The Mediterranean Sea is characterized by a relatively strong west to
east salinity gradient, which makes it an area suitable for testing the
effect of salinity on foraminiferal shell geochemistry. We collected
living specimens of the planktonic foraminifer Globigerinoides ruber albus to analyse the relation between element / Ca ratios,
stable oxygen isotopes of their shells, and surface seawater salinity,
isotopic composition and temperature. The oxygen isotopes of sea
surface water also correlate with salinity in the Mediterranean during
winter, which is when sampling for this study took place. Seawater oxygen and hydrogen
isotopes are positively correlated in both the eastern and western
Mediterranean Sea, although the
relationship differs from previously reported values, especially in the eastern region. The slope between salinity and seawater oxygen isotopes is lower
than previously published results. Still, despite the rather modest slope,
seawater and foraminiferal carbonate oxygen isotopes are correlated in
our dataset, albeit with large residuals and high residual
variability. This scatter could be due to either biological variability
in vital effects or environmental variability. Numerical models
backtracking particles show that ocean-current-driven mixing of particles
of different origins might dampen sensitivity and could result in an
offset caused by horizontal transport. Results show that Na / Ca is
positively correlated with salinity and independent of
temperature. As expected, foraminiferal Mg / Ca increases with temperature, which is in line with earlier calibrations, and in the high
salinity environment. By using living foraminifera during winter, the
previously established Mg / Ca–temperature calibration is extended to
temperatures below 18 ∘C, which is a fundamental
prerequisite of using single foraminifera for reconstructing past
seasonality.
Introduction
Ocean circulation plays an important role in the Earth's climate, as it
redistributes heat and also impacts global biogeochemical
cycles. Seawater temperature and salinity are key parameters for
reconstructing ocean circulation, as together they determine
seawater density and, in turn, large-scale circulation patterns,
including a substantial part of the meridional overturning
circulation. Reconstruction of past ocean environments largely relies
on so-called proxy calibrations in which a variable that can be
measured in the geological record is related to a target environmental
parameter. The incorporation of trace metals in foraminiferal shell
carbonate, for example, is a popular tool used to reconstruct past ocean
parameters. More specifically, the incorporation of Mg (often
expressed as the calcite's Mg / Ca) increases exponentially with
seawater temperature, as first observed in culture studies
(Nürnberg et al., 1996) and later confirmed by field calibrations
(Anand et al., 2003).
In addition to temperature, salinity and inorganic carbon chemistry
also affect Mg / Ca in some species of foraminifera (Allison et al.,
2011; Dueñas-Bohórquez et al., 2011; Geerken et al., 2018;
Gray et al., 2018; Hönisch et al., 2013; Kisakürek et al.,
2008; Lea et al., 1999). For the best possible accuracy, such effects
need to be corrected for when using foraminiferal Mg / Ca for the
reconstruction of temperature; this calls for independent proxies for
these other environmental parameters.
Currently, salinity is often reconstructed through indirect
relationships with other variables, such as the ratio of stable oxygen
isotopes of seawater, which are recorded in planktonic foraminifera
(Rohling, 2007), although direct approaches have also recently been suggested (Wit et al., 2013; Bertlich et al., 2018). As the seawater
oxygen isotope ratio and salinity are both affected by evaporation and
precipitation, the two often are linearly related (Rohling, 2007; Bahr
et al., 2013), with their calibration depending on
local conditions. If foraminifera precipitate their calcite in
equilibrium with respect to seawater oxygen isotopes, their
δ18O should reflect that of the seawater and, hence,
salinity. However, as the seawater temperature affects stable oxygen
isotope fractionation during calcification (McCrea,
1950; Urey et al., 1951), independent temperature
reconstructions are needed to estimate seawater δ18O from
δ18Ocalcite (Rohling, 2007). Independent
temperature reconstructions can be based on organic
proxies such as U37K′ (Prahl and Wakeham, 1987),
TEX86 (Schouten et al., 2006) or the Mg / Ca of the foraminifera
themselves (Mashiotta et al., 1999; Elderfield and
Ganssen, 2000). The accuracy and precision of such
reconstructions is debated, because the propagation of errors from the combined
inaccuracies of the analyses and the uncertainties in calibrations due
to combining several proxies is difficult to assess and seems too
large for meaningful reconstructions of changes in salinity over time
(Rohling, 2007). Due to the lack of a suitable alternative
approach, the use of Mg / Ca to determine the temperature effect of
foraminiferal δ18O continues to be applied in settings
that are prone to large changes in salinity, such as the Mediterranean
Sea. This calls for an independent in situ calibration in which all of the parameters involved are measured and are not determined by
proxy relationships.
Culture experiments using the benthic, symbiont-barren Ammonia tepida (Wit et al., 2013) and the planktonic Globigerinoides ruber (pink) (Allen et al., 2016) have shown that Na incorporation in
foraminiferal shell carbonate is positively correlated with seawater
salinity. A field calibration confirmed this positive correlation for
the planktonic foraminiferal species G. ruber albus (Mezger
et al., 2016), as well as for Trilobatus sacculifer
(previously called Globigerinoides sacculifer) in the Red Sea
and the Atlantic Ocean (Mezger et al., 2016; Bertlich et al.,
2018). Comparison of Na / Ca–salinity calibrations shows, however,
that absolute Na / Ca values and sensitivities to salinity vary
between species (Mezger et al., 2016).
When using field calibrations to constrain the accuracy and precision of
potential reconstruction approaches, it is important to also consider
the potential impact of lateral transport of foraminifera due to
(ocean) currents. Foraminifera collected at a specific sampling
location might actually have added the majority of their shell
carbonate at a different location and, hence, under different
environmental conditions, as they have been transported to the sampling
location. This may add to the uncertainty in the variable to
cross-correlate against or even introduce a bias in the resulting
calibration. Recently this has been suggested for dinoflagellate cysts
(Nooteboom et al., 2019) and planktonic foraminifera,
collected from the water column (Ganssen and Kroon, 1991), from
sediment (van Sebille et al., 2015) and also from sediment traps
(Steinhardt et al., 2014), but it can also be applied
to specimens collected living from the sea surface.
Here, we used a plankton pump and seawater samples collected from the
Mediterranean Sea in January and February 2016 to test the viability of
deconvolving salinity from combined temperature and seawater oxygen
isotope reconstructions. We also investigate the potential of the
newly developed salinity proxy Na / Ca in the Mediterranean Sea. Using
samples collected in winter, we also extend the calibration of Mg / Ca
to seawater temperature for G. ruber albus towards its lower
temperature tolerance limits (14 ∘C; Bijma et al.,
1990), which is essential for the application of this
species in past seasonality reconstructions.
Materials and methods
During two cruises (NESSC cruises 64PE406 and 64PE407, RV Pelagia)
between 12 January and 25 February 2016, a total of 98 plankton
samples were collected from the surface waters of the Mediterranean
Sea along an east–west transect using a plankton pump system (Ottens,
1992). Surface water was continuously pumped onboard from
a water depth of 5 m and led through a plankton net with
100 µm mesh size. Replacing the cod end every 6 h
(filtering 57 m3 of seawater on average, constantly
monitored using a water gauge), accumulated samples were washed out of
the net into a 90 µm sieve, rinsed thoroughly with
deionized water to remove smaller particles and salts, and
subsequently stored onboard at -80 ∘C. At NIOZ, all
plankton samples were then freeze-dried, and dry oxidation by low-temperature ashing (100 ∘C) was used to combust the
organic material while minimizing the potential impacts on carbonate trace
metal concentrations and δ18O (Fallet et al.,
2009). After ashing, samples were rinsed again
thoroughly with deionized water and ethanol to remove potential ash
residues. A variety of samples containing specimens of
G. ruberalbus (Morard et al., 2019) were selected to
cover a large range of salinities and temperatures. Specimens used for
analyses were selected from the size fraction between 150 and 250 µm,
even though it has been reported that
G. ruber albus and Globigerinoides elongatus cannot
always be confidently distinguished at this size fraction due to similar morphology (Aurahs
et al., 2011). Surface seawater samples for stable oxygen isotopes
were collected every 60 min from the same pump, resulting in a
set of 309 samples. A volume of 2 mL was stored without
headspace at 4 ∘C during the cruise to be analysed at
the home laboratory.
The elemental ratios of the final foraminiferal chamber (named the
F-chamber) of individual shells were measured by laser ablation
quadrupole inductively coupled plasma mass spectrometry (LA-Q-ICP-MS)
using a circular spot with a diameter of 60–80 µm,
depending on the size of the last chamber. The laser system (NWR193UC,
New Wave Research) at NIOZ was used in combination with a
two-volume sample cell (TV2), which allows for the detection of variability in
elemental ratios within the foraminiferal chamber wall due to a short
wash-out time of 1.8 s (van Dijk et al., 2017). Ablating only F-chambers minimizes the sampling of older carbonate
that might have formed under different environmental conditions due to
lateral and vertical transport. All specimens were ablated with an
energy density of 1±0.1Jcm-2 and a repetition rate of
6 Hz in a helium environment. A 0.7 Lm-1 helium
flow transported the resulting aerosol to an in-house custom-built smoothing
device before entering the quadrupole ICP-MS (iCAP Q, Thermo Fisher
Scientific). Masses of 7Li, 11B, 23Na, 24Mg, 25Mg, 27Al, 43Ca, 44Ca,
57Fe, 88Sr, 137Ba and 238U were monitored, and 44Ca served as an internal
standard for the quantification of the associated elements. The synthetic
carbonate standard MACS-3 was used for calibration; in addition,
carbonate standards JCp-1, JCt-1 and NFHS-1 (NIOZ foraminifera house
standard; Mezger et al., 2016) as well as glass standards SRM NIST610
and NIST612 were used for monitoring data quality. The accuracy of the
analyses was 97 %, while the precision was 3.0 % for Mg and 2.4 %
for Na measurements.
Stable oxygen and carbon isotopes of foraminiferal calcite were
measured on groups of whole specimens different from those used for
LA-Q-ICP-MS, using an automated carbonate device (Kiel IV, Thermo Scientific) which was connected to a Thermo Finnigan MAT 253 dual-inlet isotope
ratio mass spectrometer (IRMS). The NBS 19 limestone was used as a
calibration standard, and the NFHS-1 standard was used for drift detection
and correction. The standard deviation and offset of the NBS19 and the
NFHS-1 were always within 0.1 ‰ for δ18O.
Due to the large amount of material required (20 to 40 µg)
and the small amount of specimens present in the samples, specimens
from different samples sometimes needed to be combined. This resulted,
for example, in combining 12 and 8 µg of foraminifera from
two adjacent transects; hence, the average temperature, salinity
and δ18O seawater for these transects was calculated
based on the relative contribution of the foraminiferal weight of the
individual transects (i.e. 60 % and 40 % respectively). Seawater oxygen and hydrogen stable isotopes were analysed with the
liquid water isotope analyser (LWIA; Los Gatos Research, Model
912-0008). This system measures the water samples using off-axis
integrated-cavity output spectroscopy (OA-ICOS). The LWIA was
connected with a GC PAL autosampler (CTC Analytics) to inject 1 µL
per measurement. To achieve this, the GC PAL autosampler was equipped with a
1.2 µL Hamilton syringe. In-house standards (S35, S45, NSW,
LGR5 and double-distilled water) were calibrated against VSMOW2 (Vienna Standard Mean Ocean Water 2),
VSLAP2 (Vienna Standard Light Antarctic Precipitation 2) and GISP2 (Greenland Ice Sheet Precipitation) obtained from the International Atomic Energy Agency in Vienna using
the same set-up. The use of VSMOW2, which has
δ18O values identical to the older SMOW (Standard Mean Ocean Water) standard,
allows for simple comparison with older data that were calibrated using
SMOW, without additional corrections. Every sample and standard was
measured 14 times sequentially: the first four runs were only used to
flush the system, whereas the last 10 measurements were used for the
analysis. Additionally, the sample
introduction line was rinsed with double-distilled water between every sample or standard. Data were
processed with LGR LWIA (Los Gatos Research Liquid Water Isotope Analyzer) post processor software v. 3.0.0.88. The average
standard deviation per sample was 0.14 ‰ for oxygen
isotope measurements and 0.71 ‰ for hydrogen isotope
measurements.
The likely provenance of the foraminifera sampled was computed by
backtracking virtual particles in a high-resolution ocean model. For
this, we used the Copernicus Marine Environmental Monitoring Service
(CMEMS) Global Reanalysis model. The ocean surface currents,
temperature and salinity are available at a daily temporal resolution and a 1/12∘ horizontal resolution. In these fields, we
backtracked particles using the OceanParcels v2.1.1 software (Lange
and van Sebille, 2017; Delandmeter and van Sebille,
2019). We released 10 000 particles at equal
spacing between the start and end locations of 25 of the transects
(i.e. all for which there were sufficient foraminiferal specimens for
isotope analysis), on the day these transects were sampled, and
tracked the particles back for 30 d with a fourth-order
Runge–Kutta algorithm with a 1 h time step, storing local
temperature, salinity and location for each particle every day. To
avoid beaching of particles, we used an “unbeaching kernel” similar to
that in Delandmeter and van Sebille (2019). The full code of the
simulations is available at
https://github.com/OceanParcels/MedForams_Daemmer/ (last access:
25 September 2020).
ResultsMediterranean Sea geochemistry
The sampled east–west transect spans a salinity gradient from 39.2 to
36.2 and an accompanying temperature gradient from
19 ∘C (east) to 14 ∘C. The
6 h intervals represented a distance of
57 km (min. 0 km, max. 117 km) on average. This
resulted in an internal variability of 0.14 salinity units and
0.33 ∘C for each of the 98 transects on average.
The δD of the Mediterranean surface seawater is
positively correlated with the local δ18O. The orthogonal
regression of the western Mediterranean can be described as δDwater=4.72×δ18Owater+1.67 (dark green). The
eastern Mediterranean is very similar to the western basin, and the relationship
between seawater δ18O and δD is δDwater=5.19×δ18Owater+1.68 (light green) here.
Statistically they cannot be told apart. This was determined using a
bootstrapping approach that generated 100 slopes and intercepts for both the
eastern and the western dataset and subsequent t testing using the mean and
standard deviation of both groups of slopes and intercepts, which resulted
in p values > 0.05. In both areas, the relationship is different
from the observations made by Gat et al. (1996), whose dataset suggested no
statistically significant relationship between δD and δ18O of the seawater (p value > 0.05).
Surface seawater δ18O is positively correlated with
sea surface salinity in the Mediterranean Sea, and the relationship observed can
be described as linear regression δ18Owater=0.17×S-5.39
(p value < 0.001, adjusted R2=0.17). Previously published
data can be combined into one dataset with a similar relationship with a
slightly steeper slope, which is offset towards relatively higher δ18O (δ18Owater=0.22×S-7.19; p value < 0.001, adjusted R2=0.48). The two regression lines are significantly
different from each other (ANOVA p value < 0.01).
Measured seawater δD values show a range from
2.83 ‰ to 9.46 ‰ VSMOW in the western
Mediterranean Sea and from 5.98 ‰ to
11.15 ‰ VSMOW in the east. Values from the individual
transects were used in combination with the δ18Owater to check for internal consistency
(Fig. 1). The δ18O values of the seawater vary between
0.13 ‰ and 2.29 ‰ VSMOW in the west and
between 0.73 ‰ and 2.43 ‰ VSMOW in the
east (Fig. 1). In our dataset, δ18O and δD of
the water are positively correlated in both the western and eastern
regions of the Mediterranean Sea (Fig. 1). The sensitivities of the
δD to δ18O correlations are
indistinguishable. The seawater oxygen isotopes are also linearly
correlated with seawater salinity (Fig. 2) and do not show an offset
between the eastern and western basins (p value < 0.001; R2=0.17).
Foraminiferal geochemistry
The foraminiferal oxygen isotope ratios
(δ18Oforaminifer) range from
-0.41 ‰ to 0.68 ‰ and are significantly
correlated with the seawater oxygen isotope ratio (Fig. 3a), albeit
with much scatter (R2=0.42, p value < 0.001). The δ18Oforaminifer are also positively correlated with sea
surface salinity (Fig. 3b), showing a similarly large amount of
scatter (R2=0.44, p value < 0.001).
G. ruber albusδ18O measurements are positively correlated (p value < 0.001) with both seawater δ18O(a) and salinity (b).
The relationships can be described using the following equations: δ18Oforaminifer=0.28×S-10.59 (adjusted R2=0.42) and
δ18Oforaminifer=0.95×δ18Owater-0.89
(adjusted R2=0.24). The relationship between δ18Owater and salinity in this subset of samples is linear and
comparable to that of the entire dataset (δ18Owater=0.13×S-3.91; p value < 0.05, R2=0.37).
Na <inline-formula><mml:math id="M151" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ca vs. salinity
Na / Ca values measured on individual F-chambers of G. ruber albus from the Mediterranean Sea range from 6.8 to
12.7 mmolmol-1 and are positively correlated with sea
surface salinity (Fig. 4a). The variability between individuals
(1–2 mmolmol-1) observed within transects is orders of
magnitude higher than the analytical uncertainty (RSD, relative standard deviation, of 5 %) and
is also higher than the uncertainty in the slope of the
Na / Ca–salinity calibration (Fig. 4a).
(a) Na / Ca measured in G. ruber albus F-chambers collected as living specimens
from the eastern and western Mediterranean Sea correlates well with local
salinity (p value < 0.001, Na/Ca=0.60×S-13.84), even though a
large natural spread of the elemental composition around the mean values per
station exists (R2=0.13). For salinities with more than five individual
Na / Ca measurements, hollow circles with whiskers indicate average values and
standard deviations respectively. (b) Mg / Ca in F-chambers of G. ruber albus specimens collected from
the water column of the Mediterranean Sea is positively correlated with sea
surface temperature and can be described with the following exponential relationship:
Mg/Ca=0.37×exp(0.14×T). For temperatures with more than five individual
Mg / Ca measurements, hollow circles with whiskers indicate average values and
standard deviations respectively. Regression lines were calculated using all individual
data points.
Mg <inline-formula><mml:math id="M165" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ca vs. temperature
Mg / Ca values measured on individual F-chambers of G. ruber albus from the Mediterranean Sea range from 1.34 to
7.63 mmolmol-1 and are positively correlated with sea surface temperatures measured in situ, although the temperature range
sampled during wintertime was rather narrow (Fig. 4b).
Particle backtracking
Particle backtracking shows that foraminifera collected at each
transect might actually have travelled long distances within the
30 d prior to sampling at the sample locations. The length of
the modelled trajectories varies greatly from location to location,
ranging between 200 and 500 km. This resulted in a variabilities
(SD, standard deviation) within one transect ranging from 0.11 to 1.0 ∘C
and from 0.03 to 0.4 salinity units.
DiscussionSalinity, <inline-formula><mml:math id="M171" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">18</mml:mn></mml:msup><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M172" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="italic">δ</mml:mi><mml:mi mathvariant="normal">D</mml:mi></mml:mrow></mml:math></inline-formula> of the seawater
A single uniform and stable trend in seawater stable isotopes with
salinity is a prerequisite for reconstructing past salinities. This is
important not only when using the stable oxygen isotopes measured on
foraminiferal shell carbonates but also for the interpretation of the
hydrogen isotopic composition of alkenones, which are also used as
proxies for palaeo-salinity (Schouten et al., 2006; Vasiliev et al.,
2013; Weiss et al., 2017).
The data presented here substantially increase the amount of data on
the relation between salinity and water isotopes of the Mediterranean
(Fig. 2). Although the new data clearly overlap with existing data,
we also observe slight but statistically significant differences in
the average salinity to δ18O relationship for the
different datasets. The overall lower δ18O values of
seawater measured here compared with the combined set of surface seawater isotopes from Stahl and Rinow (1973), Pierre et al. (1986), Gat
et al. (1996), Pierre (1999) and Cox (2010) of approximately
0.3 ‰ (Fig. 2) may be explained by inter-decadal,
seasonal and geographical variability between sample sets, or by a
combination of these factors. Importantly, such offsets also give a
first-order indication of the limit to the accuracy and precision of
reconstructions of past salinity using a combined temperature–stable
isotope approach from the primary relationship used.
Although Gat et al. (1996) reported a markedly different δD/δ18O relationship for the eastern Mediterranean Sea
compared with that of the western Mediterranean Sea, our results show no
sign of such a longitudinal discontinuity for the same area
(Fig. 2). This implies that the water isotopic composition of the
entire Mediterranean Sea can primarily be described by a single mixing
line between two end-members, with high vs. lower salinity
respectively. The remarkable trend in δD/δ18O observed previously by Gat et al. (1996) was explained
as a deuterium excess effect due to a combination of the composition
of the lowermost air vapour and mixing with the enriched surface
waters, which is most notable in winter months. The discrepancy in the
δD/δ18O relationship observed between our data
and those of Gat et al. (1996) may be due to inter-decadal variability
in the hydrological cycle or differences in seasonal
coverage. Thus, the observations of Gat et al. (1996) were potentially
related to unusual conditions, spatially restricted features
not covered by our sampling locations or the fact that the hydrological cycle in the
eastern Mediterranean has recently changed considerably. Either way,
the observed offset between the western and the eastern basins is
apparently not stable and should, therefore, probably not be considered
when using Mediterranean stable isotope signatures for reconstructing
palaeo-salinities.
The ratio of Na / Ca in G. ruber albus appears to be independent of seawater
temperature. While Mezger et al. (2016) showed a negative relationship
between temperature and foraminiferal Na / Ca in specimens collected from the
Red Sea, the addition of new data from the Mediterranean Sea clearly shows
that the previously hypothesized negative impact of temperature on Na / Ca is
likely an artefact of the negative relationship of temperature and salinity
in the Red Sea and that temperature has no significant impact on Na / Ca.
Na <inline-formula><mml:math id="M183" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ca vs. salinity
The Na / Ca ratios measured on the carbonate shells of
G. ruber albus from the Mediterranean Sea are significantly
and linearly correlated with salinity (Fig. 4a). This relationship is
similar to the one previously reported for plankton pump-collected
G. ruber albus from the Red Sea (Mezger et al., 2016).
Mezger et al. (2016) suggested that there might a combined effect of
different environmental factors such as carbonate chemistry, salinity
and temperature on the Na / Ca values in the field-collected
specimens. It is not possible to decouple these factors in the Red Sea
as they are strongly related. In contrast to the Red Sea where
there is a strong negative correlation between salinity and
temperature, the Mediterranean sea surface salinity and temperature
are positively correlated with each other; thus, comparing our data to that of
Mezger et al. (2016) allows for the temperature to be decoupled from salinity (Fig. 5). This shows that the correlation between foraminiferal
Na / Ca values and temperature observed in the Red Sea was not causal
and was more likely caused by salinity (Mezger et al., 2016). If
temperature would have a significant effect on the Na / Ca values in
G. ruber albus, we would expect different slopes and/or
offsets for the Na / Ca to salinity calibrations for the Mediterranean
Sea and Red Sea. This implies that temperature has no or only a minor
impact on Na / Ca ratios in G. ruber albus shells, which is
in line with similar findings that have shown a lack of a temperature effect on
the Na / Ca of T. sacculifer (Bertlich et al., 2018). The
average standard deviation in Na / Ca values for a given salinity
corresponds approximately to 2 salinity units, using the calibration
given here (Fig. 4a). This large variability is similar to the
inter-chamber and inter-specimen variability in other El / Ca ratios,
such as in Mg / Ca reported by Sadekov et al. (2008),
and appears to be inherent to single-chamber El / Ca (de Nooijer
et al., 2014b). It has been suggested that such variability between
individuals and also between different chambers of the same
individual may be caused by differences in the living depth and, hence,
environmental conditions (Mezger et al., 2018), lateral transport
(van Sebille et al., 2015) or variability in element incorporation
during biomineralization due to vital effects (Erez, 2003; de Nooijer
et al., 2014a; Spero et al., 2015), or individual timing of chamber
formation (Dämmer et al., 2019). As the specimens used here were
collected from surface waters and add new chambers very frequently,
vertical or lateral migration into waters with significantly different
conditions as suggested by Mezger et al. (2018) and Van Sebille
et al. (2015) appears to be an unlikely cause of heterogeneity
between specimens in this case. The relatively large scatter in the
Na / Ca values observed for single chambers (Fig. 4a) implies that
accurate and precise reconstructions of salinity can only be based on
combining a substantial number of specimens (Wit et al., 2013).
If salinity is reconstructed from the Na / Ca measurements using the
calibration published by Mezger et al. (2016) and compared
to salinity measured in situ in the Mediterranean Sea, the
reconstructed salinity follows the in situ measurements closely, almost
1:1. The largest deviation from this 1:1 relationship occurs in
the lower salinity range: at a salinity of 36.52, the reconstructed
salinity estimates underestimate in situ salinity values by 0.71 salinity units. The
average difference between in situ salinity measurements and salinity
reconstructed based on one single-chamber measurement is an
underestimation of salinity by 0.46 salinity units. This is still
higher than the theoretical uncertainty associated with combining
foraminiferal δ18O and temperatures derived from
Mg / Ca measured for exactly the same specimens (Rohling, 2007). An
uncertainty (1SD) of 1 ∘C in the Mg / Ca–temperature
calibration (which may be particularly optimistic at high seawater
temperatures) would result in an uncertainty of ∼0.37 units for
the reconstructed difference between the two salinities. This approach
would lead to an improved salinity reconstruction when the (change in)
past temperatures are determined more precisely, for example, by
reducing the error through increased sample size. The same applies for
salinity reconstructions based on Na / Ca, for which a limited number of calibrations are available, and, hence, leaves room for improvement.
The relationship between Mg / Ca in G. ruber albus and temperature during
calcification can be described using the following exponential equation for a temperature range from 15.1 to
29.1 ∘C:
Mg/Ca=0.278×exp(0.093×T).
While these reconstructions and the lack of a strong
temperature effect are very encouraging results for the use of Na / Ca
as a salinity proxy, the incorporation of Na into foraminiferal
calcite does not appear to be homogenous across the entire shell. It
has been shown that the majority of Na in G. ruber albus is
located in the spines (Mezger et al., 2018, 2019), which are not well
preserved in the fossil record.
<italic>G. ruber albus</italic> Mg <inline-formula><mml:math id="M209" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ca values
The increase in Mg / Ca in G. ruberalbus with
temperature (Fig. 4b) fits recent calibration efforts for
Mg incorporation and for temperature (e.g. Gray et al., 2018). As
salinity and inorganic carbon chemistry also both affect Mg
incorporation in this species (Kisakürek et al., 2008; Gray
et al., 2018), and the Mediterranean exhibits large gradients in these
parameters, it is necessary to correct measured Mg / Ca values for
these parameters. After normalizing Mg / Ca values to a seawater
salinity of 35, using the calibration of Gray et al. (2018), the
dependency of the Mg / Ca on temperature is similar to previously
reported calibrations (e.g. Gray et al., 2018), although the Mg / Ca
values at the lowermost temperatures appear to be higher than
expected (Fig. 6). This could potentially be caused by a combination
of an underestimation of the salinity effect in these highly saline
waters, as salinities observed here are well outside the
calibration range used by Gray et al. (2018), and low temperatures, which
have comparatively little impact on the foraminiferal Mg / Ca.
Adding our results to published Mg / Ca–temperature calibrations for
G. ruber albus (Anand et al., 2003; Babila et al., 2014;
Fallet et al., 2010; Friedrich et al., 2012; Gray et al., 2018;
Haarmann et al., 2011; Huang et al., 2008; Kisakürek et al., 2008;
Mathien-Blard and Bassinot, 2009; McConnell and Thunell, 2005; Mohtadi
et al., 2009) now extends the combined calibration to lower
temperatures (i.e. <18∘C), maintaining a
comparatively low temperature sensitivity in the colder part of the
calibration (Fig. 6). This not only increases confidence in the
application of Mg / Ca in this species as a palaeo-temperature
reconstruction tool for colder temperatures but also supports the
application of individual foraminiferal Mg / Ca values for
reconstructing seasonality (Wit et al., 2010). Although low densities have previously been reported for
G. ruber albus in the Mediterranean Sea during wintertime,
including their absence in large areas (Pujol and Grazzini,
1995; Bárcena et al., 2004), our
finding implies that the lowest Mg / Ca values can be related to winter
temperatures. G. ruber albus is not only present throughout
the year, as also shown by Rigual-Hernández et al. (2012) and
Avnaim-Katav et al. (2020), but it also registers the in situ
temperature, even during seasons that are close to its lower
temperature limit. Admittedly, the large scatter also observed at one
single sampling time (i.e. season) makes the deconvolution of
seasonality from analysing single specimen Mg / Ca values challenging.
(a) Example of backtracked pathways for a single transect (the
area marked using a white rectangle in panel c). The colour indicates the time
before sampling up to 30 d. (b) Analysing the different environmental
conditions at the different locations of these potential paths shows that the
foraminifera sampled very likely experienced a large range of temperatures
and salinities. (c) The variability in the potential
environmental conditions experienced changes considerably from location to location, as
indicated by notation of 1 standard deviation for both parameters for each
sampling location. The maps in panels (a) and (c) were generated using Ocean Data View
version 4.
<inline-formula><mml:math id="M224" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">18</mml:mn></mml:msup><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
<inline-formula><mml:math id="M225" display="inline"><mml:msub><mml:mi/><mml:mtext>foraminifer</mml:mtext></mml:msub></mml:math></inline-formula>
Role of lateral transport on <inline-formula><mml:math id="M226" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">18</mml:mn></mml:msup><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M227" display="inline"><mml:msub><mml:mi/><mml:mtext>foraminifer</mml:mtext></mml:msub></mml:math></inline-formula>
The horizontal transport of planktonic foraminifera may increase their exposure
to variable environmental conditions, including different
temperatures, salinities and seawater stable isotope compositions (van
Sebille et al., 2015). Comparing the sampled transects with the
calculated backtracking trajectories shows that the area where the
foraminifera might be derived from, especially close to
the straits (Alboran Sea and Strait of Sicily), potentially extends over
considerable distances and, therefore, encompasses considerable variability with respect to environmental
parameters. Due to the surface variability in temperature and salinity
during the sampling period, the calculated variability in these
parameters varied between 0.11 and 1.03 ∘C per
transect and 0.04 and 0.39 salinity units per transect (Fig. 7b, c). This means that the majority of foraminifera experienced a
variability of approximately 0.5 ∘C and 0.15 salinity
units.
The relationship between δ18Oseawater measured
in the Mediterranean Sea and δ18Oseawater calculated from
foraminiferal geochemistry (G. ruber albus). The relationship shown with dashed lines and
cross-shaped markers represents values calculated using foraminiferal
δ18O as well as Mg / Ca as an additional temperature proxy to
decouple the effect of temperature and salinity on δ18O. The
relationship shown with the continuous lines and circular markers shows the
same samples; however, instead of using temperature values derived from
foraminiferal Mg / Ca ratios, in situ measurements for temperature were used, and
the relationship can be described as δ18Owater_reconstructed=2.62(±0.69)×δ18Owater_measured-63.99(±26.11) with an adjusted R2 of 0.37. The temperature gradient was
2.2 ∘C.
When considering calibrations, this does not affect the measured
proxy variables, as the difference may be unbiased, but it adds to
the uncertainty of the environmental parameter to be
reconstructed. As foraminifera grow by periodically adding chambers
and as the size of the added chambers increases exponentially in
many species, the carbonate added closer to the sampling location
makes up a larger proportion of the total shell mass than carbonate
added at earlier life stages. Therefore, chambers formed early during
a foraminifer's life have less impact on the average shell composition; hence, the calibration and the backtracking trajectories
(Fig. 7a–c) indicate the largest possible range of conditions
experienced by a single foraminifer. This is relevant when considering
whole-shell chemistry (i.e. oxygen isotopes; Fig. 4a) and, to a lesser
extent, when considering the elemental composition of the final
chamber (Fig. 4b). The last chamber is affected by a much smaller
range of environmental conditions, i.e. only the time span during which
the final chamber was built – not more than a few days prior to
sampling.
Because δ18O of the calcite could not be measured on
F-chambers alone, as for element / Ca ratios, and several specimens
were needed for a single analysis, the results reflect the average composition
of foraminiferal populations at the sampling areas. The averaging
effectively cancels out differences due to inter- and intra-individual
variability but not offsets due to lateral transport. When transport
directions are largely uniform, this result in biases and should not
add to the scatter in the calcite's isotope composition. Hence, this
transport affects the calibration, but it does not affect precision.
Implications for proxies
Combining existing calibrations for foraminiferal Mg / Ca and
temperature (Gray et al., 2018) and calibrations relating
δ18Oforaminifer with temperature (Mulitza
et al., 2003), the δ18Oseawater can be
calculated. Using our dataset, we assess the quality of such
reconstructions by comparison to measured δ18Oseawater (Fig. 8). The Mg / Ca values used here
were not corrected for salinity effects, as salinity is the target
parameter that has to be reconstructed and is, thus, treated as
unknown. Even though there is a carbonate ion effect on the Mg / Ca in
G. ruber albus (Evans et al., 2016; Gray et al., 2018;
Kisakürek et al., 2008), the measured values were not corrected
for this, as this factor is also unknown in palaeo-reconstructions.
Calculated and measured δ18Oseawater do not
follow a 1:1 correspondence; this could be caused by uncertainties
in the different proxy calibrations, analytical uncertainties,
the heterogeneous element and isotope composition within and between
specimens; variability in the location and timing of their
calcification; and the effect of salinity and pH on Mg / Ca. The lack
of a strong correlation between calculated and measured
δ18Oseawater in our dataset implies that
calculating salinity from reconstructed
δ18Oseawater values will not yield
meaningful salinity reconstructions, as reconstructed values for
δ18Oseawater are not well correlated with δ18Oseawater measured in
situ. Calculating
salinities from δ18Oseawater clearly adds
much uncertainty due to spatial and temporal variability in the
correlation of these two parameters (Conroy et al., 2017; LeGrande and
Schmidt, 2006; McConnell et al., 2009).
It is important to note that the scatter in the foraminiferal
chemistry can only be explained by lateral transport to a small degree
(Fig. 7). This effect may be larger in areas where the environmental
conditions vary more strongly over the distance travelled by the
foraminifer and/or in basins where there is simply more lateral
transport over the foraminifers' lifetime. In our exercise, the
calculated trajectories add only a minor component to the uncertainty
in T (often within 0.75 ∘C; Fig. 7) and salinity
(often within 0.25 salinity units).
In our dataset, the uncertainty in salinity estimates based on
δ18Oseawater is much smaller when using temperatures measured in
situ (Fig. 8). The sum of squares of the
residuals (the difference between reconstructed and measured values) is
9.04 when using temperatures derived from Mg / Ca and
δ18Oforaminifer but only 3.56 when using
temperatures measured in situ, indicating a better reconstruction.
This shows that the uncertainty or offset in temperatures derived from
Mg / Ca, although the Mg / Ca–temperature relationship has been studied
relatively extensively for G. ruber albus, is most likely the
most limiting step. Even though temperatures
reconstructed from Mg / Ca in our dataset deviated less than 2 ∘C
from the measured temperature, these small offsets have a large effect
on the reconstructed δ18Oseawater. Thus, it is
crucial to choose temperature proxies carefully, use a large
enough number of specimens for analysis, be aware of the potential
effects of lateral particle transport as well as other environmental
parameters, and to be conscious about how errors propagate in
palaeoclimate reconstructions.
Combining all foraminiferal shell chemistry results show that
salinities based on δ18O and Mg / Ca may allow for the calculation of past salinity under some
specific conditions, but the
uncertainties in δ18Oseawater are large,
even in a setting with a large salinity gradient such as the
Mediterranean Sea. This is in line with predictions of uncertainty
based on theoretical considerations (Rohling, 2007). The most limiting
step in these calculations is the reconstruction of past temperatures,
which should be better than 2∘. Therefore, the development, validation
and improvement of other, more direct salinity proxies such as
foraminiferal Na / Ca remains crucial for more reliable
palaeo-salinity reconstructions.
Conclusions
Using plankton pump samples from the Mediterranean Sea, we showed the following:
The relationship of Mg / Ca in G. ruber albus and seawater temperature at lower temperatures follows an exponential
relationship; therefore, the proxy can now be applied to lower
temperature ranges (<18∘C) than before, covering
almost the entire temperature tolerance range of that species, although the sensitivity of the calibration is comparatively low at low
temperatures.
The combination of foraminiferal δ18O
and Mg / Ca along with assumptions about
δ18Oseawater values and
δ18Oseawater–salinity relationships does
not lead to useful reconstructions of seawater salinity.
Foraminiferal Na / Ca correlates well with sea surface salinity and is
independent of temperature, making it a potentially valuable tool
for salinity reconstructions.
Data availability
Upon publication, the data on which this paper is
based will be available at the 4TU.Centre for Research Data
(10.4121/13246616.v1, de Nooijer et al., 2020.).
Author contributions
LKD, LdN and GJR designed the study and performed the
sample collection. LKD and JGH prepared and processed the samples and the
corresponding data. EvS performed the particle backtracking. All authors
were involved in data interpretation. LKD drafted the paper with
contributions from all authors.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
We thank the editor as well as Michal Kucera and a second,
anonymous referee for their comments and suggestions that helped to improve
this paper. We thank the captain, crew and scientific staff of RV
Pelagia NESSC cruises 64PE406 and 64PE407, especially Anne Roepert (Utrecht
University) who collected the majority of the seawater samples used in this
study. We also thank Sharyn Ossebaar, Piet van Gaever and Wim Boer (NIOZ)
for their vital technical assistance as well as Geert-Jan A. Brummer
(NIOZ/Vrije Universiteit Amsterdam) for his support during sample
preparation and many discussions.
Financial support
This research has been supported by the NESSC.
Review statement
This paper was edited by Alessio Rovere and reviewed by Michal Kucera and one anonymous referee.
ReferencesAllen, K. A., Hönisch, B., Eggins, S. M., Haynes, L. L., Rosenthal, Y.,
and Yu, J.: Trace element proxies for surface ocean conditions: A synthesis
of culture calibrations with planktic foraminifera, Geochim. Cosmochim.
Ac., 193, 197–221, 10.1016/j.gca.2016.08.015, 2016.Allison, N., Austin, H., Austin, W., and Paterson, D. M.: Effects of seawater
pH and calcification rate on test Mg / Ca and Sr / Ca in cultured individuals of
the benthic, calcitic foraminifera Elphidium williamsoni, Chem. Geol.,
289, 171–178, 10.1016/j.chemgeo.2011.08.001, 2011.Anand, P., Elderfield, H., and Conte, M. H.: Calibration of Mg / Ca thermometry
in planktonic foraminifera from a sediment trap time series,
Paleoceanography, 18, 1050, 10.1029/2002PA000846, 2003.Aurahs, R., Treis, Y., Darling, K., and Kucera, M.: A revised taxonomic and
phylogenetic concept for the planktonic foraminifer species Globigerinoides
ruber based on molecular and morphometric evidence, Mar. Micropaleontol.,
79, 1–14, 10.1016/j.marmicro.2010.12.001, 2011.Avnaim-Katav, S., Herut, B., Rahav, E., Katz, T., Weinstein, Y., Alkalay, R., Berman-Frank, I., Zlatkin, O., and Almogi-Labin, A.: Sediment trap and
deep sea coretop sediments as tracers of recent changes in planktonic
foraminifera assemblages in the southeastern ultra-oligotrophic Levantine
Basin, Deep-Sea Res. Pt. II, 171, 104669,
10.1016/j.dsr2.2019.104669, 2020.Babila, T. L., Rosenthal, Y., and Conte, M. H.: Evaluation of the
biogeochemical controls on B / Ca of Globigerinoides ruber white from the
Oceanic Flux Program, Bermuda, Earth Planet. Sc. Lett., 404, 67–76,
10.1016/j.epsl.2014.05.053, 2014.Bahr, A., Schönfeld, J., Hoffmann, J., Voigt, S., Aurahs, R., Kucera, M., Flögel, S., Jentzen, A., and Gerdes, A.: Comparison of Ba/Ca and δ18Owater as freshwater proxies: A multi-species core-top study on planktonic foraminifera from the vicinity of the Orinoco River mouth, Earth Planet. Sc. Lett., 383, 45–57, 10.1016/j.epsl.2013.09.036, 2013.Bárcena, M. A., Flores, J. A., Sierro, F. J., Pérez-Folgado, M., Fabres, J., Calafat, A., and Canals, M.: Planktonic response to main oceanographic changes in the Alboran Sea (Western Mediterranean) as documented in sediment traps and surface sediments, Mar. Micropaleontol., 53, 423–445, 10.1016/j.marmicro.2004.09.009, 2004.Bertlich, J., Nürnberg, D., Hathorne, E. C., de Nooijer, L. J., Mezger, E. M.,
Kienast, M., Nordhausen, S., Reichart, G.-J., Schönfeld, J., and Bijma, J.:
Salinity control on Na incorporation into calcite tests of the planktonic
foraminifera Trilobatus sacculifer – evidence from culture experiments and surface sediments, Biogeosciences, 15, 5991–6018, 10.5194/bg-15-5991-2018, 2018.Bijma, J., Faber, W. W., and Hemleben, C.: Temperature and salinity limits for growth and survival of some planktonic foraminifers in laboratory cultures, J. Foraminifer. Res., 20, 95–116, 10.2113/gsjfr.20.2.95, 1990.Conroy, J. L., Thompson, D. M., Cobb, K. M., Noone, D., Rea, S., and
Legrande, A. N.: Spatiotemporal variability in the δ18O-salinity
relationship of seawater across the tropical Pacific Ocean,
Paleoceanography, 32, 484–497, 10.1002/2016PA003073, 2017.
Cox, K.: Stable Isotopes as Tracers for Freshwater Fluxes into the North Atlantic, Doctoral Thesis, University of Southampton, Southampton , UK, 178 pp., 2010.Dämmer, L. K., Nooijer, L. J. De and Reichart, G. J.: Light Impacts Mg
Incorporation in the Benthic Foraminifer Amphistegina lessonii, Front. Mar.
Sci., 6, 1–8, 10.3389/fmars.2019.00473, 2019.Delandmeter, P. and van Sebille, E.: The Parcels v2.0 Lagrangian framework: new field interpolation schemes, Geosci. Model Dev., 12, 3571–3584, 10.5194/gmd-12-3571-2019, 2019.de Nooijer, L. J., Spero, H. J., Erez, J., Bijma, J., and Reichart, G. J.:
Biomineralization in perforate Foraminifera, Earth-Sci. Rev., 135,
48–58, 10.1016/j.earscirev.2014.03.013, 2014a.de Nooijer, L. J., Hathorne, E. C., Reichart, G. J., Langer, G., and Bijma, J.: Variability in calcitic Mg / Ca and Sr / Ca ratios in clones of the benthic
foraminifer Ammonia tepida, Mar. Micropaleontol., 107, 32–43,
10.1016/j.marmicro.2014.02.002, 2014b.de Nooijer, L., Daemmer, L., van Sebille, E., Haak, J., and Reichart, G.-J.: Data belonging to the publication “Evaluation of oxygen isotopes and trace elements in planktonic foraminifera from the Mediterranean Sea as recorders of seawater oxygen isotopes and salinity”, Dataset, 4TU.ResearchData, 10.4121/13246616.v1, 2020.Dueñas-Bohórquez, A., Raitzsch, M., de Nooijer, L. J., and Reichart, G.-J.: Independent impacts of calcium and carbonate ion concentration on Mg
and Sr incorporation in cultured benthic foraminifera, Mar. Micropaleontol.,
81, 122–130, 10.1016/j.marmicro.2011.08.002, 2011.Erez, J.: The source of ions for biomineralization in foraminifera and their
implications for paleoceanographic proxies (Review), Rev. Mineral.
Geochem., 54, 115, 10.2113/0540115, 2003.Elderfield, H. and Ganssen, G.: Past temperature and δ18O of surface ocean waters inferred from foraminiferal Mg / Ca ratios, Nature, 405, 442–445, 10.1038/35013033, 2000.Evans, D., Wade, B. S., Henehan, M., Erez, J., and Müller, W.: Revisiting carbonate chemistry controls on planktic foraminifera Mg / Ca: implications for sea surface temperature and hydrology shifts over the Paleocene–Eocene Thermal Maximum and Eocene–Oligocene transition, Clim. Past, 12, 819–835, 10.5194/cp-12-819-2016, 2016.Fallet, U., Boer, W., Van Assen, C., Greaves, M., and Brummer, G. J. A.: A novel application of wet oxidation to retrieve carbonates from large organic-rich samples for ocean-climate research, Geochem. Geophy. Geosy., 10, Q08004, 10.1029/2009GC002573, 2009.Fallet, U., Brummer, G. J., Zinke, J., Vogels, S., and Ridderinkhof, H.:
Contrasting seasonal fluxes of planktonic foraminifera and impacts on
paleothermometry in the Mozambique Channel upstream of the Agulhas Current,
Paleoceanography, 25, PA4223, 10.1029/2010PA001942, 2010.Friedrich, O., Schiebel, R., Wilson, P. A., Weldeab, S., Beer, C. J.,
Cooper, M. J., and Fiebig, J.: Influence of test size, water depth, and
ecology on Mg / Ca, Sr / Ca, δ18O and δ13C in nine modern
species of planktic foraminifers, Earth Planet. Sc. Lett., 319–320,
133–145, 10.1016/j.epsl.2011.12.002, 2012.
Ganssen, G. and Kroon, D.: Evidence for Red Sea surface circulation from
oxygen isotopes of modern surface waters and planktonic foraminiferal tests,
Paleoceanography, 6, 73–82, 1991.Gat, J. R., Shemesh, A., Tziperman, E., Hecht, A., Georgopoulos, D., and
Basturk, O.: The stable isotope composition of waters of the eastern
Mediterranean Sea, Earth Planet. Sc. Lett., 101, 6441–6451,
10.1016/0012-821X(84)90103-1, 1996.Geerken, E., de Nooijer, L. J., van Dijk, I., and Reichart, G.-J.: Impact of salinity on element incorporation in two benthic foraminiferal species with contrasting magnesium contents, Biogeosciences, 15, 2205–2218, 10.5194/bg-15-2205-2018, 2018.Gray, W. R., Weldeab, S., Lea, D. W., Rosenthal, Y., Gruber, N., Donner, B.,
and Fischer, G.: The effects of temperature, salinity, and the carbonate
system on Mg / Ca in Globigerinoides ruber (white): A global sediment trap
calibration, Earth Planet. Sc. Lett., 482, 607–620,
10.1016/j.epsl.2017.11.026, 2018.Haarmann, T., Hathorne, E. C., Mohtadi, M., Groeneveld, J., Klling, M., and
Bickert, T.: Mg / Ca ratios of single planktonic foraminifer shells and the
potential to reconstruct the thermal seasonality of the water column,
Paleoceanography, 26, 1–14, 10.1029/2010PA002091, 2011.Hönisch, B., Allen, K. A., Lea, D. W., Spero, H. J., Eggins, S. M.,
Arbuszewski, J., DeMenocal, P., Rosenthal, Y., Russell, A. D., and
Elderfield, H.: The influence of salinity on Mg / Ca in planktic foraminifers
– Evidence from cultures, core-top sediments and complementary δ18O,
Geochim. Cosmochim. Ac., 121, 196–213, 10.1016/j.gca.2013.07.028,
2013.Huang, K. F., You, C. F., Lin, H. L., and Shieh, Y. T.: In situ calibration
of Mg / Ca ratio in planktonic foraminiferal shell using time series sediment
trap: A case study of intense dissolution artifact in the South China Sea,
Geochem. Geophy. Geosy., 9, Q04016, 10.1029/2007GC001660, 2008.Kisakürek, B., Eisenhauer, A., Böhm, F., Garbe-Schönberg, D., and
Erez, J.: Controls on shell Mg / Ca and Sr / Ca in cultured planktonic
foraminiferan, Globigerinoides ruber (white), Earth Planet. Sc. Lett.,
273, 260–269, 10.1016/j.epsl.2008.06.026, 2008.Lange, M. and van Sebille, E.: Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age, Geosci. Model Dev., 10, 4175–4186, 10.5194/gmd-10-4175-2017, 2017.Lea, D. W., Mashiotta, T. A., and Spero, H. J.: Controls on magnesium and
strontium uptake in planktonic foraminifera determined by live culturing,
Geochim. Cosmochim. Ac., 63, 2369–2379,
10.1016/S0016-7037(99)00197-0, 1999.LeGrande, A. N. and Schmidt, G. A.: Global gridded data set of the oxygen
isotopic composition in seawater, Geophys. Res. Lett., 33, 1–5,
10.1029/2006GL026011, 2006.Mashiotta, T. A., Lea, D. W., and Spero, H. J.: Glacial-interglacial changes in Subantarctic sea surface temperature and δ18O-water using foraminiferal Mg, Earth Planet. Sc. Lett., 170, 417–432, 10.1016/S0012-821X(99)00116-8, 1999.Mathien-Blard, E. and Bassinot, F.: Salinity bias on the foraminifera Mg / Ca
thermometry: Correction procedure and implications for past ocean
hydrographic reconstructions, Geochem. Geophy. Geosy., 10, Q12011,
10.1029/2008GC002353, 2009.McConnell, M. C. and Thunell, R. C.: Calibration of the planktonic
foraminiferal Mg / Ca paleothermometer: Sediment trap results from the Guaymas
Basin, Gulf of California, Paleoceanography, 20, 1–18,
10.1029/2004PA001077, 2005.McConnell, M. C., Thunell, R. C., Lorenzoni, L., Astor, Y., Wright, J. D.
and Fairbanks, R.: Seasonal variability in the salinity and oxygen isotopic
composition of seawater from the Cariaco Basin, Venezuela: Implications for
paleosalinity reconstructions, Geochem. Geophy. Geosy., 10, Q06019,
10.1029/2008GC002035, 2009.McCrea, J. M. M.: On the isotopic chemistry of carbonates and a paleotemperature scale, J. Chem. Phys., 18, 849–857, 10.1063/1.1747785, 1950.Mezger, E. M., de Nooijer, L. J., Boer, W., Brummer, G. J. A., and Reichart, G. J.: Salinity controls on Na incorporation in Red Sea planktonic
foraminifera, Paleoceanography, 31, 1562–1582,
10.1002/2016PA003052, 2016.Mezger, E. M., de Nooijer, L. J., Siccha, M., Brummer, G.-J. A., Kucera, M.
and Reichart, G. J.: Taphonomic and Ontogenetic Effects on Na / Ca and Mg / Ca
in Spinose Planktonic Foraminifera From the Red Sea, Geochem. Geophy., Geosy., 18, 4174–4194, 10.1029/2018GC007852, 2018.Mezger, E. M., de Nooijer, L. J., Bertlich, J., Bijma, J., Nürnberg, D., and
Reichart, G.-J.: Planktonic foraminiferal spine versus shell carbonate Na
incorporation in relation to salinity, Biogeosciences, 16, 1147–1165,
10.5194/bg-16-1147-2019, 2019.Mohtadi, M., Steinke, S., Groeneveld, J., Fink, H. G., Rixen, T., Hebbeln, D., Donner, B., and Herunadi, B.: Low-latitude control on seasonal and
interannual changes in planktonic foraminiferal flux and shell geochemistry
off south Java: A sediment trap study, Paleoceanography, 24, PA1201,
10.1029/2008PA001636, 2009.Morard, R., Füllberg, A., Brummer, G.-J. A., Greco, M., Jonkers, L.,
Wizemann, A., Weiner, A. K. M., Darling, K., Siccha, M., Ledevin, R.,
Kitazato, H., de Gardiel-Thoron, T., de Vargas, C., Kucera, M., De
Garidel-Thoron, T., de Vargas, C., Kucera, M., de Gardiel-Thoron, T., de
Vargas, C., and Kucera, M.: Genetic and morphological divergence in the
warm-water planktonic foraminifera genus Globigerinoides, PLoS One, 14,
1–30, 10.1371/journal.pone.0225246, 2019.Mulitza, S., Boltovskoy, D., Donner, B., Meggers, H., Paul, A., and Wefer, G.: Temperature: δ18O relationships of planktonic foraminifera
collected from surface waters, Palaeogeogr. Palaeocl.,
202, 143–152, 10.1016/S0031-0182(03)00633-3, 2003.Nooteboom, P. D., Bijl, P. K., van Sebille, E., von der Heydt, A. S., and Dijkstra, H. A.: Transport bias by ocean currents in sedimentary microplankton assemblages: Implications for paleoceanographic reconstructions, Paleoceanogr. Paleocl., 34, 1178–1194, 10.1029/2019PA003606, 2019.Nürnberg, D., Bijma, J., and Hemleben, C.: Assessing the reliability of magnesium in foraminiferal calcite as a proxy for water mass temperatures, Geochim. Cosmochim. Ac., 60, 803–814, 10.1016/0016-7037(95)00446-7, 1996.Ottens, J. J.: April and August Northeast Atlantic surface water masses reflected in planktic foraminifera, Netherlands J. Sea Res., 28, 261–283, 10.1016/0077-7579(92)90031-9, 1992.Pierre, C.: The oxygen and carbon isotope distribution in the Mediterranean
water masses, Mar. Geol., 153, 41–55,
10.1016/S0025-3227(98)00090-5, 1999.
Pierre, C., Vergnaud Grazzini, C., Thuoron, D., and Saliège, J.-F.:
Compositions Isotopiques de L'Oxygène Et Du Carbone Des Masses D'Eau
Mèditerranèe, Mem. Soc. Geol. It., 36, 165–174,
1986.
Prahl, F. G. and Wakeham, S. G.: Calibration of unsaturation patterns in long-chain ketone compositions for palaeotemperature assessment, Nature, 330, 367–369, 1987.Pujol, C. and Grazzini, C. V.: Distribution patterns of live planktic foraminifers as related to regional hydrography and productive systems of the Mediterranean Sea, Mar. Micropaleontol., 25, 187–217, 10.1016/0377-8398(95)00002-I, 1995.Rigual-Hernández, A. S., Sierro, F. J., Bárcena, M. A., Flores, J. A., and Heussner, S.: Seasonal and interannual changes of planktic
foraminiferal fluxes in the Gulf of Lions (NW Mediterranean) and their
implications for paleoceanographic studies: Two 12-year sediment trap
records, Deep-Sea Res. Pt. I, 66, 26–40,
10.1016/j.dsr.2012.03.011, 2012.Rohling, E. J.: Progress in paleosalinity: Overview and presentation of a
new approach, Paleoceanography, 22, 1–9, 10.1029/2007PA001437, 2007.Sadekov, A., Eggins, S. M., De Deckker, P., and Kroon, D.: Uncertainties in
seawater thermometry deriving from intratest and intertest Mg / Ca variability
in Globigerinoides ruber, Paleoceanography, 23, 1–12,
10.1029/2007PA001452, 2008.Schouten, S., Ossebaar, J., Schreiber, K., Kienhuis, M. V. M., Langer, G., Benthien, A., and Bijma, J.: The effect of temperature, salinity and growth rate on the stable hydrogen isotopic composition of long chain alkenones produced by Emiliania huxleyi and Gephyrocapsa oceanica, Biogeosciences, 3, 113–119, 10.5194/bg-3-113-2006, 2006.Spero, H. J., Eggins, S. M., Russell, A. D., Vetter, L., Kilburn, M. R., and
Hönisch, B.: Timing and mechanism for intratest Mg / Ca variability in a
living planktic foraminifer, Earth Planet. Sc. Lett., 409, 32–42,
10.1016/j.epsl.2014.10.030, 2015.
Stahl, W. and Rinow, U.: Sauerstoffisotopenanalysen an
Mittelmeerwässern: Ein Beitrag zur Problematik von
Paläotemperaturbestimmungen, “Meteor” Forschungsergebnisse. R. C. Geol.
Geophys., 14, 55–59, 1973.Steinhardt, J., Cléroux, C., Ullgren, J., de Nooijer, L., Durgadoo, J. V., Brummer, G. J., and Reichart, G. J.: Anti-cyclonic eddy imprint on calcite geochemistry of several planktonic foraminiferal species in the Mozambique Channel, Mar. Micropaleontol., 113, 20–33, 10.1016/j.marmicro.2014.09.001, 2014.
Urey, H. C., Lowenstam, H. A., Epstein, S., and McKinney, C. R.: Measurement of Paleotemperatures and Temperatures and the Southeastern United States, B. Geol. Soc. Am., 62, 399–416, 10.1130/0016-7606(1951)62[399:MOPATO]2.0.CO;2, 1951.van Dijk, I., de Nooijer, L. J., and Reichart, G.-J.: Trends in element incorporation in hyaline and porcelaneous foraminifera as a function of pCO2, Biogeosciences, 14, 497–510, 10.5194/bg-14-497-2017, 2017.van Sebille, E., Scussolini, P., Durgadoo, J. V., Peeters, F. J. C.,
Biastoch, A., Weijer, W., Turney, C., Paris, C. B., and Zahn, R.: Ocean
currents generate large footprints in marine palaeoclimate proxies, Nat.
Commun., 6, 6521, 10.1038/ncomms7521, 2015.Vasiliev, I., Reichart, G. J., and Krijgsman, W.: Impact of the Messinian
Salinity Crisis on Black Sea hydrology-Insights from hydrogen isotopes
analysis on biomarkers, Earth Planet. Sc. Lett., 362, 272–282,
10.1016/j.epsl.2012.11.038, 2013.Weiss, G. M., Pfannerstill, E. Y., Schouten, S., Sinninghe Damsté, J. S., and van der Meer, M. T. J.: Effects of alkalinity and salinity at low and high light intensity on hydrogen isotope fractionation of long-chain alkenones produced by Emiliania huxleyi, Biogeosciences, 14, 5693–5704, 10.5194/bg-14-5693-2017, 2017.Wit, J. C., Reichart, G. J., A Jung, S. J., and Kroon, D.: Approaches to unravel seasonality in sea surface temperatures using paired single-specimen foraminiferal δ18O and Mg / Ca analyses, Paleoceanography, 25, PA4220, 10.1029/2009PA001857, 2010.Wit, J. C., de Nooijer, L. J., Wolthers, M., and Reichart, G. J.: A novel salinity proxy based on Na incorporation into foraminiferal calcite, Biogeosciences, 10, 6375–6387, 10.5194/bg-10-6375-2013, 2013.