Introduction
Stable isotope values in foraminifera
The oxygen isotope ratio in the shells of planktonic foraminifera
(δ18Oshell) is used to reconstruct changes in water
properties of the upper water column (e.g. temperature, salinity,
stratification) as well aid in palaeoclimatological reconstructions (e.g.
defining water mass characteristics, global ice volume). Understanding how
this ratio is translated from the ambient environment into the shells of
individual foraminifera is therefore important to aid reconstructions and
reduce the uncertainty in reconstructed parameters. The
δ18Oshell values recorded are a product of the temperature
and the isotopic composition of seawater (δ18Osw), itself a
product of the evaporation and dilution (e.g. precipitation, riverine runoff
and ice melt) of seawater and hence directly correlated with salinity, which
is further modulated by species-specific preferences and metabolic effects
(i.e. vital effects). Reconstructions often utilize δ18O
produced from a number of pooled specimens, without reconciling how this
impacts sample heterogeneity and therefore the resultant climatic
interpretation (Fig. 1). Assuming minimal disruption from sedimentary
processes such as dissolution (McCorkle et al., 1997) or bioturbation
(Hutson, 1980; Lougheed et al., 2018; Löwemark, 2007; Löwemark and
Grootes, 2004; Löwemark et al., 2008; Trauth et al., 1997), the variance
associated within a pooled δ18O value is a product of the life
histories of each individual that comprises the single measurement (Lougheed
et al., 2018; Shackleton, 1967) and the underlying biological and ecological
controls that govern such “individual” depth distribution within the water
column and seasonal occurrence (e.g. Peeters et al., 2002; Schiebel and
Hemleben, 2017).
Representatives of species used within this study. Light microscope
from core top location and scanning electron microscope (SEM) images used to
highlight particular features were collected using plankton tows and plankton
pumps from the Arabian Sea during the NIOP cruise (Peeters, 2000; Peeters et
al., 2002). Note that this final sac-like chamber of Trilobatus sacculifer has various unique morphologies, including a thinner walled
variety giving the specimen's F chamber a translucent quality (similar to i
and vi). The species Globigerinoides ruber has two morphotypes
referred to as (xi–xii) senso stricto (s.s.) and (viii–x) senso lato
(s.l.), whilst Neogloboquadrina dutertrei is distinguished from
other species of Neogloboquanids by the presence of a “tooth”.
Research question and hypotheses
In this paper we present the results of a number of experiments using single
shells and dissected parts of single shells of planktonic foraminifera.
Analysis of small quantities has been made possible with advances in
techniques aimed at the routine measurement of microvolume amounts of
CO2 (Feldmeijer et al., 2015; Ganssen et al., 2011; Ishimura et
al., 2012; Metcalfe et al., 2015; Scussolini et al., 2013; Takagi et al.,
2015, 2016; van Sebille et al., 2015; Vetter et al., 2017; Wit et al., 2010,
2013). In order to evaluate the ecological and physiological impacts on the
stable isotope values of foraminifera, three species of planktonic
foraminifera (T. sacculifer; G. ruber white and N. dutertrei; Fig. 2) were picked from a modern core top sample from the
Tropical Atlantic Ocean (Fig. 3). Given its gross morphology, in which
individual chambers can be “cleanly” dissected with minimal interference
from other chambers (Lougheed et al., 2018; Shuxi and Shackleton, 1989; Spero
and Lea, 1993; Takagi et al., 2015, 2016), several experiments were first
performed on T. sacculifer (Fig. 2i: vii). These experiments focused
upon: (1) the differences between successive chambers (Lougheed et al., 2018;
Shuxi and Shackleton, 1989; Spero and Lea, 1993; Takagi et al., 2015, 2016);
(2) the size–isotope relationship of foraminifera, expanding upon Metcalfe
et al. (2015) and Feldmeijer et al. (2015) and (3) the difference in the
variance between species. In the section below, we address three fundamental
questions related to the oxygen isotope ecology of planktonic foraminifera.
In the first question we aim to find out whether there is evidence for depth
integrated growth of calcite in a surface-dwelling species. In the second
experiment we focus on the question whether shell size and oxygen isotope
composition are correlated. Finally, for the third experiment, we investigate
whether the oxygen isotope composition of shells of different species from
the same geographic location share the same variability.
Location Map of RETRO multi-core GS07-150-24 plotted on a basemap of
sea surface δ18Oeq seasonality. Location of multi-core
(black diamond) plotted on a seasonal oxygen isotope equilibrium
(Δδ18O) basemap, calculated by subtracting the maximum
and the minimum (δ18Oeq) of WOA13 temperature and salinity
data converted into input variables for a rearranged (Kim and O'Neil, 1997)
equation. Core location has an estimated Δδ18O of
0.6 ‰. Note that the coastline basemap of WOA13 is of a far lower
resolution than Mathworks MatLab® 2016
Mapping toolbox; thus, white areas around the coast represent a lack of
data.
Question 1. Do individuals belonging to the species T. sacculifer calcify at one specific depth or undergo depth migration?
The “average” depth habitat of planktonic foraminifera of several species
was first defined by Emiliani (1954) revealing that different species occupy
discretely different depth habitats, independently corroborated by the later
work of Jones (1967) by the presence or absence of species in stratified net
tows. However, the offset in δ18O measured between specimens
growing within the euphotic surface waters and those collected from the
seabed indicated that depth habitat is not confined to a single depth
(Duplessy et al., 1981; Mix, 1987); instead, this “average” species depth
habitat would be a weighted average of the various chamber calcification
depths occurring during an individual's ontogeny (Kozdon et al., 2009a, b;
Shuxi and Shackleton, 1989; Takagi et al., 2015, 2016). Data from plankton
tow studies combined with reproduction at depth would suggest that
foraminifera migrate through the water column during ontogeny (Fig. 1). For
certain species of foraminifera (i.e. T. sacculifer and G. ruber); however, a portion of the shell may have grown deeper in the water
column than the living depths estimated by plankton tows (Lohmann, 1995),
i.e. either a calcite crust triggered by temperature change (Hemleben and
Spindler, 1983; Hemleben et al., 1985; Srinivasan and Kennett, 1974) or
reproduction-triggered gametogenic calcification. For the first objective, we
aim to test whether T. sacculifer performs depth migration, which
would result in a deviation in the geochemistry between the different
chambers of a single specimen and also in a deviation from the conditions at
the sea surface. A one-sample Student's t-test was used to test the claim
that there is no difference between the mean of the final chamber and the
remaining shell of T. sacculifer, i.e. the difference is equal to
zero:
LetX=δ18OF-δ18O<F.H0:μX=0,H1:μX≠0.
By computing the difference and using a reference value of 0, we do not
invalidate the rule of independence that a two-sample Student's t-test
would require between the two sample populations. This dependence is based
upon the inference that μF and μ<F could conceivably be
considered to be “before” and “after” measurements, and thus the value of
μ<F could have an impact upon the value of μF.
Question 2. Does the δ18Oshell of
T. sacculifer covary with size?
Our second research objective is an expansion of the first objective, as
deriving palaeo-SST from the δ18O compositions of
foraminiferal shell is based on the assumption that a given specimen
calcifies at, or produces a large proportion of its shell at, one specific
depth in the water column. However, a portion of the variability associated
with stable isotope measurements in foraminifera is believed to be
size-dependent (Ezard et al., 2015). These size dependencies are typically
attributed to biological effects and relate to depth migration through
ontogeny (Feldmeijer et al., 2015; Metcalfe et al., 2015). For instance,
investigations into the population dynamics of living specimens of T. sacculifer in the central Red Sea revealed that whilst this species in
general occupies the upper 80 m of the water column distinct size classes
were shown to have clear depth preferences (Bijma and Hemleben, 1994;
Hemleben and Bijma, 1994) with small foraminifera (100 to 300 µm)
in the upper 20 m and progressive larger foraminifera with depth to the
point that the largest specimens (>700 µm) lived between 60 and
80 m. Calcification at different depths throughout their life span may cause
a deviation in the δ18O values of individuals from different
sizes, depending on the ambient water column structure, which would therefore
reflect different depths and thus the selection of an appropriate size
fraction may or may not unduly influence palaeoclimate reconstructions. The
aim of this second objective is to further expand upon the results of our
first question and test whether the different depth preferences for different
sizes of T. sacculifer, have an effect on the
δ18Oshell. Three size fractions were studied to learn more
about the effect of size on δ18Oshell and a one-way
analysis of variance (one-way ANOVA) with a post hoc test used to detect
intra-sample differences was used to test the hypothesis that there is no
difference between the means of the different size fractions of T. sacculifer:
H0:μδ18Osmall=μδ18Omedium=μδ18Olarge,H1:at least one of the means is different from the others.
Question 3. Do different species of planktic foraminifera from
the same geographic location share the same single-specimen δ18Oshell variability?
Having focused upon a single species for the first two research questions,
our third question focuses upon the variability of foraminifera isotope
values, which are considered to represent seasonality, and whether fossil
shells from different species share similar δ18Oshell
variability. Commonly when referencing seasonality, temperature is considered
as the variable of interest. However, the tropics have relatively small
seasonal temperature variability compared with higher latitudes, the core is
situated along the north-eastern coast of Brazil which may be influenced by
the shift in the ITCZ (Jaeschke et al., 2007). Temperature and salinity have
opposing effects on the overall oxygen isotope composition. Surface-dwelling
species of planktonic foraminifera, T. sacculifer (Fig. 2i: vii);
G. ruber (Fig. 2viii: xiii); and the thermocline dwelling N. dutertrei (Fig. 2xiv: xix) were picked from the core top. All species are
symbiotic (Schiebel and Hemleben, 2017) which limits the depth of the maximum
growth. A one-way ANOVA was used to test, whether the means of each species
are equal or whether the alternative hypothesis that one or more of the
species means differs from one another, with the following hypothesis:
H0:μδ18OT.sacculifer=μδ18OG.ruber=μδ18ON.dutertrei,H1:atleastoneofthemeansisdifferentfromtheothers.
In addition to the ANOVA test for testing multiple means, we use a
Kolmogorov–Smirnov (K–S) test to test whether the species stem from a
similar δ18O distribution, with the claim in the null
hypothesis being equal (i.e. not significantly different) distributions.
Three tests were carried out: T. sacculifer vs. N. dutertrei, T. sacculifer vs. G. ruber and N. dutertrei vs. G. ruber respectively. For Objective 3, the
hypothesis is that the δ18Oshell variability varies for
different species from the same location, which would mean that different
species from the same location can give a different temperature and/or
seasonality derivation (Mix, 1987; Roche et al., 2018). Overall, the
hypothesis is that different processes cause deviations from the sea surface
equilibrium. More insight into the presence and size of these deviations can
possibly be used to account for future climate reconstructions.
Method and material
Material and general methodology
Multi-core GS07-150-24 was collected on board the RV G.O. Sars at a
depth of 2412 m offshore of north-eastern Brazil (3∘46.474′ S,
37∘03.849′ W; Fig. 3). Following sub-sampling, the top of the core
was washed over a >63 µm sieve, dried overnight, before being
dry sieved over a 150 and 500 µm mesh. Regardless of the research
question, each specimen underwent the same methodological protocol which aims
to reduce uncertainty (e.g. specimen misidentification; anomalous or abnormal
features) within single-shell stable isotope analysis by cataloguing
morphology and physical features of specimens prior to destructive analysis.
After picking, the selected specimens were given a unique identifier, imaged
in the umbilical position (Fig. 2) using a Nikon Digital Research microscope
with a prior motorized stage. The motorized stage enables multiple images to
be taken at pre-determined intervals in µm. These images were then
combined using Nikon Digital Research D software into an extended depth of
focus (EDF) image. Each EDF image was then used to measure the diameter and
surface area of both the final chamber and the whole shell, using the same
programme. Groups of specimens were imaged together, with little impact upon
the resolution (1 pixel, depending on the magnification, is equal to 0.3 to
1.5 µm) and placed into individual slides in order to generate a
high throughput. After imaging, specimens were weighed individually in tin
capsules using a Mettler-Toledo UMT microbalance (manufacturers precision
0.1 µg). In total 207 specimens of T. sacculifer were
picked, weighed and measured for size. Following these measurements,
specimens selected for research questions 1 (δ18O difference
between F and <F) and 2 (δ18O difference between size)
underwent additional steps, outlined in Sect. 2.2 (dissection of chambers)
and Sect. 2.3 (size fractions), prior to stable isotope analysis.
For δ18O and δ13C analysis, shells and/or
single chambers between 5 and 70 µg were placed in a 4.5 mL
borosilicate exetainer vial, whereas shells between 20 and 145 µg
were placed in larger 12 mL borosilicate exetainer vials (Breitenbach and
Bernasconi, 2011; Feldmeijer et al., 2015; Metcalfe et al., 2015). Each vial
was sealed with a cap with a pierce able septum, placed in a heated block
(45 ∘C), before being flushed with helium for 3 or 5 min to remove
the ambient air (flow rate >100 mL min-1) depending on the size of
the vial. Each sample was reacted with a few drops of phosphoric acid
(H3PO4) for 160 min, transferred using a continuous flow of
helium into a GasBench II preparation device, in which impurities were
removed, before being introduced into a Thermo Delta+ mass spectrometer.
Results were reported as δ values in per mil (‰),
following voltage correction of the amplitude of mass 44 using grains of
150–180 µm of Vrije Universiteit Internal Carbonate Standard
(VICS: δ18O=-5.44 ‰; δ13C=1.35 ‰) in order to be placed on the V-PDB scale. The precision of
within-run international standards of IAEA-CO-1 and IAEA-CO-603 (minimum n=10), placed to book-end every 6 samples, was better than 0.14 ‰ for
both δ18O and δ13C. Shell size, weight and
stable isotope data are available online (Pracht et al.,
2018).
Specific methodology for Question 1
To make inferences about depth migration (Research Question 1) 57 specimens
of T. sacculifer were picked from two size fractions: 150–500 and
>500 µm. Selection of specimens was based on the following
criteria: (1) specimens were intact, or did not appear externally to be
broken or damaged; (2) specimens were not visibly discoloured or overly
contaminated with clay; (3) specimens were not kummerform (Bé et al.,
1971; Berger, 1969, 1970; Olsson, 1973), and/or it was possible for the
sac-like chamber to be dissected; and (4) specimens and their final chambers
were judged to be heavier than 6 µg to ensure sufficient mass for
measuring on the mass spectrometer. Following the standard protocol, the
final sac-like chamber was amputated (Shuxi and Shackleton, 1989; Spero et
al., 1993; Ishimuru et al., 2012) from the rest of the shell with a number
7 dissecting scalpel, so that each shell was analysed in two portions, the
last chamber (δ18OF) and a shell without the last
chamber (δ18O<F). Those shells, minus the F-chamber,
that still exceeded >150 µg were analysed in two parts. The
remainder of the shell was placed between two glass slides, crushed,
homogenized and then separated into two portions (identified as A and B). The
isotope value of δ18O<F was calculated by using a
weighted mean of the measured δ18O from these two portions (a
and b), with the following:
δ18Oμ<F=δ18O<Fa⋅amplitudea+δ18O<Fb⋅amplitudebamplitudea⋅amplitudeb,
where the amplitude is the amount of CO2 of mass 44 produced in
mVolts, which is linearly related to sample weight.
Specific methodology for Question 2
To make inferences about the effect of size on the measured isotopic
composition (Research Question 2), 41 whole shells of T. sacculifer were picked from the >150 and >500 µm size
fractions and subdivided based upon measured size. Three size classes were
determined: small: 222–316 µm (n=10); medium:
373–467 µm (n=16); and large: 511–597 µm (n=15). The size classes have uneven widths with ranges of 94 µm, 94
and 86 µm respectively. All δ18Oshell values of
G. ruber and T. sacculifer, irrespective of size, were
corrected for their vital effect.
Specific methodology for Question 3
To determine whether species of planktonic foraminifera from the same
geographic location share the same or similar single specimens, δ18Oshell variability specimens of G. ruber (n=20) and
N. dutertrei (n=14) were picked from the same interval. These
shells underwent the same methodology outlined in Sect. 2.1 for
photographing, weighing and isotope analysis.
Atlas data (temperature, salinity and
δ18OC)
World Ocean Atlas 2013 (WOA13; Boyer et al., 2013) was used as an average
climatology at the core site, temperature and salinity was extracted from the
live access server (LAS) of NOAA. The oxygen isotope equilibrium values
calculated by first computing the oxygen isotope of seawater (δ18Osw) from WOA 13 salinity using the oxygen isotope database of
LeGrande and Schmidt (2006). A regional mask was used on a global grid to
define which regional equation to use, regions were redefined to fit
established conventions on the definitions of particular ocean basins
(similar to the approach of Roche et al., 2018). Values of salinity that
represent riverine outflow (PSU<10) were excluded from the
resultant reanalysis of the salinity vs. oxygen isotope of seawater
relationship of the tropical Atlantic Ocean (LeGrande and Schmidt, 2006).
Both WOA13 temperature and the computed δ18Osw were then
used as input values for the equation of Kim and O'Neil (1997), rearranged
from the relationship between temperature and the fractionation of oxygen
isotopes in planktonic foraminifera, to derive the oxygen isotope equilibrium
(δ18Oeq):
δ18Oeq=25.778-3.333×43.704+T0.5+δ18Osw,
Here, Kim and O'Neil (1997) is used to define an inorganic equilibrium value
of δ18Oc this equation is chosen to avoid potential
differences due to (1) light level; (2) foraminiferal size; (3) ontogenetic
level (Bemis et al., 1998, 2000); and (4) species (Mulitza et al., 1999b). To
account for similar absolute measured values between species which are not
produced by concurrent depth or seasonal preferences between species but
instead by species-specific disequilibria from values obtained from ambient
seawater equilibrium (so-called “vital effects”) a correction was applied.
The δ18O values of T. sacculifer and G. ruber were corrected by 0.48 ‰ (1σ=0.15 ‰;
Peeters, 2000; Peeters et al., 2004). To understand the results, a
probabilistic determination of the seasonal-depth distribution using a fitted
normal distribution to the single-specimen data was calculated by fitting the
probabilities of δ18Oshell to the seasonal and depth
distribution of δ18Oeq. Fitting was accomplished using a
normal distribution; therefore, to test whether the data come from a normal
distribution, a K–S test (data normalized first) and an Anderson–Darling
test were performed. The probability determined for each
δ18Oshell is then transposed onto the
δ18Oeq of the core top.
Results
To aid the reader, the stable isotope values in the following section are
reported to two or three decimal places to report the results of the
statistical tests without introducing rounding errors; this should not be
misconstrued as reflecting a greater degree of certainty in the isotope
values after the decimal point.
Size vs. weight of T. sacculifer
During the picking and selection process, a total of 207 specimens of
T. sacculifer was measured and weighted. Ninety-eight of these were
eventually analysed for stable isotopes; however data on size and weight for
all 207 specimens were processed to make interferences about the relation
between these two parameters (Fig. 4). For comparison, the measured size and
weight data were plotted alongside a theoretical hollow foraminifer (similar
to Orbulina universa) in which the shell weight is calculated by
assuming a constant porosity and the density of calcite is
2.71 kg-1 m-2. This approach highlights the complexity when
dealing with foraminiferal weight when both chamber number and chamber wall
thickness is variable, there is a clear increase in the spread in shell
weight (Fig. 4a) when the area is larger than 4×105 µm2 this is likely either the result of chamber
thickening or non-linear growth of the foraminiferal shell. After completion
of the first chamber, during the construction of subsequent chambers of a
Rotaliid foraminifer an additional layer of calcite is added to the previous
chambers, making them a incrementally thicker. This makes the weight increase
deviate from a linear relation and also makes that the final chamber has less
thick (and therefore lighter) walls than its predecessors (Bé and Lott,
1964). Regarding shell size vs. shell weight, a heteroscedastic relation was
found. For smaller tests, little variance was present, deviation from the
regression line increased when the area of the test increased, indicating
more variability in shell weight for bigger shells. A possible explanation
can be found in the fact that when shells grow larger, they tend to get more
divergent or erratic forms (Fig. 4a), this especially goes for the final
chambers. A relatively low weight in large specimens is then caused by a
relatively large F chamber. Because the F chamber has a relatively thin
wall and therefore a low weight, the shell of large specimens is lighter than
expected (Bé and Lott, 1964). A relatively high weight in large specimens
is caused by a big <F and small F. The chambers of <F have thicker
walls and therefore a relatively high weight, causing a positive deviation
from the size-weight regression line. A heteroscedastic relation also
appeared between the area of the final chamber and the area of the whole
shell. In Fig. 4b it is visible that when the area of the whole shell size
increases, the variance becomes bigger. Large specimens often have
disproportionally large or small final chambers, with no clear relationship
between total shell size and the size of the final chamber. Compared to
smaller shells, big shells tend to have relative small or big final chambers,
which are not in proportion with the shell.
Physical properties of T. sacculifer. (a) Size vs.
weight of T. sacculifer; the data are overlaid on a theoretical
calculation of what the shell weight would be of a spherical hollow
foraminifer with consistent porosity, assuming the density of calcite. Colour
represents variation in wall thickness used to calculate the difference
between the inner and outer sphere volume. (b) The area of the final
chamber vs. the whole shell area of specimens measured, pictures inset
highlight the morphology associated with the spread in the datasets. The
scatter points filled colour reflects the ratio between the maximum ferret
diameter with and without the last chamber. The linear regression equation is
y=0.0002x-4.5243 (r2=0.8985; n=207).
Final chamber vs. rest of shell δ18O.
(a) Raw δ18O values of rest of shell (blue) and final
chamber (red) plotted as a histogram, vertical bars represent sample means.
Fitted normal distributions for rest of shell (μ<F; blue) and final
chamber (μF red), with mean average values are also indicated. Histogram
bins are in 0.25 ‰ bin intervals, the equivalent of ∼1 ∘C depending on whether the data are on the high or low end of
the scale. (b) Histogram of the same specimen difference in
δ18O (≡Δδ18O) between <F and
F. Vertical green lines at Δδ18O of ±1 ‰
represent a ∼4 ∘C temperature variation, a vertical red line
denotes no difference (Δδ18O=0). The average
Δδ18O (μ=0.203) is shown as a black vertical line.
(c, d) Scatter plot of the same data plotted as either
the (c) <F remaining of the shell and (d) the
F chamber δ18O vs. Δδ18O. Vertical
error bars represent the square root of the sum of the error's squared
ErrorA2+ErrorB2 and the horizontal a single machine error. Blue line is the
linear regression and the blue a confidence interval on the regression. All
values in per mil (‰) on the V-PDB scale.
Question 1: depth migration
Measured δ18O values are plotted as a histogram in Fig. 5a for
δ18O<F and δ18OF. The mean
δ18O values for the final chambers and the shells without
final chambers, were δ18OF‾=-1.234 ‰ and δ18O<F‾=-1.437 ‰ respectively, indicating the means of the two groups
differ by approximately 0.203 ‰, with the final chamber having a
more negative value than the shells without the final chamber. In Fig. 5b, a
histogram of Δδ18O, which represents the difference
between δ18O<F and δ18OF is
shown. The data are normally distributed, with a mean (difference) of
+0.23 ‰ (Table 1). The one-sample t-test results in a p-value
of <0.05, therefore the null hypothesis can be rejected at a significance
level of α=0.05, and it is possible to conclude that the
Δδ18O is statistically different from 0. In other words,
the difference between final chamber δ18O and the
δ18O value of the shell with the last chamber removed, is
positive and significantly different from zero at the 95 % confidence
level. The positive value indicates that growth of the final chamber occurs,
on average, at a lower temperature. A scatter plot between Δδ18O and δ18O<F (r=0.61; n=57); and
δ18OF (r=0.69; n=57) shows that there is a
statistically significance between the variables (Fig. 5c and d). The
significance of r being non-zero was statistically tested using Pearson's
correlation coefficient. The critical value for the absolute value of the
correlation coefficient for an α of 0.05 where n=50 is 0.273 and
n=60 is 0.250. Our n (=57) taking into account the number of degrees
of freedom (d.f. = n-2) lies between these values of n. Since our
correlation coefficients are higher than these critical values, it is
possible to conclude that they are different from zero. The correlation
coefficients are also significant for an α of 0.01 (C.V. = 0.354;
for d.f. = 50).
Results of the Student's t-test for a single group. Testing the
δ18OF-δ18Oshell-F. Test value: 0 (testing whether the
difference between δ18OF and
δ18Oshell-F is statistically equal to 0).
Count
57
Mean
0.20
Variance
0.16
SD
0.40
Std. error
0.054
Mean difference
0.20
Degrees of freedom
56
t value
3.78
t probability
0.0004
Box plots of the oxygen isotope values (δ18O) vs.
size and for different species of planktonic foraminifera.
(a) Small, medium and large (see the text for definitions of sizes
represented; note the uneven size interval). (b) The (right-hand
side) box plots are the range in oxygen isotopes corrected for vital effects
(circles with arrows) calculated from in situ water sampling (plankton pump
and plankton tow; Frank Peeters, unpublished data). The central bar of each
box represents the median.
Results of the ANOVA test for size fractions. Comparison of the
means of the three different size classes: small, medium and large.
Analysis of variance results
Source
Degrees of freedom (DF)
Sum of squares (SS)
MS
F-value
P-value
Total
40
2.49
0.06
2.12
0.13
A
2
0.25
0.13
Error
38
2.24
0.06
Tukey's all pair comparison
Mean difference
|q|
P
95 % CL
δ18Oshell small vs. δ18Oshell medium
0.17
2.52
0.19
-0.06 to 0.41
δ18Oshell small vs. δ18Oshell large
0.03
0.36
0.9646
-0.22 to 0.27
δ18Oshell large vs. δ18Oshell medium
0.15
2.41
0.2162
-0.06 to 0.36
Question 2: covariance with size
The mean δ18O for the small, medium and large size fractions
of T. sacculifer was -1.12 ‰, -1.30 ‰ and
-1.15 ‰ respectively (Fig. 6; Table 2),
with the smallest and largest shells having a less negative mean value than
the medium shells. The resultant ANOVA test p-value of 0.136 (>0.05)
however indicates that the null hypothesis of equal means cannot be rejected;
the observed differences between the different size classes are therefore not
enough to state that there is a statistically significant difference between
the mean δ18Oshell of the small (222–316 µm);
medium (373–467 µm) and large (511–597 µm) shells.
Question 3: similarity in species-specific variability for a
single site?
The mean δ18O of the single specimens of N. dutertrei, T. sacculifer and G. ruber were -0.84 ‰;
-0.82 ‰ and -1.15 ‰ respectively (Fig. 6b;
Table 3). An ANOVA to test whether the species had
equal means resulted in a p-value of 0.0001 which led to a rejection of the
null hypothesis (p<0.05) that the species have equal means. A post hoc
Tukey all pair comparison, using vital effect corrected δ18O
values, shows that the mean δ18Oshell of G. ruber
differed significantly from both T. sacculifer (p=0.0004) and
N. dutertrei (p=0.0017), whereas the difference between
T. sacculifer and N. dutertrei was not significant (p=0.9492). Using the uncorrected, for vital effect
(Table 4), δ18O values all species
show statistical difference between one another. The range in species
δ18O is less than 1 ‰, from largest to smallest the
range of N. dutertrei (δ18Omin.:
-1.33 ‰; δ18Omax.: -0.46 ‰;
δ18Orange: 0.86 ‰) is larger than T. sacculifer (min. -1.20; max. -0.39; range: 0.81 %) and G. ruber (min. -1.55; max. -0.78; range 0.76) (Fig. 6b). However, for three
F-tests, to determine whether the species has equal variances, the
resultant F-value is less than the F-test critical value and therefore
the null hypothesis that they have equal variances could not be convincingly
rejected with the data measured. A Kolmogrov–Smirnov test was used to test
whether the three species come from the same distribution, which would
indicate the three species have recorded the same climate signal. Three tests
were carried out, each comparing the distributions of two species at the
time. The test comparing T. sacculifer and N. dutertrei,
resulted in a p-value of 0.9697 (α=0.05), meaning it is unable to
reject the null hypothesis. This means that we found no evidence that the two
species have a different probability distribution. For N. dutertrei
vs. G. ruber (p=0.012) and T sacculifer vs. G. ruber (p=0.030), the null hypothesis however could be rejected; therefore, the two
species record significantly different variability in δ18O.
Results of the ANOVA test comparing the means of the three different
species corrected for vital effect: T. sacculifer, G. ruber
and N. dutertrei.
Analysis of variance results
Source
DF
SS
MS
F
P
Total
49
3.85
0.08
10.91
0.00013
A
2
1.22
0.61
Error
47
2.63
0.06
Tukey's all pair comparison
Mean difference
|q|
P
95 % CL
T. sacculifer vs. G. ruber
0.33
5.90
0.0004
0.14 to 0.52
T. sacculifer vs. N. dutertrei
0.03
0.44
0.9492
-0.18 to 0.24
N. dutertrei vs. G. ruber
0.30
5.22
0.0017
0.104 to 0.504
Results of the ANOVA test comparing the means of the three different
species uncorrected for vital effect: T. sacculifer, G. ruber and N. dutertrei.
Analysis of variance results
Source
DF
SS
MS
F
P
Total
49
7.71
0.16
44.99
<0.0001
A
2
5.07
2.53
Error
47
2.65
0.06
Tukey's all pair comparison
Mean difference
|q|
P
95 % CL
T. sacculifer vs. G. ruber
0.78
13.41
<0.0001
0.58 to 0.98
T. sacculifer vs. N. dutertrei
0.45
7.39
<0.0001
0.24 to 0.66
N. dutertrei vs. G. ruber
0.33
5.87
0.0004
0.14 to 0.52
Season or depth, predicting likely depth habitats of planktonic
foraminiferal species using inferred equilibrium oxygen isotope values
(δ18Oeq). World Ocean Atlas (WOA13) temperature and
salinity were used to compute the
equilibrium oxygen isotope value using the tropical Atlantic δ18O–salinity relationship defined by LeGrande and
Schmidt (2006) input into a rearranged form of Kim
and O'Neil (1997) (see Sect. 2.4).
(a) Contour plot of δ18Oeq, plotted as depth in
metres vs. day in year. Note the uneven depth interval distribution inherent
within the WOA dataset. Black arrows represent depths chosen in
(c) to calculate cumulative distribution, species
symbols represent inferred depths of
mean average values. (b) The seasonal minimum and maximum (grey
band) in δ18Oeq for each depth interval, coloured bars
represent depth intervals that are similar to isotopic values of the three
species. (c) Cumulative density distribution of the three species
plotted alongside the CDF for 20, 100, 125 and 150 m distributions; values
are plotted as probability (F(x)) vs. oxygen isotope value. All values
plotted in per mil (‰) on the V-PDB scale.
Discussion
Depth migration
Numerous studies have subdivided the species T. sacculifer into the
forms with a distinct final chamber, referred to as “sac-like”, from
“non-sac” forms referred to by its junior synonym G. trilobus. The
division between these forms is not exclusively for studies with geochemical
analysis but is also commonly found in studies using faunal abundance counts.
In fact, a number of studies where T. sacculifer is used as a proxy
for palaeoclimate have removed the final chamber to avoid potential bias
caused by the assumed depth migration (Coadic et al., 2013). In our results
we show a mean difference of approximately 0.203 ‰ between
δ18OF and δ18O<F, i.e. those
forms that would be described as T. sacculifer and those as
G. trilobus, with <F having more negative values
(δ18O<F‾=-1.437 ‰) than
F (δ18OF‾=-1.234 ‰).
A number of species of foraminifera, including the species analysed here
(Bird et al., 2018), are associated with symbiotic algae that undergo diurnal
migration into and out of the shell and vacuoles in the foraminifer's
cytoplasm, a major function is their facilitation of both growth and
longevity of an individual foraminifer (Anderson and Be, 1976; Bé et al.,
1982; Caron et al., 1982; Faber et al., 1988, 1989; Gastrich, 1987; Hemleben
et al., 1989; Spero and DeNiro, 1987; Spero and Lea, 1993; Spero and Parker,
1985). As such the presence of symbionts places limits upon the range of
depth habitat: juvenile foraminifer must either be re-infected by or capture
new symbiotic algae (Hemleben et al., 1989; Spero, 1998) whilst adult
foraminifera with symbiotic associations would do well to remain within the
photic zone. Using the mean δ18Osw of the sample location
of 0.42 ‰ (WOA13; Boyer et al., 2013) and the mean
δ18O of F and <F respectively, mean temperatures of 24.5
and 25.5 ∘C were derived which indicates a potential mean depth
below and above 100 m respectively. The euphotic zone depth varies both
regionally and temporally, from a lower limit of 20 m to greater than 120 m
globally, with measured sites displaying variability between <40 to >100 m on seasonal timescales (Buesseler and Boyd, 2009; Siegel et al.,
2014). Spero (1998) reflecting on the evolutionary advantages for a species
known to harbour symbiotic algae to calcify below the photic zone considered
that there are none, and instead as planktonic foraminifera are at the mercy
of ocean currents such specimens that reflect too deep growth (Lohmann, 1995)
could represent descent or advection out of their suitable habitat range. In
fact, our results highlight the complexity of the individual life histories
of individual foraminifer like many species of (phyto- and or zoo-)plankton
which are heavier than water (Huisman et al., 2002) their persistence within
the upper water column, despite a sinking trajectory that should take them
below conditions of light and nutrients sufficient for growth, may relate to
turbulence and advection (Huisman et al., 2002; Margalef, 1978; Riley et al.,
1949; Shigesada and Okubo, 1981; Sverdrup, 1953). Our results show that
whilst the mean difference in δ18O, between F and <F, is
weighted toward a colder signal within the final chamber, there are however a
number of shells that record a warmer signal in the F chamber (n=8 for
<-0.25 ‰; or n=16 for <0.0 ‰). Although the role
of turbulence remains enigmatic (Davila and Hunt, 2001; Ruiz et al., 2004),
with Margalef (1978) suggesting that favoured species (i.e. those with spines
or bubble capsules) and size of specimens depend on whether turbulence is low
or high, within a turbulent water column the overall population average may
suggest a trajectory of a downward descent, whereas the descent of an
individual shell may be much more complicated. Our results suggest that there
is a difference between chambers F and <F; on average the formation of
the final chamber occurs in water approximately 1 ∘C colder than the
chambers formed prior, suggesting both ontogenetic depth migration to deeper
waters and a potential offset from the surface signal.
Calculated δ18O probability (p(δ18O)). (a) Single-specimen isotope measurements for G. ruber, with a fitted normal distribution. (b) These data are used
to produce a cumulative distribution function plot (CDF), with statistical
output for an Anderson–Darling test, and a Kolmogorov–Smirnov test
following data normalization (failure to reject the null hypothesis at the
5 % confidence suggests the data are not statistically different from a
standard normal distribution, red line in plot). (c) In situ
δ18Oeq values predicted from a regional-specific equation
(LeGrande and Schmidt, 2006) and a rearranged form of (Kim and O'Neil, 1997)
with WOA13 temperature and salinity values as input values.
(d) Resultant calculated p(δ18O); the probability
of each discrete δ18O is denoted as p(δ18O)
mapped upon the δ18Oeq WOA13 values. The grey region
represents the area between 0 m and the first probable depth that may have
become overprinted during depth migration.
The statistical significance between either chambers F δ18O
and/or <Fδ18O, and the Δδ18O (Fig. 5c
and d) could indicate that the environment in which the early chambers (<F)
form determines the final chambers δ18O (Fig. 5c); the warmer
SST (more negative δ18O values) specimens have a larger
Δδ18O, which could indicate the specimen lived during
stratified water conditions (Fig. 1, scenario B). Likewise, the colder SST
(more positive δ18O values) specimens have a smaller
difference; therefore, these specimens could represent those that live under
mixed conditions (Fig. 1, scenario A). Specimens that show a warming between
F and <F chambers could theoretically have calcified during a period of
change, a transition from a stratified to a mixed (or vice versa) water
column.
Difference between F and <F: an underestimation?
The difference in the isotopic value between successive chambers may not
depend solely on depth migration during ontogeny but may be altered by
chamber thickening. Two types of chamber thickening are known to exist: a
calcite crust seen in Neogloboquanids and Globorotalids; and gametogenetic
calcite (GAM) seen in Orbulina universa and T. sacculifer.
Whilst both types are produced at the end of the life cycle and therefore
deeper in the water column, one is considered to represent low temperature
thickening of the shell, and the other a pre-reproduction thickening of the
shell. Thickening of the pre-existing chambers that compose a single shell in
response to a particular environmental parameter or at the end of the life
cycle may bias the resultant isotopic composition; depending on the water
column structure and depth of the mixed layer (Fig. 1, scenarios A and B),
the calcite produced in such a way may be indistinguishable isotopically from
older chambers. Whilst the size of this bias induced by GAM may have been
overestimated in the literature, for instance using cultures, Hamilton et al.
(2008) showed that approximately 80 % of the shell material is pre-GAM;
new evidence suggests that the Δδ18O between pre-GAM and
GAM is ∼1 ‰ (Wycech et al., 2018). The same work suggests that
GAM comprises 32 % to 44 % of T. sacculifer shells.
Determining how many of the <F and F chambers are altered by GAM is
complicated because GAM calcite precipitates on the outer “exposed”
edges/margin of the shell; the amount of GAM relates to the surface area.
Now, by removing the final chamber, a section of this surface area would not
have been exposed during GAM formation. Therefore, the size of the
over-printing is a product of both the amount of GAM calcite and the surface
area exposed. Our results should therefore be considered as the minimum
deviation between <F and F.
Calculated δ18O probability (p(δ18O)). As per Fig. 8, with individual isotope values, CDF distribution,
WOA13 δ18Oeq and resultant p(δ18O) but
with T. sacculifer.
Covariance with size
The trends in size–isotope values have been grouped into what Berger et
al. (1978) considered to be three types: “normal”
showing enrichment with increased size; “reversed” showing depletion with
increased size and “mixed” in which neither enrichment or depletion with
increasing size occurs. From our data there is no statistical difference in
the δ18O of the three different size classes, despite the
appearance of a “mixed” signal, meaning there is absence of evidence to
state that the δ18O of T. sacculifer is subjected to
a size effect. Evidence from our final chamber comparison shows that
individuals undergo depth migration. Berger et al. (1978) considered that
such a scenario should result in a “normal” size–isotope trend; however,
depth migration with size is not demonstrated in the δ18O of
the distinct size fractions. Berger et al. (1978) further considered that the
“mixed” trend poses a problem in the interpretation of δ18O
solely in terms of depth migration. However, a study of population dynamics
in the Red Sea indicate following reproduction at depth from the preceding
generation, juveniles ascend in the water column to mature, where after these
maturing foraminifera descend when reaching the reproductive size (Bijma and
Hemleben, 1994; Hemleben and Bijma, 1994). How small forms would migrate from
depth is unknown, although ascending particles due to low density do exist in
the marine environment (Azetsu-Scott and Passow, 2004; Mari, 2008; Mari et
al., 2007). This would lead the smallest shells to have calcite that was
formed in deeper, colder waters, medium-sized shells to consist of calcite
formed at the surface, in warmer waters and larger shells formed of calcite
from deeper, colder waters. One caveat to such a scenario is that (Brummer et
al., 1987, 1986) considered juvenile-neanic stages of the planktonic
foraminiferal life cycle to be less than 100–200 µm, distinctly
smaller than the shell sizes measured here. Peeters et al. (1999) have shown
that the size frequency distribution associated with the adult population of
numerous planktonic foraminiferal species is distinctly gaussian in shape and
thus variance around the mean should be considered as “dwarfs” and
“giants” (Berger, 1971), thus a mixed signal may reflect extra-seasonal
growth. A point of caution with size–isotope trends is that (Metcalfe et
al., 2015) previously showed that such trends can either be consistent down
core (e.g. G. truncatulinoides) or varying (e.g. G. bulloides and G. inflata) and therefore upscaling one relationship
either spatially and/or temporally may lead to erroneous results.
Calculated δ18O probability (p(δ18O)). As per Fig. 8, with individual isotope values, CDF distribution,
WOA13 δ18Oeq and resultant p(δ18O) but
with N. dutertrei.
Species-specific variability
The comparison between the δ18Oshell values of the three
species demonstrated that G. ruber (μ=-1.15 ‰) has a
different mean δ18O value and a different δ18O
distribution than either T. sacculifer (μ=-0.82 ‰) or
N. dutertrei (μ=-0.84 ‰). Solving the
palaeotemperature equations for each species using the mean
δ18O values gives an equivalent temperature of
24.1 ∘C for G. ruber, 22.6 ∘C for N. dutertrei and 22.5 ∘C for T. sacculifer. This suggests a
difference in depth habitat and/or season of growth between G. ruber
and the other two species further
highlighted by a comparison with the annual average and cumulative
distribution functions (CDFs) for specific depths (Fig. 7b and c).
Disentangling the signals of depth migration from seasonal habitat is
complicated given the commonality between isotope values from similar depths
and different seasons and vice versa. For instance, the same average isotope
value will have a shallower depth habitat in May than in September. To
illustrate this, at two specific depths (100 and 125 m; based on Fig. 6c),
the δ18Oshell of the foraminifera, corrected for the vital
effect, was compared to the δ18Oeq over the year for a
number of discrete depth levels in the water column, to find out at which
depth level(s) a given species could grow, assuming a uniform shell flux over
the year (Fig. 7a). For N. dutertrei and T. sacculifer
these potential depths and seasons of growth are similar, following from the
fact that their mean δ18Oshell and δ18Oshell variability is not significantly different. It was found that
T. sacculifer and N. dutertrei could potentially occur
year-round at ∼125 and at ∼100 m from respectively August to
December and February to June. G. ruber in its place reflects the
year-round temperature at 100 m of depths and autumn/winter temperatures
(August to December) at a depth of 125 m. Wit et al. (2010) stated that the
variability within single-shell δ18O measurements could be a
proxy for seasonality (Ganssen et al., 2011; Vetter et al., 2017), which was
inferred from measurements of single species (G. ruber) for multiple
core locations to test this inference. Here we tested whether different
species are influenced by seasonality in a similar or dissimilar way.
Our results imply that species can be used as indicators of year-round
seasonality, because the variability in single-shell δ18O
matches the variability in annual temperature derived from the climatological
average of WOA13, but only at species-specific depths (T. sacculifer
and N. dutertrei for 125 m, and G. ruber for 100 m). The
probability plots of the season–depth habitat, as indicated by Figs. 8–10,
show that the calcification depth recorded by the shell δ18O
is a narrow interval between 50 and 200 m. Despite evidence to the contrary,
δ18O does not implicitly record sea surface temperatures,
collection of foraminifera by SCUBA (Bird et al., 2018; Spero, 1998) and net
collection (Ottens, 1992; Kroon and Ganssen, 1989; Ganssen and Kroon, 1991)
at or in close proximity to the sea surface represents a part of, but not
their full, life cycle. This situation is further exacerbated by both a
shallow or deep mixed layer giving a potential homogeneous
δ18O signal from surface to deep (Fig. 1) and the unknown
quantity of the vital effect when attempting to derive depths from core top
material. It is worth reiterating, here, several conclusions of previous
studies (Wilke et al., 2006). Foraminiferal depth habitat is a continuous
variable from zygote fusion to eventual reproduction-induced mortality.
However, chambers represent a distinct event covering a short period of time
(∼12 h); the calcification depths of chambers therefore reflect
discrete intervals along this continuous depth habitat. As chamber size
increases progressively, in normal forms (Berger, 1969), from the earliest to
the final chamber the contribution of each chamber to the cumulative signal
increases iteratively and can be approximated by a mass balance (e.g. Wilke
et al., 2006). As the shell sinks through the water column, during its life,
the signal will become progressively skewed toward a deeper “colder”
signal. Modification of this signal via crust formation or GAM calcite will
bias the signal further toward higher δ18O and a colder
signal. The depth habitat of foraminifera is not static globally; instead,
its dynamism represents a complex interaction between food, temperature,
water column structure and, where appropriate, light. Discrepancies between
previously published work should not be considered in depth but on the
various attributes of the water column present, as it is those parameters
altering with depth that ultimately allow foraminiferal growth to occur.
Conclusions
To gain more insight into biological and ecological processes that influence
the δ18Oshell of planktonic foraminifera, three research
questions with associated hypotheses were tested. First, we tested depth
migration and found that a significant difference in δ18O
between the final chamber (δ18OF, μ=-1.23 ‰) and the test minus the final chamber is observed in
T. sacculifer. This difference in δ18Oshell is
equal to a temperature difference of 1 ∘C, suggestive that the final
chamber is formed via depth migration in waters that are approximately
1 ∘C cooler than the chambers formed prior. Second, we tested
covariance with size and found that despite evidence for depth migration
during the life and growth of T. sacculifer there is an absence for
a size effect on T. sacculifer with no statistical difference in the
δ18Oshell of the three different size classes. Third, we
tested species-specific δ18O variability to quantify the
effect upon the populations from proxy archives. Comparison between
T. sacculifer (μ=-0.82 ‰), G. ruberwhite (μ=-1.15 ‰) and N. dutertrei
(μ=-0.84 ‰) indicate that G. ruber has both a
significantly different mean and variability in δ18O,
suggestive that the species lives in warmer shallower waters (i.e. ∼90–120 m vs. ∼100–130 m). However, inferences about depth and/or
seasonal habitat is complicated by the fact that similar
δ18Oeq values occur in both time and depth. It is possible,
based upon our results that T. sacculifer and N. dutertrei
could potentially occur year-round at 125 m of depth and at 100 m of depth
from respectively January to August and February to June. G. ruber
in its place, reflects the year-round temperature at 100 m of depths, and
autumn/winter temperatures (August to December) at a depth of 125 m. These
results highlight the complicated nature of interpreting oxygen isotopes even
for the modern record in line with previous findings (Kretschmer et al.,
2018; Roche et al., 2018). Depth migration, size and species-specific
variability all influence the values of δ18O within a
foraminiferal shell and therefore the resultant palaeoclimate reconstructions
conclusions drawn from their isotope values.