# Seawater pH reconstruction using boron isotopes in multiple planktonic foraminifera species with different depth habitats and their potential to constrain pH and pCO(2) gradients

Maxence Guillermic, Sambuddha Misra, Robert A. Eagle, Alexandra Villa, Fengming Chang, Aradhna Tripati

► To cite this version:

Maxence Guillermic, Sambuddha Misra, Robert A. Eagle, Alexandra Villa, Fengming Chang, et al. Seawater pH reconstruction using boron isotopes in multiple planktonic foraminifera species with different depth habitats and their potential to constrain pH and pCO(2) gradients. Biogeosciences, 2020, 17 (13), pp.3487-3510. 10.5194/bg-17-3487-2020. hal-02933374

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# Seawater pH reconstruction using boron isotopes in multiple planktonic foraminifera species with different depth habitats and their potential to constrain pH and pCO₂ gradients

Maxence Guillermic<fnref n="1" />,<fnref n="2" />, Sambuddha Misra<fnref n="3" />,<fnref n="4" />, Robert Eagle<fnref n="1" />,<fnref n="2" />, Alexandra Villa<fnref n="1" />,<fnref n="5" />, Fengming Chang<fnref n="6" />, and Aradhna Tripati<fnref n="1" />,<fnref n="2" />

**Correspondence:** Maxence Guillermic (maxence.guillermic@gmail.com) and Aradhna Tripati (atripati@g.ucla.edu)

Received: 3 July 2019 – Discussion started: 8 August 2019

Revised: 28 April 2020 – Accepted: 15 May 2020 – Published: 8 July 2020

**Abstract.** Boron isotope systematics of planktonic foraminifera from core-top sediments and culture experiments have been studied to investigate the sensitivity of δ¹¹B of calcite tests to seawater pH. However, our knowledge of the relationship between δ¹¹B and pH remains incomplete for many taxa. Thus, to expand the potential scope of application of this proxy, we report δ¹¹B data for seven different species of planktonic foraminifera from sediment core tops. We utilize a method for the measurement of small samples of foraminifera and calculate the δ¹¹B-calcite sensitivity to pH for *Globigerinoides ruber*, *Trilobus sacculifer* (sacc or without sacc), *Orbulina universa*, *Pulleniatina obliquiloculata*, *Neogloboquadrina dutertrei*, *Globorotalia menardii*, and *Globorotalia tumida*, including for unstudied core tops and species. These taxa have diverse ecological preferences and are from sites that span a range of oceanographic regimes, including some that are in regions of air–sea equilibrium and others that are out of equilibrium with the atmosphere. The sensitivity of δ¹¹Bcarbonate to δ¹¹Bborate (e.g., Δδ¹¹Bcarbonate/Δδ¹¹Bborate) in core tops is consistent with previous studies for *T. sacculifer* and *G*.

ruber and close to unity for *N. dutertrei*, *O. universa*, and combined deep-dwelling species. Deep-dwelling species closely follow the core-top calibration for *O. universa*, which is attributed to respiration-driven microenvironments likely caused by light limitation and/or symbiont–host interactions. Our data support the premise that utilizing boron isotope measurements of multiple species within a sediment core can be utilized to constrain vertical profiles of pH and pCO₂ at sites spanning different oceanic regimes, thereby constraining changes in vertical pH gradients and yielding insights into the past behavior of the oceanic carbon pumps.

## 1 Introduction

The oceans are absorbing a substantial fraction of anthropogenic carbon emissions, resulting in declining surface ocean pH (IPCC, 2014). Yet there is a considerable uncertainty over the magnitude of future pH change in different parts of the ocean and the response of marine biogeochemistry.

<footnote n="1">¹Department of Earth, Planetary, and Space Sciences, Department of Atmospheric and Oceanic Sciences, Institute of the Environment and Sustainability, UCLA, University of California – Los Angeles, Los Angeles, CA 90095, USA</footnote>

<footnote n="2">²Laboratoire Géosciences Océan UMR6538, UBO, Institut Universitaire Européen de la Mer, Rue Dumont d'Urville, 29280 Plouzané, France</footnote>

<footnote n="3">³Indian Institute of Science, Centre for Earth Sciences, Bengaluru, Karnataka 560012, India</footnote>

<footnote n="4">⁴The Godwin Laboratory for Palaeoclimate Research, Department of Earth Sciences, University of Cambridge, Cambridge, UK</footnote>

<footnote n="5">⁵Department of Geoscience, University of Wisconsin, Madison, WI 53706, USA</footnote>

<footnote n="6">⁶Key Laboratory of Marine Geology and Environment, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China</footnote>
cal cycles to physiochemical parameters (T, pH) caused by
climate change (Bijma et al., 2002; Ries et al., 2009). There-
fore, there is an increased interest in reconstructing past sea-
water pH (Hönisch and Hemming, 2004; Liu et al., 2009; Wei
et al., 2009; Douville et al., 2010), in understanding spatial
variability in aqueous pH and carbon dioxide (pCO₂) (Fos-
ter, 2008; Martínez-Boti et al., 2015b; Raitzsch et al., 2018),
and in studying the response of the biological carbon pump
using geochemical proxies (Yu et al., 2007, 2010, 2016).

Although all proxies for carbon cycle reconstruction are
complex in nature (Pagani et al., 2005; Tripati et al., 2009,
2011; Allen and Hönisch, 2012), the boron isotope compo-
sition of foraminiferal tests (expressed as δ¹¹Bcarbonate) is
emerging as one of the more robust available tools (Ni et
al., 2007; Foster et al., 2008, 2012; Henehan et al., 2013;
Martínez-Boti et al., 2015b; Chalk et al., 2017). The study of
laboratory-cultured foraminifera has demonstrated a system-
atic dependence of the boron isotope composition of tests on
solution pH (Sanyal et al., 1996, 2001; Henehan et al., 2013,
2016). Core-top measurements on globally distributed sam-
ples also show a boron isotope ratio sensitivity to pH with
taxa-specific offsets from the theoretical fractionation line of
borate ions (Rae et al., 2011; Henehan et al., 2016; Raitzsch
et al., 2018).

Knowledge of seawater pH, in conjunction with con-
straints on one other carbonate system parameter (total al-
kalinity (TA), DIC (dissolved inorganic carbon), [HCO₃⁻],
[CO₃²⁻]), can be utilized to constrain aqueous pCO₂. Appli-
cation of empirical calibrations for boron isotope ratio, deter-
mined for select species of foraminifera from core tops and
laboratory cultures, has resulted in accurate reconstructions
of pCO₂ utilizing downcore samples from sites that are cur-
rently in quasi-equilibrium with the atmosphere at present.
Values of pCO₂ reconstructed from planktonic foraminifera
boron isotope ratios are analytically indistinguishable from
ice core CO₂ records (Foster et al., 2008; Henehan et al.,
2013; Chalk et al., 2017).

The last decade has produced several studies aiming at re-
constructing past seawater pH using boron isotopes to con-
strain atmospheric pCO₂ in order to understand the changes
in the global carbon cycle (Hönisch et al., 2005, 2009; Fos-
ter et al., 2008, 2012, 2014; Seki et al., 2010; Bartoli et al.,
2011; Henehan et al., 2013; Martínez-Boti et al., 2015a, b;
Chalk et al., 2017). In addition to reconstructing atmospheric
pCO₂, the boron isotope proxy has been applied to mixed-
layer planktonic foraminifera at sites out of equilibrium with
the atmosphere to constrain past air-sea fluxes (Foster et al.,
2014; Martínez-Boti et al., 2015b). A small body of work
has examined whether data for multiple species in core-top
(Foster et al., 2008) and down-core samples could be used to
constrain vertical profiles of pH through time (Palmer et al.,
1998; Pearson and Palmer, 1999; Anagnostou et al., 2016).

Here we add to the emerging pool of boron isotope
data in planktonic foraminifera from different oceanographic

regimes, including data for species that have not previously
been examined. We utilize a low-blank (15 to 65 pg B),
high-precision (2 SD on the international standard JCP-1
is 0.20‰, n = 6) δ¹¹Bcarbonate analysis method for small
samples (down to ~250 µg CaCO₃), modified after Misra
et al. (2014a), to study multiple species of planktonic
foraminifera. The studied sediment core tops span a range of
oceanographic regimes, including open-ocean oligotrophic
settings and marginal seas. We constrain calibrations for dif-
ferent species, and we compare results to published work
(Foster et al., 2008; Henehan et al., 2013, 2016; Martínez-
Boti et al., 2015b; Raitzsch et al., 2018). We also test whether
these data support the application of boron isotope measure-
ments of multiple species within a sediment core as a proxy
for constraining vertical profiles of pH and pCO₂.

## 2 Background

2.1 Planktonic foraminifera as archives of seawater pH

Planktonic foraminifera are used as archives of past envi-
ronmental conditions within the mixed layer and thermo-
cline, as their chemical composition is correlated with the
physiochemical parameters of their calcification environment
(Ravelo and Fairbanks, 1992; Elderfield and Ganssen, 2000;
Dekens et al., 2002; Anand et al., 2003; Sanyal et al., 2001;
Ni et al., 2007; Henehan et al., 2013, 2015, 2016; Howes et
al., 2017; Raitzch et al., 2018). The utilization of geochem-
ical data for multiple planktonic foraminifera species with
different ecological preferences to constrain vertical gradi-
ents has been explored in several studies. The framework for
such an approach was first developed using modern samples
of planktonic foraminifera for oxygen isotopes, where it was
proposed as a tool to constrain vertical temperature gradients
and study physical oceanographic conditions during periods
of calcification (Ravelo and Fairbanks, 1992).

Because planktonic foraminifera species complete their
life cycle in a particular depth habitat due to their ecological
preference (Ravelo and Fairbanks, 1992; Farmer et al., 2007),
it is theoretically possible to reconstruct water column pro-
files of pH using boron isotope ratio data from multiple taxa
(Palmer and Pearson, 1998; Anagnostou et al., 2016). The
potential use of an analogous approach to reconstruct past
profiles of seawater pH was first highlighted by Palmer and
Pearson (1998) on Eocene samples to constrain water depth
pH gradients. However, in these boron isotope-based studies,
it was assumed that boron isotope offset from seawater and
foraminiferal carbonate was constant, which is an assump-
tion not supported by subsequent studies (e.g., Hönisch et al.,
2003; Foster et al., 2008; Henehan et al., 2013, 2016; Rait-
szch et al., 2018; Rae, 2018). Furthermore, boron isotope ra-
tio differences between foraminifera species inhabiting wa-
ters of the same pH make the acquisition of more core-top
and culture data essential for applications of the proxy.
## 2.2 Boron systematics in seawater

Boron is a conservative element in seawater with a long residence time ($\tau_B \sim 14$ Myr) (Lemarchand et al., 2002). In seawater, boron exists as trigonal boric acid $B(OH)_3$ and tetrahedral borate ion $B(OH)_4^-$ (borate). The relative abundance of boric acid and borate ions is a function of the ambient seawater pH. At standard open-ocean conditions ($T = 25$ °C and $S = 35$), the dissociation constant of boric acid is 8.60 (Dickson, 1990), implying that boron mainly exists in the form of boric acid in seawater. The fact that the $pK_B$ and seawater pH (e.g., $\sim 8.1$, NBS) values are similar implies that small changes in seawater pH will induce strong variations in the abundance of the two boron species (Fig. 1).

Boron has two stable isotopes, $^{10}$B and $^{11}$B, with average relative abundances of 19.9% and 80.1%, respectively. Variations in B isotope ratio are expressed in conventional delta ($\delta$) notation:

$$ \delta^{11}\text{B} (\text{\textperthousand}) = 1000 \times \left( \frac{\frac{^{11}\text{B}}{^{10}\text{B}_{\text{Sample}}} - 1 \right), \quad (1) $$

where positive values represent enrichment in the heavy isotope $^{11}$B and negative values enrichment in the light isotope $^{10}$B, relative to the standard reference material. Boron isotope values are reported versus the NIST SRM 951 boric acid standard (Cantazaro et al., 1970).

$B(OH)_3$ is enriched in $^{11}$B compared to $B(OH)_4^-$ with a constant offset between the two chemical species, within the range of physiochemical variation observed in seawater, given by the fraction factor ($\alpha$). The fractionation ($\varepsilon$) between $B(OH)_3$ and $B(OH)_4^-$ of $27.2 \pm 0.6\text{\textperthousand}$ has been empirically determined by Klochko et al. (2006) in seawater. Note that Nir et al. (2015) calculate this fractionation, using an independent method, to be $26 \pm 1\text{\textperthousand}$, which is within the analytical uncertainty of the Klochko et al. (2006) value. We use a fractionation of $27.2\text{\textperthousand}$ determined by Klochko et al. (2006) in this study.

## 2.3 Boron isotopes in planktonic foraminifera calcite

Many biogenic carbonate-based geochemical proxies are affected by “vital effects” or biological fractionations (Urey et al., 1951). The $\delta^{11}\text{B}_{\text{carbonate}}$ in foraminifera exhibits species-specific offsets (see Rae et al., 2018, for review) compared to theoretical predictions for the boron isotopic composition of $B(OH)_4^-$ (expressed as $\delta^{11}\text{B}_{\text{borate}}$, $\alpha = 1.0272$; Klochko et al., 2006). As the analytical and technical aspects of boron isotope measurements have improved (Foster et al., 2008; Rae et al., 2011; Misra et al., 2014b; Lloyd et al., 2018), evidence for taxonomic differences has not been eliminated but has become increasingly apparent (Foster et al., 2008, 2016; Marschall and Foster, 2018; Henehan et al. 2013, 2016; Rae et al., 2018; Raitzsch et al., 2018).

At present, culture and core-top calibrations have been published for several planktonic species including *Trilo-

batus sacculifer, Globigerinoides ruber, Globigerina bulloides, Neogloboquadrina pachyderma, and *Orbulina universa* (Foster et al., 2008; Henehan et al., 2013, 2015; Sanyal et al., 1996, 2001). Although the boron isotopic composition of several species of foraminifera is now commonly used for reconstructing surface seawater pH, for other species, there is a lack of data constraining the sensitivity of boron isotopes in foraminiferal carbonate and borate ions in seawater.

## 2.4 Origin of biological fractionations in foraminifera

Perforate foraminifera are calcifying organisms that maintain a large degree of biological control over their calcification space, and thus mechanisms of biomineralization may be of significant importance in controlling the $\delta^{11}\text{B}$ of the biogenic calcite. The biomineralization of foraminifera is based on seawater vacuolization (Erez, 2003; de Nooijer et al., 2014) with parcels of seawater being isolated by an organic matrix, thereby creating a vacuole filled with seawater. Recent work has also demonstrated that even if the chemical composition of the reservoirs is modified by the organism, seawater is directly involved in the calcification process with vacuoles formed at the periphery of the shell (de Nooijer et al., 2014). Culture experiments by Rollion-Bard and Erez (2010) have proposed that the pH at the site of biomineralization is elevated to an upper pH limit of $\sim 9$ for the shallow-water, symbiont-bearing benthic foraminifera *Amphistegina lobifera*, which would support a pH modulation of a calcifying fluid in foraminifera. The extent to which these results apply to planktonic foraminifera is not known, although pH modulation of calcifying fluid may influence the $\delta^{11}\text{B}$ of planktonic foraminifera.

For taxa with symbionts, the microenvironment surrounding the foraminifera is chemically different from seawater due to photosynthetic activity (Jørgensen et al., 1985; Rink et al., 1998; Köhler-Rink and Kühl, 2000). Photosynthesis by symbionts elevates the pH of microenvironments (Jørgensen et al., 1985; Rink et al., 1998; Wolf-Gladrow et al., 1999; Köhler-Rink and Kühl, 2000), while calcification and respiration decrease microenvironment pH (Eqs. 2 and 3).

$$ \begin{align} & \mathrm{Ca}^{2+} + 2\mathrm{HCO}_3^- \leftrightarrow \mathrm{CaCO}_3 + \mathrm{H}_2\mathrm{O} + \mathrm{CO}_2 \quad \text{or} \nonumber \\ & \mathrm{Ca}^{2+} + \mathrm{CO}_3^{2-} \leftrightarrow \mathrm{CaCO}_3 \quad [\text{calcification}] \tag{2} \end{align} $$

$$ \mathrm{CH}_2\mathrm{O} + \mathrm{O}_2 \leftrightarrow \mathrm{CO}_2 + \mathrm{H}_2\mathrm{O} \quad [\text{respiration/photosynthesis}] \quad (3) $$

$\delta^{11}\text{B}$ in foraminifera is primarily controlled by seawater pH but also depends on the pH alteration of microenvironments due to calcification, respiration, and symbiont photosynthesis. $\delta^{11}\text{B}_{\text{carbonate}}$ should therefore reflect the relative dominance of these processes and may account for species-specific $\delta^{11}\text{B}$ offsets. Theoretical predictions from Zeebe et al. (2003) and foraminiferal data from Hönisch et al. (2003) explored the influence of microenvironment pH in the $\delta^{11}\text{B}$ signature of foraminifera. Their work also suggested that for a given species there should be a constant offset observed
<figure><img src="image_3.png" /><figcaption>**Figure 1.** (a) Speciation of B(OH)₃ and B(OH)₄⁻ as a function of seawater pH (total scale), (b) δ¹¹B of dissolved inorganic boron species as a function of seawater pH, (c) sensitivity of δ¹¹B of B(OH)₄⁻ for a pH ranging from 7.6 to 8.4. T = 25 °C, S = 35, δ¹¹B = 39.61‰ (Foster et al., 2010), and dissociation constant α = 1.0272 (Klochko et al., 2006).</figcaption></figure>

between the boron isotope composition of foraminifera and borate ions over a large range of pH, imparting confidence in utilizing species-specific boron isotope data as a proxy for seawater pH.

Comparison of boron isotope data for multiple planktonic foraminiferal species indicates that taxa with high levels of symbiont activity such as *T. sacculifer* and *G. ruber* show higher δ¹¹B values than the δ¹¹B of ambient borate (Foster et al., 2008; Henehan et al., 2013; Raitzsch et al., 2018). The sensitivities Δδ¹¹Bcarbonate/Δδ¹¹Bborate (hereafter referred to as the slope) of existing calibrations suggest a different species-specific sensitivity for these species compared to other taxa (Sanyal et al., 2001; Henehan et al., 2013, 2015; Raitzsch et al., 2018). For example, *Orbulina universa* exhibits a lower δ¹¹B than in situ δ¹¹B values of borate ions (Henehan et al., 2016), consistent with the species living deeper in the water column characterized by reduced photosynthetic activity.

It is possible that photosynthetic activity by symbionts might not be able to compensate for changes in calcification and/or respiration, leading to an acidification of the microenvironment. It is interesting to note that for *O. universa* the slope determined for the field-collected samples is not statistically different from unity (0.95 ± 0.17) (Henehan et al., 2016), while culture experiments report slopes of ≤ 1 for multiple species including *G. ruber* (Henehan et al., 2013), *T. sacculifer* (Sanyal et al., 2001), and *O. universa* (Sanyal et al., 1999). More core-top and culture calibrations are needed to refine those slopes and understand if significant differences are observed, which is part of the motivation for this study.

## 2.5 Planktic foraminifera depth and habitat preferences

The preferred depth habitat of different species of planktonic foraminifera depends on their ecology, which in turn is dependent on hydrographic conditions. For example, *G. ruber* is commonly found in the mixed layer (Fairbanks and Wiebe, 1980; Dekens et al., 2002; Farmer et al., 2007) during the summer (Deuser et al., 1981), whereas *T. sacculifer* is present in the mixed layer until mid-thermocline depths (Farmer et al., 2007) during spring and summer (Deuser et al., 1981, 1989). Specimens of *P. obliquiloculata* and *N. dutertrei* are abundant during winter months (Deuser et al., 1989), with an acme in the mixed layer (~60 m) for *P. obliquiloculata* and at mid-thermocline depths for *N. dutertrei* (Farmer et al., 2007). In contrast, *O. universa* tends to record annual average conditions within the mixed layer. Specimens of *G. menardii* calcify within the seasonal thermocline (Fairbanks et al., 1982; Farmer et al., 2007; Regenberg et al., 2009), and in some regions in the upper thermocline (Farmer et al., 2007), and record annual temperatures. *G. tumida* is found at the lower thermocline or below the thermocline and records annual average conditions (Fairbanks and Wiebe, 1980; Farmer et al., 2007; Birch et al., 2013). Although the studies listed above showed evidence for species-specific living depth habitat affinities, recent direct observations showed that environmental conditions (e.g., temperature, light) were locally responsible for the variability in the living depth of certain foraminifera species in the eastern North Atlantic (Rebotim et al., 2017).
<table><caption>**Table 1.** Box core information.</caption><thead><tr><th>Label</th><th>Box core</th><th>Site</th><th>Latitude (N)</th><th>Longitude (E)</th><th>Depth (m b.s.l.)</th><th>Oceanic regime</th><th><sup>14</sup>C age (year)</th></tr></thead><tbody><tr><td colspan="8">Atlantic Ocean</td></tr><tr><td>CD107-a</td><td>CD107</td><td>A</td><td>52.92</td><td>-16.92</td><td>3569</td><td>non-upwelling</td><td>&lt;3000<sup>a</sup></td></tr><tr><td colspan="8">Indian Ocean</td></tr><tr><td>FC-01a</td><td>WIND-33B</td><td>I</td><td>-11.21</td><td>58.77</td><td>3520</td><td>non-upwelling</td><td></td></tr><tr><td>FC-02a</td><td>WIND-10B</td><td>K</td><td>-29.12</td><td>47.55</td><td>2871</td><td>non-upwelling</td><td>7252 ± 27<sup>b</sup></td></tr><tr><td colspan="8">Arabian Sea</td></tr><tr><td>FC-12b</td><td>CD145</td><td>A150</td><td>23.30</td><td>66.70</td><td>151</td><td>seasonal upwelling</td><td></td></tr><tr><td>FC-13a</td><td>CD145</td><td>A3200</td><td>20.00</td><td>65.58</td><td>3190</td><td>seasonal upwelling</td><td></td></tr><tr><td colspan="8">Pacific Ocean</td></tr><tr><td>WP07-01</td><td></td><td></td><td>-3.93</td><td>156.00</td><td>1800</td><td>non-upwelling</td><td>7300–8600<sup>c</sup></td></tr><tr><td>A14</td><td></td><td></td><td>8.02</td><td>113.39</td><td>1911</td><td>non-upwelling</td><td>7300–8600<sup>c</sup></td></tr><tr><td>806</td><td></td><td>A</td><td>0.32</td><td>159.36</td><td>2521</td><td>equatorial divergence</td><td>7300–8600<sup>c</sup></td></tr><tr><td>807</td><td></td><td>A</td><td>3.61</td><td>156.62</td><td>2804</td><td>equatorial divergence</td><td>7300–8600<sup>c</sup></td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Figure 2.** Map showing locations of the core tops used in this study (white diamonds). Red open circles represent the sites used for in situ carbonate parameters from the GLODAP database (Key et al., 2004).</figcaption></figure>

# 3 Materials and methods

## 3.1 Localities studied

Core-top locations were selected to span a broad range of seawater pH, carbonate system parameters, and oceanic regimes. Samples from the Atlantic Ocean (CD107-A), Indian Ocean (FC-01a and FC-02a), Arabian Sea (FC-13a and FC-12b), and Pacific Ocean (WP07-01, A14, and Ocean Drilling Program 806A and 807A) were analyzed; characteristics of the sites are summarized in Tables 1 and S7 and Figs. 2 and 3.

Atlantic site CD107-a (CD107 site A) was cored in 1997 by the Benthic Boundary Layer program (BENBO) (Black, 1997 – cruise report RRS *Charles Darwin* cruise 107). Arabian Sea sites FC-12b (CD145 A150) and FC-13a (CD145 A3200) were retrieved by the *Charles Darwin* in the Pak-

istan margin in 2004 (Bett, 2004 – cruise report no. 50 RRS *Charles Darwin* cruise 145). A14 was recovered by a box corer in the southern area of the South China Sea in 2012. Core WP07-01 was obtained from the Ontong Java Plateau using a giant piston corer during the Warm Pool Subject Cruise in 1993. Holes 806A and 807A were retrieved on Leg 130 by the Ocean Drilling Program (ODP). The top 10 cm of sediment from CD107-A has been radiocarbon dated to be Holocene <3 kyr (Thomson et al., 2000). Samples from multiple box cores from Indian Ocean sites were radiocarbon dated as Holocene <7.3 kyr (Wilson et al., 2012). Samples from western equatorial Pacific site 806B, close to site WP07-01, are dated to between 7.3 and 8.6 kyr (Lea et al., 2000). Arabian Sea and Pacific core-top samples were not radiocarbon dated but are assumed to be Holocene.

## 3.2 Species

Around 50–100 foraminifera shells were picked from the 400 to 500 µm fraction size for *Globorotalia menardii* and *Globorotalia tumida*, >500 µm for *Orbulina universa*, and from the 250–400 µm fraction size for *Trilobatus sacculifer* (w/o sacc, without sacc-like final chamber), *Trilobatus sacculifer* (sacc, sacc-like final chamber), *Globigerinoides ruber* (white, sensu stricto), *Neogloboquadrina dutertrei*, and *Pulleniatina obliquiloculata*. The samples picked for analyses were visually well preserved.

<footnote><sup>a</sup> Thomson et al., 2000. <sup>b</sup> Wilson et al., 2012. <sup>c</sup> Age for core top of site 806B from Lea et al. (2000).</footnote>
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Preindustrial data versus depth for the sites used in this study. The figure shows seasonal temperatures (extracted from World Ocean Database 2013), density anomaly (kg m⁻³), and preindustrial pH and preindustrial δ¹¹B of H₄BO₄⁻ (calculated from the GLODAP database and corrected for anthropogenic inputs). Dotted lines are the calculated uncertainties based on errors on TA and DIC from the GLODAP database.</figcaption></figure>
## 3.3 Sample cleaning

Briefly, picked foraminifera were gently cracked open, clay was removed with successive ultrasonication steps in MQ water and methanol, and then they were checked for coarse-grained silicates. The next stages of sample processing and chemical separation were performed in a class 1000 clean lab equipped with boron-free HEPA filters. Samples were cleaned using full reductive and oxidative cleaning (Boyle, 1981; Boyle and Keigwin, 1985; Barker et al., 2003). Samples from the South China Sea (sites A14, E035) presented high Mn and high Fe. Due to potential Fe-Mn oxide and hydroxides the reductive cleaning was used. Previous comparisons of cleaning methods have shown there is no impact of the reductive step on B/Ca (Misra et al., 2014b), but there is an impact of the reductive step on Mg/Ca (Barker et al., 2003 and others). Nevertheless, it is possible that Fe-Mn oxide and hydroxides can result in non-negligible Mg and B contamination. Because this study was designed to investigate boron proxies and in order to be consistent in methodology, the reductive cleaning was used at all sites. Cleaned samples selected for this study did not yield high Mn concentrations (see Supplement for discussion on contamination).

A final leaching step with 0.001 N HCl was done before dissolution in 1 N HCl. Hydrochloric acid was used to allow complete dissolution of the sample including Fe-Mn oxide and hydroxides if present. Each sample was divided into two aliquots: an aliquot for boron purification and one aliquot for trace element analysis.

## 3.4 Reagents

Double-distilled HNO₃ and HCl acids (from Merck® grade) and a commercial bottle of ultrapure-grade HF were used at Brest. Double-distilled acids were used at Cambridge. All acids and further dilutions were prepared using double-distilled 18.2 MΩ cm⁻¹ MQ water. Working standards for isotope ratio and trace element measurements were freshly diluted on a daily basis with the same acids used for sample preparation to avoid any matrix effects.

## 3.5 Boron isotopes

Boron purification for isotopic measurement was done utilizing the microdistillation method developed by Gaillardet et al. (2001) for Ca-rich matrices by Wang et al. (2010) and adapted at Cambridge by Misra et al. (2014a). A total of 70 µL of carbonate sample dissolved in 1 N HCl was loaded on a cap of a clean fin legged 5 mL conical beaker upside down. The tightly closed beaker was put on a hot plate at 95 °C for 15 h. The beakers were taken off the hot plate and were allowed to cool for 15 min. The cap where the residue formed was replaced by a clean one. Then, 100 µL of 0.5 % HF was added to the distillate.

Boron isotopic measurements were carried out on a Thermo Scientific® Neptune+ MC-ICP-MS at the University of Cambridge. The Neptune+ was equipped with a Jet interface and two 10¹³Ω resistors. The instrumental setup included Savillex® 50 µL min⁻¹ C-flow self-aspirating nebulizer, a single-pass Teflon® Scott-type spray chamber constructed utilizing Savillex® column components, a 2.0 mm Pt injector from ESI®, a Thermo® Ni “normal”-type sample cone, and ‘X’ type skimmer cones. Both isotopes of boron were determined utilizing 10¹³Ω resistors (Misra et al., 2014a; Lloyd et al., 2018).

The sample size for boron isotope analyses typically ranged from 10 ppb B (~5 ng B) to 20 ppb B samples (~10 ng B). Instrumental sensitivity for ¹¹B was 17 mV ppb⁻¹ B (e.g., 170 mV for 10 ppb B) in wet plasma at a 50 µL min⁻² sample aspiration rate. Intensity of ¹¹B for a sample at 10 ppb B was typically 165 mV ± 5 mV, which closely matched the 170 mV ± 5 mV of the standard. Due to the low boron content of the samples, extreme care was taken to avoid boron contamination during sample preparation and reduce memory effect during analysis. Procedural boron blanks ranged from 15 to 65 pg B and contributed to less than <1 % of the sample signal. The acid blank during analyses was measured at ≤ 1 mV on ¹¹B, meaning a contribution <1 % of the sample intensity; no memory effect was observed within and across sessions. No matrix effect resulting from the mix HCl/HF was observed on the δ¹¹B.

Analyses of external standards were done to ensure data quality. For δ¹¹B measurements one carbonate standard and one coral were utilized: the JCp-1 (Geological Survey of Japan, Tsukuba, Japan) international standard (Gutjahr et al., 2014) and the NEP coral (Porites sp., δ¹¹B = 26.12±0.92‰, 2SD, n = 33, Holcomb et al., 2015, and Sutton et al., 2018, Table S2 in the Supplement) from University of Western Australia–Australian National University. A certified boric acid standard, the ERM© AE121 (δ¹¹B = 19.9±0.6‰, SD, certified), was used to monitor reproducibility and drift during each session (Vogl and Rosner, 2011; Foster et al., 2013; Misra et al., 2014b). Results for the isotopic composition of the NEP coral are shown in Table S2, average values are δ¹¹BNEP = 25.70±0.93‰ (2SD, n = 22) over seven different analytical sessions with each number representing an ab initio processed sample. Our results are within error of published values of 26.20±0.88‰ (2SD, n = 27) and 25.80±0.89‰ (2SD, n = 6) by Holcomb et al. (2015) and Sutton et al. (2018), respectively. Chemically cleaned JCp-1 samples were measured at 24.06±0.20 (2SD, n = 6) and are within error of published values of 24.37±0.32‰, 24.11±0.43‰, and 24.42±0.28‰ by Holcomb et al. (2015), Farmer et al. (2016), and Sutton et al. (2018), respectively.

## 3.6 Trace elements

The calcium concentration of each sample was measured on an inductively coupled plasma atomic emission spectrome-
ter (ICP-AES) Ultima 2 HORIBA at the Pôle spectrométrie Océan (PSO), UMR6538 (Plouzané, France). Samples were then diluted to fixed calcium concentrations (typically 10 ppm or 30 ppm Ca) using 0.1 M HNO₃ and 0.3 M HF matching multielement standard Ca concentration to avoid any matrix effects (Misra et al., 2014b). Levels of remaining HCl (<1 %) in these diluted samples were negligible and did not contribute to matrix effects. Trace elements (e.g., X/Ca ratios) were analyzed on a Thermo Scientific® Element XR high-resolution inductively coupled plasma mass spectrometer (HR-ICP-MS) at the PSO, Ifremer (Plouzané, France).

Trace element analyses were done at a Ca concentration of 10 or 30 ppm. The typical blanks for a 30 ppm Ca session were 7Li <2%, 11B <7%, 25Mg <0.2%, and 43Ca <0.02%. Additionally, blanks for a 10 ppm Ca session were 7Li <2.5%, 11B <10%, 25Mg <0.4%, and 43Ca <0.05%. Due to strong memory effect for boron and instrumental drift on the Element XR, long sessions of conditioning were done prior to analyses. Boron blanks were driven below 5% of signal intensity usually after 4 to 5 d of continuous analyses of carbonate samples. External reproducibility was determined on the consistency standard Cam-Wuellestorfi (courtesy of the University of Cambridge) (Misra et al., 2014b), Table S3. Our X/Ca ratio measurements on the external standard Cam-Wuellestorfi were within error of the published value all the time (Table S3), validating the robustness of our trace element data. Analytical uncertainty of a single measurement was calculated from the reproducibility of the Cam-Wuellestorfi, measured during a particular mass spectrometry session. The analytical uncertainties (2SD, *n* = 31, Table S3) on the X/Ca ratios are ±0.4 µmol mol⁻¹ for Li/Ca, ±7 µmol mol⁻¹ for B/Ca, and ±0.01 µmol mol⁻¹ for Mg/Ca, respectively.

## 3.7 Oxygen isotopes

Carbonate δ¹³C and δ¹⁸O were measured on a GasBench II coupled to a Delta V mass spectrometer at the stable isotope facility of Pôle spectrométrie Océan (PSO), Plouzané. Around 20 shells were weighed, crushed, and had clay removed following the same method described in Sect. 3.3 (Barker et al., 2003). The recovered foraminifera were weighed in tubes and flushed with He gas. Samples were then digested in phosphoric acid and analyzed. Results were calibrated to the Vienna Pee Dee Belemnite (VPDB) scale by international standard NBS19, and analytical precision on the in-house standard Ca21 was better than ±0.11‰ for δ¹⁸O (SD, *n* = 5) and ±0.03‰ for δ¹³C (SD, *n* = 5).

## 3.8 Calcification depth determination

We utilized two different chemo-stratigraphic methods to estimate the calcification depth (CD) in this study (Tables S6 and S7). The first method (CD1), commonly used in paleo-oceanography, utilizes δ¹⁸O measurements of the carbonate

(δ¹⁸O<sub>c</sub>) to estimate calcification depths (referred to as δ¹⁸O-based calcification depths) (Schmidt et al., 2002; Mortyn et al., 2003; Sime et al., 2005; Farmer et al., 2007; Birch et al., 2013). Rebotim et al. (2017) also showed good correspondence between living depth habitat and calcification depth derived using CD1. The second method (CD2) utilizes Mg/Ca-based temperature estimates (T<sub>Mg/Ca</sub>) to constrain calcification depths (Quintana Krupinski et al., 2017). However, we note that reductive cleaning leads to a decrease in Mg/Ca that in turn would result in a bias towards deeper calcification depths, which is not the case when we utilize non-Mg/Ca-based methodologies. In both cases, the prerequisite was that vertical profiles of seawater temperature are available for different seasons in ocean atlases and cruise reports and that hydrographic data and geochemical proxy signatures can be compared to assess the depth in the water column that represents the taxon's maximum abundance.

Because both methods have their uncertainties (in one case use of taxon-specific calibrations and in the other analytical limitations), both estimates of calcification depth were compared to published values for the basin (CD3) and where available for the same site (Table S6). To select which calcification depth to use for further calculations, we first looked at CD₁, CD₂, and CD₃. If CD1 and CD2 were similar we selected this calcification depth, and if CD₁ and CD₂ were different we chose literature values, CD₃, when available. For some less studied species, like *G. tumida*, *G. menardii*, or *P. obliquiloculata*, CD₃ was not always available but when available showed good correspondence with our CD₂. Moreover due to availability of Mg/Ca-derived temperature taxon-specific calibrations, we preferentially use CD₂ for those species.

We applied (based on uncertainties of our measurements) an uncertainty of ±10 m for calcification depths >70 m and an uncertainty of ±20 m when calcification depths <70 m. Direct observations of living depths of foraminifera remain limited. However, the depth uncertainties reported here are in line with the uncertainties calculated based on direct observations in the eastern North Atlantic which give a standard error on average living depths ranging from 6 to 22 m for the same species (Rebotim et al., 2017). The decrease in Mg/Ca due to reductive cleaning was not taken into account because it has not been studied for most of the species used in this study and because the depth uncertainty applied based on δ¹⁸O analytical error is conservative relative to the uncertainty of a 10% decrease in Mg/Ca equivalent that would be equivalent to ~1.2 °C. The depth habitats utilized to derive in situ parameters are summarized in Table S7.

## 3.9 δ¹¹B<sub>borate</sub>

Two carbonate system parameters are needed to fully constrain the carbonate system. Following the approach of Foster et al. (2008), we used the GLODAP database (Key et al., 2004) corrected for anthropogenic inputs in order to esti-
mate preindustrial carbonate system parameters at each site. Temperature, salinity, and pressure for each site are from the World Ocean Database 2013 (Boyer et al., 2013). We utilized the R© code in Henehan et al. (2016) (courtesy of Michael Henehan) to calculate the δ¹¹B<sub>borate</sub> and δ¹¹B<sub>borate</sub> uncertainty and derive our calibrations. Uncertainty for δ¹¹B<sub>borate</sub> utilizing Henehan's code was similar to uncertainty calculated by applying 2SD of the δ¹¹B<sub>borate</sub> profiles within the limits imposed by our calcification depth.

The MATLAB® template provided by Zeebe and Wolf-Gladow (2001) was used to calculate *pCO₂* from TA; temperature, salinity, and pressure were included in the calculations. Total boron was calculated from Lee et al. (2010), and *K*₁ and *K*₂ were calculated from Mehrbach et al. (1973) refitted by Dickson and Millero (1987).

Statistical tests were performed utilizing GraphPad® software, and linear regressions for calibration were derived utilizing R© code in Henehan et al. (2016) (courtesy of Michael Henehan) with *k* (number of wild bootstrap replicates) equal to 500.

# 4 Results

## 4.1 Depth habitat

The calcification depths utilized in this paper are summarized in Tables S6 and S7, including a comparison of calcification depth determination methods. The calculated calcification depths are consistent with the ecology of each species and the physical properties of the water column of the sites. Specimens of *G. ruber* and *T. sacculifer* appear to be living in the shallow mixed layer (0–100 m), with *T. sacculifer* living or migrating deeper than *G. ruber* (down to 125 m). Specimens of *O. universa* and *P. obliquiloculata* are living in the upper thermocline; *G. menardii* is found in the upper thermocline until the thermocline depth specific to the location; *N. dutertrei* is living near thermocline depths and *G. tumida* is found in the lower thermocline.

Data from the multiple approaches for calculating calcification depth (CD1, CD2, and CD3) imply that some species inhabit deeper environments in the western equatorial Pacific (WEP) relative to the Arabian Sea, which in turn are deeper-dwelling than the same morphospecies occurring in the Indian Ocean. In some cases, we find evidence for differences in habitat depth of up to ~100 m between the WEP and the Arabian Sea. This trend is observed for *G. ruber* and *T. sacculifer*, but not for *O. universa*.

Some differences are observed between the two methods for calcification depth determination that are based on δ¹⁸O and Mg/Ca (CD1 and CD2). These differences might be due to the choice of calibration. Alternatively, our uncertainties for δ¹⁸O imply larger uncertainties on calcification depth determinations that use this approach, compared to Mg/Ca-based estimates.

## 4.2 Empirical calibrations of foraminiferal

δ¹¹B<sub>carbonate</sub> to δ¹¹B<sub>borate</sub>

Results for the different species analyzed in this study are presented in Figs. 4 and 5 and summarized in Table 2; additionally, published calibrations for comparison are summarized in Table 3.

### 4.2.1 G. ruber

Samples were picked from the 250–300 µm fraction, except for the WEP sites where *G. ruber* shells were picked from the 250–400 µm fraction. Weight per shell averaged 11±4 µg (*n* = 4, SD), although the weight was not measured on the same subsample analyzed for δ¹¹B and trace elements or at the WEP sites. In comparison to literature, the size fraction used for this study was smaller: Foster et al. (2008) used the 300–355 µm fraction, Henehan et al. (2013) utilized multiple size fractions (250–300, 250–355, 300–355, 355–400, and 400–455 µm), and Raitzsch et al. (2018) used the 315–355 µm fraction.

Our results for *G. ruber* (Fig. 4) are in close agreement with published data from other core tops, sediment traps, tows, and culture experiments for δ¹¹B<sub>borate</sub> > 19‰ (Foster et al., 2008; Henehan et al., 2013; Raitzsch et al., 2018). However, the two data points from δ¹¹B<sub>borate</sub> < 19‰ are lower compared to previous studies. Elevated δ¹¹B<sub>carbonate</sub> values relative to δ¹¹B<sub>borate</sub> have been explained by the high photosynthetic activity of symbionts (Hönisch et al., 2003; Zeebe et al., 2003). Three calibrations have been derived (Table 3). Linear regression on our data alone yields a slope of 1.12 (±1.67). The uncertainty is significant given limited data in our study, and given this large uncertainty, our sensitivity of δ¹¹B<sub>carbonate</sub> to δ¹¹B<sub>borate</sub> is also consistent with the low sensitivity trend of culture experiments from Sanyal et al. (2001) or Henehan et al. (2013). The second calibration made compiling all data from literature shows a sensitivity similar (e.g., 0.46 (±0.34)) to the one recently published by Raitzsch et al. (2018) (e.g., 0.45 (±0.16), Table 3). The third linear regression made only on data from the 250–400 µm fraction from our study and from the 250–300 µm fraction from Henehan et al. (2013) yields a sensitivity of 0.58 (±0.91) similar to culture experiments from Henehan et al. (2013) (e.g., 0.6 (±0.16), Table 3). This third calibration is offset by ~-0.4‰ (*p*>0.05) compared to culture calibration from Henehan et al. (2013).

### 4.2.2 *T. sacculifer*

δ¹¹B<sub>carbonate</sub> results for *T. sacculifer* (sacc and without sacc) (Fig. 4) are compared to published data (Foster et al., 2008; Martínez-Boti et al., 2015b; Raitzsch et al., 2018). Results for *T. sacculifer* are in good agreement with the literature and exhibit higher δ¹¹B<sub>carbonate</sub> compared to expected δ¹¹B<sub>borate</sub> at their collection location. A linear regression through our data
<table><caption>Table 2. Analytical results of δ¹³C, δ¹⁸O, and δ¹¹B and elemental ratios Li/Ca, Ba/Ca, and Mg/Ca.</caption><thead><tr><th>Core</th><th>Species</th><th>Fraction size (µm) (%e)</th><th>δ¹³C<sup>a</sup> (%e)</th><th>δ¹⁸O<sup>a</sup> (%e)</th><th>δ¹¹B<sub>1</sub><sup>c</sup> (%e)</th><th>δ¹¹B<sub>2</sub><sup>c</sup> (%e)</th><th>δ¹¹B<sup>b</sup> average (µmol mol<sup>-1</sup>)</th><th>Li/Ca<sup>c</sup> (µmol mol<sup>-1</sup>)</th><th>B/C<sup>c</sup> (µmol mol<sup>-1</sup>)</th><th>Mg/C<sup>c</sup> (µmol mol<sup>-1</sup>)</th><th>Mn/C<sup>c</sup> (µmol mol<sup>-1</sup>)</th><th>Fe/C<sup>c</sup></th></tr></thead><tbody><tr><td colspan="12" style="text-align: left; font-weight: bold;">Atlantic Ocean</td></tr><tr><td>CD107a</td><td>O. universa</td><td>&gt;500</td><td>1.99±0.03</td><td>1.25±0.11</td><td>16.85±0.31 (2SD, nAEI21 = 11)</td><td>16.95±0.31 (2SD, nAEI21 = 11)</td><td>16.90±0.22</td><td>13.9±0.4</td><td>68±7</td><td>3.60±0.01</td><td>13±7</td><td>0.16±0.01</td></tr><tr><td colspan="12" style="text-align: left; font-weight: bold;">Indian Ocean</td></tr><tr><td>FC-01a</td><td>G. ruber (white ss)</td><td>250-300</td><td>1.37±0.03</td><td>-1.32±0.11</td><td>19.33±0.31 (2SD, nAEI21 = 11)</td><td>19.41±0.31 (2SD, nAEI21 = 11)</td><td>19.37±0.22</td><td>15.4±0.4</td><td>109±7</td><td>3.98±0.01</td><td>10±7</td><td>0.07±0.01</td></tr><tr><td>FC-01a</td><td>T. sacculifer (sace)</td><td>300-400</td><td>1.88±0.03</td><td>-2.20±0.11</td><td>18.71±0.24 (2SD, nAEI21 = 10)</td><td>18.73±0.24 (2SD, nAEI21 = 10)</td><td>18.72±0.17</td><td>87±7</td><td>3.45±0.01</td><td>9±7</td><td>0.03±0.01</td><td></td></tr><tr><td>FC-01a</td><td>T. sacculifer (without sace)</td><td>300-400</td><td>2.02±0.03</td><td>-1.05±0.11</td><td>19.13±0.24 (2SD, nAEI21 = 10)</td><td>19.32±0.24 (2SD, nAEI21 = 10)</td><td>19.23±0.17</td><td>12.1±0.4</td><td>82±7</td><td>3.42±0.01</td><td>14±7</td><td>0.03±0.01</td></tr><tr><td>FC-01a</td><td>O. universa</td><td>&gt;500</td><td></td><td></td><td>15.50±0.26 (2SD, nAEI21 = 14)</td><td></td><td>15.50±0.26</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FC-01a</td><td>P. obliquiculata</td><td>300-400</td><td>1.00±0.03</td><td>-0.55±0.11</td><td>16.40±0.26 (2SD, nAEI21 = 14)</td><td></td><td>16.10±0.26 (2SD, nAEI21 = 14)</td><td>16.25±0.18</td><td>15.4±0.4</td><td>78±7</td><td>2.06±0.01</td><td>14±7</td><td>0.05±0.01</td></tr><tr><td>FC-01a</td><td>G. menandii</td><td>300-400</td><td>1.64±0.03</td><td>0.43±0.11</td><td>17.52±0.26 (2SD, nAEI21 = 14)</td><td>17.69±0.26 (2SD, nAEI21 = 14)</td><td>17.60±0.18</td><td>12.7±0.4</td><td>63±7</td><td>2.26±0.01</td><td>8±7</td><td>0.07±0.01</td></tr><tr><td>FC-01a</td><td>N. duerrei</td><td>300-400</td><td>1.28±0.03</td><td>-0.43±0.11</td><td>16.40±0.31 (2SD, nAEI21 = 11)</td><td>16.59±0.31 (2SD, nAEI21 = 11)</td><td>16.50±0.22</td><td>18.6±0.4</td><td>73±7</td><td>1.81±0.01</td><td>11±7</td><td>0.03±0.01</td></tr><tr><td>FC-01a</td><td>G. tumida</td><td>300-400</td><td>1.29±0.03</td><td>-0.53±0.11</td><td>16.21±0.31 (2SD, nAEI21 = 10)</td><td>16.18±0.31 (2SD, nAEI21 = 11)</td><td>16.20±0.22</td><td>10.0±0.4</td><td>61±7</td><td>1.79±0.01</td><td>11±7</td><td>0.02±0.01</td></tr><tr><td>FC-02a</td><td>G. ruber (white ss)</td><td>250-300</td><td>0.30±0.03</td><td>-1.40±0.11</td><td>20.02±0.24 (2SD, nAEI21 = 10)</td><td>19.90±0.24 (2SD, nAEI21 = 10)</td><td>19.96±0.17</td><td>18.2±0.4</td><td>125±7</td><td>3.47±0.01</td><td>10±7</td><td>0.07±0.01</td></tr><tr><td>FC-02a</td><td>T. sacculifer (sace)</td><td>300-400</td><td>1.43±0.03</td><td>-1.60±0.11</td><td>20.07±0.24 (2SD, nAEI21 = 10)</td><td>19.93±0.24 (2SD, nAEI21 = 10)</td><td>20.00±0.17</td><td>14.2±0.4</td><td>106±7</td><td>3.30±0.01</td><td>10±7</td><td>0.03±0.01</td></tr><tr><td>FC-02a</td><td>O. universa</td><td>&gt;500</td><td>1.79±0.03</td><td>0.02±0.11</td><td>18.05±0.26 (2SD, nAEI21 = 14)</td><td>17.97±0.26 (2SD, nAEI21 = 14)</td><td>18.01±0.18</td><td>14.8±0.4</td><td>67±7</td><td>4.40±0.01</td><td>11±7</td><td>0.05±0.01</td></tr><tr><td>FC-02a</td><td>P. obliquiculata</td><td>300-400</td><td>0.34±0.03</td><td>0.56±0.11</td><td>16.35±0.26 (2SD, nAEI21 = 14)</td><td>16.69±0.26 (2SD, nAEI21 = 14)</td><td>16.52±0.18</td><td>16.6±0.4</td><td>83±7</td><td>2.33±0.01</td><td>7±7</td><td>0.03±0.01</td></tr><tr><td>FC-02a</td><td>G. menandii</td><td>300-400</td><td>1.73±0.03</td><td>-0.51±0.11</td><td>17.77±0.26 (2SD, nAEI21 = 14)</td><td>17.77±0.26 (2SD, nAEI21 = 14)</td><td>17.77±0.26</td><td>15.8±0.4</td><td>125±7</td><td>2.21±0.01</td><td>17±7</td><td>0.03±0.01</td></tr><tr><td>FC-02a</td><td>N. duerrei</td><td>300-400</td><td>1.03±0.03</td><td>-0.55±0.11</td><td>16.78±0.31 (2SD, nAEI21 = 14)</td><td>17.03±0.31 (2SD, nAEI21 = 11)</td><td>16.91±0.22</td><td>18.6±0.4</td><td>82±7</td><td>2.13±0.01</td><td>13±7</td><td>0.07±0.01</td></tr><tr><td>FC-02a</td><td>G. tumida</td><td>300-400</td><td>1.64±0.03</td><td>-0.28±0.11</td><td>16.93±0.26 (2SD, nAEI21 = 14)</td><td>16.95±0.26 (2SD, nAEI21 = 14)</td><td>16.94±0.18</td><td>15.6±0.4</td><td>87±7</td><td>1.90±0.01</td><td>17±7</td><td>0.04±0.01</td></tr><tr><td colspan="12" style="text-align: left; font-weight: bold;">Arabian Sea</td></tr><tr><td>FC-12b</td><td>G. ruber (white ss)</td><td>250-300</td><td>0.58±0.03</td><td>-2.82±0.11</td><td>21.30±0.31 (2SD, nAEI21 = 11)</td><td>21.23±0.31 (2SD, nAEI21 = 11)</td><td>21.26±0.22</td><td>19.5±0.4</td><td>164±7</td><td>5.76±0.01</td><td>14±7</td><td>0.16±0.01</td></tr><tr><td>FC-12b</td><td>T. sacculifer (sace)</td><td>300-400</td><td>1.76±0.03</td><td>-2.15±0.11</td><td>19.65±0.31 (2SD, nAEI21 = 11)</td><td>19.57±0.31 (2SD, nAEI21 = 11)</td><td>19.61±0.22</td><td>14.6±0.4</td><td>101±7</td><td>4.28±0.01</td><td>17±7</td><td>0.26±0.01</td></tr><tr><td>FC-12b</td><td>T. sacculifer (without sace)</td><td>300-400</td><td>1.97±0.03</td><td>-2.19±0.11</td><td>20.32±0.31 (2SD, nAEI21 = 11)</td><td>20.37±0.31 (2SD, nAEI21 = 11)</td><td>20.34±0.22</td><td>16.7±0.4</td><td>116±7</td><td>4.90±0.01</td><td>20±7</td><td>0.14±0.01</td></tr><tr><td>FC-12b</td><td>O. universa</td><td>&gt;500</td><td>1.89±0.03</td><td>-1.59±0.11</td><td>18.13±0.20 (2SD, nAEI21 = 6)</td><td>18.13±0.20</td><td>13.6±0.4</td><td>103±7</td><td>6.91±0.01</td><td>10±7</td><td>0.06±0.01</td><td></td></tr><tr><td>FC-12b</td><td>P. obliquiculata</td><td>300-400</td><td>0.5±0.03</td><td>-1.58±0.11</td><td>16.45±0.26 (2SD, nAEI21 = 14)</td><td>16.30±0.18</td><td>16.7±0.4</td><td>95±7</td><td>3.61±0.01</td><td>69±7</td><td>0.38±0.01</td><td></td></tr><tr><td>FC-12b</td><td>G. menandii</td><td>300-400</td><td>1.05±0.03</td><td>-0.97±0.11</td><td>16.2±0.26 (2SD, nAEI21 = 14)</td><td>16.20±0.26</td><td>14.8±0.4</td><td>75±7</td><td>3.44±0.01</td><td>52±7</td><td>0.17±0.01</td><td></td></tr><tr><td>FC-12b</td><td>N. duerrei</td><td>300-400</td><td>1.35±0.03</td><td>-1.57±0.11</td><td>17.77±0.24 (2SD, nAEI21 = 10)</td><td>17.73±0.24 (2SD, nAEI21 = 10)</td><td>17.1±0.4</td><td>75±7</td><td>3.25±0.01</td><td>46±7</td><td>0.25±0.01</td><td></td></tr><tr><td>FC-13a</td><td>G. ruber (white ss)</td><td>250-300</td><td>0.08±0.03</td><td>-3.71±0.11</td><td>20.27±0.24 (2SD, nAEI21 = 10)</td><td>20.15±0.24 (2SD, nAEI21 = 10)</td><td>16.4±0.4</td><td>147±7</td><td>4.52±0.01</td><td>13±7</td><td>0.08±0.01</td><td></td></tr><tr><td>FC-13a</td><td>T. sacculifer (without sace)</td><td>300-400</td><td>1.59±0.03</td><td>-2.46±0.11</td><td>17.85±0.29 (2SD, nAEI21 = 12)</td><td></td><td>15.7±0.4</td><td>121±7</td><td>5.49±0.01</td><td>13±7</td><td>0.49±0.01</td><td></td></tr><tr><td>FC-13a</td><td>P. obliquiculata</td><td>300-400</td><td>0.00±0.03</td><td>-0.97±0.11</td><td>16.51±0.26 (2SD, nAEI21 = 14)</td><td>16.50±0.26 (2SD, nAEI21 = 14)</td><td>16.51±0.18</td><td>18.7±0.4</td><td>79±7</td><td>4.43±0.01</td><td>30±7</td><td>0.43±0.01</td></tr><tr><td>FC-13a</td><td>G. menandii</td><td>300-400</td><td>0.75±0.03</td><td>-1.07±0.11</td><td>16.74±0.20 (2SD, nAEI21 = 6)</td><td></td><td>16.74±0.20</td><td>92±0.4</td><td>60±7</td><td>1.99±0.01</td><td>19±7</td><td>0.07±0.01</td></tr><tr><td>FC-13a</td><td>N. duerrei</td><td>300-400</td><td>0.71±0.03</td><td>-1.41±0.11</td><td>14.43±0.24 (2SD, nAEI21 = 10)</td><td>14.40±0.24 (2SD, nAEI21 = 10)</td><td>14.41±0.17</td><td>15.7±0.4</td><td>69±7</td><td>1.98±0.01</td><td>15±7</td><td>0.06±0.01</td></tr><tr><td colspan="12" style="text-align: left; font-weight: bold;">Pacific Ocean</td></tr><tr><td>WP07-a</td><td>G. ruber (white ss)</td><td>250-400</td><td></td><td></td><td>19.12±0.29 (2SD, nAEI21 = 12)</td><td>19.12±0.29</td><td>14.5±0.4</td><td>144±7</td><td>4.32±0.01</td><td>15±7</td><td>0.16±0.01</td><td></td></tr><tr><td>WP07-a</td><td>T. sacculifer (sace)</td><td>250-400</td><td></td><td></td><td>20.13±0.21 (2SD, nAEI21 = 11)</td><td>20.13±0.21</td><td>12.7±0.4</td><td>92±7</td><td>4.44±0.01</td><td>22±7</td><td>0.05±0.01</td><td></td></tr><tr><td>WP07-a</td><td>T. sacculifer (without sace)</td><td>250-400</td><td></td><td></td><td>18.10±0.31 (2SD, nAEI21 = 11)</td><td>18.07±0.22</td><td>12.3±0.4</td><td>192±7</td><td>4.51±0.01</td><td>21±7</td><td>0.08±0.01</td><td></td></tr><tr><td>WP07-a</td><td>O. universa</td><td>500-630</td><td></td><td></td><td>18.13±0.26 (2SD, nAEI21 = 14)</td><td>18.06±0.18</td><td>11.9±0.4</td><td>71±7</td><td>7.52±0.01</td><td>11±7</td><td>0.02±0.01</td><td></td></tr><tr><td>WP07-a</td><td>P. obliquiculata</td><td>250-400</td><td></td><td></td><td>16.08±0.26 (2SD, nAEI21 = 14)</td><td>16.14±0.18</td><td>13.4±0.4</td><td>72±7</td><td>3.02±0.01</td><td>7±7</td><td>0.03±0.01</td><td></td></tr><tr><td>WP07-a</td><td>G. menandii</td><td>250-400</td><td></td><td></td><td>14.74±0.26 (2SD, nAEI21 = 14)</td><td>14.53±0.26 (2SD, nAEI21 = 14)</td><td>14.64±0.18</td><td>85±7</td><td>2.68±0.01</td><td>26±7</td><td>0.08±0.01</td><td></td></tr><tr><td>WP07-a</td><td>N. duerrei</td><td>250-400</td><td></td><td></td><td>16.91±0.31 (2SD, nAEI21 = 11)</td><td>16.99±0.31 (2SD, nAEI21 = 11)</td><td>16.95±0.22</td><td>86±7</td><td>3.66±0.01</td><td>42±7</td><td>0.63±0.01</td><td></td></tr><tr><td>WP07-a</td><td>G. tumida</td><td>250-400</td><td></td><td></td><td>16.45±0.26 (2SD, nAEI21 = 14)</td><td>16.32±0.26 (2SD, nAEI21 = 14)</td><td>16.39±0.18</td><td>10.6±0.4</td><td>58±7</td><td>2.55±0.01</td><td>16±7</td><td>0.10±0.01</td></tr><tr><td>806A</td><td>T. sacculifer (without sace)</td><td>250-400</td><td></td><td></td><td>17.53±0.36 (2SD, nAEI21 = 11)</td><td></td><td>17.53±0.36</td><td>14.40±0.4</td><td>77±7</td><td>3.89±0.01</td><td>7±7</td><td>0.15±0.01</td><td></td></tr><tr><td>807A</td><td>T. sacculifer (without sace)</td><td>250-400</td><td></td><td></td><td>18.38±0.21 (2SD, nAEI21 = 11)</td><td>18.17±0.21 (2SD, nAEI21 = 11)</td><td>18.28±0.15</td><td>12.54±0.4</td><td>87±7</td><td>4.24±0.01</td><td>17±7</td><td>0.09±0.01</td></tr><tr><td>A14</td><td>G. ruber (white ss)</td><td>250-400</td><td></td><td></td><td>19.17±0.24 (2SD, nAEI21 = 10)</td><td>19.17±0.24 (2SD, nAEI21 = 10)</td><td>19.42±0.17</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>A14</td><td>T. sacculifer (sace)</td><td>250-400</td><td></td><td></td><td>19.53±0.24 (2SD, nAEI21 = 10)</td><td>19.53±0.24 (2SD, nAEI21 = 10)</td><td>18.84±0.24 (2SD, nAEI21 = 10)</td><td>18.88±0.17</td><td></td><td></td><td></td><td></td></tr><tr><td>A14</td><td>T. sacculifer (without sace)</td><td>250-400</td><td></td><td></td><td>18.93±0.24 (2SD, nAEI21 = 10)</td><td>18.93±0.24 (2SD, nAEI21 = 10)</td><td>17.80±0.26 (2SD, nAEI21 = 14)</td><td>17.20±0.18</td><td></td><td></td><td></td><td></td></tr><tr><td>A14</td><td>O. universa</td><td>500-560</td><td></td><td></td><td>17.33±0.26 (2SD, nAEI21 = 14)</td><td>14.39±0.31 (2SD, nAEI21 = 11)</td><td>14.39±0.31</td><td>16.9±0.4</td><td>75±7</td><td>1.99±0.01</td><td>35±7</td><td>0.04±0.01</td></tr></tbody></table>

<footnote>a Uncertainties given in SD (see text). b When two measurements were carried out uncertainty was calculated with $\Delta = \sqrt{(1/\Sigma_i^2)(1/\Sigma_i^2)}$, with only one measurement the error was determined on reproducibility of the AEI21 standard. c Uncertainty given in SD, calculated on the reproducibility of Can-Wuethersoft (see text and Table S3).</footnote>
<table><caption>**Table 3.** Species-specific δ¹¹B~carbonate~–to–δ¹¹B~borate~ calibrations from literature and from our data.</caption><thead><tr><th>Species</th><th>Size fraction (µm)</th><th>Material</th><th>Instrument (original)</th><th>Regression method</th><th>δ¹¹B<sub>borate</sub> = f (δ¹¹B<sub>calcite</sub>)</th><th>n</th><th>Calibration number</th><th>Reference</th></tr></thead><tbody><tr><td>G. ruber</td><td>~ 380</td><td>Culture/core tops/plankton tows</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 9.52(±2.02)]/0.66(±0.11)</td><td></td><td></td><td>Henehan et al. (2013)</td></tr><tr><td>G. ruber</td><td>315–355</td><td>Core tops</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 11.78(±2.20)]/0.45(±0.16)</td><td></td><td></td><td>Raitzsch et al. (2018)</td></tr><tr><td>T. sacculifer</td><td>n.d.</td><td>Culture/artificial seawater enriched in B</td><td>N-TIMS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 3.94(±4.02)]/0.82(±0.22)</td><td></td><td></td><td>Sanyal et al. (2001) refitted Martínez-Botí et al. (2015)</td></tr><tr><td>T. sacculifer</td><td>315–355</td><td>Core tops</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 8.86(±5.27)]/0.59(±0.21)</td><td></td><td></td><td>Raitzsch et al. (2018)</td></tr><tr><td>O. universa</td><td>no effect</td><td>Core tops/plankton tows/sediment traps</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 0.42(±2.85)]/0.95(±0.17)</td><td></td><td></td><td>Henehan et al. (2016)</td></tr><tr><td>O. universa</td><td>>425</td><td>Core tops</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 5.69(±7.51)]/1.26(±0.39)</td><td></td><td></td><td>Raitzsch et al. (2018)</td></tr><tr><td>G. bulloides</td><td>300–355</td><td>Core tops/sediment trap</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 3.440(±4.584)]/1.074(±0.252)</td><td></td><td></td><td>Martínez-Botí et al. (2015)</td></tr><tr><td>G. bulloides</td><td>315–355</td><td>Core tops</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 3.81(±13.17)]/1.13(±0.72)</td><td></td><td></td><td>Raitzsch et al. (2018)</td></tr><tr><td>N. pachyderma</td><td>150–200</td><td>Core tops</td><td>MC-ICP-MS</td><td></td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 3.38</td><td></td><td></td><td>Yu et al. (2013)</td></tr><tr><td>G. ruber</td><td>250–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 9.11(±0.73)]/0.58(±0.91)</td><td>9</td><td>0</td><td>This study, Henehan et al. (2013)</td></tr><tr><td>G. ruber</td><td>250–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 1.23(±0.59)]/1.12(±1.67)</td><td>5</td><td>1</td><td>This study, Henehan et al. (2013)</td></tr><tr><td>G. ruber</td><td>250–455</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 11.73(±0.83)]/0.46(±0.34)</td><td>40</td><td>2</td><td>This study, Foster et al. (2008), Henehan et al. (2016), Raitzsch et al. (2018)</td></tr><tr><td>T. sacculifer (sace and without sacc)</td><td>250–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 6.06(±0.25)]/1.38(±1.33)</td><td>11</td><td>3</td><td>This study</td></tr><tr><td>T. sacculifer (sace and without sacc)</td><td>250–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 4.09(±0.86)]/0.83(±0.48)</td><td>27</td><td>4</td><td>This study, Foster et al. (2008), Raitzsch et al. (2018)</td></tr><tr><td>N. daturrei</td><td>300–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 0.34(±1.83)]/0.93(±0.55)</td><td>5</td><td>5</td><td>This study</td></tr><tr><td>N. daturrei</td><td>300–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 3.88(±0.65)]/0.72(±0.74)</td><td>9</td><td>6</td><td>This study, Foster et al. (2008)</td></tr><tr><td>O. universa</td><td>400–600</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 8.01(±23)]/1.38(±2.67)</td><td>5</td><td>7</td><td>This study</td></tr><tr><td>O. universa</td><td>400–600</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> + 2.08(±0.59)]/1.06(±0.13)</td><td>36</td><td>8</td><td>This study, Henehan et al. (2016), Raitzsch et al. (2018)</td></tr><tr><td>G. menardii</td><td>400–600</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 5.36(±1.36)]/0.65(±0.76)</td><td>5</td><td>9</td><td>This study</td></tr><tr><td>G. tumida</td><td>400–600</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 6.33(±2.52)]/0.57(±1.2)</td><td>3</td><td>10</td><td>This study</td></tr><tr><td>P. obliquiloculata</td><td>300–400</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 5.59(±4.16)]/0.59(±0.65)</td><td>6</td><td>11</td><td>This study, Henehan et al. (2016)</td></tr><tr><td>Deep-dweller</td><td>300–600</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 1.99(±0.13)]/0.82(±0.27)</td><td>22</td><td>12</td><td>This study</td></tr><tr><td>Deep-dweller</td><td>300–600</td><td>Core tops</td><td>MC-ICP-MS</td><td>Bootstrap</td><td>δ¹¹B<sub>borate</sub> = [δ¹¹B<sub>calcite</sub> – 0.18(±0.6)]/0.95(±0.13)</td><td>54</td><td>13</td><td>This study, Foster et al. (2008), Henehan et al. (2016), Raitzsch et al. (2018)</td></tr></tbody></table>

n.d.: not determined.
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Boron isotopic measurements of mixed-layer foraminifera plotted against $\delta^{11}\text{B}_{\text{borate}}$. $\delta^{11}\text{B}_{\text{borate}}$ was characterized by determination of the calcification depth of foraminifera utilizing data presented in Fig. 3. (a) *G. ruber*, (b) *T. sacculifer*, (c) *O. universa*. Monospecific calibrations (Table 3) and error bars on $\delta^{11}\text{B}_{\text{borate}}$ were derived utilizing the wild bootstrap code from Henehan et al. (2016), while errors on the $\delta^{11}\text{B}_{\text{carbonate}}$ for this study are reported as $2\sigma$ of measured AE121 standards during the session of the sample. Calibrations were also derived on the 250–400 size fraction for *G. ruber* and *T. sacculifer* (black dashed lines). Data reported on those graphs have been measured with an MC-ICP-MS.</figcaption></figure>

alone yields a slope of 1.3 ± 0.2 but is not statistically different to the results from Martínez-Boti et al. (2015b) (Table 3), ($p$>0.05). However, when compiled with published data using the bootstrap method a slope of 0.83 ± 0.48 is calculated, with a large uncertainty given the variability in the data. It is also noticeable that *T. sacculifer* (without sacc) samples from

the WEP have a $\delta^{11}\text{B}_{\text{carbonate}}$ close to expected $\delta^{11}\text{B}_{\text{borate}}$ and are significantly lower compared to the combined *T. sacculifer* of other sites ($p$ = 0.01, unpaired *t* test). When regressing data from the 250–400 µm fraction, our results are not significantly different from the regression through data that combine all size fractions (Fig. 4).
<figure><img src="image_7.png" /></figure>

**Figure 5.** Boron isotopic measurements of deep-dwelling foraminifera (δ¹¹Bcarbonate) plotted against δ¹¹Bborate. δ¹¹Bborate was constrained using foraminiferal calcification depths. (a) *P. obliquiloculata*, (b) *G. menardii*, (c) *N. dutertrei*, (d) *G. tumida*. (e) Compilation of deep dweller species. Monospecific calibrations are summarized in Table 3.
### 4.2.3 *O. universa* and deeper-dwelling species: *N. dutertrei*, *P. obliquiloculata*, *G. menardii*, and *G. tumida*

Our results for *O. universa* (Fig. 4), *N. dutertrei*, *P. obliquiloculata*, *G. menardii*, and *G. tumida* (Fig. 5) exhibit lower $\delta^{11}\text{B}_{\text{carbonate}}$ compared to the expected $\delta^{11}\text{B}_{\text{borate}}$ at their collection location. These data for *O. universa* are not statistically different from the Henehan et al. (2016) calibration ($p$>0.05). Our results for *N. dutertrei* expand upon the initial measurements presented in Foster et al. (2008). The different environments experienced by *N. dutertrei* in our study permit us to extend the range and derive a calibration for this species; the slope is close to unity (0.93 ± 0.55) and is not significantly different ($p$>0.05) from the *O. universa* calibration previously reported by Henehan et al. (2016) (e.g., 0.95 ± 0.17). The data for *P. obliquiloculata* exhibit the largest offset from the theoretical line. The range of $\delta^{11}\text{B}_{\text{borate}}$ from the samples we have of *G. menardii* and *G. tumida* is not sufficient to derive calibrations, but the $\delta^{11}\text{B}_{\text{carbonate}}$ measured for those species is in good agreement with the *N. dutertrei* calibration and Henehan et al. (2016) calibration for *O. universa*.

For *O. universa* and all deep-dwelling species, the slopes are not statistically different from Henehan et al. (2016) ($p$>0.05) and are close to unity. If data for deep-dwelling foraminiferal species are pooled together with each other and with data from Henehan et al. (2016) and Raitzch et al. (2018), we calculate a slope of 0.95 (±0.13) ($R^2$ = 0.7987, $p$<0.0001); if only our data are used, we calculate a slope that is not significantly different (0.82±0.27; $p$<0.05).

### 4.2.4 Comparison of core-top and culture data

The data for *G. ruber* and *T. sacculifer* from the core tops we measured are broadly consistent with previous published results. The calibrations between these core-top-derived estimates and culture experiments are not statistically different due to small datasets and uncertainties on the linear regressions (Henehan et al., 2013; Martinez-Boti et al., 2015; Raitzsch et al., 2018; Table 3). The sensitivities of the species analyzed are not statistically different and are close to unity.

## 4.3 B/Ca ratios

B/Ca ratios are presented in Table 2 and Fig. 6. B/Ca data are species-specific and consistent with previous work (e.g., compiled in Henehan et al., 2016) with ratios higher for *G. ruber* > *T. sacculifer* (sacc) > *T. sacculifer* (without sacc) > *P. obliquiloculata* > *O. universa* > > *G. menardii* > *N. dutertrei* > *G. tumida* > *G. inflata* > *N. pachyderma* > *G. bulloides* (Fig. 6). This study supports species-specific B/Ca ratios as previously published (Yu et al., 2007; Tripati et al., 2009, 2011; Allen and Hönisch, 2012; Henehan et al., 2016). Differences between surface- and

<figure><img src="image_8.png" /><figcaption>**Figure 6.** Box plots of B/Ca ratios for multiple foraminifera species, including *T. sacculifer* (this study; Foster et al., 2008; Ni et al; 2007; Seki et al., 2010), *G. ruber* (this study; Babila et al., 2014; Foster et al., 2008; Ni et al., 2007), *G. inflata*, *G. bulloides* (Yu et al., 2007), *N. pachyderma* (Hendry et al., 2009; Yu et al., 2013), *N. dutertrei* (this study; Foster et al., 2008), *O. universa*, *P. obliquiloculata*, *G. menardii*, and *G. tumida* (this study).</figcaption></figure>

deep-dwelling foraminifera are observed, with lower values and a smaller range for the deeper-dwelling taxa ($58–126 \mu\text{mol mol}^{-1}$ vs. $83–190 \mu\text{mol mol}^{-1}$ for shallow dwellers); however, the trend for the surface dwellers can also be driven by interspecies B/Ca variability. The B/Ca data for deep-dwelling taxa exhibit a significant correlation with $[\text{B(OH)}_4^-]/[\text{HCO}_3^-]$ ($p$<0.05) but no correlation with $\delta^{11}\text{B}_{\text{carbonate}}$, and temperature (Fig. S3). Surface-dwelling species have B/Ca ratios that exhibit significant correlations with $[\text{B(OH)}_4^-]/[\text{HCO}_3^-]$, $\delta^{11}\text{B}_{\text{carbonate}}$ and temperature. The sensitivity of B/Ca to $[\text{B(OH)}_4^-]/[\text{HCO}_3^-]$ is lower for deep-dwelling species compared to surface-dwelling species. When all the B/Ca data are compiled, significant trends are observed with $[\text{B(OH)}_4^-]/[\text{HCO}_3^-]$, $\delta^{11}\text{B}_{\text{carbonate}}$, and temperature (Fig. S3). When comparing data from all sites together, a weak decrease in B/Ca with increasing calcification depth is observed ($R^2$ = 0.11, $p$<0.05, Fig. S4). A correlation also exists between B/Ca and the water depths of the cores (not significant, Fig. S4).

# 5 Discussion

## 5.1 Sources of uncertainty relating to depth habitat and seasonality at studied sites

### 5.1.1 Depth habitats and $\delta^{11}\text{B}_{\text{borate}}$

Because foraminifera will record ambient environmental conditions during calcification, the accurate characterization of in situ data is needed not only for calibrations but also
to understand the reconstructed record of pH or pCO₂. The species we examined are ordered here from shallower to deeper depth habitats: *G. ruber* > *T. sacculifer* (sacc) > *T. sacculifer* (without sacc) > *O. universa* > *P. obliquiloculata* > *G. menardii* > *N. dutertrei* > *G. tumida* (this study; Birch et al., 2013; Farmer et al., 2007), although the specific water depth will vary depending on the physical properties of the water column of the site (Kemle-von Mücke and Oberhänsli, 1999). We note that calculation of absolute calcification depths can be challenging in some cases as many species often transition to deeper waters at the end of their life cycle prior to gametogenesis (Steinhardt et al., 2015).

We find that assumptions about the specific depth habitat a species of foraminifera is calcifying over, in a given region, can lead to differences of a few per mill in calculated isotopic compositions of borate (Fig. 3). Hence this can cause a bias in calibrations if calcification depths are assumed instead of being calculated (i.e., with δ¹⁸O and/or Mg/Ca). Factors including variations in thermocline depth can impact depth habitats for some taxa. At the sites we examined, most of the sampled species live in deeper depth habitats in the WEP relative to the Indian Ocean, which in turn is characterized by deeper depth habitats than in the Arabian Sea. In the tropical Pacific, *T. sacculifer* is usually found deeper than *G. ruber* except at sites characterized by a shallow thermocline, in which case both species tend to overlap their habitat (e.g., ODP Site 806 in the WEP which has a deeper thermocline than at ODP Site 847 in the eastern equatorial Pacific, EEP) (Rickaby et al., 2005). The difference in depth habitats for *T. sacculifer* and *N. dutertrei* between the WEP and EEP can be as much as almost 100 m (Rickaby et al., 2005).

### 5.1.2 Seasonality and in situ δ¹¹B<sub>borate</sub>

As discussed by Raitzsch et al. (2018), depending on the study area, foraminiferal fluxes can change throughout the year. Hydrographic parameters related to carbonate chemistry may change across seasons at a given water depth. We therefore recalculated the theoretical δ¹¹B<sub>borate</sub> using seasonal data for temperature and salinity and annual values for TA and DIC for each depth at each site. The GLODAP (2013) (Key et al., 2004) database does not provide seasonal TA or DIC values.

The low sensitivity of δ¹¹B<sub>borate</sub> to temperature and salinity means that calculated δ¹¹B<sub>borate</sub> values for each water depth at our sites were not strongly impacted (Fig. S1 in the Supplement). Thus, these findings support Raitzsch et al. (2018), who concluded that calculated δ¹¹B<sub>borate</sub> values corrected for seasonality were within the error of non-corrected values for each water depth. As Raitzsch et al. (2018) highlight, seasonality might be more important at high-latitude sites where seasonality is more marked; however, the seasonality of primary production will also be more tightly constrained due to the seasonal progression of win-

ter light limitation and intense vertical mixing and summer nutrient limitation.

Data for our sites suggest that most δ¹¹B<sub>borate</sub> variability we observe does not come from seasonality but from the assumed water depths for calcification. With the exception of a few specific areas such as the Red Sea (Henehan et al., 2016; Raitzsch et al., 2018), at most sites examined seasonal δ¹¹B<sub>borate</sub> at a fixed depth does not vary by more than ~0.2‰. We conclude that seasonality has a relatively minor impact on the carbonate system parameters at the sites we examined.

### 5.2 δ¹¹B, microenvironment pH, and depth habitats

It is common for planktonic foraminifera to have symbiotic relationships with algae (Gast and Caron, 2001; Shaked and de Vargas, 2006). The family Globigerinidae, including *G. ruber*, *T. sacculifer*, and *O. universa*, commonly has dinoflagellate algal symbionts (Anderson and Be, 1976; Spero, 1987). The families Pulleniatinidae and Globorotaliidae (e.g., *P. obliquiloculata*, *G. menardii*, and *G. tumida*) have chrysophyte algal symbionts (Gastrich, 1988) and *N. dutertrei* hosts pelagophyte symbionts (Bird et al., 2018). The relationship between the symbionts and the host is complex. Nevertheless, this symbiotic relationship provides energy (Hallock, 1981b) and promotes calcification in foraminifera (Duguay, 1983; Erez et al., 1983) by providing inorganic carbon to the host (Jørgensen et al., 1985).

There are several studies indicating that the δ¹¹B signatures in foraminiferal calcite reflect microenvironment pH (Jørgensen et al., 1985; Rink et al., 1998; Köhler-Rink and Kühl, 2000; Hönisch et al., 2003; Zeebe et al., 2003). Foraminifera with high photosynthetic activity and symbiont density, such as *G. ruber* and *T. sacculifer*, are expected to have a microenvironment pH higher than ambient seawater and a δ¹¹B<sub>carbonate</sub> higher than expected δ¹¹B<sub>borate</sub>, which is the case in our study and in previous studies (Foster et al., 2008; Henehan et al., 2013; Raitzsch et al., 2018). We also observed in our study that *N. dutertrei*, *G. menardii*, *P. obliquiloculata*, and *G. tumida* record a lower pH than ambient seawater, with δ¹¹B<sub>carbonate</sub> lower than expected δ¹¹B<sub>borate</sub>, and we suggest the results are consistent with lower photosynthetic activity compared to the mixed-layer dwelling species. These observations, based on δ¹¹B<sub>carbonate</sub> measurements, are in line with direct observations from Takagi et al. (2019) that show dinoflagellate-bearing foraminifera (*G. ruber*, *T. sacculifer*, and *O. universa*) tend to have a higher symbiont density and photosynthesis activity while *P. obliquiloculata*, *G. menardii*, and *N. dutertrei* have lower symbiont density and *P. obliquiloculata* and *N. dutertrei* have the lowest photosynthetic activity. In the same study, *P. obliquiloculata* exhibited minimum symbiont densities and levels of photosynthetic activity, which may explain why *P. obliquiloculata* exhibited the lowest microenvironment pH as recorded by δ¹¹B.
Based on the observations of Takagi et al. (2019), we can assume that the low $\delta^{11}$B of *O. universa* and *T. sacculifer* (without sacc) from the WEP is explained by low photosynthetic activity. It has been shown for *T. sacculifer* and *O. universa* that symbiont photosynthesis increases with higher insolation (Jørgensen et al., 1985; Rink et al., 1998) and the photosynthetic activity is therefore a function of the light level the symbionts received. This is, in a natural system, dependent on the depth of the species in the water column. For the purpose of this study, we do not consider turbidity which also influences the light penetration in the water column. In this case, photosynthetically active foraminifera living close to the surface should record microenvironment pH (thus $\delta^{11}$B) that is more sensitive to water depth changes. A deeper habitat reduces solar insolation, and as a consequence may lower symbiont photosynthetic activity, possibly reducing pH in the foraminifera's microenvironment. This is supported by the significant trend observed between $\Delta^{11}$B and the calcification depth for *G. ruber* and *T. sacculifer* at our sites (Fig. S2), where microenvironment pH decreases with calcification depth. We observe a significant decrease in $\delta^{11}$B in the WEP for *T. sacculifer* (without sacc) compared to the other sites ($p<0.05$). Additionally, the $\Delta^{11}$B ($\Delta^{11}$B=$\delta^{11}$B$_{carbonate}$-$\delta^{11}$B$_{borate}$) of *G. ruber* and *T. sacculifer* (without sacc and sacc) is significantly lower in the WEP compared to the other sites ($p<0.05$).

*T. sacculifer* has the potential to support more photosynthesis due to its higher symbiont density, and higher photosynthetic activity compared to other species, which may support higher symbiont-host interactions (Takagi et al., 2019). These results would be consistent with a greater sensitivity of *T. sacculifer*'s photosynthetic activity with changes in insolation-water depth. To test if the low $\delta^{11}$B signature of *T. sacculifer* (without sacc) in the WEP is related to a decrease in light at greater water depth, we have independently calculated the calcification depth of the foraminifera based on various light insolation culture experiments (Jørgensen et al., 1985) and the microenvironment $\Delta$pH derived from our data (Fig. 7a and b). This exercise showed that the low $\delta^{11}$B of *T. sacculifer* (without sacc) from the WEP can be explained by the reduced light environment due to a deeper depth habitat in the WEP (Fig. 7b). It can also be noted that *T. sacculifer* exhibits the largest variation in symbiont density versus test size (Takagi et al., 2019), suggesting that lower size fraction reported for the WEP (250–400 µm) compared to the 300–400 µm at the other sites can be related to a decrease in photosynthetic activity and a lower $\delta^{11}$B. Unfortunately, no weight-per-shell data were determined on foraminifera samples to constrain whether test size was significantly different across sites. Future studies could use shell weights to test these relationships.

When the same approach of independently reconstructing calcification depth based on culture experiments is applied to *O. universa*, the boron data suggest a microenvironment pH of 0.10 to 0.20 lower than ambient seawater pH, which

would be in line with the species living deeper than 50 m (light compensation point (Ec); Rink et al., 1998), which is consistent with our calcification depth reconstructions. The low $\delta^{11}$B$_{carbonate}$ of *O. universa* compared to *T. sacculifer* for the similar calcification depth at some sites (e.g., FC-02a, WP07-a) might reflect differences in photosynthetic potential between the two species, which is supported by observation of a lower photosynthetic potential in *O. universa* than in *T. sacculifer* (Tagaki et al., 2019).

Microenvironment $\Delta$pH based on our $\delta^{11}$B$_{carbonate}$ data was calculated for the rest of the species. We observed that microenvironment $\Delta$pH is higher in *T. sacculifer* > *G. ruber* > *T. sacculifer* (without sacc – WEP) > *O. universa*, *N. dutertrei*, *G. menardii*, *G. tumida* > *P. obliquiloculata*. These results are in line with the photosymbiosis findings from Takagi et al. (2019). Also, the higher $\delta^{11}$B data from the west African upwelling published by Raitzsch et al. (2018) for *G. ruber* and *O. universa* may reflect a higher microenvironment pH due to a relatively shallow habitat, higher insolation, and high rates of photosynthesis by symbionts. This could highlight a potential issue with calibration when applied to sites with different oceanic regimes as the $\delta^{11}$B species-specific calibrations could also be location-specific for the mixed dweller species.

Microenvironment pH for *N. dutertrei*, *G. menardii*, and *G. tumida* is similar to *O. universa* and suggests a threshold for a respiration-driven $\delta^{11}$B signature. This threshold can be induced by a change of photosynthetic activity at lower light intensity in deeper water and/or differences in symbiont density and/or by the type of symbionts at greater depth (non-dinoflagellate symbionts). We also note that *P. obliquiloculata*, which has the lowest symbiont density and photosynthetic activity (Takagi et al., 2019), has the lowest microenvironment pH compared to other deeper-dweller species, supporting our hypothesis that respiration can control microenvironment pH. The deep-dwelling species sensitivity of $\delta^{11}$B$_{carbonate}$ to $\delta^{11}$B$_{borate}$ with values close to unity might also be explained by relatively stable respiration-driven microenvironments, as the deeper-dweller species do not experience large changes of insolation (e.g., photosynthesis), thereby making them a more direct recorder of environmental pH.

### 5.3 $\delta^{11}$B sensitivity to $\delta^{11}$B$_{borate}$ and relationship with B/Ca signatures

In inorganic calcite, $\delta^{11}$B$_{carbonate}$ and B/Ca data have shown to be sensitive to precipitation rate with a higher precipitation rate increasing $\delta^{11}$B$_{carbonate}$ (Farmer et al., 2019) and B/Ca (Farmer et al., 2019; Gabitov et al., 2014; Kaczmarek et al., 2016; Mavromatis et al., 2015; Uchikawa et al., 2015). A recent study from Farmer et al. (2019) has proposed that in foraminifera at higher precipitation rates, more borate ions may be incorporated into the carbonate mineral, while more boric acid may be incorporated at lower precipitation rates.
<figure><img src="image_9.png" /><figcaption>**Figure 7.** (a) Box plot showing the calculated microenvironment pH difference (Δ microenvironment pH) between microenvironment and external pH based on the δ¹¹B data. (b) This figure shows that a decrease in insolation can explain the low δ¹¹B from the WEP. Light penetration profile in the western Pacific, with E₀ in the WEP of 220 J s⁻¹ m⁻² (Weare et al., 1981) and a light attenuation coefficient of 0.028 (m⁻¹) (Wang et al., 2008). Theoretical depths were calculated for a decrease in microenvironment pH of ΔpH₁ = -0.02 (e.g., WP07-a); ΔpH₁ = -0.04 (e.g., A14), ΔpH₂ = -0.06 (e.g., 806A). Light penetration corresponding to Ec is ~ 12%, ΔpH₀ ~ 7%, ΔpH₁ ~ 5%, ΔpH₂ ~ 1%, and respective calcification depths are 75, 90, 110, and 150 m. The grey band is the calcification depth calculated that explains the Δ microenvironment pH from ΔpH₀ to ΔpH₂. Dotted lines show the range of the calcification depth for *T. sacculifer* (without sacc) in the WEP utilized in this study.</figcaption></figure>

The authors also suggest this may explain low sensitivities of culture experiments.

When combining all literature data, *T. sacculifer* and *G. ruber* have sensitivities of δ¹¹Bcarbonate to δ¹¹Bborate of 0.83±0.48 and 0.46±0.34, respectively, in line with previous literature and paleo-CO₂ reconstructions. Also, if we only take into account our data, and the observation that the sensitivity of δ¹¹Bcarbonate to δ¹¹Bborate is not statistically different from unity for most of the species investigated, we can speculate that for these taxa, changes in precipitation rate and contributions of boric acid are not likely to be important. If considering only the data from this study, *G. ruber* (1.12±1.67) and *T. sacculifer* (1.38±1.35) present higher sensitivities of δ¹¹Bcarbonate to δ¹¹Bborate. We can then again speculate that the observed high values for δ¹¹Bcarbonate at high seawater pH can be due to higher precipitation rates. We note this could also be consistent with the higher sensitivity of B/Ca signatures in these two surface dwelling species to ambient [B(OH)₄⁻]/[HCO₃⁻] relative to deeper-dwelling species. Those interspecific differences still remain to be explained; however, part of this variability is likely due to changes in the carbonate chemistry of the microenvironment resulting in changing competition between carbonate and bicarbonate. A caveat is that we can not exclude specific biological processes and that in taxa with a non-respiration-driven microenvironment, changes in day/night calcification ratios also impact observed values. As indicated by Farmer et al. (2019), studies of calcite precipitation rates in foraminifera may help to improve our understanding of the fundamental basis of boron-based proxies.

## 5.4 Evaluation of species for pH reconstructions and water depth pH reconstructions

This data set allows us to reassess the utility of boron-based proxies for the carbonate system. The main aim of using boron-based proxies relates to the reconstruction of past oceanic conditions, specifically pH and pCO₂. Mixed-layer species (e.g., *G. ruber* and *T. sacculifer*) are potential archives for atmospheric CO₂ reconstructions. Other species can shed light on other aspects of the carbon cycle including the physical and biological carbon pumps.

There are a few main inferences we can make. When integrated with published data, the sensitivities of δ¹¹Bcarbonate to δ¹¹Bborate for *G. ruber* and *T. sacculifer* are similar to those in previous studies (Martínez-Boti et al., 2015b; Raitzsch et al., 2018), which supports the fidelity of previous paleo-reconstructions that use published calibrations between δ¹¹Bcarbonate and δ¹¹Bborate. The regression we have made for *G. ruber* supports a decrease in δ¹¹Bcarbonate with decreasing size fractions (offset of -0.4‰, *p*>0.05) with the sensitivity of δ¹¹Bcarbonate to δ¹¹Bborate not being statistically different from a higher size fraction (*p*<0.05). The variability in our weight per shell for our *G. ruber*, based on data from Henehan et al. (2013), can potentially imply a deviation down to 1‰ relative to the calibration line from Henehan et al. (2013), which can be in line with the maximum deviation observed in our data (~ 1.2‰) and not inconsistent with a size effect explaining the offset in our calibration. Our δ¹¹Bcarbonate data and the sensitivity to δ¹¹Bborate of *O. universa* support previous data from Henehan et al. (2016). *N. dutertrei* δ¹¹Bcarbonate data span a large range of pH, al-
<figure><img src="image_10.png" /><figcaption>**Figure 8.** Water depth pH profiles reconstructed at every site applying the monospecific calibrations derived from our results (Table 3). The figure shows measured δ¹¹Bcalcite, δ¹¹Bborate calculated according to different calibrations (see Table 3 and text), calculated pH based on δ¹¹B (pH<sub>δ¹¹B</sub>), and pCO₂ calculated from pH<sub>δ¹¹B</sub> and alkalinity.</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**Figure 9.** Evaluation of the reconstructed parameters, δ<sup>11</sup>B<sub>borate</sub>, pH, and pCO<sub>2</sub> versus in situ parameters calculated in Fig. 8 (based on δ<sup>11</sup>B and alkalinity). The recalculated parameters are consistent with in situ data, except for *G. ruber*, and this variability might be explained by the different test sizes within measured size fractions.</figcaption></figure>

lowing us to derive a robust calibration with δ<sup>11</sup>B<sub>borate</sub>. It
remains premature to assume that a unique calibration with
a slope of ~ 0.9 can be used for all deeper-dwelling species.
More data are needed for *P. obliquiloculata*, *G. menardii*, and
*G. tumida* to robustly test this assertion.

In order to derive accurate reconstructions of past ambient
pH and pCO2, accurate species-specific calibrations need to
be used that are constrained by core tops or samples from
similar types of settings (Figs. 8, 10, S6). Lower δ<sup>11</sup>B sig-
natures in T. sacculifer (without sacc) are observed in the
WEP, which may be explained by the deeper depth habitat
for this taxa, as lower light levels might reduce symbiont
photosynthetic activity. Also, we show that a correction is
needed for T. sacculifer (without sacc) in the WEP in order
to accurately reconstruct atmospheric CO2. When applying
calibrations nos. 2 and 4 to T. sacculifer and G. ruber (com-
pilation of all data, Table 3), our data show more variability,
especially for G. ruber which leads to the larger mismatch
compared to in situ parameters. The greater divergence of
reconstructed values from in situ measurements is observed
at site WPO7-01 for both T. sacculifer (without sacc) and
G. ruber. More data would be needed to determine a proper
correction for both species and a core-top study will be de-
terminant for future downcore reconstructions, especially in
the WEP. We also find that for two species the boron isotope
proxy is a relatively straightforward recorder of ambient pH,
with sensitivities close to unity observed for O. universa and
N. dutertrei.

There is also promise in using multiple species in a sam-
ple from different hydrographic regimes to reconstruct verti-
cal profiles of pH and pCO2. We are able to reproduce pH
and pCO2 profiles from multiple sites with different water
column structures (Fig. 8) with those reconstructions within
error of the in situ values, for most sites. In order to avoid
circularity, to validate these calibrations, we recalculated am-
bient pH and pCO2 by first excluding site-specific data and
then recalculating species-specific calibrations, followed by
application to each specific site. The comparison of the two

methods, first using all the data to derive the calibration and
recalculate pH and pCO₂ (circular) and second by exclud-
ing the site of interest, deriving calibrations, and calculat-
ing pH and pCO₂ (not circular), does not show significant
differences and validates the robustness of the calibrations
(Fig. S5). We utilized the calibrations derived from our data
for *G. ruber* (calibration nos. 1 and 2, Table 3), *T. sacculifer*
(calibration nos. 3 and 4, Table 3), *O. universa* (calibration
no. 8, Table 3), and *P. obliquiloculata* (calibration no. 11,
Table 3), and for *N. dutertrei*, *G. tumida*, and *G. menardii*
we utilized the calibration on the compilation of the deep
dwellers (calibration no. 13, Table 3). Results are shown in
Fig. 8 and evaluated in Fig. 9. For *G. menardii*, more data
would be helpful to provide additional constraints. Results
for *G. ruber* are the most scattered, potentially due to dif-
ference in test sizes (Henehan et al., 2013) or depth habitat.
Results reaffirm the importance of working with narrow size
fractions (Henehan et al., 2013), the utilization of calibra-
tions derived from the same size fraction, or use of offsets to
take into account this size fraction effect and the importance
of core-top studies before paleo-application.

**6 Conclusions and future implications**

Our study has extended the boron isotope proxy with data for new species and sites. The work supports previous work showing that depth habitats of foraminifera vary depending on the oceanic regime, and this can impact boron isotope sig-natures. Low δ¹¹B values in the WEP compared to other re-gions for *T. sacculifer* (without sacc) may be explained by a reduction in microenvironment pH due to a deeper depth habitat associated with reduced irradiance and thus photo-synthetic activity.

In order to accurately develop downcore reconstructions,
constraining the depth habitat using core-top studies is im-
portant, as the same species can record the seawater pH at
different water depths, potentially introducing biases when
comparing between different locations. Also, we speculate
that a change of the thermocline depth in the past could imply variations in depth habitat and introduce biases in the reconstructions, but further work is needed to test this assertion.

The sensitivity of $\delta^{11}\text{B}_{\text{carbonate}}$ to pH is in line with previously published data for *T. sacculifer* and *G. ruber*. The sensitivity of $\delta^{11}\text{B}_{\text{carbonate}}$ to pH of *O.universa* (mixed dweller), *N. dutertrei*, *G. menardii*, and *G. tumida* (deep dwellers) is similar, but more data are needed to fully determine those sensitivities. The similarity of boron isotope calibrations for deep-dwelling taxa might be related to similar respiration-driven microenvironments.

Reconstruction of seawater pH and carbonate system parameters is achievable using foraminiferal $\delta^{11}\text{B}$, but additional core-top and down-core studies reconstructing depth profiles will be needed in order to further verify calibrations published to date. Past pH and $\text{pCO}_2$ water depth profiles can potentially be created by utilizing multiple foraminiferal species in concert with taxon-specific calibrations for similar settings. This approach has much potential for enhancing our understanding of the past workings of the oceanic carbon cycle and the biological pump.

*Data availability.* Data is available at NOAA (https://www.ncdc.noaa.gov/paleo/study/30352, Guillermic et al., 2020).

*Supplement.* The supplement related to this article is available online at: https://doi.org/10.5194/bg-17-3487-2020-supplement.

*Author contributions.* RE and AT wrote the proposals that funded the work. AT and FC provided the samples. MG, SM, and AT contributed to the experimental design. AV helped for sample preparation. MG and SM contributed to developing the method of boron isotope analysis. MG performed the measurements with assistance from SM. MG conducted the data analysis. MG drafted the paper, which was edited by all authors. Interpretation was led by MG, AT, and SM with input from RE, AV, and FC.

*Competing interests.* The authors declare that they have no conflict of interest.

*Acknowledgements.* The authors wish to thank Jesse Farmer for his valuable and detailed comments on the current paper and a previous version of the paper. We wish to thank Michael Henehan for helpful discussion, comments on the manuscript, and help with the code. We also want to thank the anonymous reviewer for helpful comments. We thank Lea Bonnin for assistance with picking samples; the IODP repository for provision of samples; the Tripati Laboratory (UCLA) for their technical support; Mervyn Greaves and Madeleine Bohlin (University of Cambridge) for technical support and use of laboratory space; Yoan Germain, Emmanuel Ponzevera, and Oanez Lebeau for technical support and use of laboratory space in Brest; and Jill Sutton for helpful conversation about

the manuscript. This research is supported by DOE BES grant DE-FG02-13ER16402, by the International Research Chair Program that is funded by the French government (LabexMer ANR-10-LABX-19-01), and IAGC student research grant 2017.

*Financial support.* This research has been supported by the DOE BES grant (grant no. DE-FG02-13ER16402), the LabexMer (grant no. ANR-10-LABX-19-01), and the IAGC (grant no. IAGC student grant 2017).

*Review statement.* This paper was edited by Markus Kienast and reviewed by Jesse Farmer, Michael Henehan, and one anonymous referee.

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