW
measurements: (1) error margin of the balance; (2) reproducibility of mean weight measurements; and (3) variation
in shell weight within a given size range. We used a Mettler
microgram scale at Grand Valley State University whose
error margin is ±5 mg. To test for reproducibility of mean
weight measurements, we made replicate weight measurements from a separately picked, second population of
foraminifers from the same species and in the same size
fractions from each sediment sample where we had a
sufficient number of foraminifers available. The reproducibility between two separately picked replicate mean weight
measurements is high (R2 = 0.97). In the following discussion 8 represents the difference between two replicate
mean weight measurements for the same species in the same
sediment sample. Mean 8 for P. obliquiloculata weight
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Figure 1. (a) General locations for samples used herein are shown as open and shaded diamonds. OJP is
Ontong Java Plateau; EEP is eastern equatorial Pacific. Dashed lines represent temperature contours for
75 m water depth after Locarnini et al. [2006]. (b) Core top sample distribution in the eastern equatorial
Pacific. MFI data are available from all samples. Shaded diamonds show samples from which N. dutertrei
SNSW were generated, and dots show samples from which P. obliquiloculata SNSW data were
generated. Dashed lines represent seafloor bathymetry.
measurements is 3.74 mg, and the standard deviation in 8
for P. obliquiloculata weight is 3.02 mg. The ratio of mean 8
to average P. obliquiloculata mean weight from all samples
(65 mg) is 5.8%. For N. dutertrei weight data, mean 8 is
2.18 mg, and its standard deviation is 2.02 mg. The ratio for
mean 8 to average N. dutertrei mean weight from all
samples (37.5 mg) is also 5.8%.
[25] Following the work of others [Rosenthal et al., 2000;
Barker et al., 2004], we examined single-foraminifer
weights within three size ranges for P. obliquiloculata
whole shells in a sample from the OJP, ERDC 89. The
variation coefficient for each size range is listed as a
percentage (Table 2) and it is the ratio of the standard
deviation for all weight measurements within the size range
to the mean weight of foraminifers in that size range. Note
that the variation coefficient for P. obliquiloculata weight in
the 355 –420 mm size range is significantly higher than that
for the two larger and wider size ranges. These results
confirm our choice for using larger P. obliquiloculata
specimens because weight variation within a size range
seems to be lower among larger foraminifers. We did not
generate single-foraminifer weight data for N. dutetrei
because an average N. dutertrei shell in the 355– 420 mm
size fraction weighs 38 mg. The uncertainty of the balance
at ±5 mg would substantially obscure the variation in our
weight measurements of individual N. dutertrei shells.
[26] Data for [CO2
3 ] at 50, 75 and 100 m water depth are
from Archer [1996, personal communication, 2001]. Other
environmental data (temperature, [NO
3 ] and AOU) at 50,
75 and 100 m are from NOAA’s World Ocean Atlases (see
Table 2. Variation Coefficients in Single P. obliquiloculata Shell
Weights in Sample ERDC 89 on the Ontong Java Plateau
Mean weight, mg
Standard deviation
Variation coefficient, %
5 of 15
355 – 420 mm
420 – 520 mm
520 – 620 mm
61.1
7.6
12.4
90.8
8.4
9.3
122.4
10.5
8.6
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
Locarnini et al. [2006] for temperature and Garcia et al.
[2006a, 2006b] for nutrients).
4. Results
[27] Our sediment samples include core tops along (1) a
depth transect on the OJP where surface ocean parameters
are mostly invariable allowing us to isolate the dissolution
signal in our proxies; and, for comparison, (2) a large group
of core top samples (more than 100) from the EEP (1808 –
4440 m depth) where surface ocean parameters are strongly
variable (Figure 1). All samples are from gravity cores.
Listings for all data used herein are available as auxiliary
material.1
4.1. Calcite Dissolution Proxies on the Ontong Java
Plateau
[28] First we compare MFI and SNSW in a subset of MFI’s
calibration samples in core tops from the OJP. These samples
compose a depth transect (1900– 4441 m) beneath surface
waters with fairly similar environmental parameters. This
allows us to isolate the CaCO3 dissolution signal in our
proxies.
[29] On OJP, MFI has a robust relationship with DCO2
3
(R2 = 0.92, Figure 2a), model-derived percent CaCO3
dissolved (R 2 = 0.88, Figure 2d), and Mg/Ca from
P. obliquiloculata shells (R2 = 0.94, Figure 2g). However,
neither P. obliquiloculata nor N. dutertrei shell weight
(Figures 2b and 2c),
correlates very well with DCO2
3
MFI-based percent CaCO3 dissolved (Figures 2e and 2f)
or Mg/Ca from P. obliquiloculata shells (Figures 2h and 2i).
[30] Though P. obliquiloculata shell weight drops with
increasing dissolution in OJP samples (Figures 2b and 2e),
we do not see a complementing relationship between MFI
and SNSW there. Instead, increasing fragmentation in
G. menardii shells appears to be happening under the same
conditions of bottom water CO2
3 undersaturation as whole
shell weight loss in P. obliquiloculatas (Figures 2a, 2b, 2d,
and 2e). In addition, Mg/Ca in P. obliquiloculata shells also
has a weak relationship with P. obliquiloculata SNSW
(Figure 2h).
[31] N. dutertrei shells are significantly less abundant and
lighter in OJP samples (OJP average weight is 27 mg) when
compared to their counterparts in the EEP (EEP average
weight is 39 mg). Broecker and Clark [2001a, 2001b] also
list lighter N. dutertrei weights (20 – 36 mg) in their samples
from the OJP within the same size fraction we used here.
4.2. Calcite Dissolution Proxies in the Eastern
Equatorial Pacific
4.2.1. Globorotalia menardii Fragmentation Index
[32] The fragmentation trend of G. menardii (MFI) has
no clear mathematical relationship with any surface ocean
parameter or DCO2
3 of bottom waters in the EEP (Figure 3).
At the same temperature at 75 m water depth (16°C) we
see a wide range to MFI (0.4 – 1). Similarly, samples under a
wide range of temperature (15°– 22°C) yield more or less
constant MFI values (1) (Figure 3). We find similar
1
Auxiliary materials are available at ftp://ftp.agu.org/apend/pa/
2007pa001344.
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patterns to that of MFI versus temperature when we plot
MFI against surface ocean [CO2
3 ], [NO 3 ] and AOU
(Figure 3). The poor relationship between MFI and bottom
water DCO2
3 in the EEP is not unexpected [Mekik et al.,
2002]. Unlike on the OJP where there is little variation in
seabed organic carbon flux, respiration of carbon in sediment pore waters drives additional CaCO3 dissolution
within sediments in the EEP [Mekik et al., 2002, 2007b].
4.2.2. Size-Normalized Shell Weight
[33] P. obliquiloculata shell weight correlates well with
MFI-based percent dissolved in the EEP (R2 = 0.79)
although it has no correlation with DCO2
3 . This is unexpected because we were not able to find a good mathematical relationship between P. obliquiloculata shell weight and
MFI-based percent dissolved or Mg/Ca in P. obliquiloculata
shells in samples from our depth transect on the OJP where
temperature and other surface ocean parameters are mostly
unchanging (Figures 2b, 2e, and 2h). It appears that in the
EEP, P. obliquiloculata shell weight is influenced by both
respiratory CaCO3 dissolution within the sediments and, to a
lesser extent, environmental parameters in the surface ocean.
Also, P. obliquiloculata SNSW has somewhat variable but
weaker relationships with all four environmental parameters
at 50 m water depth (R2 = 0.46– 0.77) (Figure 4). We are
using exponential relationships because they provide the
best fit with our data.
[34] N. dutertrei SNSW in core tops from the EEP
(Figure 5) show no significant correlation with any dissolution or environmental parameter. However, we see a moderately strong correlation between MFI-based percent
CaCO3 dissolved and N. dutertrei SNSW (Figure 5b) if
equatorial samples are removed. We also observe a correla
tion between [CO2
3 ] and/or [NO 3 ] at the DCM and
N. dutertrei SNSW, again if equatorial samples are removed
(Figures 5d and 5e). Furthermore, N. dutertrei shell weight
in equatorial samples seem to be heavier than what the
trend seen in other samples indicates (Figures 5c – 5f); and
N. dutertrei weights from just north of the equator are
heavier than those from immediately south of the equator.
5. Discussion
5.1. Comparison of Dissolution Proxies on the Ontong
Java Plateau
[35] Both our SNSW data using P. obliquiloculata shells
and those of Broecker and Clark [2001a] using smaller
individuals of the same species have weak correlations with
DCO2
3 on the OJP (Figure 2b). This is different than the
robust relationship between P. obliquiloculata SNSW and
bottom water CO2
3 undersaturation [Broecker and Clark,
2001a].
[36] The discrepancy lies in the different terms used to
in bottom waters.
describe undersaturation of CO 2
3
Broecker and Clark [2001a] use [CO2
3 ]*, which they
define as a depth normalized bottom water [CO2
3 ] indicator
based on [CO2
3 ] values extrapolated from GEOSECS. The
values given by Archer [1996] are also derived
DCO2
3
from GEOSECS, but these are based on the empirical
relationship between [CO2
3 ] and temperature, salinity, O2
and nutrients, and CaCO3 solubility formulations. We use
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
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Figure 2. All samples shown here are from OJP. (a) MFI versus DCO32. (b) P. obliquiloculata SNSW
versus DCO32. Stars show SNSW data (355– 415 mm) from Broecker and Clark [2001a]. Diamonds
show data from this study (420– 520 mm). (c) N. dutertrei SNSW versus DCO32. Stars show SNSW data
from Broecker and Clark [2001a, 2001b]. Diamonds show data from this study. Both are from the
355– 420 mm size fraction. (d) MFI versus model-derived estimates of percent calcite dissolved. (e)
P. obliquiloculata SNSW versus MFI-based percent calcite dissolved estimates in MFI’s calibration
samples. (f) N. dutertrei SNSW versus MFI-based percent calcite dissolved estimates. (g) MFI versus
Mg/Ca in P. obliquiloculata shells. (h) P. obliquiloculata SNSW versus Mg/Ca in P. obliquiloculata.
(i) N. dutertrei SNSW versus Mg/Ca in P. obliquiloculata.
Archer’s [1996] DCO2
data herein for comparing MFI
3
with SNSW in order to maintain consistency with former
work on MFI [Mekik et al., 2002; Mekik and François,
2006; Mekik et al., 2007a, 2007b], and because MFI data
are not available for the sample set used by Broecker and
Clark [2001a].
5.2. Postdepostional Calcite Dissolution and
Environmental Parameters in Foraminifer Habitat
Waters
[37] It is difficult to isolate the influence of a single
specific surface ocean parameter on CaCO3 dissolution
proxies in the EEP for two reasons. First, all our core tops
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
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Figure 3. MFI versus DCO32 and environmental parameters at 75 m water depth in core top samples
from the eastern equatorial Pacific. Shaded line in first plot showing MFI versus DCO32 represents the
correlation line between these same parameters in core tops from the OJP (Figure 2a).
are from regions where bottom waters are undersaturated
2
with respect to CO2
3 (DCO3 ranges between 0.42 and
41.8 mmol/kg among locations of our samples). Thus we
do not have samples that experienced no dissolution. Even
if we had very shallow samples (<1700 m), there is still the
possibility of supralysoclinal CaCO3 dissolution in sedi-
ments of this region [e.g., de Villiers, 2005]. Second, all
environmental parameters covary in the EEP (Table 1).
[38] Bijma et al. [1999] demonstrated that Orbulina universa shell weight in laboratory cultures is primarily influenced by [CO2
3 ] of water in which the organism calcifies.
The influence of [CO2
3 ] on shell thickness and shell weight
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
Figure 4. P. obliquiloculata SNSW data versus (a) DCO32 and environmental parameters (b) MFI
percent dissolved calcite, (c) water temperature, (d) carbonate ion and (e) nitrate concentrations, and
(f) apparent oxygen utilization at 50 m water depth in core top samples from the eastern equatorial Pacific.
In Figure 4b, color coding indicates [CO32] at 50 m water depth in the EEP. In Figures 4c – 4f, color
coding indicates three dissolution brackets estimated with MFI.
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
Figure 5. N. dutertrei SNSW data versus (a) DCO32 and environmental parameters (b) MFI-based
percent calcite dissolved, (c) water temperature, (d) carbonate ion and (e) nitrate concentrations, and
(f) apparent oxygen utilization at the deep chlorophyll maximum (N. dutertrei habitat depths from
Loubere [2001]) in core top samples from the eastern equatorial Pacific. Yellow triangles show samples
falling in the region between the equator and 5°S, and yellow circles show samples from the region
between the equator and 5°N.
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
should not be restricted to O. universa and Globigerinoides
sacculifer [Bijma et al., 2002]. Naik and Naidu [2007]
provided evidence in core tops from the western tropical
Indian Ocean supporting the strong effect of [CO2
3 ] in
calcification waters on SNSW of both N. dutertrei and
P. obliquiloculata while Barker and Elderfield [2002]
demonstrated the same effect in down core work. Even
studies on shell chemistry, not just SNSW, show that the
18
[CO2
3 ] of habitat waters may bias results (e.g., d O and
13
d C [Spero et al., 1997] and U/Ca [Russell et al., 2004]).
Although our data set does not allow us to rule out the
potential effect of the other three environmental parameters
on SNSW (because all surface ocean parameters covary in
this region), previous studies point to [CO2
3 ] in calcification waters as the most influential environmental parameter
on shell weight. So, we will focus our discussion around the
effect of [CO2
3 ] in habitat waters on SNSW in the EEP.
[39] In order to examine the effect of [CO2
3 ] of habitat
waters on the dissolution trend seen in P. obliquiloculata
shell weight, we grouped our samples into three ranges
of [CO2
3 ] at 50 m water depth (<175, 175 – 220, and
>220 mmol/kg) (Figure 4b). If calcite dissolution were
the only influence on P. obliquiloculata shell weight in
the EEP, we would expect the distribution of [CO2
3 ] values in
Figure 4b to be overlapping and random. Instead, SNSW of
P. obliquiloculata (Figure 4) seems to respond both to
postdepositional CaCO3 dissolution in the sediments (R2 =
0.79; estimated with MFI) and, most likely, [CO2
3 ] of waters
at 50 m in the EEP. Our results are supported by Naik and
Naidu’s [2007] findings of the strong influence of [CO2
3 ] in
calcification waters on P. obliquiloculata SNSW.
[40] Likewise, we grouped samples into three categories
based on the extent of dissolution each experienced (<45%,
45 –60%, and >60%). The width of each dissolution category (15%) in Figures 4c – 4f is within MFI’s error
margin. Again, both dissolution and [CO2
3 ] in ambient
waters appear to influence P. obliquiloculata shell weight
(Figure 4d), but there is also a systematic decrease in the
sensitivity of P. obliquiloculata SNSW to [CO2
3 ] in samples
which have experienced high dissolution (green dots).
[41] We performed multiple linear regression analysis to
further explore the effect of postdepositional calcite dissolution and [CO2
3 ] at 50 m water depth on P. obliquiloculata
SNSW. In our analysis P. obliquiloculata SNSW is the
dependent variable and MFI-based percent CaCO3 dissolved and [CO2
3 ] at 50 m are the independent variables.
We used the resulting multiple linear regression equation
(Figure 6) to estimate P. obliquiloculata SNSW from MFIbased percent CaCO3 dissolved and [CO2
3 ] at 50 m. water
depth as input parameters for each sample. We find a high
correlation between measured P. obliquiloculata weights
and those calculated with the regression equation (Figure 6).
This suggests that 83% of the variation in P. obliquiloculata
SNSW in our samples may be explained by the effects of
both postdepositional CaCO3 dissolution and [CO2
3 ] at 50 m
water depth (Figure 6).
5.3. Geographic Controls on Dissolution Proxies
[42] All environmental variables in the EEP covary
(Table 1), but we believe the environmental factor most
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Figure 6. Multiple linear regression equation between
Mg/Ca in P. obliquiloculata and MFI-based percent calcite
dissolved and [CO32] at 50 m in samples from the EEP.
likely affecting N. dutertrei shell weight in our EEP samples
is [CO2
3 ] at DCM depths (Figure 5d) because of strong
laboratory evidence supporting the effect of [CO2
3 ] in
ambient waters on shell weight [Bijma et al., 1999, 2002]
and core top work showing the influence of surface ocean
[CO2
3 ] on N. dutertrei SNSW [Naik and Naidu, 2007].
[CO2
3 ] at the DCM seems to increase from south to north
across the EEP with the exception of relatively low [CO2
3 ]
in the equatorial region.
[43] Within the EEP, areas beneath the North Equatorial
Counter Current and in the southwest beyond the upwelling
zone contain the heaviest N. dutertrei shells within our
given size ranges (Figure 7). Both of these areas have very
low chlorophyll concentrations (low productivity) in surface
waters. By contrast, lighter N. dutertrei shells are found
beneath upwelling regions on the equator by the South
Equatorial Current (Figure 7) and at the Costa Rica Dome
[Fiedler and Talley, 2006], where productivity is high.
[44] The geographic pattern of SNSW for N. dutertrei
populations in the EEP may indicate the presence of
‘‘cryptic species’’ of N. dutertrei, which may prefer specific
environmental factors [Darling et al., 1996; Huber et al.,
1997; Darling et al., 1999; Kucera and Darling, 2002;
Darling et al., 2003]. Cryptic species are distinct genotypes
within a morphospecies that can be difficult to identify with
morphological features alone. The distribution of N. dutertrei
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Figure 7. Distribution of N. dutertrei SNSW in the eastern equatorial Pacific. Abbreviations are
NEqCC, North Equatorial Counter Current; SEqC, South Equatorial Current; and CRD, Costa Rica
Dome. Contours represent N. dutertrei shell weight in mg. The image is overlain on the chlorophyll-based
surface ocean productivity map of Behrenfeld and Falkowski [1997].
SNSW could reflect intraspecific ecophenotypic variation,
multiple genotypes or both, particularly where the SNSW
does not seem to be influenced by [CO2
3 ] (Figure 5d). We
would need DNA data from our N. dutertrei specimens to
discern among these possibilities, but this data is not available. We note, though, that Kucera and Darling [2002], using
DNA data, describe three distinct genotypes for N. dutertrei
but only one for P. obliquioculata and one for G. menardii.
This finding may explain the regional distribution of
N. dutertrei shell weight as evidence of multiple populations
of the N. dutertrei morphotype in the EEP distinguished by
their shell thickness.
[45] Schmidt et al. [2003, 2004] reported that planktonic
foraminifer size relates to latitude. They attribute this
change to surface water temperature, because higher temperatures promote growth in foraminifers. Schmidt et al.
[2004] also conclude that planktonic foraminifer assemblages tend to be smaller in upwelling regions. Although they
do not present SNSW data, it is possible that the SNSW
distribution of N. dutertrei across the EEP (Figure 7) reflects
variations in temperature and upwelling.
[46] Furthermore, the SNSW of N. dutertrei also varies
between the OJP and EEP, with much lighter specimens on
the OJP. Broecker and Clark [2001a] note that N. dutertrei
shells from the Atlantic Ocean are heavier than those from
the Indian and Pacific Oceans. Thus there appears to be
multiple populations of the N. dutertrei morphotype both in
the EEP and across the equatorial Pacific between the EEP
and OJP.
[47] One last geographic control on dissolution proxies
stems from the absence of G. menardiis in Atlantic sediments from the Last Glacial Maximum (LGM). This limits
MFI’s applicability in down core work in Atlantic cores.
5.4. Other Complicating Factors
[48] A factor often ignored in studies using foraminifer
SNSW is that significant shell loss may occur as foraminifer
tests settle though the water column; however, this has not
been well established for many foraminifer species because
of the scarcity of sediment trap data. Schiebel [2002]
estimated that only 25% of initially produced foraminifer
shell material settles to the bottom. In a more recent study,
Schiebel et al. [2007] illustrated that Globigerina bulloides
and Globigerinita glutinata lose an average of 19% of their
original shell weight while settling through the twilight
zone, 100 – 1000 m water depth. They detected no average
test weight loss below the twilight zone, and report that
foraminifer shells may even gain weight there. On the other
hand, most foraminifer tests experiencing dissolution
through the water column likely belong to juveniles because
most foraminifers in sediments are gametogenic and probably sank to the seabed rapidly after death (J. Bijma,
personal communication, 2006). Thus dissolution of adult
tests during sinking seems unlikely. Moreover, fragmentation of G. menardii shells in the water column has not been
reported. G. menardiis are known to be somewhat resistant
to dissolution even in sediments [Berger, 1968, 1970;
Thompson and Saito, 1974] and are used often to estimate
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MEKIK AND RATERINK: CALCITE DISSOLUTION IN THE DEEP SEA
deep-sea CaCO3 dissolution [Oba, 1969; Ku and Oba,
1978; Peterson and Prell, 1985a, 1985b; Mekik et al.,
2002; Mekik and François, 2006].
6. Conclusions
[49] We explored the significance of environmental influences on two deep-sea CaCO3 dissolution proxies in a large
number of core top samples from the tropical Pacific: sizenormalized foraminifer shell weight and the G. menardii
fragmentation index. We find that SNSW and MFI do not
complement each other and, instead, trace dissolution
concurrently in core tops from both the OJP and the
EEP. The dissolution signal in P. obliquiloculata SNSW
is weak in samples from the OJP where surface ocean
parameters are mostly constant. Conversely, SNSW of
P. obliquiloculata shells in samples from the EEP carries
a strong dissolution signal. Though we cannot isolate which
environmental parameter is affecting P. obliquiloculata
shell weight in the EEP with our data, we are able to show
that P. obliquiloculata SNSW responds to both postdepositional shell dissolution and surface ocean parameters there.
N. dutertrei SNSW, on the other hand, shows a distinct
latitudinal pattern in the EEP in keeping with regional highproductivity zones and current systems suggesting that
there may be intraspecific ecophenotypic variations in this
morphotype in the EEP which may be reflected in its
SNSW.
[50] Our study is not the first to find an environmental
influence of foraminifers’ calcification waters on their
SNSW. This is the first study, however, where environmental effects on SNSW are documented with core top
sediment samples in the EEP where calcite dissolution is
driven by both bottom water DCO2
3 and organic carbon
degradation in sediment pore waters. This is important for
paleoceanographic work because calibration equations
from core top sediment samples are often used for down
core applications and because culture experiments and
sediment trap data are few. Furthermore, it is not possible
to reliably study postdepositional shell dissolution in laboratory work and with sediment traps because the effect of
organic carbon degradation in sedimentary pore waters on
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calcite dissolution is difficult to mimic in a laboratory
setting.
[51] Although our results cannot offer a clear mechanistic
explanation for the variation in shell weight in the EEP and
further work with laboratory cultures is required to accomplish this, the correlations we demonstrate between SNSW
and both MFI-based percent dissolved values and surface
ocean parameters, particularly [CO2
3 ], cannot be ignored in
down core applications. Our findings suggest that caution
must be used when making paleoceanographic inferences
from SNSW variations in the paleorecord.
[52] Finally, we show that MFI-based percent CaCO3
dissolved estimates are mostly insensitive to surface ocean
environmental parameters in G. menardii’s calcification
waters in the EEP. Mekik and François [2006] showed
linear decreases in Mg/Ca and Mg/Sr in P. obliquiloculata
and G. menardii shells with increasing dissolution estimated
using MFI. Mekik et al. [2002, 2007a, 2007b] demonstrated
MFI’s applicability outside its calibration area in core top
samples from the EEP upwelling region. Loubere et al.
[2004] and Richaud et al. [2007] showed MFI’s applicability in down core work in reconstructing paleocalcite fluxes.
With all of these qualities, MFI seems to approach our
definition of the ideal CaCO3 dissolution proxy described in
the introduction of this paper with three caveats: (1) a
biological/ecological bias in MFI remains to be explored;
(2) MFI’s range of percent dissolved is still limited to 25–
76%; and (3) G. menardiis are absent in Atlantic sediments
from the LGM. Thus the ideal CaCO3 dissolution proxy is
still elusive.
[53] Acknowledgments. This manuscript benefited substantially
from many fruitful discussions with Paul Loubere and Roger François.
Constructive and thoughtful comments by Jerry Dickens and three anonymous reviewers much improved our manuscript. We gratefully acknowledge the curators and repositories that provided sediment samples and help
in selecting cores for this work (June Padman, Oregon State University;
Larry Peterson, RSMAS; Rusty Lotti-Bond, Lamont-Doherty Earth Observatory; Warren Smith, Scripps Institution of Oceanography; and curators at
the University of Hawaii). Thanks also go to the National Science
Foundation for the support it provides to those repositories. This study
was supported in full by grant OCE0326686 from the National Science
Foundation.
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F. Mekik, Department of Geology, Grand
Valley State University, Allendale, MI 49401,
USA. (mekikf@gvsu.edu)
L. Raterink, Department of Earth and
Environmental Sciences, Wright State University,
Dayton, OH 45435, USA.