The boron isotopic composition (δ11B) of benthic foraminifera provides a valuable
tool to reconstruct past deep-water pH. As the abundance of monospecific species might be limited
in sediments, microanalytical techniques can help to overcome this problem, but such studies on
benthic foraminiferal δ11B are sparse. In addition, microanalytics provide
information on the distribution of δ11B at high spatial resolution to increase
the knowledge of biomineralization processes, for example. For this study, we investigated the intra- and
inter-shell δ11B variability of the epibenthic species Cibicidoides wuellerstorfi, which is widely used in paleoceanography, by secondary ion mass spectrometry
(SIMS) and femtosecond laser ablation multicollector inductively coupled plasma mass spectrometry
(LA-MC-ICPMS). While the average δ11B values obtained from these different
techniques agree remarkably well with bulk solution values to within ±0.1 ‰, a
relatively large intra-shell variability was observed. Based on multiple measurements within
single shells, the SIMS and LA data suggest median variations of 4.8 ‰ and 1.3 ‰
(2σ), respectively, while the larger spread for SIMS is attributed to the smaller volume of
calcite being analyzed in each run. When analytical uncertainties and volume-dependent differences
in δ11B variations are taken into account for these methods, the intra-shell
variability is estimated to be on the order of ∼3 ‰ and ∼0.4‰
(2σ) on a ∼20 and 100 µm scale, respectively. In comparison, the
δ11B variability between shells exhibits a total range of ∼3 ‰ for
both techniques, suggesting that several shells need to be analyzed for accurate mean
δ11B values. Based on a simple resampling method, we conclude that ∼12
shells of C. wuellerstorfi must be analyzed using LA-MC-ICPMS to obtain an accurate
average value within ±0.5 ‰ (2σ) to resolve pH variations of ∼0.1. Based on our findings, we suggest preferring the conventional bulk solution MC-ICPMS over the
in situ methods for paleo-pH studies, for example. However, SIMS and LA provide powerful tools for
high-resolution paleoreconstructions, or for investigating ontogenetic trends in
δ11B.
Introduction
The boron isotopic composition (δ11B) of benthic foraminifera has been used to
reconstruct deep-water pH (Hönisch et al., 2008; Rae et al., 2011; Raitzsch et al., 2020; Yu et
al., 2010) and to estimate the Cenozoic evolution of seawater δ11B (Raitzsch and
Hönisch, 2013). The underlying mechanism behind the boron isotope method lies in the constant
equilibrium fractionation of 27.2‰±0.6‰ between the pH-dependent speciation of trigonal
boric acid and the tetrahedral borate in seawater (Klochko et al., 2006), where only the borate ion
is incorporated into the foraminifera test (Branson et al., 2015; Hemming and Hanson, 1992).
However, while the number of studies on planktonic foraminiferal δ11B to estimate
surface-ocean pH has rapidly increased within the last decade, deep-sea pH reconstructions based on
benthic foraminifera are relatively rare (Hönisch et al., 2008; Rae et al., 2011; Raitzsch et
al., 2020; Yu et al., 2010). Possible reasons for this might be the lower abundance of benthic
foraminifera, compared to planktonic species, and a limited selection of species that truly record
bottom-water rather than pore-water conditions (Rae et al., 2011). Fortunately, there are two
suitable candidates, Cibicidoides wuellerstorfi and Cibicidoides mundulus, that
cover a relatively large oceanographic and stratigraphic range, and which have a high boron content
of ∼12–27 ppm (Raitzsch et al., 2011; Yu and Elderfield, 2007). Although their high
[B] may partly compensate for the low abundance in the sediments, in many cases the availability of
enough specimens for δ11B analysis remains limiting.
Here, microanalytical techniques such as laser ablation multicollector inductively coupled plasma
mass spectrometry (LA-MC-ICPMS) and secondary ion mass spectrometry (SIMS) can help to overcome the
problem of sample limitation. These techniques have already been successfully used for a variety of
biogenic carbonates to gain information on biomineralization processes or seasonal pH variations
(e.g., Blamart et al., 2007; Fietzke et al., 2015; Howes et al., 2017; Kaczmarek et al., 2015a; Mayk
et al., 2020; Rollion-Bard and Erez, 2010; Sadekov et al., 2019). However, microanalytical analysis
of δ11B is usually afflicted with larger uncertainties in terms of repeatability
and reproducibility, as well as of natural δ11B heterogeneity within single shells
and within a population. In addition, some recent studies using LA-MC-ICPMS suggest correction modes
for measured δ11B values because detected interferences on the 10B peak,
possibly due to scattered Ca ions from the carbonate sample, can result in large offsets from the
expected value (Thil et al., 2016; Sadekov et al., 2019; Standish et al., 2019), whereas in other
studies this matrix-induced effect was not observed (Fietzke et al., 2010; Kaczmarek et al., 2015b;
Mayk et al., 2020).
Also, the reported analytical reproducibility for δ11B in biogenic carbonate using
LA-MC-ICPMS differs considerably among different studies, ranging between ±0.22‰ and
1.60 ‰ (2σ=2 standard deviations), determined from repeated measurements of either a carbonate or
glass standard (Fietzke et al., 2010; Kaczmarek et al., 2015b; Mayk et al., 2020; Sadekov et al.,
2019; Standish et al., 2019; Thil et al., 2016). As there is no standardized protocol nor a
commercially available homogenized δ11B carbonate standard for determining the
analytical uncertainty of LA-MC-ICPMS, this issue remains the most challenging task to compare the
different labs and instruments. The most commonly used carbonate standards with well-constrained
boron isotopic compositions are samples from a coral (JCp-1) and a giant clam (JCt-1), provided by
the Geological Survey of Japan (e.g., Inoue et al., 2004; Okai et al., 2004). However, for
microanalytical analysis the standard is usually powdered in a mortar and finally pressed to a
pellet, which is produced individually in each laboratory, thus potentially resulting in different
heterogeneities (e.g., through different grain sizes or applied pressures) in each pellet. This
issue is also true for SIMS analyses, and the reported reproducibility is strongly linked to the
in-house reference material used (e.g., Kaseman et al., 2009; Rollion-Bard and Blamart, 2014).
In this study, we investigate a population of 23 specimens of C. wuellerstorfi, which is a
widely used benthic foraminifer species in paleoceanographic studies, to extend our knowledge of
δ11B variability within and between individuals. The aim of our study is to
demonstrate the capabilities and limitations of δ11B analyses in
C. wuellerstorfi on a microscale. For this purpose, we used the femtosecond LA-MC-ICPMS and
SIMS techniques and compared the results with bulk-solution MC-ICPMS. Finally, we examine the size
of population required for targeted δ11B uncertainty levels in paleoceanographic
studies using LA-MC-ICPMS.
Material and methodsForaminifer samples
For this study, we used sediment samples from GeoB core 1032-3, taken in the Angola Basin on the
Walvis Ridge at a water depth of 2505 m. From a Holocene interval (6–8 cm,
5.6 ka), 23 pristine (glassy) shells of the benthic foraminifer species
C. wuellerstorfi from the size fraction >350µm were picked and prepared for
subsequent microanalytical analysis. Five large specimens (>400µm) were embedded in
epoxy and polished down to a planar surface for SIMS analyses, while the remaining 18 specimens were
mounted on carbon tape for LA measurements. From these 18 individuals, two large tests were analyzed
for detailed chamber-to-chamber variability, while the remaining 16 tests were used to measure
quasi-bulk δ11B by ablating large shell areas, preceded by measurements of the
smaller umbilical knob area.
Secondary ion mass spectrometry
For the ion microprobe analyses, we used the same technique as described in Rollion-Bard et
al. (2003) and Blamart et al. (2007). Boron isotopic compositions were measured with the Cameca ims
1270 ion microprobe at CRPG-CNRS, Nancy, France. A primary beam of 16O- ions generated
using a radio frequency plasma source (Malherbe et al., 2016) with an intensity of 50 nA was
focused to a spot of about 20 µm. A mass resolution of 3000 was used for B isotope
analyses, allowing the elimination of all isobaric interferences. Boron isotopes were analyzed in
mono-collection mode using the central electron multiplier. The dead time of the electron multiplier
was determined before the analytical session and set to 65 ns. A pre-sputtering of
120 s was applied before the analysis itself. The typical intensities of 11B+
in foraminifer tests were between 2000 and 4500 counts per second (cps), depending on the boron
concentration. The analysis consists of 60 cycles of 10 s for 10B+ and
6 s for 11B+, respectively. The reference material was a calcium carbonate with
a B concentration of 22 ppm and a δ11B of 16.76‰±0.11 ‰,
relative to the standard reference material (SRM) NIST 951 (WP22, value determined at IPGP using the
method of Louvat et al., 2014). The reproducibility, as estimated by multiple measurements of the
reference material, was 2.48 ‰ (2σ, n=8) and is very close to the predicted
2σ uncertainty derived from counting statistics.
Femtosecond laser ablation MC-ICPMS
Boron isotope measurements were performed using a customized UV-femtosecond laser ablation system
coupled to a Plasma II MC-ICPMS (Nu Instruments) at the AWI, Bremerhaven. The laser ablation system
is based on a Ti:sapphire regenerative amplifier system (Solstice, Spectra-Physics, USA) operating
at the fundamental wavelength of 775 nm with a pulse width of 100 fs and pulse
energy of 3.5 mJ per pulse. Consecutive frequency conversion results in an output beam
with a wavelength in the UV spectra (193 nm) and a pulse energy of 0.08 mJ. The
short femtosecond pulses were shown to have major advantages over nanosecond pulses for a wide range
of element and isotope ratios with respect to laser-induced and particle-size-related fractionation,
thus enabling non-matrix-matched calibrations (e.g., Horn and von Blanckenburg, 2007; Steinhoefel et
al., 2009).
The sample and standard materials were mounted in an ablation chamber with an active volume of
ca. 45 cm3 and ablated in a helix-mode scan at a speed of 2 mms-1 by using a
laser spot size of ∼40µm. This technique allows ablation craters of
almost any diameter to be produced, in this study ranging from ∼80µm for analysis of
single chambers to ∼400µm to cover whole shells. The aerosol was transported via a
He gas flow (∼0.5Lmin-1) and admixed with Ar gas
(∼0.5Lmin-1) before entering the MC-ICP-MS. Torch position, ion optics and gas
flows were optimized to gain maximum signal intensity and stability on 10B and
11B peaks. The mass spectrometer was equipped with standard Ni sample and skimmer cones
for dry plasma conditions. The radio frequency power was set to 1300 W. Boron isotopes were
determined on Daly detectors, where high-mass D5 was used for 11B and D0 for
10B. Each measured sample 11B/10B was normalized to
11B/10B measurements of the glass standard NIST SRM 610
(δ11B=0‰ NBS 951), using the standard-sample-bracketing technique. The
analyses were performed at low mass resolution (M/ΔM∼2000, 5 ‰), which was
sufficient to resolve all interferences.
We performed mass scans on the peaks of 10B and 11B for both gas blanks (laser
off) and measurements on carbonate (laser on) (Fig. 1) to investigate possible effects by scattered
ions of matrix elements as observed in some recent studies (Sadekov et al., 2019; Standish et al.,
2019). For our set-up, we can exclude such matrix-induced effects, which is in line with Fietzke et
al. (2010) and Mayk et al. (2020). Hence, there was no need to correct the raw LA data as done in
the recent studies by Sadekov et al. (2019) and Standish et al. (2019). Before analysis, sample and
standard materials were pre-ablated to remove potential surface contamination. Laser repetition
rates ranged between 12 and 60 Hz to match the signal intensity between carbonate samples
and standard material NIST SRM 610 (∼300000cps on 11B). As ablation
efficiency and hence signal intensity may vary with progressively increasing surface roughness and
crater depth, we adjusted the repetition rate, if required, to target intensity matching between
sample and standard. Whereas this approach could result in bulgy time-resolved isotope signals, as
shown in Fig. 2, clean calcium carbonate was identified from a plateau-like
11B/10B signal. Conversely, any contaminated phase from partial ablation of clay
infillings, indicated by dropping 11B/10B ratios accompanied by rising [B], were
excluded from further data treatment (Fig. 2).
Mass scans over atomic masses 10 (blue) and 11 (red) using Daly detectors, where peak
center coincidence appears at ∼10.25amu in the center cup. (a) Gas blank
(laser off), showing the typical double peak of 40Ar4+ and 10B, and the
11B peak. (b) Signal of ablated calcium carbonate (laser on). The baseline
exhibits only electronic noise from the Daly detectors, but no sign of unresolved interferences on
10B as matrix-induced scattered Ca ion. Note that the signal intensity is on a
logarithmic scale.
(a) Example of time-resolved laser ablation analysis for 10B and
11B of a C. wuellerstorfi shell using Daly detectors, preceded by a
∼60s blank measurement. Dots represent 1 s cycles, and lines 5-point running averages. Open symbols are data that are excluded by the 2σ outlier
test. (b) Example of a shell that was penetrated by the laser beam, resulting in the
ablation of clay infillings.
Each analysis was preceded by an on-peak gas blank measurement of 60 s on 10B and
11B, which was subtracted from the LA signal. The LA analysis itself was assessed by
calculating the mean of the blank-corrected 11B/10B signal within an interval
of up to 370 cycles (1 s each), where all data exceeding two standard deviations were
removed as outliers. After analysis, B was washed out for 120 to 180 s until reaching
background levels before a new measurement was started. A typical blank had ∼7000cps
on 11B at the beginning of a session but decreased to less than 3000 cps during
the course of a day. As signal intensity on 11B was aimed at ∼ 300 000 cps,
the signal-to-noise ratio was on the order of ∼100.
Accuracy of boron isotope measurements was frequently checked by ablating an in-house carbonate
standard that was also used for SIMS analysis (i.e. WP22, Rollion-Bard et al., 2003). The average
δ11B of 16.49‰±1.26 ‰ (2σ, n=20) for WP22 is very close to the
bulk solution values (δ11B=16.60‰±0.30‰ (2σ, n=6) measured at
AWI, and δ11B=16.76‰±0.11‰ measured at IPGP). As the measurement
uncertainty is mainly dependent on the ablation time, we report measurement uncertainties (as
2σ) for each δ11B analysis as a function of analysis time, which was
determined from multiple measurements of NIST glass standards and carbonate standards, and which is
very close to the predicted uncertainty based on counting statistics (Fig. 3).
Measurement uncertainty of 11B/10B (2σ) at count rates of
300 000 cps (11B) as a function of the laser ablation time. The uncertainty of
each boron isotope measurement is calculated based on this relationship (black solid line). A
major portion (∼70%) of the measurement uncertainty is related to Poisson-distributed
counts (red dashed line).
Bulk solution MC-ICPMS
After LA analyses, the 18 shells were carefully removed from the carbon tape and cleaned following
the procedure outlined by Raitzsch et al. (2018). Briefly, foraminifer shells were gently crushed
under a binocular between two glass slides and transferred to Eppendorf vials. After the clay
removal and oxidative cleaning steps, the samples were leached in 0.001 NHNO3
and finally dissolved in 60 µL of 1 NHNO3.
Prior to boron isotope analysis, we used the micro-distillation technique to separate B from the
calcium carbonate matrix (Gaillardet et al., 2001; Misra et al., 2014; Raitzsch et al., 2018; Wang
et al., 2010). The distillate was diluted with 400 µL of 0.3 NHNO3. The B concentration of a small aliquot was determined using a quick (20 s)
on-peak measurement of 11B on Faraday cup H9 using a Nu Plasma II MC-ICPMS (AWI,
Bremerhaven). The remainder of the sample was then diluted to yield a solution with a [B] of
3 ppb and concentration-matched with the SRM NBS 951 to within ±3%.
For isotope ratio measurements, boron was collected on Daly detectors, where high-mass D5 was used
for 11B and D0 for 10B. Boron isotope data were measured in triplicate using the
standard-sample-bracketing technique and reported in delta notation normalized to SRM NBS 951:
δ11Bsample=11B/10Bsample11B/10BNIST951-1⋅1000.
When 2σ of the mean derived from the triplicate was smaller than the long-term
reproducibility (0.30 ‰), we report the latter as the measurement uncertainty. In addition,
a small fragment of an in-house carbonate reference material WP22, used for our SIMS and LA-MC-ICPMS
study, was cleaned and measured exactly the same way as the foraminifera sample to obtain a bulk
δ11B value for comparison (16.60‰±0.30‰). This value is almost
identical to that measured at IPGP using the bulk solution ICP-MS (16.76‰±0.11‰).
Results and discussionIntra-shell δ11B variability
The results from SIMS measurements conducted on five large specimens reveal a high
δ11B variability ranging between 4.6 and 6.8 (mean 5.2) ‰ (2σ, 2 standard deviation
of n individual measurements) within single shells, based on 8 to 19 single-spot analyses on each
shell. A similar variability of 4.4 ‰ (2σ) on average is observed for measurements
within single chambers (Fig. 4). Since it is difficult to distinguish between the very small
(i.e. the juvenile) chambers in the central part, we allocated these measurements to the umbilical
“knob”, which is also equivalent to the thick central part of the spiral side used for LA
measurements. If δ11B is averaged for each chamber (one to three analyses per chamber),
the mean variability between chambers is 4.2 ‰ (2σ) (Fig. 4). The two specimens
measured chamber by chamber with LA also show variable δ11B, but with a much lower
variation of ∼1.1‰ (2σ), compared to the SIMS data (Fig. 4). The average
δ11B variability from all 16 shells measured multiple times is
∼1.3‰ (2σ).
Intra-shell variability of δ11B using SIMS (a) and LA-MC-ICPMS
(b) on selected large individuals of C. wuellerstorfi. The residual
Δδ11B (difference between single-spot and mean δ11B,
Eq. 2) averaged from all analyzed specimens is shown for each chamber (f is the final chamber,
f-1 the penultimate one, and so on). Orange color stands for higher-than-mean and blue for
lower-than-mean values. Lighter colors indicate data that are based on only one measurement. The
inset table summarizes the measured intra-shell variability derived from the two techniques.
Here the question arises of whether the difference in δ11B variability between the two
methods is due to differences in analytical uncertainty or different scales of natural
heterogeneity. If we consider an average uncertainty of ±0.9‰ for LA (Fig. 3),
intra-shell variability is reduced from 1.3 ‰ to 0.4 ‰. As the 2σ
measurement uncertainty for SIMS is roughly ±2.5‰, the remaining difference in
variability between SIMS and LA methods of ∼2.3‰ is likely due to the different
sampling volumes and hence related to heterogeneous boron isotopic distribution in the test. While
the spot size for the SIMS method is ∼20 and ∼1µm at depth, the
laser-ablated volume ranges from 80 to 100 µm in diameter (Fig. 4) and approximately
10 µm at depth. Consequently, the ∼200 times larger volume analyzed by LA would
reduce the δ11B variability detected by SIMS to
∼0.2(=2.3/√200)‰. Hence we argue that the “true” δ11B
heterogeneity is scale-dependent and assumedly on the order of ∼3 and ∼0.4‰
(2σ) on a ∼20 and 100 µm grid, respectively.
To examine potential systematic trends in δ11B among successive chambers, we
calculated the residual boron isotopic composition Δδ11B for each site within
each shell by comparing the B isotopic composition of a single-chamber
δ11Bsingle with the mean value of the shell
δ11Bmean:
Δδ11B=δ11Bsingle-δ11Bmean.
The SIMS data suggest that Δδ11B tends to decrease from the penultimate
chamber (f-1) towards chamber f-5 by roughly 4 ‰ (Fig. 4), whereas no systematic change
exists between chambers f-6 and the juvenile chambers. However, it is compelling that also the LA
results suggest a decreasing trend in Δδ11B from the final chambers towards
chamber f-5 by more than 0.5 ‰, while in the earlier chambers no systematic change can be
observed (Fig. 4). For both methods, Wilcoxon–Mann–Whitney tests and Welch's t tests suggest that
the Δδ11B change between the final chambers and f-5 is statistically
insignificant at a 95 % significance level (p values ≥ 0.07). However, decreasing
δ11B from the final chamber towards earlier chambers would be in line with the LA
study by Sadekov et al. (2019) showing a ∼2 ‰ decrease along the last whorl of
C. wuellerstorfi. A similar pattern was also observed for B/Ca, with the
highest value in the final chamber (Raitzsch et al., 2011; Sadekov et al., 2019), suggesting a
strong biological influence or kinetic (i.e. growth rate) effect on boron incorporation. An in-depth
discussion of biological and calcification processes is beyond the scope of this study, but the
discovery of such high variability has implications for the use of
δ11B-microanalytical techniques in paleoceanographic studies (e.g., Rollion-Bard
and Erez, 2010).
Another notable feature derived from LA and SIMS is the elevated δ11B (by
∼0.5‰ on average) of the umbilical knob, compared to the whole-shell
δ11B. This is confirmed by supplementary ablation of the knob of individuals, which
were used for whole-shell analysis in Sect. 3.2. On average, umbilical knob δ11B
was ∼0.4‰ higher than the value derived from the larger ablated area (see inset
picture in Fig. 7), although this behavior is not systematic and was observed in only two thirds of
the cases.
Inter-shell δ11B variability
Apart from the seven specimens used for inspecting the chamber-to-chamber variability, 16
individuals of C. wuellerstorfi were laser-ablated using a large area of at least
300 µm in diameter to cover a major part of the spiral side, and in 14 specimens
subsequently analyzed for the composition of the thicker umbilical knob using a smaller crater
(inset picture in Fig. 7). This way, we approached quasi-bulk δ11B values for
single shells. Together with the δ11B medians from the two specimens described in
the previous section, a total of 18 shells were used for determining the inter-shell
δ11B variability using LA-MC-ICPMS (Fig. 5). It should be noted that we usually
report the average as median, since it is less sensitive to outliers than the mean and also
reflects the average of a non-uniform distribution. For SIMS analyses, the medians of single-spot
analyses were calculated for each of the five shells.
Violin, box and jitter plots showing the distribution of all single-site
δ11B values and single-shell means, both for the SIMS and laser ablation
techniques. For comparison, the distribution of δ11B values measured on the
in-house reference material WP22 is displayed as well. The green dashed lines and bars represent
the bulk solution δ11B±2σ values.
The SIMS data reveal a huge spread of single-spot δ11B across the five specimens
(Sect. 3.1), but the δ11B values averaged for each shell exhibit a narrower range
between tests, with a median δ11B of 16.08‰±2.70‰ (2σ)
(Fig. 5). In contrast, the single-site LA data across all 18 individuals show a smaller variation
in δ11B than the SIMS data, where the values averaged for each shell yield a median
of 15.90‰±1.62‰ (2σ). Both the average δ11B measurement
uncertainty for LA of ±0.9 ‰ (2σ) and the variation difference between
foraminiferal shells and WP22 of ∼0.4‰ suggest a residual inter-shell variability on the order of 0.4 ‰ to 0.7 ‰. Similarly, if an uncertainty of ±2.50 ‰
(2σ) for SIMS measurements is taken into account, the remaining inter-shell variability is
only ∼0.2‰. Therefore, we estimate the “true” variability between shells of a
population to be ∼0.4‰, which is the same as the variation estimated for the
intra-shell variability (Sect. 3.1).
For shells where both large areas and knobs were measured (n=14), it is interesting to note that
if only the large LA craters are considered, the mean δ11B is
15.87‰±1.78‰ (2σ), while it is 16.27‰±2.75‰ (2σ), if solely
the small LA craters are taken into account (see Fig. 7, inset picture). As the volume of the large
LA craters is ∼3 times larger than the smaller ones, the resulting variability among means of
three resampled small-crater values is 1.59(=2.75/√3)‰ (2σ), which is quite
close to the 1.78 ‰ derived from large craters, and confirms our conclusion that the
δ11B variability is dependent on the scale at which it is measured.
Bulk solution δ11B
Both the SIMS and LA results reveal median values that match the bulk δ11B of
15.99‰±0.30‰ (2σ) measured in solution to within analytical uncertainties
(Fig. 5). It should be noted again that the same specimens measured in solution had been measured
before by LA, ensuring that we compare different techniques based on the same set of
samples. Similarly, the average δ11B of 16.48‰±1.26‰ (2σ) in
the reference material WP22 determined with LA-MC-ICPMS is not distinguishable from the bulk
solution value of 16.60‰±0.30‰ (2σ), which confirms the robustness of the LA
technique, and also the SIMS results, as the median foraminifera values are identical for LA and
SIMS techniques.
The δ11B values obtained from all three methods fit in with the calibration data
set for C. wuellerstorfi from the study by Rae et al. (2011) (Fig. 6) and confirm that the
boron isotopic composition in this species closely matches that of borate of ambient
seawater. Further, it proves that LA-MC-ICPMS and SIMS yield accurate results for
δ11B, if the data set is large enough to overcome the issues of intra- and
inter-shell variability (∼0.4‰), and analytical uncertainty of micro-analytical
techniques (∼±0.9 ‰ and ±2.5 ‰ for LA and SIMS, respectively).
Median δ11B of Holocene (5.6 ka) C. wuellerstorfi from
GeoB core 1032 (Walvis Ridge, South Atlantic) measured with different techniques, shown along with
the core-top calibration from (Rae et al., 2011). Note that the bulk solution analysis of this
study was carried out on the same population measured before with laser ablation. Pooled
δ11B uncertainties for SIMS (n=5 shells) and LA-MC-ICPMS (n=18 shells) are
shown as numbers, as error bars exceed the y axis scale.
Implications for paleoreconstruction studies
The large intra- and inter-shell variations in δ11B described in Sects. 3.1 and 3.2
raise the question whether microanalytical techniques such as SIMS or LA-MC-ICPMS can be used for
analyzing δ11B in C. wuellerstorfi to reconstruct past deep-water pH. The
SIMS method requires careful embedding of foraminifer shells in epoxy and polishing down to a planar
surface, which precludes further processing for bulk solution analyses, for example. However, because the
size of the beam spot is small (20 µm or less), it is still possible to measure some
other elemental and isotopic ratios at the same location on the sample; e.g., the same foraminifera
specimens were used to measure δ18O (Rollion-Bard et al.,
2008), δ11B
(Rollion-Bard and Erez, 2010) and δ7Li (Vigier et al., 2015). The SIMS technique is
very useful for biomineralization studies (e.g., Rollion-Bard and Erez, 2010), but for
paleoreconstruction of deep-sea pH, where high precision is necessary, it may not be the most
appropriate technique for routine downcore δ11B analysis. However, here we will
inspect LA-MC-ICPMS as a potential tool for paleo-pH studies.
To attain information on the number of shells required for accurate LA analysis of
δ11B to within a target uncertainty, we applied a Monte Carlo approach to generate
two data sets with 10 000 δ11B data each, within a quoted uncertainty of
±1.68 ‰ and ±2.75 ‰ (2σ) for “large crater” and “knob”
measurements, respectively, as given by the original data set (n=16 and n=14, resp.). The
average δ11B values are considered identical between large craters and umbilical
knobs, as in the original data they agree to within analytical uncertainty. Then we applied the
“combn()” function of the R package “utils v3.4.4” (R Core Team, 2018) on each of the
simulated data sets. With this function, we can calculate the uncertainty by generating all possible
combinations of n shells taken from the simulated populations. For instance, if we would randomly
pick five shells from this sediment sample, the analyzed δ11B would be accurate to
within ±0.75 ‰ with a probability of 95 %, if large areas, and
±1.22 ‰, if only the knob areas were analyzed. If we targeted a standard uncertainty of
±0.50 ‰, which is equivalent to a pH uncertainty of roughly ±0.1, we would need to
measure ∼12 specimens with LA, if large areas, and ∼14 specimens, if only the knob areas
were analyzed (Fig. 7). The relationship between number of analyzed shells (n) and the estimated
2σ uncertainty is given by the quoted variability uq, i.e. the measured
δ11B variation across a population (as 2σ), and n:
2σ=uqn.
Given that the analysis uncertainty of the same amount measured in solution is about
±0.3 ‰, bulk solution analysis appears to be the more convenient technique for
reconstructing paleo-pH. In contrast, the LA technique may be useful for generating high-resolution
records, where sharp pH trends would partly compensate for the larger standard uncertainty or when
only a few foraminifera specimens are available. Further, LA, like SIMS, has the potential to provide
insight into ontogenetic δ11B variations, helping to better understand the
biological uptake of boron during chamber formation.
Results from Monte Carlo simulations of 2σ uncertainty for δ11B
using LA-MC-ICPMS in relation to the number of analyzed C. wuellerstorfi shells (n). In
red is the estimated uncertainty based on “large crater”, and in blue on “umbilical knob”
measurements (see inset scanning electron microscope picture for different areas). The estimated 2σ uncertainty can
be described by a function of the quoted uncertainty (uq) and n (Eq. 3).
Conclusions
Microanalytical methods such as SIMS or LA-MC-ICPMS are potentially powerful tools for studying
biomineralization processes or possible alternatives to conventional bulk solution analysis of
δ11B in benthic foraminifera, if sample material is limited. For this study, we
measured a population of 23 C. wuellerstorfi in total using SIMS and femtosecond
LA-MC-ICPMS and compared the results with the bulk-solution δ11B, revealing
consistent average values among the different techniques. While the medians agree to within
±0.1 ‰, a large intra-shell variability was observed, with up to 6.8 ‰ and
4.5 ‰ (2σ) derived from the SIMS and LA methods, respectively. We propose that the
larger spread for SIMS, compared to LA, can be attributed to the much smaller volume
(∼200-1) of calcite being analyzed in each run and hence supposedly reflects a larger
heterogeneity of δ11B in the foraminiferal test on a smaller scale. When analytical
uncertainties and scale-dependent differences in δ11B variations are taken into
account, the intra-shell variability is likely on the order of ±0.4‰ and 3 ‰
(2σ) on a 100 and 20 µm scale, respectively.
The δ11B variability between shells exhibits total ranges of ∼3 ‰
for both techniques, suggesting that a number of shells needs to be analyzed for accurate mean
δ11B values. We applied a simple resampling method and conclude that about 12
shells of C. wuellerstorfi must be analyzed using LA-MC-ICPMS to obtain an accurate average
value to within ±0.5 ‰ (2σ). Hence, we suggest that, based on this high number
of required individuals, the bulk solution MC-ICPMS method remains the first choice for analysis of
δ11B in routine paleo-pH studies.
Data availability
The boron isotope data collected for this study are available from Table S1
in the Supplement.
The supplement related to this article is available online at: https://doi.org/10.5194/bg-17-5365-2020-supplement.
Author contributions
MR, CRB, IH, and JB conceived the study. MR, CRB, and PL
carried out measurements, analyzed the data, and performed data statistics. AB, KUR, and GS maintained
and provided access to analytical instruments at AWI. JB, CRB,
and IH raised funding for the French-German project “B2SeaCarb”. MR produced the figures for the paper. MR
and CRB wrote the first draft of the paper,
and all authors interpreted, edited, and reviewed the paper.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This research was carried out in the framework of the joint French/German
project “B2SeaCarb” and was supported by the Deutsche Forschungsgemeinschaft
(DFG) grant number BI 432/10-1 to Jelle Bijma and DFG grant number HO 3257/5-1 to Ingo Horn.
On the French side, the project was supported by the French National
Research Agency (ANR) grant number ANR-16-CE92-0010 to Claire Rollion-Bard. Claire Rollion-Bard thanks Nordine Bouden (CRPG) for his technical help, and the MARUM GeoB core repository is
acknowledged for providing sediment samples. Kaoru Kubota as well as the
referees Dennis Mayk and Lubos Polerecky are thanked for their help in improving the paper.
Financial support
This research has been supported by the Deutsche Forschungsgemeinschaft (grant nos. BI 432/10-1 and HO 3257/5-1) and the Agence Nationale de la Recherche (grant no. ANR-16-CE92-0010).The article processing charges for this open-access publication were covered by the University of Bremen.
Review statement
This paper was edited by Jack Middelburg and reviewed by Dennis Mayk and Lubos Polerecky.
ReferencesBlamart, D., Rollion-Bard, C., Meibom, A., Cuif, J.-P., Juillet-Leclerc, A., and
Dauphin, Y.: Correlation of boron isotopic composition with ultrastructure in the deep-sea coral
Lophelia pertusa: Implications for biomineralization and paleo-pH,
Geochem. Geophy. Geosy., 8, Q12001, 10.1029/2007GC001686, 2007.Branson, O., Kaczmarek, K., Redfern, S. A. T., Misra, S., Langer, G., Tyliszczak, T.,
Bijma, J., and Elderfield, H.: The coordination and distribution of B in foraminiferal calcite,
Earth Planet. Sc. Lett., 416, 67–72, 10.1016/j.epsl.2015.02.006, 2015.Fietzke, J., Heinemann, A., Taubner, I., Böhm, F., Erez, J., and Eisenhauer, A.:
Boron isotope ratio determination in carbonates via LA-MC-ICP-MS using soda-lime glass standards
as reference material, J. Anal. At. Spectrom., 25, 1953, 10.1039/c0ja00036a, 2010.Fietzke, J., Ragazzola, F., Halfar, J., Dietze, H., Foster, L. C., Hansteen, T. H.,
Eisenhauer, A., and Steneck, R. S.: Century-scale trends and seasonality in pH and temperature for
shallow zones of the Bering Sea, P. Natl. Acad. Sci. USA, 112, 2960–2965,
10.1073/pnas.1419216112, 2015.Gaillardet, J., Lemarchand, D., Göpel, C., and Manhès, G.: Evaporation and
Sublimation of Boric Acid: Application for Boron Purification from Organic Rich Solutions,
Geostand. Newsl., 25, 67–75, 10.1111/j.1751-908X.2001.tb00788.x, 2001.Hemming, N. G. and Hanson, G. N.: Boron isotopic composition and concentration in modern
marine carbonates, Geochim. Cosmochim. Ac., 56, 537–543, 10.1016/0016-7037(92)90151-8,
1992.Hönisch, B., Bickert, T., and Hemming, N. G.: Modern and Pleistocene boron isotope
composition of the benthic foraminifer Cibicidoides wuellerstorfi, Earth
Planet. Sci. Lett., 272, 309–318, 10.1016/j.epsl.2008.04.047, 2008.Horn, I. and von Blanckenburg, F.: Investigation on elemental and isotopic fractionation
during 196 nm femtosecond laser ablation multiple collector inductively coupled plasma
mass spectrometry, Spectrochim. Acta B-At. Spectrosc., 62, 410–422,
10.1016/j.sab.2007.03.034, 2007.Howes, E. L., Kaczmarek, K., Raitzsch, M., Mewes, A., Bijma, N., Horn, I., Misra, S.,
Gattuso, J.-P., and Bijma, J.: Decoupled carbonate chemistry controls on the incorporation of
boron into Orbulina universa, Biogeosciences, 14, 415–430, 10.5194/bg-14-415-2017,
2017. Inoue, M., Nohara, M., Okai, T., Suzuki, A., and Kawahata, H.: Concentrations of Trace
Elements in Carbonate Reference Materials Coral JCp-1 and Giant Clam JCt-1 by Inductively
Plasma-Mass Spectrometry, Geostand. Geoanal. Res., 28, 411–416, 2004.Kaczmarek, K., Horn, I., Nehrke, G., and Bijma, J.: Simultaneous determination of
δ11B and B / Ca ratio in marine biogenic carbonates at nanogram level, Chem. Geol.,
392, 32–42, 10.1016/j.chemgeo.2014.11.011, 2015a.Kaczmarek, K., Langer, G., Nehrke, G., Horn, I., Misra, S., Janse, M., and Bijma, J.:
Boron incorporation in the foraminifer Amphistegina lessonii under a decoupled carbonate
chemistry, Biogeosciences, 12, 1753–1763, 10.5194/bg-12-1753-2015, 2015b.Kasemann, S. A., Schmidt, D. N., Bijma, J., and Foster, G. L.: In situ boron isotope
analysis in marine carbonates and its application for foraminifera and palaeo-pH, Chem. Geol.,
260, 138–147, 10.1016/j.chemgeo.2008.12.015, 2009.Klochko, K., Kaufman, A. J., Yao, W., Byrne, R. H., and Tossell, J. A.: Experimental
measurement of boron isotope fractionation in seawater, Earth Planet. Sci. Lett., 248, 276–285,
10.1016/j.epsl.2006.05.034, 2006.Louvat, P., Moureau, J., Paris, G., Bouchez, J., Noireaux, J., and Gaillardet, J.: A
fully automated direct injection nebulizer (d-DIHEN) for MC-ICP-MS isotope analysis: application
to boron isotope ratio measurements, J. Anal. At. Spectrom., 29, 1698–1707,
10.1039/C4JA00098F, 2014.Malherbe, J., Penen, F., Isaure, M.-P., Frank, J., Hause, G., Dobritzsch, D., Gontier,
E., Horréard, F., Hillion, F., and Schaumlöffel, D.: A New Radio Frequency Plasma Oxygen
Primary Ion Source on Nano Secondary Ion Mass Spectrometry for Improved Lateral Resolution and
Detection of Electropositive Elements at Single Cell Level, Anal. Chem., 88, 7130–7136,
10.1021/acs.analchem.6b01153, 2016.Mayk, D., Fietzke, J., Anagnostou, E., and Paytan, A.: LA-MC-ICP-MS study of boron
isotopes in individual planktonic foraminifera: A novel approach to obtain seasonal variability
patterns, Chem. Geol., 531, 119351, 10.1016/j.chemgeo.2019.119351, 2020.Misra, S., Owen, R., Kerr, J., Greaves, M., and Elderfield, H.: Determination of
δ11B by HR-ICP-MS from mass limited samples: Application to natural carbonates
and water samples, Geochim. Cosmochim. Ac., 140, 531–552, 10.1016/j.gca.2014.05.047, 2014. Okai, T., Suzuki, A., Terashima, S., Inoue, M., Nohara, M., Kawahata, H., and Imai, N.:
Collaborative Analysis of GSJ/AIST Geochemical Reference Materials JCp-1 (Coral) and JCt-1 (Giant
Clam), Chikyu Kagaku, 38, 281–286, 2004.Rae, J. W. B., Foster, G. L., Schmidt, D. N., and Elliott, T.: Boron isotopes and B / Ca
in benthic foraminifera: Proxies for the deep ocean carbonate system, Earth Planet. Sc. Lett.,
302, 403–413, 10.1016/j.epsl.2010.12.034, 2011.Raitzsch, M. and Hönisch, B.: Cenozoic boron isotope variations in benthic
foraminifers, Geology, 41, 591–594, 10.1130/G34031.1, 2013.Raitzsch, M., Hathorne, E. C., Kuhnert, H., Groeneveld, J., and Bickert, T.: Modern and
late Pleistocene B / Ca ratios of the benthic foraminifer Planulina wuellerstorfi
determined with laser ablation ICP-MS, Geology, 39, 1039–1042, 10.1130/G32009.1, 2011.Raitzsch, M., Bijma, J., Benthien, A., Richter, K.-U., Steinhoefel, G., and Kučera,
M.: Boron isotope-based seasonal paleo-pH reconstruction for the Southeast Atlantic – A
multispecies approach using habitat preference of planktonic foraminifera, Earth
Planet. Sc. Lett., 487, 138–150, 10.1016/j.epsl.2018.02.002, 2018.Raitzsch, M., Bijma, J., Bickert, T., Schulz, M., Holbourn, A., and Kučera, M.:
Eccentricity-paced atmospheric carbon-dioxide variations across the middle Miocene climate
transition, Clim. Past Discuss., 10.5194/cp-2020-96, in review, 2020.R Core Team: A Language and Environment for Statistical Computing, R Foundation for
Statistical Computing, Vienna, available at: https://www.R-project.org (last
access: 29 February 2020), 2018. Rollion-Bard, C. and Blamart, D.: In: Biomineralization Sourcebook: Characterization of
Biominerals and Biomimetic Materials, pp. 249–261, CRC Press, Taylor & Francis Group, Boca
Raton, FL, 2014.Rollion-Bard, C., Erez, J., and Zilberman, T.: Intra-shell oxygen isotope ratios in the benthic foraminifera genus Amphistegina and the influence of seawater carbonate chemistry and temperature on this ratio, Geochim. Cosmochim. Ac., 72, 6006–6014, 10.1016/j.gca.2008.09.013, 2008.Rollion-Bard, C. and Erez, J.: Intra-shell boron isotope ratios in the symbiont-bearing
benthic foraminiferan Amphistegina lobifera: Implications for δ11B vital
effects and paleo-pH reconstructions, Geochim. Cosmochim. Ac., 74, 1530–1536,
10.1016/j.gca.2009.11.017, 2010.Rollion-Bard, C., Chaussidon, M., and France-Lanord, C.: pH control on oxygen isotopic
composition of symbiotic corals, Earth Planet. Sc. Lett., 215, 275–288,
10.1016/S0012-821X(03)00391-1, 2003.Sadekov, A., Lloyd, N. S., Misra, S., Trotter, J., D'Olivo, J., and McCulloch, M.:
Accurate and precise microscale measurements of boron isotope ratios in calcium carbonates using
laser ablation multicollector-ICPMS, J. Anal. At. Spectrom., 34, 550–560,
10.1039/C8JA00444G, 2019.Standish, C. D., Chalk, T. B., Babila, T. L., Milton, J. A., Palmer, M. R. and Foster,
G. L.: The effect of matrix interferences on in situ boron isotope analysis by laser ablation
multi-collector inductively coupled plasma mass spectrometry, Rapid Commun. Mass Sp., 33,
959–968, 10.1002/rcm.8432, 2019.Steinhoefel, G., Horn, I., and von Blanckenburg, F.: Matrix-independent Fe isotope
ratio determination in silicates using UV femtosecond laser ablation, Chem. Geol., 268, 67–73,
10.1016/j.chemgeo.2009.07.010, 2009.Thil, F., Blamart, D., Assailly, C., Lazareth, C. E., Leblanc, T., Butsher, J., and
Douville, E.: Development of laser ablation multi-collector inductively coupled plasma mass
spectrometry for boron isotopic measurement in marine biocarbonates: new improvements and
application to a modern Porites coral, Rapid Commun. Mass Sp., 30, 359–371,
10.1002/rcm.7448, 2016.Vigier, N., Rollion-Bard, C., Levenson, Y., and Erez, J.: Lithium isotopes in
foraminifera shells as a novel proxy for the ocean dissolved inorganic carbon (DIC), C.R. Geosci.,
347, 43–51, 10.1016/j.crte.2014.12.001, 2015.Wang, B.-S., You, C.-F., Huang, K.-F., Wu, S.-F., Aggarwal, S. K., Chung, C.-H., and
Lin, P.-Y.: Direct separation of boron from Na- and Ca-rich matrices by sublimation for stable
isotope measurement by MC-ICP-MS, Talanta, 82, 1378–1384, 10.1016/j.talanta.2010.07.010,
2010.
Yu, J. and Elderfield, H.: Benthic foraminiferal B / Ca ratios reflect deep water
carbonate saturation state, Earth Planet. Sc. Lett., 258, 73–86,
10.1016/j.epsl.2007.03.025, 2007.Yu, J., Foster, G. L., Elderfield, H., Broecker, W. S., and Clark, E.: An evaluation of
benthic foraminiferal B / Ca and δ11B for deep ocean carbonate ion and pH
reconstructions, Earth Planet. Sc. Lett., 293, 114–120, 10.1016/j.epsl.2010.02.029, 2010.