# Exploring the Potential for Time-Variable Vital Effects in Planktic Foraminifera, Globigerinoides Ruber

R. Brown, Thomas B. Chalk, Megan Wilding, Bastian Hambach, P. Wilson, G. Foster

► To cite this version:

R. Brown, Thomas B. Chalk, Megan Wilding, Bastian Hambach, P. Wilson, et al. Exploring the Potential for Time-Variable Vital Effects in Planktic Foraminifera, Globigerinoides Ruber. Paleooceanography and Paleoclimatology, 2025, 40 (9), pp.e2024PA005078. 10.1029/2024PA005078. hal-05450601

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# Paleoceanography and Paleoclimatology®

## RESEARCH ARTICLE

10.1029/2024PA005078

**Key Points:**

* Stable oxygen, carbon, and boron isotope ratios are used to evaluate "vital effects" in the planktic foraminifera *Globigerinoides ruber*

* No significant changes in "vital effects" are observed between the Plio-Pleistocene Transition and the Holocene

* *Globigerinoides ruber* specific boron isotope proxy calibrations based on modern specimens are applicable to the Plio-Pleistocene Transition

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

R. M. Brown,
brown@cerege.fr

**Citation:**

Brown, R. M., Chalk, T. B., Wilding, M. R., Hambach, B., Wilson, P. A., & Foster, G. L. (2025). Exploring the potential for time-variable vital effects in planktic foraminifera, *Globigerinoides ruber*. *Paleoceanography and Paleoclimatology, 40*, e2024PA005078. https://doi.org/10.1029/2024PA005078

Received 5 DEC 2024
Accepted 28 AUG 2025

**Author Contributions:**

**Conceptualization:** R. M. Brown,
T. B. Chalk, Bastian Hambach,
G. L. Foster

**Formal analysis:** R. M. Brown

**Funding acquisition:** Bastian Hambach,
G. L. Foster

**Investigation:** R. M. Brown, Megan
R. Wilding, Bastian Hambach,
P. A. Wilson, G. L. Foster

**Methodology:** R. M. Brown, T. B. Chalk,
Bastian Hambach, G. L. Foster

**Resources:** Megan R. Wilding,
Bastian Hambach, P. A. Wilson,
G. L. Foster

© 2025. The Author(s).
This is an open access article under the
terms of the Creative Commons
Attribution License, which permits use,
distribution and reproduction in any
medium, provided the original work is
properly cited.

<figure><img src="image_2.png" /></figure>

## Exploring the Potential for Time-Variable Vital Effects in Planktic Foraminifera, *Globigerinoides Ruber*

R. M. Brown¹,² ID, T. B. Chalk¹,² ID, Megan R. Wilding¹, Bastian Hambach¹ ID, P. A. Wilson¹ ID, and G. L. Foster¹ ID

¹School of Ocean and Earth Science, University of Southampton, Waterfront Campus, National Oceanography Centre Southampton SO14 3ZH, Southampton, UK, ²Aix Marseille University, CNRS, IRD, INRAE, CEREGE, Technopole Environnement Arbois-Méditerranée BP 80 13545 Aix-en-Provence, Aix-en-Provence, France

**Abstract** The boron isotopic composition (δ¹¹B) of planktic foraminifera is a powerful proxy for reconstructing past seawater pH and thus atmospheric CO₂. *Globigerinoides ruber* has been used extensively to generate high resolution δ¹¹B-CO₂ records for the last 3.5 million years. However, these records rely on the assumption of stability in the empirical δ¹¹B<sub>ruber</sub>-to-δ¹¹B<sub>borate</sub> calibration, which was established using culture and core-top data obtained from modern specimens. It remains unclear whether this modern calibration is applicable on geological timescales. Here, we investigate this in a number of ways. Firstly, we examine the depth distribution of *G. ruber* during the Plio-Pleistocene Transition. We then report a suite of geochemical proxies including δ¹¹B for *G. ruber* across a range of test sizes and morphotypes and finally compare *G. ruber* δ¹¹B reconstructions of seawater borate ion, pH and CO₂ to those from *Trilobatus trilobus*, another surface dwelling planktic foraminifera species. Taking these data together, we find no evidence for a change in *G. ruber* vital effects or depth habitat during the Plio-Pleistocene Transition with respect to those of the Holocene. We conclude that the utilization of the present δ¹¹B<sub>ruber</sub>-to-δ¹¹B<sub>borate</sub> calibration is suitable for at least the last 3 million years.

## 1. Introduction

The boron isotopic composition (δ¹¹B) of planktic foraminifera is now widely used to reconstruct atmospheric CO₂ throughout the Cenozoic (Guillermic et al., 2022; Henehan et al., 2019; Hönisch et al., 2009; Rae et al., 2021). This is possible because of the pH dependent abundance and distinct isotopic composition of the dominant aqueous species of boron: borate ion (B(OH)₄⁻) and boric acid (B(OH)₃; Foster & Rae, 2016; Hemming & Hanson, 1992). Borate ions are predominantly incorporated into the precipitating calcite of the foraminiferal test, due to its negative charge and lattice compatibility allowing it to substitute for carbonate (DeCarlo et al., 2018) or bicarbonate ion (Hemming & Hanson, 1992) in the calcite lattice:

$$0.5CaCO_3 + B(OH)_4^- \rightleftharpoons Ca_{0.5}(HBO_4^-) + 0.5CO_3^{2-} \quad (1)$$

$$CaCO_3 + B(OH)_4^- \rightleftharpoons Ca(HBO_3) + HCO_3^- + H_2O \quad (2)$$

By measuring the δ¹¹B of planktic foraminifera calcite tests (δ¹¹B<sub>foram</sub>), we access a record of the δ¹¹B of borate of seawater (δ¹¹B<sub>borate</sub>) and can thus reconstruct changes in surface ocean pH. However, small differences between δ¹¹B<sub>borate</sub> of the ambient seawater and δ¹¹B measured in planktic foraminifera (as reviewed in Foster & Rae, 2016, Figure 1) imply the presence of at least one secondary control.

These differences between δ¹¹B<sub>borate</sub> and δ¹¹B<sub>foram</sub> can be attributed to "vital effects" arising from foraminiferal physiological processes interacting with and modifying the immediate environment around the precipitating test (Hönisch et al., 2003; Spero, 1992; Zeebe et al., 2003, 2008). While various experimental studies suggest that the inorganic precipitation of calcite results in rate dependent fractionation between δ¹¹B<sub>borate</sub> and δ¹¹B<sub>calcite</sub> (Noireaux et al., 2015; Uchikawa et al., 2015), δ¹¹B of benthic foraminifera show a close approximation to δ¹¹B<sub>borate</sub> (Figure 1, Rae et al., 2011). This suggests these inorganic experiments are not good analogs of the processes occurring in foraminifera (Henehan et al., 2022), that may for instance, involve transient metastable phases (e.g., Jacob et al., 2017) which have not currently been explored in the inorganic experiments.

The δ¹¹B vital effect behavior in planktic foraminifera as illustrated through differences between δ¹¹B<sub>foram</sub> and δ¹¹B<sub>borate</sub>, and the species specific δ¹¹B<sub>foram</sub> to δ¹¹B<sub>borate</sub> relationships evident in Figure 1, can be described by a
**Supervision:** T. B. Chalk, Megan

R. Wilding, Bastian Hambach,

P. A. Wilson, G. L. Foster

**Visualization:** R. M. Brown

**Writing – original draft:** R. M. Brown

**Writing – review & editing:**

R. M. Brown, T. B. Chalk, Megan

R. Wilding, Bastian Hambach,

P. A. Wilson, G. L. Foster

Diffusive Boundary Layer (DBL) model (Figure 2; Jørgensen & Revsbech, 1985; Wolf-Gladrow et al., 1999; Zeebe et al., 1999, 2003). The DBL-model suggests that, because a typical planktic foraminifera is less than 1,000 µm (1 mm) in diameter, smaller than the size of the smallest turbulent eddies in the surface ocean, transport of solutes near the surface of the foraminifera is dominated by diffusion (Wolf-Gladrow et al., 1999; Zeebe et al., 1999, 2003). The composition of the calcite test thus reflects conditions of this microenvironment, which although ultimately connected to the ambient seawater, is continuously impacted by the physiology of the living foraminifera. The photosynthesis of symbionts in symbiont-bearing foraminifera is important in this regard as CO₂(aq) is consumed, increasing pH locally, resulting in the δ¹¹B₃ₘₐₗ recording values offset positively relative to the ambient δ¹¹B₃ₘₐₗ outside of the microenvironment (Rink et al., 1998, Figures 1 and 2). Conversely, the absence of symbionts in some planktic foraminifera species leaves respiration and calcification dominating, with both processes elevating CO₂(aq) and reducing the local pH, causing the δ¹¹B₃ₘₐₗ to be more negative than the ambient δ¹¹B₃ₘₐₗ (Figures 1 and 2). For symbiont-barren, slow growing benthic foraminifera, rates of respiration and calcification are lower than rates of diffusion such that there is little or no difference between local and ambient pH and there is no resolvable difference in δ¹¹B₃ₘₐₗ and δ¹¹B₃ₘₐₗ (Figure 1, Foster & Rae, 2016). Orbulina universa is an exception to this pattern, falling below the 1:1 line in spite of the presence of dinoflagellate symbionts (Figure 1). Henehan et al. (2016) suggest the apparent acidification of the O. universa microenvironment is a consequence of it inhabiting a large depth range (0–200 m; e.g. Fairbanks, 1989; Rebotim et al., 2017) in comparison to other symbiont bearing foraminifera such as *T. trilobus* (0–100 m) and *G. ruber* (0–70 m) whereby it calcifies at light levels that are likely below the photosynthetic compensation depth such that any increase in pH from photosynthesis is canceled out by comparatively relatively higher rates of respiration and calcification (Henehan et al., 2016). These δ¹¹B based observations are supported by limited micro-electrode studies (e.g., Glas et al., 2012; Jørgensen et al., 1985; Rink et al., 1998) and careful work with foraminiferal cultures has shown that these differences are persistent, systematic, and can relatively easily be accounted for with species specific calibrations to describe their gradients compared to that predicted from δ¹¹B₃ₘₐₗ (Henehan et al., 2013, 2016; Sanyal et al., 1996, 2001).

The DBL-model suggests that vital effects are driven by the chemical offsets resulting from the foraminiferal biology interacting with its environment. A little explored possibility is the potential for δ¹¹B-related foraminiferal vital effects to change over time. For instance, they might be expected to vary if changes in the thermal niche of the foraminifera (e.g., water temperature) altered the balance of respiration, photosynthesis and calcification, given that all these processes are temperature and pressure dependant and thus vary with habitat and/or species (Boscolo-Galazzo et al., 2021; Lombard et al., 2009, 2010; Woodhouse et al., 2021, 2023).

It has been hypothesized that warmer Pliocene water temperatures caused a habitat migration to deeper waters and/or a change in the underlying foraminifera biology (a shift in the balance of respiration, photosynthesis, and calcification) that altered the δ¹¹B₃ₘₐₗ-δ¹¹B₃ₘₐₗ relationship for *Globingeroidies ruber* (Dyez et al., 2018). The principal evidence for an evolution in the δ¹¹B-vital effect of *G. ruber* is that during the Plio-Pleistocene Transition the available δ¹¹B-CO₂ records from *G. ruber* estimate atmospheric CO₂ to be significantly higher (~50 ppm) than those from the planktic foraminifera *Trilobatus trilobus* (formerly *T. sacculifer*, Figure 3; Bartoli et al., 2011; Dyez et al., 2018; Hönisch et al., 2023; Martínez-Botí, Foster, et al., 2015). Dyez et al. (2018) discuss at great detail how these offsets in CO₂ between *T. trilobus* and *G. ruber* for the Plio-Pleistocene Transition remain when equivalent assumptions are made regarding ocean chemistry are used to calculate CO₂ The Plio-Pleistocene Transition is a period of intense climate change associated with major changes in CO₂ and is often used as a partial analog period for future climate change (Lunt et al., 2008, 2010; Martínez-Botí, Foster, et al., 2015). Understanding the origin for the disagreement between published *T. trilobus* and *G. ruber* CO₂ estimates is therefore important for constraining the role of CO₂ in the global climate system, testing future climate model predictions and refining estimates of climate sensitivity.

*G. ruber* originates in the Early Pliocene and is a “workhorse” planktic foraminifera, generating thousands of paleo-climate records. However, there are multiple morphotypes (8) of *G. ruber* that show small but significant changes in geneology, morphology, geochemistry and ecology (Kearns et al., 2023; Morard et al., 2019). These changes in morphology between morphotypes are gradual and sometimes difficult to determine (Kearns et al., 2023). Failing to account for these differences in morphology, and thus ecology, can lead to misinterpreting paleoclimate records. The most discussed morphotypes of *G. ruber* are the sensu stricto (ss) and sensu lato (sl) morphotypes (e.g., Antonarakou et al., 2015; Aurahs et al., 2009, 2011; Carter et al., 2017; Kearns et al., 2023; Wang, 2000). The relative geochemistry of the ss and sl morphotypes suggest that while both live in the upper
<figure><img src="image_3.png" /><figcaption>**Figure 1.** Previously published $\delta^{11}\text{B}_{\text{borate}}-\delta^{11}\text{B}_{\text{calcite}}$ calibrations for foraminifera, as characterized via MC-ICPMS, adapted from (Henehan et al., 2016). Calibrations for G. ruber (Foster, 2008; Henehan et al., 2013) based on cultured (filled) and core top (empty) specimens, T. trilobus (yellow, Sanyal et al., 2001), Globigerina bulloides (green, Martínez-Botí, Marino et al., 2015), Globorotalia inflata (blue, Henehan et al., 2016), Orbulina universa (purple, Henehan et al., 2016) and epifaunal benthic foraminifera (black, Rae et al., 2011). Bold lines indicate fitted linear model using a SIMEX regression (Lederer & Seibold, 2019).</figcaption></figure>

water column (0–200 m), sl occupies a deeper habitat in the water column than that of ss (Kearns et al., 2023; Steinke et al., 2005; Wang, 2000). These morphotype issues are compounded by extensive cryptic morphospeciation that may or may not be associated with new ecologies (Aurahs et al., 2009, 2011). In contrast, *T. trilobus*, another “workhorse” planktic foraminifera shows no cryptic speciation and has only two easily distinguishable morphotypes: one with a large flattened final chamber and one without (Spezzaferri et al., 2015). *T. trilobus* originated at the beginning of the Neogene and, is believed to be more ecologically stable on million-year timescales compared to *G. ruber* given the relative lack of morphotype diversity and cryptic speciation (Dyez et al., 2018).

Previous attempts to investigate foraminiferal vital effects have studied shell size dependent changes in geochemical composition (e.g., Edgar et al., 2017; Ezard et al., 2015; Si & Aubry, 2018). The basis of this approach is that many aspects of foraminiferal biology (e.g., rates of respiration, photosynthesis and calcification) vary with test size (Henehan et al., 2010, 2017; Lombard et al., 2009). Therefore, analyzing changes in geochemical composition as a function of test size through time can provide insight into vital effects and the potential for foraminiferal evolution to impact them. Thus, temporal change in test size-dependent geochemical composition may preclude a straightforward application of the modern vital-effect calibration (Edgar et al., 2017; Ezard et al., 2015; Si & Aubry, 2018; Woodhouse et al., 2021, 2023). Previous attempts have been made to examine the relationship between test size and stable carbon ($\delta^{13}\text{C}$) and oxygen ($\delta^{18}\text{O}$) isotope ratios (Edgar et al., 2017; Ezard et al., 2015; Friedrich et al., 2012) and $\delta^{11}\text{B}$ (Henehan et al., 2013; Hönisch et al., 2003;
<figure><img src="image_4.png" /></figure>

**Figure 2.** Schematic diagram of the diffusive boundary model adapted from (Wolf-Gladrow et al., 1999; Zeebe et al., 1999, 2003). Here, the foraminifera is assumed spherical. $R_1$ indicate radius of the outer foraminiferal chamber. $R_2$ is the edge of the symbiont halo (dashed line). Lines coming out from the foraminifera represent the spines. Green shading indicates photosynthesizing symbiotic algae located within the symbiotic halo. Respiration and calcification occur within the radius of foraminiferal chamber ($R_1$). Photosynthesis occurs within the symbiont halo, between $R_1$ and $R_2$. CO$_2$ diffuses through the pores (small dots) on the shell. Beyond $R_2$ conditions are those of the ambient seawater (e.g., where $\delta^{11}\text{B}_{\text{borate}}$ corresponds to local pH).

Shuttleworth, 2020) in the modern and compared with the Late Pleistocene, but so far, such relationships are unknown for *G. ruber* through the last 3 million years.

Here, we investigate potential changes to vital effects by measuring the variation of $\delta^{11}\text{B}$, $\delta^{18}\text{O}$ and $\delta^{13}\text{C}$ in *G. ruber* sensu stricto (ss) during the Plio-Pleistocene Transition (2.3–3.0 Ma) across a range of test sizes (150–500 µm) and comparing these data to existing Holocene and Pleistocene data. We also investigate potential changes in sub-species depth habitat by measuring the $\delta^{18}\text{O}$ and $\delta^{13}\text{C}$ isotopes of *G. ruber* morphotypes sensu stricto (ss) and sensu lato (sl) during the Plio-Pleistocene Transition and again compare the differences observed to data from the Late Pleistocene. Previously published comparisons between $\delta^{11}\text{B}$ of *G. ruber* and *T. trilobus* at ODP 999 have not occurred in the exact same sediment samples resulting in temporal offsets between data points. As such, we present new sediment sample paired $\delta^{11}\text{B}$, $\delta^{11}\text{B}_{\text{borate}}$, pH and CO$_2$ reconstructions covering the Plio-Pleistocene Transition from *G. ruber* and *T. trilobus* to determine if there is a significant difference in CO$_2$ reconstructions. For the first time this is applied in the same sediment samples, removing potential biases arising from aliasing, spatial variation, and analytical method that may have impacted previous such comparisons (Bartoli et al., 2011; de la Vega et al., 2020; Dyez et al., 2018; Martínez-Botí, Foster, et al., 2015).
<figure><img src="image_5.png" /></figure>

**Figure 3.** Records of climate change across the Plio-Pleistocene Transition. (a) prob-stack benthic foraminiferal oxygen isotope stack (Ahn et al., 2017). (b) Mg/Ca-SST estimates for CO₂ estimates from Bartoli et al. (2011; T. trilobus, green dots) and Martínez-Botí, Marino et al. (2015, black, (g) ruber). (c) CO₂ records from ODP 999 using (g) ruber δ¹¹B-CO₂ estimates (blue, Martínez-Botí, Foster, et al., 2015; De la Vega et al., 2020) and T. trilobus δ¹¹B-CO₂ (green, Bartoli et al., 2011). Dark blue and light blut represent 68% and 95% confidence intervals respectively. See Methods for details on recalculating (g) ruber and T. trilobus-CO₂. The δ¹¹B<sub>borate</sub>–δ¹¹B<sub>foram</sub> calibration for TIMS measured T. trilobus (Dyez et al., 2018) was used when recalculating the Bartoli et al. (2011) data set. (d) Boxplot of overlapping CO₂ estimates from (g) ruber and T. trilobus (2,300–3,330 ka).

**2. Materials and Methods**

**2.1. Sample Selection and Preparation**

Our data come from ODP Site 999 (Caribbean Sea, 12°44.64 N and 78°44.36 W, 2,828 mbsf). Today the surface waters at this site are in close CO₂ equilibrium with the atmosphere (Figure S1 in Supporting Information S1, Gregor & Gruber, 2021) and this site has been used previously to reconstruct changes in atmospheric CO₂ across the last glacial cycle, Mid-Pleistocene Transition, Plio-Pleistocene Transition and Mid-Pliocene Warm Period (Bartoli et al., 2011; Chalk et al., 2017; de la Vega et al., 2020, 2023; Dyez et al., 2018; Martínez-Botí, Foster, et al., 2015). Here, planktic and benthic foraminifera were sampled from between 70 and 100 m below the seafloor at ODP 999 (corresponding to ages of 2.3–3.0 Ma) increasing temporal resolution. 199 samples of 20 cm³ were taken at 10 cm intervals (temporal resolution of one sample per ~3 kyrs).

All samples were dried at 40–50°C and weighed before being washed with 15 MΩ cm Milli-Q water over a 63 µm sieve. On average 5 tests (ranging between 1 and 10) of the benthic foraminifera *Cibicidoides wuellerstorfi* were hand separated from the >212–500 µm fraction and measured for δ¹³C and δ¹⁸O. An age model for the interval 2.3 to 3.0 Ma was constructed by combining these data with Haug et al. (1999) correcting δ¹⁸O at ODP 999 by 0.64‰ to the LR04 (Lisiecki & Raymo, 2005) benthic oxygen isotope stack to remove interspecies differences and tuning the combined record via 34 tie-points in Analyseries (Figure S2 in Supporting Information S1; Table S2 https://10.5281/zenodo.15323176; Paillard et al., 2005).

Around 10–20 tests of sensu stricto (ss) *G. ruber* (white) and of sensu lato (sl), as defined by Wang (2000), were picked from 184 depths at ODP 999 from the 300–355 µm size fraction run for δ¹³C and δ¹⁸O in part to examine potential planktic-benthic differences in δ¹⁸O age model, but also to provide insights into the relative habitat depths of the two morphotypes. Of the 184 sediment samples, a subset of 15 of sediment samples were selected at an average time step of ~50 kyrs (Figure S3 in Supporting Information S1). From this sub-sample, around 10–20 tests of *G. ruber* (ss) were hand separated from the 150–200 µm, 200–250 µm, 250–300 µm, 355–400 µm, 400–
450 µm and 450–500 µm size fractions and were analyzed for δ¹³C and δ¹⁸O. The tests were homogenized, and ~50 µg was analyzed for δ¹³C and δ¹⁸O in the Thermo Scientific Kiel IV Carbonate Device coupled with a MAT253 isotope ratio mass spectrometer in the SIRMS Laboratory at the University of Southampton. The data were normalized using a two-point calibration with NBS-18 and NBS-19 (IAEA, Vienna, Austria) and reported relative to Vienna PeeDee Belemnite (VPDB). In-house reference material (GS1) was used for quality assurance purposes and to report instrument precision which is (0.03‰ for δ¹³C and 0.06‰ for δ¹⁸O at 1 standard deviation).

## 2.2. Boron Analytical Procedures

To evaluate the relationship between foraminifera test size and δ¹¹B, six samples were selected from 2.3 to 3.0 Ma at an average time step of ~115 kyrs and dry sieved to separate the 250–300 µm, 300–355 µm, 355–400 µm and 400–450 µm size fractions (Figure S3 in Supporting Information S1). From these samples, 1–2 mg of foraminifera tests (100–200 individuals) were hand separated and run for boron isotopes and trace element analysis for each species.

To compare δ¹¹B-CO₂ reconstructions from *G. ruber* and *T. trilobus*, an additional 9 samples with a time step of ~64 kyr were selected and *G. ruber* (white, ss) and *T. trilobus* were separated from the 300–355 µm size fraction (the normal size range for δ¹¹B-CO₂ studies, Figure S3 in Supporting Information S1). Approximately 1–2 mg of foraminifera tests (100–400 individuals) were hand separated and run for boron isotopes and trace element analysis for each species.

Separated foraminifera tests were crushed between cleaned glass microscope slides and cleaned according to established oxidative cleaning protocols (Barker et al., 2003; Foster, 2008). Samples were dissolved in 0.075 M HNO₃, centrifuged for 5 min to remove any insoluble residue, and transferred to screw top Teflon vials for storage prior to analysis and chemical separation. Boron was separated from the dissolved samples using Amberlite IRA-743 boron-specific anion exchange resin via column chemistry following established procedures (Foster, 2008; Foster et al., 2013). Boron isotopes were measured on a Thermo Scientific Neptune multicollector inductively coupled mass spectrometer at the University of Southampton with 10¹²Ω resistors according to methods described elsewhere (Foster, 2008; Foster et al., 2013). Following Foster (2008), NH₃ gas was added at ~0.04 L/min to aid wash out as NH₃ creates a basic environment on the outer surfaces of the droplets in the spray chamber reducing boron build up four-fold and reducing memory effects (Al-Ammar et al., 2000). A total procedural blank (TPB) is measured with every column batch, averaging ~60 pg (~0.3% of average sample size) with a mean δ¹¹B of -4‰ (±33 ‰). A TPB correction was made using the measured isotopic composition of the TPB for the column batch and its associated B blank, giving a typical TPB correction on δ¹¹B ≪ 0.2‰. External reproducibility is determined from repeat analyses of NIST 8301coral = 24.17 ± 0.19 ‰ (n = 66, 24.17‰ ± 0.18 certified value; Stewart et al., 2021) and calculated according to Rae et al. (2011):

$$2\sigma = 1.87 \times e^{-20.6 \times [^{11}\text{B}]} + 0.22 \times e^{-0.43 \times [^{11}\text{B}]} \quad (3)$$

Where [¹¹B] is the intensity of the ¹¹B signal in volts measured on 10¹²Ω resistors. We recorded a typical external reproducibility of 2s.d. = 0.20‰ for a 50 ppb sample, the typical concentration for our samples. A 20 µl aliquot was taken prior to column chemistry for trace element analysis (including B/Ca, Mg/Ca, Al/Ca, Mn/Ca, Fe/Ca and Sr/Ca). Elemental analyses were performed on a Thermo-Fisher Scientific Element 2 single collector sector field ICPMS at University of Southampton following established methods (Henehan et al., 2015). For this study, analytical reproducibility for Mg/Ca and B/Ca was ±5% (2s.d.). Trace element data were used to check clay removal efficiency. All samples had Al/Ca ratios of <200 µmol mol⁻¹, and typically <60 µmol mol⁻¹. No correlation was observed between Al/Ca and Mg/Ca, Al/Ca and δ¹¹B, or Al/Ca and B/Ca, indicating clay contamination is highly unlikely to impact the results collected here.

## 2.3. δ¹¹B<sub>borate</sub> and pH Calculations

Given that the concentration of borate and boric acid are dependent on pH, in order to maintain a constant δ¹¹B of seawater, the δ¹¹B signatures of borate and boric acid vary with pH. As such, the δ¹¹B<sub>borate</sub> can be related to the pH of seawater:
$$pH = pK_{B}^{*} - \log_{10}\left(-\frac{\delta^{11}B_{sw} - \delta^{11}B_{borate}}{\delta^{11}B_{sw} - \alpha_{B} \times \delta^{11}B_{borate} - (\alpha_{B} - 1) \times \alpha}\right) \quad (4)$$

where $pK_B^*$ is the disassociation constant for boric acid at in situ temperature derived from sample Mg/Ca ratio (see below), salinity and pressure (assumed = 1 atm) using the “seacarb” package in R (Gattuso et al., 2022), $\delta^{11}B_{borate}$ is the isotopic composition of borate, $\delta^{11}B_{sw}$ is the $\delta^{11}B$ of seawater, and $\alpha_B$ is the isotopic fractionation between the two species of boron in seawater and is determined as $1.00272 \pm 0.0006\%$ (Klochko et al., 2006). Given that surface ocean salinity is not believed to have changed substantially over the past 3 million years and has little influence on $\delta^{11}B$ (Horita et al., 2002), salinity was held constant at 35 psu with a generous uncertainty to account for glacial-interglacial variability ($\pm$3 psu, Horita et al., 2002). Existing $\delta^{11}B_{sw}$ reconstructions do not show a clear $\delta^{11}B_{sw}$ trend over the last 3 million years (Greenop et al., 2017). Based on this observation, alongside the long residence time of boron (10–14 million years, Lemarchand et al., 2002), we follow de la Vega et al. (2020) and assume a modern $\delta^{11}B_{sw}$ for the Late Pliocene (39.61‰ $\pm$ 0.2‰, Foster et al., 2010).

To calculate pH, a species-specific calibration needs to be applied to convert measured $\delta^{11}B_{ruber}$ to $\delta^{11}B_{borate}$ (Foster & Rae, 2016). For *T. trilobus*, we use the calibration slope from Sanyal et al. (2001) calculated following Martínez-Botí et al. (2015a) with the intercept altered so the regression passes through core-top *T. trilobus* (300–355 µm) data from Seki et al. (2010) from ODP 999 with calculated surface water $\delta^{11}B_{borate}$ from Foster (2008). For *G. ruber* (white, ss) we apply a size fraction correction to the intercept from Henehan et al. (2013).

$$\delta^{11}B_{borate} = \frac{\delta^{11}B_{trilobus} - 2.934(\pm 0.80)}{0.830 (\pm 0.043)} \quad (5)$$

$$\delta^{11}B_{borate} = \frac{\delta^{11}B_{ruber} - (9.52 + (0.005 \times r - 2.185)) (\pm 1.44)}{0.60 (\pm 0.04)} \quad (6)$$

where $\delta^{11}B_{ruber}$ is the $\delta^{11}B$ measured in *G. ruber*, $\delta^{11}B_{trilobus}$ is the $\delta^{11}B$ measured in *T. trilobus* and *r* is the mean test size fraction.

To convert pH to CO₂ a second carbonate system parameter is required. Here, Dissolved Inorganic Carbon (DIC) was taken from estimates by Sosdian et al. (2018) for the Plio-Pleistocene. Sosdian et al. (2018) used a combination of deep ocean pH derived from previously published boron isotopes of benthic foraminifera, and carbonate ion estimates from fluid inclusions and model simulations of the Carbonate Compensation Depth to solve for DIC. See Sosdian et al. (2018) for more details.

CO₂(aq) was calculated from DIC and $\delta^{11}B$-derived pH:

$$CO_2(aq) = \frac{DIC}{1 + \frac{K_1^*}{[H^+]} + \frac{K_2^*}{[H^+]}} \quad (7)$$

Where CO₂ (aq) is the concentration of CO₂ in seawater, $[H^+]$ is the concentration of protons derived from $\delta^{11}B$-pH, and $K_1^*$ and $K_2^*$ are the first and second dissociation constants of carbonic acid in seawater respectively calculated in R with “seacarb” (Gattuso et al., 2022; Lueker et al., 2000). Atmospheric CO₂ (ppm) was then calculated according to Henry's Law assuming modern disequilibrium between surface ocean and atmosphere at ODP 999 (20 ppm $\pm$ 10, Figure S1 in Supporting Information S1, (Gregor & Gruber, 2021)):

$$CO_2(g) = \frac{CO_2(aq)}{K_0} - 20 (\pm 10) \text{ ppm} \quad (8)$$

Where $K_0^*$ is Henry's constant and was calculated with the “seacarb” package in R (Gattuso et al., 2022; Lueker et al., 2000). A Monte Carlo approach ($n$ = 10,000) was used to calculate uncertainties associated with the 95% and 68% confidence envelopes. All input uncertainties were assumed to be normally distributed.
## 2.4. Mg/Ca Temperature Calibration

Mg/Ca values were used to estimate the local temperature using the calibrations of Dekens et al. (2002, Equations 9 and 10), with a correction for past Mg/Ca of seawater (Mg/Ca<sub>sw</sub>) derived from Zhou et al. (2021) following the method from Hasiuk and Lohmann (2010) using 0.41 as the power constant (Evans & Muller, 2012, Equation 11).

$$ \text{SST}_{\text{trilobus}} = \ln\left(\frac{\text{Mg/Ca}_{\text{corrected}}}{0.37}\right) \div 0.09 + 0.36 \times \text{depth} \quad (9) $$

$$ \text{SST}_{\text{ruber}} = \ln\left(\frac{\text{Mg/Ca}_{\text{corrected}}}{0.38}\right) \div 0.09 + 0.61 \times \text{depth} \quad (10) $$

$$ \text{Mg/Ca}_{\text{corrected}} = \text{Mg/Ca} \div \left( \frac{\text{Mg/Ca}_{\text{sw}}}{\text{Mg/Ca}_{\text{sw corrected}}} \right)^{0.41} \quad (11) $$

where SST<sub>trilobus</sub> and SST<sub>ruber</sub> are the SST estimates from *G. ruber* and *T. trilobus* samples respectively, Mg/Ca<sub>corrected</sub> is the Mg/Ca of the sample corrected to Mg/Ca of seawater, depth is the water depth of the ODP 999 (2,828 m), Mg/Ca is the measured Mg/Ca of the sample, Mg/Ca<sub>sw</sub> is the Mg/Ca of seawater for the age of the sample, and Mg/Ca<sub>sw</sub> is the Mg/Ca of modern sea water (5.2 mmol mol<sup>-1</sup>).

It has been suggested that pH plays an important role in the Mg/Ca ratio of certain foraminifera species including *G. ruber* such that changes in pH should be included in the calibration (Gray et al., 2018, 2019). To evaluate methodological uncertainty on calculated temperatures and CO<sub>2</sub>, we performed 12 sensitivity tests with Mg/Ca-derived SST using the calibrations of Gray et al. (2018, 2019) and Dekens et al. (2002). Each calibration was then corrected for depth-dependent dissolution, secular changes in Mg/Ca<sub>sw</sub> and a combination of depth-dependent dissolution and changes in Mg/Ca<sub>sw</sub> (See Table S1 in Supporting Information S1). The results are displayed in Figure S5 in Supporting Information S1.

Despite the growing evidence for the requirement for a pH adjustment for Mg/Ca (Gray et al., 2018, 2019), we find that, when applying it to the warm Pliocene, our SSTs are unrealistically low (>5°C cooler than modern; see supplement). As such we opt to not apply a pH correction to the Mg/Ca-derived temperatures used here. We note that the SSTs we calculate this way are in broad agreement with Uk<sub>37</sub><sup>-</sup>-derived temperatures from this site. Furthermore, use of the pH correction has little effect on the calculated offset in CO<sub>2</sub> between *G. ruber* and *T. trilobus* because both species are similarly affected.

To test whether there was a meaningful change in the depth habitat of *G. ruber* (ss) that may be reflected in Mg/Ca temperature estimates, we calculated the gradient between measured δ<sup>18</sup>O from *C. wullestorfi* and *G. ruber* (ss) for the Plio-Pleistocene Transition from the same sample. We then compared the difference in δ<sup>18</sup>O with previously published δ<sup>18</sup>O from *C. wullestorfi* and *G. ruber* (ss) from Chalk et al. (2017) from the Late Pleistocene from the same sample. We observe no significant difference in the planktic benthic offset between the Plio-Pleistocene Transition and the Late Pleistocene (Wilcox test, n = 13, p > 0.8, Figure S6 in Supporting Information S1) and can therefore assume that there is no meaningful temporal change in the depth habitat of *G. ruber* and observed changes in temperature are reflective of changes in surface ocean temperature and not migration of *G. ruber* through the water column.

## 2.5. Statistical Analysis

To quantify the relationships between test size and test geochemistry, a linear SIMEX fit (Küchenhoff et al., 2007; Lederer et al., 2017) is applied using the “simex” package in R to account for uncertainty in both the X and Y axes (Lederer & Seibold, 2019). To remove the potential influence of secular and whole ocean variation in chemistry on foraminifera composition and better aid the comparison between the Holocene and Plio-Pleistocene Transition, we normalize the data to the mean value across size fractions for a given sediment sample (Figure S7 in Supporting Information S1):

$$ \Delta x = x_i - \bar{x} \quad (12) $$
Where *x* represents proxy value, Δ*x* is the difference between each proxy value relative to the mean for all foraminiferal sizes from that sediment sample, *x*ᵢ is the measured proxy value, and x̄ is the mean proxy value across all measured size ranges for any given sediment sample (Figure S7 in Supporting Information S1).

# 3. Results and Discussion

## 3.1. Origins of Test-Size Variations in δ¹³C, δ¹¹B and δ¹⁸O of G. Ruber

The strong positive associations between planktic test size and δ¹³C and δ¹¹B as observed in the data presented here (Figures 4a and 4b) are a well-documented feature of planktic foraminifera (Edgar et al., 2017; Ezard et al., 2015; Henehan et al., 2013; Hönisch & Hemming, 2004). Reported *G. ruber* δ¹³C and δ¹¹B values for the Plio-Pleistocene Transition and Holocene show a positive relationship between δ¹³C, δ¹¹B and test size (Figures 4a, 4b, 4e, and 4f). When normalized to the sediment sample average δ¹³C/δ¹¹B (Δδ¹³C/Δδ¹¹B), the fitted SIMEX linear models are within error for Plio-Pleistocene and Holocene data (Figures 4b–4f).

According to the DBL model, the relative increase in δ¹³C and δ¹¹B with test size is attributed to an increase in the relative rate of photosynthesis versus respiration and calcification as foraminiferal test size increases (Figure 2, Hönisch & Hemming, 2004; Wolf-Gladrow et al., 1999; Zeebe et al., 1999, 2003). The transport of carbon to the internal carbon pool via the DBL is dominated by diffusion, such that changes in the relative rates of photosynthesis, respiration, and calcification will influence the isotopic composition of the carbon available to foraminifera for calcification (Wolf-Gladrow et al., 1999; Zeebe et al., 1999). Therefore, an increase in the rate of photosynthesis will lower DBL CO₂, enrich the remainder in ¹³C (photosynthesis strongly favors ¹²C), and increase pH, thus increasing both the test δ¹³C and δ¹¹B; while an increase in the relative importance of respiration will raise DBL CO₂ depleted in ¹³C (respired carbon is rich in ¹²C) and lower pH, decreasing both δ¹³C and δ¹¹B (Bé et al., 1982; Spero & Williams, 1989; Wolf-Gladrow et al., 1999; Zeebe et al., 1999, 2003, 2008). In addition, increased rates of calcification will lower the DBL pH (calcification decreases Alkalinity by 2 mol and DIC by 1 mol for every mole of CaCO₃ produced) reducing δ¹¹B in the test. The effect of increased calcification on δ¹³C is to increase δ¹³C but this influence is minor relative to the influence of respiration and photosynthesis (Zeebe et al., 2008). Thus, the positive association between test size and δ¹³C/δ¹¹B is consistent with an increase in the relative rate of photosynthesis with test size dominating over the effects of calcification and respiration, with the net effect to decrease local concentration of CO₂ and increasing the local pH.

This increase in the relative rate of photosynthesis with test size suggested by δ¹³C and δ¹¹B could reflect: (i) a shallower growth environment for larger individuals with increased light availability and greater symbiont photosynthetic activity (Hönisch & Hemming, 2004); or (ii) an increase in the relative rate of photosynthesis independent of light availability as foraminiferal size increases (Hönisch et al., 2021a; Lombard et al., 2009; Rink et al., 1998; Takagi et al., 2019). Plankton tows consistently find larger individuals of *G. ruber* living deeper in the water column than smaller individuals though still within a narrow range of the water column (0–70 m, Meilland et al., 2021; Rebotim et al., 2017). If photosynthetic rate was entirely dependent on depth habitat and light availability therefore, we would expect a reduction in the rate of photosynthesis with test size, which is not found. Culture studies of *G. ruber* and *O. universa* have observed an increase in the rate of photosynthesis relative to respiration with test size, independent of light availability (Lombard et al., 2009, 2010; Rink et al., 1998). Recent fluorometry experiments have suggested that this is due to increased concentrations of symbionts observed in larger individuals enabling increased rates of photosynthesis (Hönisch et al., 2021b; Takagi et al., 2019) and is facilitated by the shallow scaling of test size with metabolism relative to other phytoplankton (Burke et al., 2025).

We observe a weak negative correlation between δ¹⁸O and foraminiferal test size during the Plio-Pleistocene Transition and Holocene (Figures 4c and 4d). Fitted linear SIMEX models for Plio-Pleistocene and Holocene data are within error of one another when fitted to measured and normalized δ¹⁸O data (Figure 4d). δ¹⁸O has also been shown to be influenced by [CO₂⁻] (and thus pH), where increasing [CO₂⁻] (increasing pH) increases the incorporation of ¹⁶O through increased kinetic fractionation from a faster growth rate at elevated [CO₂⁻], lowering δ¹⁸O (Spero et al., 1997). The increase in DBL pH with test size suggested by the observed increase in δ¹¹B and δ¹³C is thus consistent with the negative relationship between test size and δ¹⁸O (Figure 4). Using the δ¹¹B<sub>ruber</sub> to δ¹¹B<sub>borate</sub> calibration by Henehan et al. (2013), our data show an increase of (0.65‰ of δ¹¹B) 0.22 pH units from smallest to largest *G. ruber* (275–450 µm). According to the culture-based study of Spero et al. (1997), there is a 0.22–0.33‰ reduction in δ¹⁸O for every increase of 0.2–0.3 pH units (Zeebe et al., 1999). The observed
<figure><img src="image_6.png" /><figcaption>Figure 4.</figcaption></figure>
<table><caption>**Table 1**

Means and Variance of δ¹⁸O, δ¹³C and δ¹¹B of G. Ruber for the Plio-Pleistocene Transition and Previously Published for the Holocene (Antonarakou et al., 2015; Carter et al., 2017; Numberger et al., 2009; Steinke et al., 2005; Wang, 2000)</caption><thead><tr><th></th><th>Plio-pleistocene transition</th><th>±1sd</th><th>Holocene</th><th>±</th><th>P</th></tr></thead><tbody><tr><td>δ¹³C</td><td>1.30</td><td>0.55</td><td>0.84</td><td>0.70</td><td>**</td></tr><tr><td>Δδ¹³C</td><td>-0.02</td><td>0.52</td><td>0.00</td><td>0.41</td><td>0.82</td></tr><tr><td>δ¹⁸O</td><td>-1.27</td><td>0.24</td><td>-1.34</td><td>0.61</td><td>0.24</td></tr><tr><td>Δδ¹⁸O</td><td>0.00</td><td>0.18</td><td>0.00</td><td>0.43</td><td>0.92</td></tr><tr><td>δ¹¹B</td><td>20.25</td><td>0.50</td><td>20.67</td><td>0.56</td><td>**</td></tr><tr><td>Δδ¹¹B</td><td>-0.01</td><td>0.26</td><td>0.00</td><td>0.34</td><td>0.91</td></tr></tbody></table>

Note. Δδ¹³C, Δδ¹⁸O and Δδ¹¹B are δ¹³C, δ¹⁸O and δ¹¹B normalized to the sample mean as described in Figure S6 in Supporting Information S1. indicates when *p* < 0.001 from student paired t-test.

increase of 0.20 (±0.05) pH units suggested from our Plio-Pleistocene Transition δ¹¹B size fraction data would thus impart a reduction of 0.23 (±0.10)% in δ¹⁸O — very similar to the mean reduction of 0.26 (±0.10)% we observe in our samples (Figure 4). Given that we do not observe any meaningful change in Mg/Ca with size in these data confirming the relatively restricted habitat of *G. ruber* (Figure S8 in Supporting Information S1, Meilland et al., 2021; Rebotim et al., 2017), and given the equivalent change in pH predicted by δ¹¹B of the same samples, we assume that changes in δ¹⁸O associated with test size are largely determined by micro-environment pH. These internal consistencies further support the applicability of the DBL model of foraminifera microenvironment as a tool to understand vital effects in δ¹¹B, δ¹³C and δ¹⁸O and their use in investigating foraminiferal vital effects.

## 3.2. Have *G. Ruber* Vital Effects Evolved?

Previous work has identified discrepancies between CO₂ estimates derived using boron isotopes of the planktic foraminifera *T. trilobus* and *G. ruber* where CO₂ estimates from *T. trilobus* are ~50 ppm lower than those from *G. ruber* (i.e., ~250 ppm vs. ~300 ppm) during the Plio-Pleistocene Transition (Figure 3, Dyez et al., 2018; Bartoli et al., 2011; Martínez-Botí, Foster, et al., 2015). The lower estimates derived from *T. trilobus* are similar to earlier CO₂ estimates made from the carbon isotopes in terrestrial plants (Cui et al., 2020; Yamamoto et al., 2022) and marine sedimentary alkenones (Seki et al., 2010; Zhang et al., 2013, 2014) for the Middle Pliocene. These discrepancies have been attributed to evolving *G. ruber* vital effects in response to colder climates in the Late Pleistocene (Dyez et al., 2018). This suggestion is supported by *G. ruber* culture experiments which documented a positive correlation between the relative rate of photosynthesis and temperature (Lombard et al., 2009). It follows that the relative rate of photosynthesis to respiration of *G. ruber* may have been greater prior to the Plio-Pleistocene Transition due to the warmer temperatures in the Pliocene (Dyez et al., 2018; Herbert et al., 2016; Lawrence et al., 2009).

Significant differences are observed between measured δ¹³C and δ¹¹B of *G. ruber* values for the Plio-Pleistocene and the Holocene: mean δ¹³C/δ¹¹B values are more positive/negative and show less variability during the Plio-Pleistocene Transition than the Holocene (Figures 4a, 4b, 4e, and 4f; Table 1). The offset in mean δ¹³C/δ¹¹B between the Plio-Pleistocene Transition and Holocene and the lower variability seen for the Plio-Pleistocene Transition are likely a function of secular changes in δ¹³C/δ¹¹B, and for the Holocene data set, the inclusion of data from multiple oceanographic settings rather than a single site (Table 1). Normalizing to the sediment sample mean allows us to compare the two time slices more robustly and evaluate the influence of test size for the two time intervals. Fitted SIMEX models to Δδ¹³C and Δδ¹¹B test-size data from the Holocene and Plio-Pleistocene are within error and indistinguishable (Figures 4a, 4b, 4e, and 4f). As such, the ΔpH predicted from the change in δ¹¹B with test size is very similar for the Holocene and Plio-Pleistocene Transition (ΔpH<sub>PPT</sub> = 0.20 ± 0.10, ΔpH<sub>Hol</sub> = 0.26 ± 0.10). The lack of any difference in gradient of δ¹³C and δ¹¹B/pH between the Plio-Pleistocene and Holocene data strongly suggest that there was no meaningful change in *G. ruber* vital effects since the Pliocene.

An alternative explanation for the *T. trilobus*-*G. ruber* CO₂ discrepancy may be the consequence of the potential migration of *G. ruber* to deeper habitats in response to warmer global temperatures. The current δ¹¹B<sub>ruber-to</sub> δ¹¹B<sub>borate</sub> is corrected for size fraction according to Holocene core top data (Henehan et al., 2013, 2016). If *G. ruber* migrated deeper/shallower, the intercept of the δ¹¹B<sub>ruber-to</sub> δ¹¹B<sub>borate</sub> calibration would decrease/increase and not correcting the intercept accordingly would reduce/increase calculated pH and increase/decrease CO₂

**Figure 4.** (g) ruber test size and stable isotope values for the Holocene (all red points) and Plio-Pleistocene Transition (all blue points). Measured δ¹⁸O (a), δ¹³C (c) and δ¹¹B (e) isotope trends and change in δ¹⁸O (b), δ¹³C (d) and δ¹¹B (f) isotope relative to the sample mean (Δδ¹⁸O/Δδ¹³C/Δδ¹¹B) for the Plio-Pleistocene Transition at ODP 999 (blue, this study) and the Holocene (red, compiled by Edgar et al. (2017), Ezard et al. (2015) and Henehan et al. (2013)). Individual sediment samples for the Plio-Pleistocene Transition are marked by age with different markers. Black circles for data measured on N-TIMS with -3.32‰ correction added (Farmer et al., 2016; Foster et al., 2013; Ni et al., 2007). For details refer to key. Error bars in the x direction represent range of test sizes measured per sample. Linear regression is a SIMEX fit (Lederer & Seibold, 2019) which incorporates x and y uncertainty for each datum; error band represent 95% confidence as calculated from the SIMEX fit. Pearson's Correlation Coefficient (*r*²; KENDALL, 1938) for Holocene (red) and Plio-Pleistocene Transition (blue) data presented in each panel.
<figure><img src="image_7.png" /><figcaption>**Figure 5.** Paired δ¹³C and δ¹⁸O analysis of (g) ruber (white) morphotypes ss and sl during the Plio-Pleistocene Transition. (a) Benthic foraminifera δ¹⁸O stack (black line, Ahn et al., 2017). Measured δ¹⁸O (b) and δ¹³C (c) from ss (green) and sl (purple) in time series. Boxplots of δ¹⁸O (d) and δ¹³C (e) of ss (green) and sl (purple) morphotypes for the Holocene (Antonarakou et al., 2015; Carter et al., 2017; Numberger et al., 2009; Steinke et al., 2005; Wang, 2000) and Plio-Pleistocene Transition (this study). p-values from paired Student *t*-test displayed on figure. Boxplots of Δδ¹⁸O<sub>ss-sl</sub> (f) and Δδ¹³C<sub>ss-sl</sub> (g) for the Late Pleistocene and Holocene (red (Antonarakou et al., 2015; Carter et al., 2017; Numberger et al., 2009; Steinke et al., 2005; Wang, 2000),) and Plio-Pleistocene Transition (blue, this study). P values from Student *t*-test displayed on figure. For box plots, the centre line represents the median, the box represents the 25th-75th percentile and whiskers extend to minima and maxima values excluding outliers.</figcaption></figure>
<caption>**Table 2**</caption>

Means and Variance of δ¹⁸O and δ¹³C of G. Ruber ss and sl Morphotypes for the Plio-Pleistocene Transition and Previously Published for the Holocene

<table><thead><tr><th></th><th></th><th>G. ruber (ss)</th><th>±1sd</th><th>G. ruber (sl)</th><th>±1sd</th><th>P</th></tr></thead><tbody><tr><td rowspan="2">Plio-Pleistocene Transition</td><td>δ¹⁸O</td><td>-1.35</td><td>0.25</td><td>-1.20</td><td>0.25</td><td>**</td></tr><tr><td>δ¹³C</td><td>1.58</td><td>0.26</td><td>1.45</td><td>0.23</td><td>**</td></tr><tr><td rowspan="2">Holocene</td><td>δ¹⁸O</td><td>-0.61</td><td>1.59</td><td>-0.40</td><td>1.48</td><td>**</td></tr><tr><td>δ¹³C</td><td>0.89</td><td>1.38</td><td>0.73</td><td>1.24</td><td>**</td></tr><tr><td></td><td>Plio-pleistocene transition</td><td></td><td>±1sd</td><td>Holocene</td><td>±</td><td>P</td></tr><tr><td></td><td>Δδ¹³C<sub>ss-sl</sub></td><td>0.14</td><td>0.23</td><td>0.17</td><td>0.66</td><td>0.61</td></tr><tr><td></td><td>Δδ¹⁸O<sub>ss-sl</sub></td><td>-0.17</td><td>0.21</td><td>-0.22</td><td>0.68</td><td>0.36</td></tr></tbody></table>

Note. ** indicates when *p* < 0.001 from Student's paired *t*-test.

estimates. In the case of the Plio-Pleistocene Transition, migration down the water column would reduce estimates of pH and thus increase estimates of CO₂.

As described earlier, *G. ruber* spp. is composed of multiple ecologically distinct morphotypes (ss, sl and more) each with distinct geochemical signatures (e.g., Antonarakou et al., 2015; Aurahs et al., 2009, 2011; Carter et al., 2017; Kearns et al., 2023; Wang, 2000). Previously documented differences between ss and sl in δ¹⁸O and δ¹³C are consistent with sl morphotype occupying deeper depths in the water column relative (~100 m below sea level) to ss (~40 m below sea level, e.g. Kearns et al., 2023; Steinke et al., 2005; Wang, 2000). Geochemical differences between morphotypes thus act as a monitor of relative habitats of the morphotypes. It therefore follows that any changes in the relative *G. ruber* ss depth habitat may be evident in differences between ss and the sl morphotypes compared to the Holocene/Late Pleistocene. Paired *t*-tests showed that during the Plio-Pleistocene Transition at ODP 999 *G. ruber* (ss) δ¹³C/δ¹⁸O values were significantly more positive/negative than those observed for the sl morphotype, consistent with previously published data for the Holocene and Late Pleistocene (see Table 1 for references; Figure 5). A Student's *t*-test reveals that there is no significant difference (*p* > 0.05) in mean Δδ¹³C<sub>ss-sl</sub>/Δδ¹⁸O<sub>ss-sl</sub> difference from the Plio-Pleistocene Transition and those from the Late Pleistocene and Holocene (Table 2, Figure 5). The similar morphotype offsets in both δ¹³C and δ¹⁸O space during the Plio-Pleistocene and Holocene imply that there was no resolvable change in the relative depth habitats (and thus vital effects) of *G. ruber* ss and sl morphotypes between the Holocene and Plio-Pleistocene Transition. This is consistent with niche stability modeling efforts that suggest there was little to no change in the occupied niche of foraminifera such as *G. ruber* during the Late Pleistocene (Antell et al., 2021; Waterson et al., 2017).

Previous work has noted that the differences in δ¹⁸O and δ¹³C between ss and sl morphotypes are smallest during glacial periods and largest during interglacial periods (e.g., Antonarakou et al., 2015; Carter et al., 2017; Wang, 2000, summarized in Table 3). This is interpreted to be the result of increased stratification of the water column during interglacials, shoaling the thermocline and increasing the temperature gradient between ss and sl.

<caption>**Table 3**</caption>

Previously Published Δδ¹³C<sub>ss-sl</sub> and Δδ¹⁸O<sub>ss-sl</sub> for the Holocene and Late Pleistocene

<table><thead><tr><th>Author</th><th>Time</th><th>Location</th><th>Δδ¹⁸O<sub>ss-sl</sub></th><th>Range</th><th>p</th><th>Δδ¹³C<sub>ss-sl</sub></th><th>Range</th><th>p</th></tr></thead><tbody><tr><td>This Study</td><td>2.3–3.0 Ma</td><td>Caribbean Sea n = 142</td><td>-0.17</td><td>-0.60–-0.38</td><td>*</td><td>0.13</td><td>-0.40–-0.66</td><td>*</td></tr><tr><td>Wang (2000)</td><td>0–40 kyr</td><td>South China sea n = 23</td><td>-0.2</td><td>-0.63–-0.19</td><td>*</td><td>0.3</td><td>0–1.3</td><td>*</td></tr><tr><td>Antonarakou et al. (2015)</td><td>0–21 kyr</td><td>Gulf of Mexico n = 76</td><td>-0.3</td><td>-2.51–-4.58</td><td>*</td><td>0.68</td><td>0–2.4</td><td>*</td></tr><tr><td>Steinke et al., 2005**</td><td>Holocene</td><td>Indo-Pacific n = 9</td><td>-0.13</td><td>-0.39–-0.08</td><td>*</td><td>0.124</td><td>0–0.3</td><td>*</td></tr><tr><td>Thirumalai et al. (2014)</td><td>Holocene</td><td>Gulf of Mexico n = 17</td><td>-0.08</td><td>0–0.56</td><td></td><td>0.13</td><td>0–0.50</td><td></td></tr><tr><td>Carter et al. (2017)</td><td>0–21 kyr</td><td>Equatorial Pacific n = 30</td><td>-0.47</td><td>-1.08–-0.89</td><td>*</td><td></td><td></td><td></td></tr><tr><td>Numberger et al., 2009**</td><td>0–460 kyr</td><td>Mediterranean Sea n = 115</td><td>-0.01</td><td>-1.22–-2.01</td><td></td><td>-0.12</td><td>-1.29–-1.06</td><td>*</td></tr></tbody></table>

Note. *p* < 0.05. Paired Welch Test due to non-parametric nature of data.
<figure><img src="image_8.png" /><figcaption>Figure 6.</figcaption></figure>
If this were the case in the Plio-Pleistocene Transition, we would expect a strong correlation of $\Delta\delta^{18}O_{ss-sl}$ with $\delta^{18}O$ of benthic foraminifera given that the benthic $\delta^{18}O$ record captures changes in global ice volume and thus tracks glacial state. However, no correlation is observed between $\delta^{18}O$ from C. wuellerstorfi ($\delta^{18}O_{wuell}$) measured from the same sample and $\Delta\delta^{18}O_{ss-sl}$ ($r^2 = 0.003$, Figure S9 in Supporting Information S1). This is either due to the smaller changes observed in $\delta^{18}O$ observed during glacial-interglacial cycles of the Plio-Pleistocene Transition (Ahn et al., 2017; Lisiecki & Raymo, 2005) and/or a less stratified water column relative to the last glacial cycle during Pliocene glacials (Antonarakou et al., 2015; Carter et al., 2017; Wang, 2000).

### 3.3. Accuracy of $\delta^{11}$B-CO$_2$ From G. Ruber in the Plio-Pleistocene Transition

The principal evidence cited for change in G. ruber vital effects during the Plio-Pleistocene Transition is the disagreement between previously published $CO_2$ estimates calculated from *T. trilobus* and *G. ruber* (Figure 3, Bartoli et al., 2011; Dyez et al., 2018; Martínez-Botí, Foster, et al., 2015). Such a straightforward comparison is however problematic due to different measurement methods (Farmer et al., 2016; Foster et al., 2013; Sosdian et al., 2018), sample aliasing (de la Vega et al., 2020) and a lack of directly comparable data (i.e., different core sites, different samples etc).

We present 9 new paired *T. trilobus*-*G. ruber* (ss, white) from the Plio-Pleistocene Transition, in addition to previously published paired analysis from the mid-Piacenzian Warm Period (de la Vega et al., 2020) also from ODP Site 999 (Figure 6). $\delta^{11}$B measurements from *T. trilobus* ($\delta^{11}B_{trilobus}$) and *G. ruber* ($\delta^{11}B_{ruber}$) range from 17.22 to 19.60‰ and 19.73–20.81‰ respectfully. These data are within the range of previously published data generated on *T. trilobus* and *G. ruber* (ss) when measured via MC-ICPMS (Figure 6, de la Vega et al., 2020; Seki et al., 2010; Sosdian et al., 2018). We observe a significant difference of ~1.8‰ in the measured $\delta^{11}$B of paired *G. ruber* ss and *T. trilobus* (Table 4). However, estimates of $\delta^{11}B_{borate}$, pH, and $CO_2$ from the paired samples do not show a significant difference when performing a paired Student's t-test (*p* > 0.05, Table 4). Both *G. ruber* and *T. trilobus* also suggest a mean reduction in $CO_2$ between 70 and 90 ppm across the Plio-Pleistocene boundary (2.8 Ma, Figure 6a) from a high of ~350 ppm in the warm Pliocene.

Preliminary regressions of *G. ruber* and *T. trilobus* $\delta^{11}$B, $\delta^{11}B_{borate}$, pH and $CO_2$ identified two data points (at 2,355 kyr and 2,878 kyr) with a notable leverage on the least-squares regression (a high Cook's distance, Figure S9 in Supporting Information S1). To avoid the influence of these points on subsequent linear regressions, we have removed them from our $\delta^{11}$B record. A SIMEX linear regression was fitted to the remaining paired $\delta^{11}$B analyses and $\delta^{11}B_{borate}$, pH and $CO_2$ estimates (See Figures 6b–6h, Table 2). Linear models fitted to $\delta^{11}B_{borate}$ pH and $CO_2$ estimates all fall within uncertainty of the 1:1 line (Figures 6b–6h).

Our data show that there is no significant difference in $\delta^{11}B_{borate}$, pH or $CO_2$ from the $\delta^{11}$B values of paired *G. ruber-T. trilobus* samples during the Plio-Pleistocene Transition (Table 4, Figure 6). Using paired samples, we are unable to reconstruct the previously identified 50–100 ppm offset between $CO_2$ estimates from *T. trilobus* and *G. ruber* in the Plio-Pleistocene Transition. This suggests that there has not been a meaningful change in the vital effects of *G. ruber* with respect to *T. trilobus*. Combined with the size-fraction and other data generated here, we thus confirm the use of the current $\delta^{11}B_{ruber-to-\delta^{11}B_{borate}}$ and $\delta^{11}B_{trilobus-to-\delta^{11}B_{borate}}$ calibrations during the Plio-Pleistocene Transition at ODP 999 to be the most appropriate. We reiterate the suggestions of de la Vega et al. (2020) that the offsets previously described are likely due to either aliased comparisons between data sets of different ages and/or the well-documented challenges of generating accurate data with the NTIMS measurement techniques — discussed in depth in Foster et al. (2013) and Farmer et al. (2016).

**Figure 6.** Paired (g) ruber (white, ss)-T. trilobus $\delta^{11}$B regressions. Comparison between $\delta^{11}$B, $\delta^{11}B_{borate}$, pH and $CO_2$ of (g) ruber and T. trilobus, showing generally good agreement between both species. $\delta^{11}B_{trilobus}$ (a), $\delta^{11}B_{borate}$ (b), pH (c) and $CO_2$ (d) estimates in time series from (g) ruber (crosses) and T. trilobus (squares) and previously published estimates (black line, G. ruber (de la Vega et al., 2020; Martínez-Botí, Foster, et al., 2015),) with 95% confidence intervals in shaded red band and error bars (e–h) Cross plots of paired *G. ruber-T. trilobus* measurements for $\delta^{11}$B (e) and estimates for $\delta^{11}B_{borate}$ (f), pH (g) and $CO_2$ (h). A 1:1 line is shown as a dashed line in each figure. Linear regression is a SIMEX fit (Lederer & Seibold, 2019) which incorporates *x* and *y* uncertainty for each datum; error band represent 95% confidence as calculated from the SIMEX fit. Equation of regressions are printed on each panel with reported errors of 2sd. Points are colored to denote age: Plio-Pleistocene Transition (green, this study) and mid-Piacenzian Warm Period (yellow (de la Vega et al., 2020). Outliers omitted from analysis highlighted by large circles.
<caption>Table 4</caption>

Means and Variance of δ¹¹B, δ¹¹B<sub>borate</sub>, pH and CO₂ of G. Ruber (ss) and T. Trilobus (n = 9)

<table><thead><tr><th></th><th>G. ruber (ss)</th><th>±1sd</th><th>T. trilobus</th><th>±1sd</th><th>Difference</th><th>p</th></tr></thead><tbody><tr><td>δ¹¹B (‰)</td><td>20.4</td><td>0.4</td><td>18.6</td><td>0.7</td><td>1.8</td><td>*</td></tr><tr><td>δ¹¹B<sub>bor</sub> (‰)</td><td>19.3</td><td>0.6</td><td>18.9</td><td>0.8</td><td>0.4</td><td>0.085</td></tr><tr><td>pH</td><td>8.14</td><td>0.048</td><td>8.13</td><td>0.064</td><td>-0.01</td><td>0.778</td></tr><tr><td>CO₂ (ppm)</td><td>282</td><td>38</td><td>287</td><td>53</td><td>-5</td><td>0.727</td></tr></tbody></table>

Note. Indicates when *p* < 0.001 from Student's paired *t*-test.

## 4. Conclusions

The foraminiferal δ¹¹B-pH proxy exhibits small vital effects largely understood to be caused by foraminifera physiology. Since the drivers of these vital effects (e.g., calcification, photosynthesis and respiration) are environmentally dependent (e.g., Lombard et al., 2009), it is reasonable to thus assume that δ¹¹B-pH vital effects may not be time-invariant (Dyez et al., 2018). However, based on the evidence presented here, we find no meaningful evidence to suggest that there was a substantial change in the vital effects of *G. ruber* through the last 3 million years. Using a number of tracers of vital effect magnitude, we do not observe any meaningful change in the relationship between foraminifera test size and Δδ¹¹B, Δδ¹⁸O or Δδ¹³C<sub>PPT-Hol</sub>. We observe similar differences in measured δ¹³C/δ¹⁸O of the ss and sl morphotypes between the Holocene and Plio-Pleistocene Transition suggesting that there has not been a change in depth habitat of *G. ruber*. Furthermore, we do not observe any statistically significant difference in the δ¹¹B<sub>borate</sub>, pH and CO₂ estimated using paired *T. trilobus* and *G. ruber* samples across the Plio-Pleistocene Transition. Our findings therefore suggest that the *G. ruber* δ¹¹B-pH calibration has not evolved through time and that the CO₂ reconstructed across the Plio-Pleistocene Transition at ODP 999 are based on an accurate record of the surface water pH. The approach applied here using paired species to estimate CO₂, and by exploring size dependent relationships between δ¹¹B, δ¹³C and δ¹⁸O within the framework of the (DBL) model, is a powerful toolkit to explore these issues in other species at other times in the geological record.

## Conflict of Interest

The authors declare no conflicts of interest relevant to this study.

## Data Availability Statement

This research used samples provided by the International Ocean Discovery Program (IODP). Planktic foraminifera primary data sets generated for this study (stable isotopes and trace element ratios) are available at zendo as Brown et al. (2025), DOI 10.5281/zenodo.15323176.

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## Acknowledgments

We are grateful to the staff at the Gulf Coast Repository and the International Ocean Discovery Program (IODP) for providing sample material. We also thank M. Wilding, B. Hambach, J. A. Milton, M. Cooper, and A. Michalik as well as the rest of the “B-team” for laboratory assistance. This work was supported by Natural Environment Research Council Grants NE/P011381/1 to G.L.F., P.A.W. and T.B.C. and NE/L002531/1 to R.M.B., the Leverhulme Trust through support to T. B.C. and the Royal Society (Challenge Grant to P.A.W. and A.J.C.) and Wolfson Merit awards to P.A.W. and G.L.F. R.B. and T.B.C. were supported by the European Research Council Grant “ForCry” (Grant101040461).
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