# Reassessment of the global distribution and diversity of modern planktonic Foraminifera from the FORCIS database

Sonia Chaabane, Ralf Schiebel, Julie Meilland, Geert-Jan Brummer, P

Graham Mortyn, Olivier Sulpis, Thomas Chalk, Xavier Giraud, Helene Howa, Azumi Kuroyanagi, et al.

► To cite this version:

Sonia Chaabane, Ralf Schiebel, Julie Meilland, Geert-Jan Brummer, P Graham Mortyn, et al. Re-assessment of the global distribution and diversity of modern planktonic Foraminifera from the FORCIS database. 2025. hal-04992524

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Reassessment of the global distribution and diversity of modern
planktonic Foraminifera from the FORCIS database

Sonia Chaabane<sup>1,2,3</sup>, Ralf Schiebel<sup>2</sup>, Julie Meilland<sup>1,4</sup>, Geert-Jan A Brummer<sup>5</sup>, P Graham Mortyn<sup>6</sup>, Olivier Sulpis<sup>1</sup>, Thomas B Chalk<sup>1</sup>, Xavier Giraud<sup>1</sup>, Helene Howa<sup>7</sup>, Azumi Kuroyanagi<sup>8</sup>, Gregory Beaugrand<sup>9</sup>, and Thibault De Garidel-Thoron<sup>1</sup>

<sup>1</sup>Aix-Marseille Université, CNRS, INRAE, CEREGE

<sup>2</sup>Department of Climate Geochemistry, Max Planck Institute for Chemistry

<sup>3</sup>Fondation pour la recherche sur la biodiversité (FRB-CESAB)

<sup>4</sup>Center for Marine Environmental Sciences, MARUM, University of Bremen

<sup>5</sup>NIOZ, Department of Ocean Systems, Netherlands Institute for Sea Research

<sup>6</sup>Universitat Autònoma de Barcelona, ICTA and Dept. of Geography

<sup>7</sup>LPG-BIAF, UMR-CNRS 6112, University of Angers

<sup>8</sup>Tohoku University Museum, Tohoku University

<sup>9</sup>UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Université Littoral Côte d'Opale, Univ. Lille, CNRS

February 18, 2025
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Reassessment of the global distribution and diversity of modern
planktonic Foraminifera from the FORCIS database

Sonia Chaabane¹, ², ³ *, Ralf Schiebel², Julie Meilland¹,⁴, Geert-Jan A. Brummer⁵, P. Graham
Mortyn⁶, Olivier Sulpis¹, Thomas B. Chalk¹, Xavier Giraud¹, Helene Howa⁷, Azumi
Kuroyanagi⁸, Gregory Beaugrand⁹, Thibault de Garidel-Thoron¹

¹ Aix-Marseille Université, CNRS, IRD, INRAE, CEREGE, Aix-en-Provence, France

² Department of Climate Geochemistry, Max Planck Institute for Chemistry, Mainz, Germany

³ Fondation pour la recherche sur la biodiversité (FRB-CESAB), Montpellier, France

⁴ MARUM, Center for Marine Environmental Sciences, University of Bremen, Bremen,
Germany

⁵ NIOZ, Royal Netherlands Institute for Sea Research, Department of Ocean Systems, Texel,
The Netherlands

⁶ Universitat Autònoma de Barcelona, ICTA and Dept. of Geography, Spain

⁷ LPG-BIAF, UMR-CNRS 6112, University of Angers, France

⁸ Tohoku University Museum, Tohoku University, Japan

⁹ Université Littoral Côte d'Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, France

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* Corresponding author

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E-mail: [sonia.chaabane@gmail.com](mailto:sonia.chaabane@gmail.com)
chaabane@cerege.fr
sonia.chaabane@mpic.de

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**Abstract**

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Planktonic Foraminifera (PF) shells are ubiquitous archives used as proxies in paleoceanography, and play a crucial role in paleoclimate reconstruction. Planktonic Foraminifera species are sensitive to both abiotic and biotic environmental parameters, and have experienced habitat shifts in response to ocean warming since the post-industrial era. In comparison to the seminal works from the 1950s to the 1970s, we reevaluate the ecological niche of planktonic Foraminifera in the modern ocean. Here, we present the most comprehensive update of their modern global ecological niches, vertical habitat distribution and thermal tolerance using the FORCIS database, which includes all available water-column sourced data over the last century. Our analysis of modern planktonic Foraminifera global distribution patterns, over the 1970–2018 interval, reveals the highest diversity in the tropical and subtropical oceans. Planktonic Foraminifera have consistently maintained a depth preference within the upper 100 m of the ocean, likely due to dependence on light and food availability. Spanning temperatures from -2°C to more than 32°C highlights the remarkable thermal tolerance and/or adaptability of PF to a wide range of temperatures. In addition, species that were once restricted to lower latitudes in the early post-industrial era (pre-1970) have been observed at higher latitudes over the past 50 years. Since the 1970s, small to medium-sized species have increased in abundance across all latitudes, from tropical to polar oceans, a trend particularly evident in the extensive data from the eastern North Atlantic. The analyses of the FORCIS database updates the evolving biogeography of modern PF, and advances our understanding of their ecology, providing revised benchmarks for paleoceanographic interpretations and the ecology of modern planktonic calcifiers.

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**Keywords**

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Modern planktonic Foraminifera, biogeography, biodiversity, depth habitat, thermal tolerance, FORCIS database

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**Introduction**
Understanding the environmental controls on plankton population dynamics is essential for predicting future marine ecosystems and their interplay with the Earth surface system. Human-driven CO₂ emissions are causing the oceans to become warmer and driving a decrease of seawater pH (e.g., Cheng et al., 2022; Jiang et al., 2019). This distinctly impacts calcareous plankton such as planktonic Foraminifera (PF), as the seawater acidification increases the energy required for calcification, and even favours dissolution of calcium carbonate in some environments (Doney et al., 2009; Fox et al., 2020; de Moel et al., 2009; Moy et al., 2009; Pallacks et al., 2023). Ocean warming alters plankton habitats, posing physiological challenges and forcing adaptability to changing food availability, ecological conditions, or increasing mortality (Ainsworth et al., 2016; Pecl et al., 2017; Poloczanska et al., 2013; Wernberg et al., 2016).

Planktonic Foraminifera form prominent climate archives and proxy signal-carriers in paleoceanography. These marine protozoans, with chambered shells (tests) made of calcite, comprise over 50 modern morphospecies and roughly 250 genotypes (Brummer and Kučera, 2022; Morard et al. 2024). Their fossil record spans approximately 170 million years and their sensitivity to environmental change makes them quintessential 'sentinel organisms' of past environments (Auderset et al. 2022; Woodhouse et al. 2023; Moretti et al., 2024). When PF precipitate their calcite shells, they incorporate elements of seawater chemistry which can be associated with oceanographic and/or climatic conditions. Their post-mortem remains, i.e. tests, descend through the water column, and accumulate on the seafloor where a small fraction of tests is preserved (e.g., Schiebel, 2002; Sulpis et al. 2021). Through their global distribution, diverse assemblages, and shell geochemistry, PF offer insights into geological and historical oceans and climate via the sedimentary record (Woodhouse et al. 2023; Swain et al. 2024).

The historical context of PF research is pivotal in understanding their biogeography. Pioneering works by Bradshaw (1959) and Allan Bé and colleagues (e.g., Bé and Tolderlund, 1971; and references therein) established the first comprehensive maps and definitions of biogeographical provinces, including temperature ranges. The classification into 'ecological groups' (i.e., tropical, subtropical, temperate, subpolar, polar, and upwelling) emerged from their meticulous efforts, forming the basis for the province names still in use today (e.g., Kucera, 2007; Schiebel and Hemleben, 2017).

Distinct ecological forcings and evolutionary processes dictate the PF distribution. It is imperative to distinguish between these factors to evaluate their responses to the evolving
conditions in the Anthropocene (Worm et al., 2006). PF community compositions are acutely sensitive to water temperature, salinity, light, seawater turbidity, and food availability, likely in response to the symbionts some of them host (Bé et al., 1977; Spero, 1987; Ottens, 1992; Schiebel et al., 2001; Schmidt et al., 2004; Ufkes et al., 1998). Nutrient-deficient surface waters, such as subtropical gyres or stratified summer conditions favour the presence of PF with photosymbionts (Hemleben et al., 1989; Schiebel et al. 2004; Siccha et al. 2009; Kuroyanagi et al. 2002). Conversely, photosymbiont-barren PF species thrive in the subsurface water column and eutrophic waters, observable in upwelling zones or during seasonal transitions such as spring blooms in mid to high latitudes (Schiebel and Hemleben, 2000; Barnard et al., 2004; Moriarty and O'Brien, 2013).

Diminished diversity in the tropics compared to the subtropics occurs in the late Cenozoic (Woodhouse et al. 2023; Swain et al. 2024) and persists through the Holocene (Yasuhara et al., 2020). Projections indicate that this trend may intensify in the next decades (Cheung and Pauly, 2016; Cheung et al., 2013; Garciá Molinos et al., 2016;), particularly in the modern calcifying plankton (Beaugrand et al., 2015; Roy et al., 2015). Current findings underscore the anthropogenic contribution to recent historical latitudinal shifts (Benedetti et al., 2021; Fenton et al., 2023; Henson et al., 2021; Jonkers et al., 2019; Strack et al., 2022; Chaabane et al. 2024a), and there is growing focus on how PF adapt to multifaceted environmental changes by changing their habitats.

This study provides a synoptic perspective on modern PF biogeography and ecological patterns, expanding upon the foundational work of Bé and Tolderlund (1971). Their pioneering framework defined the main biogeographical provinces, though their methodology was constrained by the limited data available at the time, and larger mesh sizes. Leveraging the extensive FORCIS global census (Chaabane et al., 2023; de Garidel-Thoron et al., 2022), we introduce a novel approach to redefining biogeographical provinces using a larger set of methodologies (eg. statistical analysis, correction for sampling bias) applied to well resolved global dataset. Our analysis refines the understanding of PF depth habitats and provides an expanded data set of their temperature ranges. These findings establish new benchmarks for paleoecological interpretations, offering a more robust ecological and biogeographical framework for geochemical proxies, paleoclimate reconstructions, and stratigraphic analyses.

## Methods
131 **1. Data selection**

132 From the comprehensive FORCIS database (Chaabane et al., 2023; de Garidel-Thoron et al., 2022) a total of 170,000 individual subsamples were retrieved from a wide variety of 133 oceanographic contexts and ecological conditions covering all major ocean basins and marine 134 provinces (Longhurst, 2007). The data used here cover the time-period from 1970 to 2018, 135 representing the most data-rich timeframe within FORCIS. The majority of the data from before 136 1970 are sparse and less comprehensive, relying mainly on the pioneering studies by Bradshaw 137 (1959) in the North and Equatorial Pacific between 1950 and 1956, and Bé and Tolderlund 138 (1971) in the North Atlantic and Indian Ocean between 1958 and 1963. In this work, we will 139 update and compare the species distributions documented before 1970, as published by Bé and 140 Tolderlund (1971), with those after 1970 using a novel approach to redefining biogeographical 141 provinces of modern PF and the recent FORCIS data compilation. Overall, the data selected for 142 this study were obtained from plankton net tows, Continuous Plankton Recorders (CPRs), 143 sediment traps, and plankton pumps from all major ocean basins for the FORCIS database. 144 Specific census count data were extracted, detailing both overall PF abundance and species- 145 specific quantifications, which were converted into contingency data (presence/absence), and 146 absolute and relative abundance for 26 species. The temporal scope of the data was categorized 147 into seasons of the Northern and Southern Hemispheres. For the Northern Hemisphere, autumn 148 is September to November; winter December to February; spring March to May, and summer 149 June to August. Conversely, in the Southern Hemisphere, spring is September to November; 150 summer December to February; autumn March to May; and winter June to August. 151

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153 **2. Harmonizing abundance and taxonomy in planktonic Foraminifera**
154 **data**

155 To ensure data consistency and to address biases stemming from sampling and post-sampling 156 methodology (e.g., plankton net mesh size) and varying taxonomic concepts, we converted the 157 abundance data sourced from FORCIS into a standard metric with abundance represented as 158 individuals per cubic metre. For the coarser test size fractions, which were primarily gathered 159 using plankton nets with mesh sizes >100 µm, we use the method detailed in Chaabane et al. 160 (2024b) to normalize to a mesh size of 100 µm. The abundance data extracted from different 161 sampling devices from plankton net and pump were converted to individuals per cubic metre 162 (individuals/m³) using size-normalized catch model equations obtained from sampling depths
on total PF of cytoplasm-filled and empty tests. For normalization of test-size fractions to 100 µm the following equations have been applied (Equations 1 and 2):

$$C_{sz\_norm}^{\infty} = C_{sz\_inf}^{sz\_sup} \frac{f_{max} - f_{sz\_norm}}{f_{sz\_sup} - f_{sz\_inf}} \quad (\text{Eq. 1})$$

where sz\_inf and sz\_sup denote the lower and upper size limits of the measured size fraction, respectively; sz\_norm represents the normalization size; and f\_Sz is the multiplication factor associated with Sz, calculated as follows:

$$f_{Sz} = 1 + (f_{max} - 1) \frac{(S_{sup,k} - S_{sup,1})}{(S_{sup,k} - S_{sup,1}) + (S_{half} - S_{sup,1})} \quad (\text{Eq. 2})$$

with S\_sup,1 and S\_sup,k being the upper size limits of size class 1 and k, respectively, with S\_half and f\_max being reported in Chaabane et al. (2024b).

This facilitates the computation of assemblages as they would have appeared if all material had been sampled using a 100 µm net, thus ensuring consistency across different sampling devices and conditions.

Furthermore, the FORCIS dataset was harmonized for taxonomic variations (Chaabane et al., 2023). Species classification followed a 'lumped' taxonomy that was endorsed by the FORCIS consortium as detailed in Chaabane et al. (2023). In this study, several morphospecies were grouped (lumped) together for data analyses such as G. ruber (G. ruber albus and G. elongatus), G. truncatulinoides (G. truncatulinoides left and G. truncatulinoides right), and T. sacculifer (T. sacculifer no sac and T. sacculifer sac). Globigerinoides ruber ruber (pink) was analyzed separately from G. ruber (white).

Based on the study of Bé and Tolderlund (1971) and adapted to a more recent concept of the species' ecology as provided by Schiebel and Hemleben (2017), we distinguish seven biogeographic provinces representing PF populations, namely tropical, subtropical, temperate, subpolar, polar, and global (for global upwelling species), slightly different from the previous bio-provinces (Bé and Tolderlund, 1971). A detailed classification is provided in Table S1.

## 3. Global distribution patterns of modern planktonic Foraminifera
Global distribution patterns of modern PF are derived from a curated version of the FORCIS database converted into ‘contingency data’ (presence or absence) of the 26 most abundant species (Fig. 1), encompassing the species reported in the work of Bé and Tolderlund (1971). The data analyzed here were obtained from plankton net tows, Continuous Plankton Recorders (CPRs), sediment traps, and plankton pumps from all major ocean basins (Fig. 2). Singular occurrences of any species in any sample were excluded from the analysis.

To define the ecological niches of the different PF species, we analyzed their presence rates across latitudinal gradients for the period between 1970 and 2018. Species presence across latitudes was quantified using a binary presence/absence metric. For each latitudinal bin (spanning 10° each), the presence rate *P* was calculated as the ratio of presence counts to the total number of samples in each 5° latitude × 5° longitude box (presence + absence) using the Equation 3:

$$P = \frac{\text{Presence Count}}{\text{Presence Count} + \text{Absence Count}} \qquad (\text{Eq. 3})$$

This formula is used to quantify species distributions across environmental gradients, as it represents the probability of presence for a given species in a particular area (e.g., McGill et al., 2007; Gotelli & Ellison, 2004). Only grids where the number of absence and/or presence is equal to at least 1 were considered (grids with zero observations were not considered).

To assess the variability and uncertainty of the presence rate, we calculated the standard error (SE) (Equation 4):

$$SE = \sqrt{\frac{P \times (I-P)}{\text{Presence Count} + \text{Absence Count}}} \qquad (\text{Eq. 4})$$

To define the ecological niche of each species, we established an ecological threshold using the presence rates. The threshold *T* for each species was calculated as a value within the observed range of presence rates, based on the minimum *P*<sub>min</sub> and maximum presence *P*<sub>max</sub> rates across all latitude bins (Equation 5). Specifically, the threshold was set as:

$$T = P_{min} + \alpha \times (P_{max} - P_{min}) \qquad (\text{Eq. 5})$$

Where:

- *P*<sub>min</sub> is the minimum presence rate in all the latitude bins (excluding zero),
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- $P_{max}$ is the maximum presence rate in all the latitude bins,

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- $\alpha$ is a scaling parameter, which determines how much of the range between the minimum and maximum is used to define the threshold.

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<figure><img src="image_5.png" /></figure>

This approach is used to define niche boundaries based on species presence probability and is often used in ecological modeling to define areas where a species is most likely to thrive (Elith et al., 2006). The threshold helps delineate areas where the species is present and ecologically viable. In addition, this threshold marks a point where the relationship between species occurrence and latitudinal bands is indicative of the overall distribution. To validate the selection of the alpha value for our threshold, a sensitivity analysis was conducted to systematically evaluate how different alpha values influence the identification of significant latitudinal bands across species. The alpha parameter, representing the scaling factor, was tested across a range of values which are 0.10, 0.15, 0.20, 0.25, and 0.30. For each species, we first calculated the minimum non-zero and maximum presence rates across latitudinal bands, followed by the computation of a threshold based on each alpha value using the Equation 5. Then, the number of significant bands was calculated for each species and each alpha value (Figs. S1 and S2).

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Subsequently, the calculated average number of significant bands across all species and the corresponding standard deviation for each alpha value were calculated (Tab. 1 and Fig. S2) providing a balanced trade-off between sensitivity (number of significant bands) and variability (standard deviation). The chosen threshold of alpha in this work is 0.20 since it consistently identifies a moderate number of significant bands across species, making it the most suitable choice for setting the threshold, ensuring to capture the central range of species occurrence without overemphasizing extreme presence values (Fig. S2). Also, it corresponds to the inflection point where latitudinal bands of species' presence rates transitioned from minimal to maximal values for all the species.

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Then, using an alpha equal to 0.2, species with presence rates falling below the calculated threshold in certain latitudinal bins were considered outside of their ecological niche. Finally, To define ecological provinces, the Northern and Southern Hemispheres were divided into 10 distinct ecoprovinces, comprising primary provinces (tropical, subtropical, temperate, subpolar, and polar), transitional ecoprovinces where these primary provinces overlap (tropical to
subtropical, subtropical to temperate, temperate to subpolar, and subpolar to polar), and a category for ubiquitous species with global distributions (Tab. S2).

## 4. Planktonic Foraminifera species distributions and biodiversity assessment in the contemporary global Ocean

Biodiversity of the PF in the contemporary ocean has been assessed for species richness, i.e., the number of species present in each sample using data from plankton nets, pumps, and CPR samples in each ocean basin of the FORCIS database (Fig. 2). The selected data from FORCIS database spans a depth range from the sea surface (0 m) to the subsurface (200 m) ocean across all seasons from the years 1970 to 2018, spanning defined latitudinal bands (Fig. 1). The analyses have been specifically focused on 26 major species, by using a ‘lumped’ taxonomy as reviewed by the FORCIS consortium (Chaabane et al., 2023). To assess biodiversity per ocean basin, the abundance data from all samples within each basin were converted to relative abundance and computed for two diversity metrics (Figs. 2 and S3), species richness and Shannon diversity index (Shannon, 1948) using the R package 'vegan' (Oksanen et al., 2022). Species richness is the count of distinct species present at a specific site. Shannon diversity index has been calculated for each ocean basin and 10° latitudinal band (Fig. S3) using the formula (Equation 6):

$$H_s = - \sum_{i=0}^{s} \rho_i * \log \rho_i \quad (\text{Eq. 6})$$

where s is the total number of species at a specific site, and $\rho_i$ represents the relative abundance of the i-th species. Shannon diversity index provides a measure of diversity that takes into account both the number of species and their relative abundances in the community. A Shannon diversity index value of zero (0) indicates that there is only one species present (no diversity), whereas higher values (approaching 1 and above) indicate increasing species diversity, with both the number of species and the evenness of their abundances contributing to a more diverse community.

In addition, the Latitudinal Diversity Gradient (LDG) of PF was explored in each ocean basin, by analyzing the variation in species richness across latitudes (Figs. 2 and S4). Data from various sampling locations were filtered to include only those with valid latitude and depth information (above 200 meters). The species presence-absence data were used to calculate
species richness for each latitude. A LOESS smoothing curve was applied to visualize the trend in species richness across latitudes.

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## 5. Average living depth of modern planktonic Foraminifera

The depth habitats of the 26 main modern PF species across various oceanic basins are derived from multinet samples from the upper 200 m of the water column. This depth range was chosen as it encompasses most of the primary distribution of PF species (Rebotim et al. 2017). All species counts obtained from coarse mesh size nets were converted to absolute abundances standardized at 100 µm in order to minimise the potential mixing of life stages, as only adult populations (with a minimum size of 100 µm) are included in the analysis. To ensure data consistency, only depth profiles with at least four data points and similar sampling resolution (including consistent sampling depth intervals) during the spring and summer months post 1970 are considered. From the selected data sets, we calculate the water depth at which each species exhibited maximum abundance per profile. This computation is instrumental in pinpointing the preferred water-depth range for each species in the respective ocean basin (Fig. 3).

The Average Living Depth (ALD) of the 26 dominant species in the modern PF populations was also determined by computing the weighted average of their mean depths across sampled intervals within the upper 200 m of the ocean using multinet samples (Tab. 2). The calculation of both the species' number concentration within those intervals (measured in individuals per cubic metre), and the minimum and maximum ALD, and associated standard error, follows the equation of Rebotim et al. (2017) and Lessa et al. (2020):

$$ALD = \frac{\sum c_i * D_i}{\sum c_i} \qquad (\text{Eq. 7})$$

where $D_i$ denoting a depth interval and $c_i$ is the abundance of a species in that depth interval. ALD was only determined at stations where at least five individuals of a given species were counted. Then, the species' depth habitat and the ALD were categorized into three distinct intervals (Meilland et al. 2021): supra-epipelagic (0–40 m), epipelagic (40–80 m), and infra-epipelagic (80–200 m).

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## 6. Assessment of thermal preferences
To ascertain the thermal tolerance of individual PF species across different ocean basins, our analyses were restricted to data from plankton net and pump samples within the FORCIS database collected post 1970 from the top 100 m of the ocean. Then, mean in-situ temperatures (measured at the time-period and depth of PF sampling) were extracted from the Hadley EN 4.2.1 Reanalysis Data analyses g10 (Good et al., 2013), at a monthly spatial resolution of 1°×1° (Figs. 4 and S5) for each sample closest to the 3D grid. The mean temperature is calculated by averaging the minimum and maximum extracted temperatures at the month of the collection and the minimum and maximum water depths that the plankton net reached during the sampling process.

To generate a heatmap (Fig. 5), species abundances were normalized within each temperature bin (i) to account for variability and facilitate inter-bin comparisons. Normalization was performed using the following steps:

First, the raw abundance of each species ($A_{s,i}$) in a given temperature bin (i) was scaled using the formula:

$$Z_{s,i} = \frac{A_{s,i} - \mu_i}{\sigma_i} \qquad (\text{Eq. 8})$$

where $\mu_i$ is the mean abundance of all species in bin i, and $\sigma_i$ is the standard deviation of species abundances in bin i. This approach centers the data around zero and scales it by the variability within each bin, ensuring comparability across bins. Then, the scaled abundances ($Z_{s,i}$) were averaged across samples within each bin to compute the mean scaled abundance per species.

## 7. Statistics

All the analyses were executed using R version 4.3.3 (2024-02-29). Data cleaning and import were facilitated by the tidyverse package, and ggplot (Wickham et al., 2016, 2019) was employed for generating the plots. The abundance normalization and scaling were implemented in R using the scale function within the dplyr workflow (Johnson & Wichern, 2007). The mutate_at function was applied to group the data by temperature bins and scale the species abundances (Wickham et al., 2019). The LOESS smoothing curve is applied using the geom.smooth() function in ggplot2 (Wickham et al., 2016).
335 **Results**

336 **1. Latitudinal gradients and habitat specialization in planktonic**
337 **Foraminifera**

338 Planktonic Foraminifera show distinct latitudinal distribution patterns, averaged over the 1970-
339 2018 time interval, with maximum diversity in the tropical and subtropical oceans (Fig. 1, 2, 4,
340 5, and S4). In contrast, PF assemblages are less diverse within the polar zones, where
341 *Neogloboquadrina pachyderma* is currently the only truly abundant species (Figs. 1 and 4).
342 However, a clear latitudinal gradient is not uniformly observed across all species. In particular,
343 opportunistic species such as *Globigerina bulloides* stand out for their patchy distribution across
344 the global ocean (Fig. 4).

345 The presence rates (Eq. 3) of species reveal distinct ecological niches for planktonic
346 Foraminifera across latitudes. *Globorotaloides hexagona* and *Globoquadrina conglomerata*
347 thrive in tropical zones (Figs. 1 and 4). Tropical to subtropical assemblages are dominated by
348 *Globigerinoides ruber ruber*, *Pulleniatina obliquiloculata*, and *Globoturborotalita rubescens*
349 (Figs. 1 and 4). In subtropical and temperate zones, species such as *Globigerinella calida*,
350 *Globigerinoides conglobatus*, *Trilobatus sacculifer*, *Neogloboquadrina dutertrei*,
351 *Globigerinella siphonifera*, *Globigerinoides ruber albus*, and *Orbulina universa* are most
352 abundant (Fig. 1). Subpolar to global species, such as *Globigerinita uvula*, reflect a remarkable
353 ecological adaptability, as they occur across a wide range of climatic zones (Figs. 1 and 3).
354 *Globorotalia scitula* and *Neogloboquadrina incompta* thrive in transitional environments
355 between temperate and subpolar zones (Figs. 1 and 4). The polar species *Neogloboquadrina*
356 *pachyderma* extends into subpolar waters (Fig. 3). Widely distributed global species, including
357 *Globigerina bulloides*, *Globigerinita glutinata*, *Turborotalita quinqueloba*, and *Globorotalia*
358 *inflata*. They span multiple climatic zones, reflecting their ecological versatility (Figs. 1 and 3).

359 The highest diversity of PF is observed in the North Atlantic, Pacific, and Indian Oceans, with
360 a maximum species richness ranging between 16 and 19 (Figs. 2 and S4). In contrast, the lowest
361 diversity is recorded in the Arctic and Southern Oceans, with a mean richness of only 3 to 4
362 species (Figs. 2 and S4). The Pacific, Atlantic, and Indian Oceans predominantly host globally
363 distributed species and those adapted from tropical to temperate zones. Temperate to polar
364 species, on the other hand, are primarily found in the Arctic and Southern oceans. Certain
365 species exhibit distinct regional distributions, such as *G. ruber ruber*, which is exclusive to the
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The Shannon diversity index reaches its peak in the low latitudes (Fig. S3), specifically between 30°S and 30°N, exhibiting values between 1 and 2. Highest Shannon diversity index values within this latitude range have been recorded in the Atlantic and Pacific Oceans. There is a noticeable decrease in the Shannon diversity Index with increasing latitude south and north of 30°. In the mid-latitudes, spanning from 30°N to 60°N and from 30°S to 60°S, the Shannon diversity Index ranges from 0.5 to 1.5. In contrast, at the high latitudes, exceeding 60°N and 60°S, Shannon diversity Index values are consistently lower than 1 (Fig. S3).

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## 2. Average living depth

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The majority of the species are present at maximum abundance in the upper epipelagic zone, i.e., the upper 100 m of the water column (Figs. 3 and 5, Tab. 2). In the supra-epipelagic level (0-40m), species such as *G. ruber ruber* and *G. conglobatus* exhibit relatively shallow ALD levels. Species like *G. ruber*, *T. sacculifer*, *N. dutertrei*, *G. uvula*, *G. cultrata*, *O. universa*, *G. rubescens*, *P. obliquiloculata*, *G. bulloides*, *G. conglomerata*, *G. glutinata*, *G. siphonifera*, *G. calida*, *G. inflata*, and *G. scitula* are more abundant in the epipelagic range (40-80 m). Within the infra-epipelagic domain (80-200m), a diverse range of species is observed, including *T. humilis*, *G. hirsuta*, *G. truncatulinoides*, *G. crassaformis*, and *G. hexagona* with varying ALD levels across different regions, suggesting variable depth preferences within more stable environments, still being subjected to seasonality.

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Global species overall maintain the same depth habitat across the Atlantic, Indian, Pacific, and Arctic oceans (Fig. 3). The South and North Atlantic host diverse PF assemblages, and surface-dwellers such as *T. sacculifer*, *G. ruber*, and *G. ruber ruber* are predominantly confined from the upper epipelagic to the epipelagic domain. Infra-epipelagic dwelling species include, for example, *G. truncatulinoides* and *G. crassaformis*, with habitats extending to 150 m water depth (and below). In the Arctic Ocean, the PF assemblage is dominated by non-spinose species such as *N. pachyderma*, *G. glutinata*, *G. uvula*, *N. incompta*, and *G. scitula*, which here occur at the top 100 m depth (Figs. 3 and 5). In the North Pacific Ocean, the distribution patterns largely align with observations from the North Atlantic, with a few noteworthy differences (Fig. 3).
The North Pacific primarily shows maximum PF occurrence within the 0 to 100 m depth range, similar to the North Atlantic, but, locally, *N. pachyderma* is found in warmer waters in the North Pacific than in the North and South Atlantic (Figs. 3 and S5). In the North Pacific, *N. pachyderma* has also been occurring in slightly deeper waters (often below 100 m) than in the North Atlantic, Indian, and Arctic oceans (mostly above 100 m; Fig. 3), while *G. bulloides* is found at greater depths in the Arctic Ocean (often below 50 m) compared to the other ocean basins (mostly above 50 m; Fig. 3). While the majority of species reside in the upper 100 m of the water column, certain species such as *G. conglobatus* and *G. conglomerata* are primarily restricted to water depths above 50 m. Conversely, species like *G. calida*, *G. rubescens*, and *H. pelagica* are often found in the lower mixed layer between 50 m and 100 m water depth. Still, species like *G. hirsuta* and *G. scitula* occur in the subsurface layer below 100 m (Fig. 5). In addition, the ALD of some species is consistent across the different basins except for few species like *T. sacculifer* and *G. siphonifera* that live shallower in the North Pacific and Indian oceans, and *G. inflata* on average lives deeper in the North Pacific and Indian oceans than in the Atlantic Ocean.

### 3. Temperature tolerance of planktonic Foraminifera

Planktonic Foraminifera are observed at temperatures spanning the full open ocean range, from about -2°C to 32°C (Figs. 4 and S5). The temperature ranges of PF are species-specific, and conventionally categorized in the literature as tropical, subtropical, temperate, subpolar, and polar (Bé, 1977; Bé and Tolderlund, 1971; Vincent and Berger, 1981). Overall, in our study, all species' temperature tolerance ranges are greater than 10°C, with a maximum range in the zones where temperature reaches 25°C. Thermal distribution patterns reveal a consistent upper limit of 32°C across tropical, subtropical, and subtropical-to-temperate species, while their lower thermal limits vary. Tropical species occur above 14°C, subtropical species above 12°C, and subtropical-to-temperate species above 3°C. Temperate species range from 8°C to 25°C, temperate-to-subpolar species from 0°C to 21°C, subpolar-to-global species from 0°C to 18°C, and polar species from -2°C to 11°C.

For instance, *G. calida* mostly occurs in warm-water (mostly subtropical) between 20°C and 30°C in the North Atlantic Ocean, but can frequently be observed at temperatures as low as 12°C (Fig. 4). Similarly, *N. dutertrei* displays preference for warmer (tropical) waters, and is found to also thrive in upwelled waters colder than adjacent stratified surface waters (Fig. S5).
Conversely, polar and subpolar species with temperature preferences around 2°C (Fig. S5) may occur in waters of up to 10°C (Figs. 4 and S5). Finally, species with a global distribution, such as *G. bulloides*, *G. glutinata*, and *T. quinqueloba* exhibit a high level of tolerance over an extensive temperature range, and often demonstrate an affinity for regionally and seasonally colder (upwelled) waters in which they are more abundant (Fig. 4). These findings show the capacity of PF individuals to endure a wide range of thermal environments.

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## Discussion

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# 1. Latitudinal distribution preferences of planktonic Foraminifera

The distribution of PF largely follows latitudinal patterns driven by sea surface temperature (SST), and matches marine ecological provinces (e.g., Bradshaw, 1957; Bé and Tolderlund, 1971; Hemleben et al., 1989; Schiebel and Hemleben, 2005; Kucera, 2007; Longhurst, 2007; Spalding et al., 2007). During the post-industrial era, the tropics and subtropics continue to serve as primary realms for warm-water PF species such as *G. ruber ruber*, *P. obliquiloculata*, *G. conglobatus* and *G. conglomerata* (Fig. 1). This confirms the previously established SST-mediated distribution patterns documented in pre-industrial records (Rillo et al., 2022; Jonkers et al. 2019). Species like *G. bulloides* and *G. glutinata* are now becoming more globally distributed from pre-industrial to modern and can thrive across diverse marine environments (Figs. 1, 2, and 4). *Globigerina bulloides* is abundant in eutrophic conditions associated with upwelling or spring blooms (Thiede, 1975; Kroon and Ganssen, 1988; Schiebel et al., 1995; Schiebel and Hemleben, 2000; Darling and Wade, 2008; Conan and Brummer, 2000; Sears et al., 2012). The opportunistic *G. bulloides* exhibits a rapid response to changes in seasonality, showcasing its adaptability to dynamic environmental conditions, as evidenced by its widespread distribution across diverse oceanic regimes and its ability to proliferate following upwelling events and productivity pulses (Fig. 1). This ecological flexibility may be supported by the adaptability of the multiple biological species, i.e., genotypes included with the classical morphotypes of *G. bulloides* (Morard et al, 2012; 2024; Darling et al 2017).

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Most PF morphotypes combine more than one genotype and 'cryptic species' with allopatric (i.e., regional speciation) occurrences (e.g., Darling and Wade, 2008; Morard et al., 2024). For example, both morphospecies *G. glutinata* and *G. bulloides* possibly include some four to ten
genotypes, respectively, with particular regional occurrences and narrower temperature ranges and ecological niches than the entire morphospecies (Darling et al., 2000; Darling and Wade, 2008; Ujiié and Lipps 2009; Seears et al., 2012; Morard et al., 2013; André, 2013; André et al., 2014). Also, different genotypes of *N. pachyderma* occur in the Arctic and Antarctic oceans (Darling and Wade, 2008; André et al., 2018). Some occurrences of *N. pachyderma* in lower latitude upwelling areas (Darling et al. 2000; Darling and Wade 2008) affirm its adaptability and competitive advantage through opportunistic strategies, paralleling its success in polar-to-subpolar waters, where it follows an *r*-selected life strategy. This strategy, characterized by rapid reproduction and high offspring numbers to facilitates survival and take advantage of the short productive seasons like the polar summer and seasonal upwelling (Jonkers et al. 2010; Ivanova et al. 1999; Meilland et al., 2023).

In comparison to the seminal works of Ruddiman et al. (1970) and Bé and Tolderlund (1971), our observations from the FORCIS database over the 1970–2018 time intervals show that species previously considered as subtropical, temperate, and subpolar have been recently found in higher latitudes suggesting that their habitat has expanded polewards (Chaabane et al., 2024a). Notably, tropical species have been transitioning to subtropical zones, subtropical species to temperate regions, temperate species to subpolar areas, and subpolar species are expanding into polar to global latitudes (Figs. 1 and 5, Tab. S1). Similar shifts have been observed in distributional patterns that began emerging from the last ice age through the pre-industrial and post-industrial eras. During the deglaciation, PF assemblages were shown to have responded rapidly to warming, significantly shifting polewards (Strack et al., 2022). This trend persisted into the pre-industrial period, when a notable tropical biodiversity depression was documented (Yasuhara et al., 2020). During the post-industrial period, new assemblages emerged (Jonkers et al., 2019) and the decline in diversity continued (Chaabane et al., 2024a). Precisely, diversity increased at higher latitudes while PF abundances, particularly in subtropical species, showed a marked decline (Chaabane et al., 2024a). This underscores the broader implications of global warming on marine biogeography. As suggested earlier, species appear to colonize new suitable habitats and ecological niches in response to changing environments rather than adapting to locally changing conditions (Chaabane et al., 2024a; Benedetti et al., 2021; Jonkers et al., 2019; Strack et al., 2022).
The post 1970 data from FORCIS database also reveals sporadic occurrences of tropical and
subtropical species in polar regions, although in limited numbers. Species like *G. calida* and *G.
rubescens* being seen in colder rather than subtropical waters (Figs. 4 and S5) indicates
transportation by oceanic currents or anomalies in ecological and climatic conditions, which
may be episodic or follow a systematic trend. Notably, species such as *N. dutertrei*, *G. calida*,
and *T. sacculifer*, typically associated with specific thermal and geographic ranges (Bé, 1982),
exhibit distinctive distribution patterns out of their pre 1970 range. These species, traditionally
associated with subtropical waters, are now being frequently observed in temperate zones of
the North Atlantic Ocean, as shown by our analysis, which may indicate evolving ecological
adaptability (Chaabane et al., 2024a). Similarly, *G. uvula*, once predominantly found in
subpolar regions, may establish a more global presence (Fig. 1). Our analysis also reveals a
shift towards smaller and medium-sized species (Tab. S1). For instance, an increasing
prevalence of *G. uvula* and *G. glutinata* may result from decreasing ambient seawater pH, i.e.,
ocean acidification (Grigoratou et al., 2019), and may suggest an adaptive response aimed at
mitigating calcification costs which would have consequences on the role of PF as inorganic
carbon exporter (Kiss et al., 2021). Also, smaller species may offer specific biological
advantages in a rapidly changing environment (Schmidt et al., 2004; Chernihovsky et al., 2020).
The shift towards smaller species may be further explained by the higher energy demands of
larger species, making them more vulnerable in environments where resources are limited
(Burke et al., 2025). The presence of substantial populations of species such as *G. conglobatus*
in low to mid latitudes and *G. uvula* in higher latitudes, which were not reported from the post-
industrial era before 1970, underscores the profound shifts occurring within marine ecosystems
(Beaugrand et al., 2003).

## 2. Longitudinal changes in planktonic Foraminifera assemblage patterns

The longitudinal patterns in the biogeography of PF become more intricate when examining the post 1970 dataset of the comprehensive FORCIS dataset. While well-established latitudinal patterns driven by sea surface temperature (SST) have been extensively documented (e.g., Schiebel and Hemleben, 2005), the post-industrial development suggests a nuanced interplay of various factors that influence the distribution of PF also along longitudinal gradients (Figs. 1 and 5).
The high PF biodiversity in the North Atlantic encompasses species traditionally acclimated to various thermal ranges (Fig. S5). To account for the effect of transportation, notably by the Gulf Stream and North Atlantic Current, which may exert a substantial influence on the distribution of species from the southwest to the northeast (Ingvaldsen et al., 2021; Polyakov et al., 2020, 2017), singular occurrences of species in any sample were not considered in the analysis. Also, the confluence of cold polar and warmer subtropical waters in the North Atlantic creates an ever-evolving mosaic of habitats, rendering it a "hotspot" for biogeographical investigations (Proud et al., 2017).

In contrast, the tropical and subtropical Indian Ocean with its monsoon-driven circulation (Schott and McCreary, 2001) presents a different case of regional and temporal complexity. Adjacent seasonal upwelling cells and stratified conditions in the subtropical gyre result in mixed assemblages of global and tropical to subtropical species, such as *G. bulloides*, *G. conglobatus*, and *G. conglomerata*, and temperate species like *G. hirsuta* (Figs. 2 and S5) (Conan and Brummer, 2000; Ivanova et al., 1999; Peeters et al., 1999; Brummer and Kroon, 1988; Schiebel et al., 2004).

The North and South Pacific exhibit a pattern predominantly characterized by the dominance of upwelling-related species in the eastern basins, and tropical and subtropical species in the western basin. This pattern tracks the interannual changes related to El Niño-Southern Oscillation (ENSO) from the eastern to western equatorial Pacific (Yamasaki et al., 2022). The conspicuous distribution of either warm-water or cold-water adapted species in the eastern South Pacific (Fig. S5) may reflect the regional and seasonal upwelling conditions off North and South America versus the oligotrophic conditions of the South Pacific subtropical gyre.

Finally, the observed complexities along longitudinal gradients in the post-industrial era may be attributed to multiple factors including anthropogenic influences like ocean warming and consequent changes in surface ocean circulation, stratification and nutrient dynamics, as well as ocean acidification (Orr et al., 2005).

### 3. Vertical distribution of planktonic Foraminifera
Depth habitats for 26 modern PF species from multiple oceanic basins were determined using
multinet data collected from the upper 200 m of the water column. Most of PF species are
confined to the uppermost 100 m of the water column from the supra-epipelagic to the
epipelagic zones (Figs. 3 and 5), which includes the surface mixed layer and euphotic zone
(e.g., Schiebel and Hemleben, 2017, and references therein). This preference for surface waters
remains consistent across various ocean basins, albeit with variations in species composition.
For instance, in the North Atlantic Ocean, species such as *G. ruber* pink, *P. obliquiloculata*,
and *G. calida* were found at depths of 35 m, 53 m, and 63 m, respectively, in this study,
compared to 40 m, 45 m, and 73 m, respectively, in Rebotim et al. (2017). In the South Atlantic
Ocean, *G. cultrata* and *O. universa* were observed at 31 m and 39 m, respectively, in this study,
and at 39 m and 30 m, respectively, in Lessa et al. (2020). In the Pacific Ocean, *G. hexagona*
was found at 132 m in this study, compared to depths below 100 m in Davis et al. (2020). In
the Indian Ocean, *N. pachyderma* and *N. incompta* were recorded at 50 m and 55 m,
respectively, in this study, and between 40 m and 60 m in Meilland et al. (2018).
In the Arctic Ocean, the assemblage predominantly comprises non-spinose, herbivorous species
like *N. pachyderma*, *G. glutinata*, and *G. uvula*, aligning with the seasonal availability and the
quality of alimentation (Fairbanks et al., 1982; Schiebel et al., 2001). Species like *G. bulloides*
exhibit a more dynamic ecological niche, which may be attributed to food availability, as well
as varying ecological niches of the different genotypes in the different global ocean basins
discussed before (Berger, 1969; Watkins et al., 1998; André et al, 2014, Mallo et al., 2017;
Morard et al., 2024). Overall, higher abundances of *G. bulloides* are related to enhanced nutrient
concentrations and algal prey under upwelling conditions and seasonal algal blooms (Cifelli,
1974; Thiede, 1975; Schiebel and Hemleben, 2000). The varying depth habitats of *G. bulloides*
in the Arctic Ocean compared to the other ocean basins (Fig. 3) may result from the availability
of algal food sources in a thick surface mixed layer in the polar summer (Meilland et al. 2020;
Tell et al., 2022).

A narrower depth distribution of species such as the one observed for *G. ruber* and *T. sacculifer*, mostly in the epipelagic zone (<60 m) in the tropical and subtropical ocean, may primarily be attributed to their photo-symbionts, which leaves them restricted to certain light regimes (Spero and Lea, 1993; Gastrich et al., 1983; Hemleben et al., 1989). This suggests a finely tuned adaptation to surface and subsurface waters and underscores the sensitivity of the species to changes in light conditions, which impact their potential response to environmental shifts.
Most PF species show a rather variable depth distribution ranging from 30 m to 70 m on average from epipelagic to infra-epipelagic zone, such as *O. universa* and *G. rubescens* in the northeast and southeast Atlantic (Fig. S5) (Field, 2004; Bé and Hamlin, 1967; Kemle-von Mücke and Oberhänsli, 1999). *Neogloboquadrina incompta* consistently occupies depths between 40 m and 70 m (Fig. S5; Tab. 2), aligning with observations in various regions (Kemle-von Mücke and Oberhänsli, 1999; Kuroyanagi and Kawahata, 2004; Mortyn and Charles, 2003; Schiebel et al., 1995). The presence of temperate species like *G. hirsuta* at varying depths hints at evolving ecological preferences, potentially in response to seasonally changing hydrologic and trophic conditions (Schiebel and Hemleben, 2017). In the Indian Ocean, the depth distribution of species including *G. conglobatus* and *G. conglomerata* possibly results from monsoon-driven changes in surface water mixing versus stratification, nutrient availability, and alimentation of the PF (Schiebel et al., 2004; Morey et al., 2005).

The presence of species with a wide depth distribution from the sea surface and across the thermocline (supra-epipelagic to epipelagic zone), such as *N. dutertrei*, *G. calida*, *G. inflata*, *H. pelagica*, *G. glutinata*, *T. humilis*, *N. pachyderma*, *G. scitula*, and *T. quinqueloba*, highlights the adaptability to varying environmental conditions (Schiebel and Hemleben, 2017). For instance, *N. dutertrei* demonstrates a varying ALD in the upper 100 m (Fairbanks et al., 1982; Kemle-von Mücke and Oberhänsli, 1999). Species like *G. inflata* and *T. humilis* exhibit a significant variability in their depth distribution, which could be due to seasonal variations in the thermocline, reflecting the complex interplay between hydrographic (e.g., fronts) and ecological factors that determine their vertical habitat in the upper 100 m, and species living in the infra-epipelagic zone (below 100 m) (Fairbanks et al., 1980; Schiebel et al., 2001; Lončarić et al., 2006). *Globorotaloides hexagona*, a possible indicator of oxygen deficient conditions in the water column, has mainly been reported from shallow sub-thermocline depths in the North Pacific (Davis et al., 2021) and (northern) Indian Ocean (Schiebel et al., 2004; Fig. 3).

Subsurface-dwelling species, such as *G. scitula*, *G. crassaformis*, and *G. truncatulinoides* have variable depth distributions typically below the seasonal thermocline (infra-epipelagic zone) during most of their post-juvenile ontogeny, in a depth-horizon that receives the prime export flux of matter from the overlying productive surface ocean (Bé and Hamlin, 1967; Kemle-von Mücke and Oberhänsli, 1999; Schmuker and Schiebel, 2002). The distribution ranges of these subsurface-dwelling species underscore their adaptability to an alimentation based on a sufficient amount of organic matter settling out of the productive surface ocean. Accordingly,
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the regional distribution of the subsurface dwelling species may also shift along with changing
biological production and surface marine trophic conditions.

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Conclusions

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A comprehensive update of the global distribution, vertical habitat, and thermal tolerance, and diversity of planktonic Foraminifera (PF) in the modern (post 1910) era has been facilitated by the FORCIS database. Analyses confirmed that PF exhibit a persistent preference for the upper 100 m, likely driven by light and food availability. Furthermore, the modern PF span a wide temperature tolerance, ranging from -2°C to 32°C, underlining the inherent ecological adaptability of these microorganisms.

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While highly diverse PF assemblages in tropical and subtropical latitudes corroborate established latitudinal distribution patterns, species confined to lower latitudes in the early post-industrial (before 1970) oceans have been occurring at higher latitudes after 1970. In addition, small to medium sized species increased in numbers over all latitudes from the tropical to polar oceans, which is particularly clear from analyses of a vast amount of data from the eastern North Atlantic.

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Despite their broad tolerance to varying environmental conditions, PF may be affected by changes in oceanic environments, such as acidification, deoxygenation, and food availability, potentially leading to changes in population dynamics and PF assemblages. Such observations furnish a nuanced understanding of PF diversity and biogeography and underscore the value of the PF as paleoceanographic archives of signal-carrying proxies for a better understanding of post-industrial (1910 to 2018) and ongoing climate and ocean change.

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Data availability

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The FORCIS database used for this paper is available on Zenodo through
[https://zenodo.org/record/8186736](https://zenodo.org/record/8186736).

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Code availability
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Codes to harmonize the abundance data were sourced from
https://zenodo.org/records/10750545.

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Acknowledgements

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Author contributions

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The study was designed by S.C., R.S., T.dG-T., J.M., G.-J.B., G.M., O.S., and T.B.C. during
the FORCIS project workshops at FRB-CESAB. T.dG-T. and R.S. are PIs of the FORCIS
project. All authors contributed to the interpretation and discussion of the results. S.C. carried
out the data analysis and wrote the paper with R.S. and contributions from all co-authors.

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Funding

Open access funding provided by CEREGE in Aix-en-Provence, France, and MPIC in Mainz, Germany. T.B.C supported by ERC StG project 101040461. This work received support from the french government under the France 2030 investment plan, as part of the Initiative d'Excellence d'Aix-Marseille Université – A*MIDEX" AMX-20-TRA-029.

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Competing interests

The authors declare that they have no conflict of interest.

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972 Wickham, H., Averick, M., Bryan, J., Chang, W., D'Agostino McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., et al. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686

976 Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN: 978-3-319-24277-4.

978 Wernberg, T., Bennett, S., Babcock, R.C., Bettignies, T. De, Cure, K., Depczynski, M., Dufois, F., Fromont, J., Fulton, C.J., Hovey, R.K., Harvey, E.S., Holmes, T.H., Kendrick, G. A., Radford, B., Santana-garcon, J., Saunders, B.J., Smale, D. A., Thomsen, M.S., Tuckett, C. A., Tuya, F., 2016. Climate-driven regime shift of a temperate marine ecosystem. Science. 353, 169-172. https://doi.org/10.1126/science.aad8745

983 Woodhouse, A., Swain, A., Fagan, W. F., Fraass, A. J., & Lowery, C. M., 2023. Late Cenozoic cooling restructured global marine plankton communities. Nature, 614 (7949), 713-718. https://doi.org/10.1038/s41586-023-05694-5

986 Worm, B., Barbier, E.B., Beaumont, N., Duffy, J.E., Folke, C., Halpern, B.S., Jackson, J.B.C., Lotze, H.K., Micheli, F., Palumbi, S.R., Sala, E., Selkoe, K.A., Stachowicz, J.J., Watson, R., 2006. Impacts of biodiversity loss on ocean ecosystem services. Science. 314, 787-790. https://doi.org/10.1126/science.1132294

990 Yasuhara, M., Wei, C.L., Kucera, M., Costello, M.J., Tittensor, D.P., Kiessling, W., Bonebrake, T.C., Tabor, C.R., Feng, R., Baselga, A., Kretschmer, K., Kusumoto, B., Kubota, Y., 2020. Past and future decline of tropical pelagic biodiversity. Proc. Natl. Acad. Sci. U. S. A. 117, 12891-12896. https://doi.org/10.1073/pnas.1916923117

994 Ziveri, P., Gray, W.R., Anglada-Ortiz, G., Manno, C., Grelaud, M., Incarbona, A., Rae, J.W.B., Subhas, A. V., Pallacks, S., White, A., Adkins, J.F., Berelson, W., 2023. Pelagic calcium carbonate production and shallow dissolution in the North Pacific Ocean. Nat. Commun. 14. https://doi.org/10.1038/s41467-023-36177-w

998
999 Figure captions
**Figure 1.** Latitudinal distribution of planktonic Foraminifera species. The left-hand side of each panel displays Robinson projection maps illustrating species presence (blue dots) and absence (gray dots) across global sampling sites (1970–2018), overlain on historical ecological provinces (colored bands) as defined by Bé and Tolderlund (1971), spanning polar, subpolar, temperate, subtropical, and tropical zones. Adjacent histograms (right-hand side of each panel) show the presence rate of each species within 10° latitude bins. Dark gray bars represent latitudinal bins where species are outside their expected ecological provinces, while light gray bars correspond to bins where species are within their expected habitats, demonstrating adaptation. The dashed red line denotes the species-specific threshold used to identify significant distribution patterns.

**Figure 2.** Biodiversity of modern planktonic Foraminifera at basin scale. Latitudinal diversity gradient displaying species richness as a function of latitude across different ocean basins, and a comprehensive representation of modern PF diversity of major groups within different ocean basins. Pie charts show the presence of species, and circles show the zones ranging from global, to polar, subpolar, temperate, subtropical, and tropical. LOESS (yellow line) curve is included to highlight the trend in species richness across latitudes.

**Figure 3.** Vertical habitat preferences of planktonic Foraminifera across various oceanic basins. The depth preferences of PF gathered via plankton tows (multinet). The dataset encompasses the upper 200 m of the water column, post-1970 in (A) North Atlantic Ocean, (B) South Atlantic Ocean, (C) North Pacific Ocean, (D) Indian Ocean, and in (E) Arctic Ocean. The species are organised from polar to tropical left to right, with global species on the extreme left.

**Figure 4.** Temperature-related abundance variations of planktonic Foraminifera. Heatmap presenting the normalized abundance of the most abundant planktonic Foraminifera species from the FORCIS database (Chaabane et al., 2023). Data are from samples collected by plankton nets and pumps across the global ocean. Temperature bins are spaced at 1 °C intervals (x-axis), and encompass the depth range of 0 to 100 m after 1970. Mean in-situ temperatures are computed from minimum and maximum temperature values extracted from the Reanalysis Data Hadley EN 4.2.1 analysis g10 dataset, providing temperature information at a 1x1° resolution.
**Figure 5.** Schematic of latitudinal and water depths patterns of the global distribution of **planktonic Foraminifera**. Post-industrial water depth habitats, latitudinal distributions, and temperature ranges of major planktonic Foraminifera species. Species are grouped by ecological provinces (post 1970) proposed in this study (global, polar, subpolar-global, subpolar, subpolar-temperate, temperate, temperate-subtropical, subtropical, subtropical-tropical, and tropical oceans) and compared to the historical (pre 1970) ecological provinces proposed by Bé and Tolderlund (1971).

1037

## Tables

1039

**Table 1.** Sensitivity analysis of alpha values and their effect on the number of significant latitudinal bands across species.

1041

<table><thead><tr><td>Alpha</td><td>Average number of significant bands</td><td>Standard deviation</td></tr></thead><tbody><tr><td>0.10</td><td>7.04</td><td>3.79</td></tr><tr><td>0.15</td><td>6.62</td><td>3.63</td></tr><tr><td>0.20</td><td>6.28</td><td>3.60</td></tr><tr><td>0.25</td><td>5.85</td><td>3.45</td></tr><tr><td>0.30</td><td>5.57</td><td>3.33</td></tr></tbody></table>

1042

**Table 2.** Average (mean ± standard error), minimum and maximum living depths (in meters below the sea surface) of various PF species across different ocean basins. Each entry represents the calculated mean depth along with its associated standard error for a particular species within a specific ocean basin. The data reveal species-specific distribution patterns, with some species exhibiting notable variations in depth preferences across different basins.

1044

1045

1046

1047

1048

<table><thead><tr><td>Species</td><td>North Atlantic</td><td>South Atlantic</td><td>North Pacific</td><td>Arctic Ocean</td><td>Indian Ocean</td></tr></thead><tbody><tr><td>Globigerinoides ruber ruber</td><td>34.94±1.02 m (10–76.83 m)</td><td>-</td><td>-</td><td>-</td><td>-</td></tr></tbody></table>
<table>
  <tr>
    <td>Globigerinoides<br>conglobatus</td>
    <td>39.17±1.81 m<br>(10-90 m)</td>
    <td>-</td>
    <td>31.52±3.38 m<br>(13.36-50.41 m)</td>
    <td>-</td>
    <td>45.94±3.99 m<br>(10-99.15 m)</td>
  </tr>
  <tr>
    <td>Globigerinoides<br>ruber</td>
    <td>40.80±1.44 m<br>(9.67-90 m)</td>
    <td>43.96±0.32 m<br>(41.76-45.05 m)</td>
    <td>50.89±9.52 m<br>(15-124.03 m)</td>
    <td>-</td>
    <td>39.43±2.07 m<br>(19.02-92.86 m)</td>
  </tr>
  <tr>
    <td>Trilobatus<br>sacculifer</td>
    <td>45.51±2.40 m<br>(10-150 m)</td>
    <td>27.15±0.52 m<br>(25.36-30.73 m)</td>
    <td>30.59±3.28 m<br>(13.22-49.24 m)</td>
    <td>-</td>
    <td>34.97±1.87 m<br>(10-67.85 m)</td>
  </tr>
  <tr>
    <td>Neogloboquadrina<br>dutertrei</td>
    <td>45.72±2.11 m<br>(10-150 m)</td>
    <td>-</td>
    <td>61.72±6.80 m<br>(22.69-136.87 m)</td>
    <td>40±2.32 m<br>(30-50 m)</td>
    <td>41.31±3.59 m<br>(10-150 m)</td>
  </tr>
  <tr>
    <td>Globigerinita<br>uvula</td>
    <td>48.69±1.99 m<br>(11.45-150 m)</td>
    <td>-</td>
    <td>-</td>
    <td>48.93±3.36 m<br>(30-86.34 m)</td>
    <td>51.61±4.32 m<br>(9.16-150 m)</td>
  </tr>
  <tr>
    <td>Globoorotalia<br>cultrata</td>
    <td>49.85±1.52 m<br>(10-101.83 m)</td>
    <td>31.51±2.67 m<br>(22.26-50 m)</td>
    <td>51.47±3.41 m<br>(30.93-70.11 m)</td>
    <td>-</td>
    <td>47.07±2.81 m<br>(10-83.54 m)</td>
  </tr>
  <tr>
    <td>Orbulina<br>universa</td>
    <td>50.84±1.94 m<br>(10-150 m)</td>
    <td>39.49±4.90 m<br>(10-78.04 m)</td>
    <td>40.48±3.37 m<br>(25.46-62.62 m)</td>
    <td>-</td>
    <td>50.69±3.47 m<br>(10-90 m)</td>
  </tr>
  <tr>
    <td>Globoturborotalita<br>rubescens</td>
    <td>51.91±1.92 m<br>(10-130 m)</td>
    <td>-</td>
    <td>45.98±5.60 m<br>(16.45-70 m)</td>
    <td>-</td>
    <td>54.91±2.81 m<br>(10-90 m)</td>
  </tr>
  <tr>
    <td>Pulleniatina<br>obliquiloculata</td>
    <td>53.62±1.73 m<br>(25-90 m)</td>
    <td>-</td>
    <td>39.25±2.47 m<br>(25.71-50.40 m)</td>
    <td>-</td>
    <td>54.74±3.58 m<br>(15.70-90 m)</td>
  </tr>
  <tr>
    <td>Globigerina<br>bulloides</td>
    <td>54.39±2.44 m<br>(10-150 m)</td>
    <td>44.12±3.23 m<br>(14.89-72.77 m)</td>
    <td>41.70±5.58 m<br>(15.29-104.97 m)</td>
    <td>76.39±4.92 m<br>(51.80-150 m)</td>
    <td>45.02±2.53 m<br>(6.40-84.62 m)</td>
  </tr>
  <tr>
    <td>Globigerinita<br>glutinata</td>
    <td>54.70±1.78 m<br>(10-150 m)</td>
    <td>18.59±1.52 m<br>(9-27.23 m)</td>
    <td>51.15±6.04 m<br>(19.68-106.20 m)</td>
    <td>46.22±2.98 m<br>(16.67-63.28 m)</td>
    <td>42.57±2.26 m<br>(90-10.83 m)</td>
  </tr>
  <tr>
    <td>Neogloboquadrina<br>incompta</td>
    <td>55.47±2.18 m<br>(10-150 m)</td>
    <td>70.92±6.34 m<br>(22.94-124.18 m)</td>
    <td>66.29±7.38 m<br>(24.43-110.30 m)</td>
    <td>57.76±2.38 m<br>(44.85-88.18 m)</td>
    <td>54.60±4.66 m<br>(10-150 m)</td>
  </tr>
  <tr>
    <td>Globigerinella<br>siphonifera</td>
    <td>58.05±1.66 m<br>(10-150 m)</td>
    <td>47.79±4.3 m<br>(18-62.69 m)</td>
    <td>40.79±2.87 m<br>(20.13-58.65 m)</td>
    <td>-</td>
    <td>46.30±2.32 m<br>(14.69-90 m)</td>
  </tr>
  <tr>
    <td>Turborotalita<br>quinqueloba</td>
    <td>60.34±2.26 m<br>(5-150 m)</td>
    <td>86.38±6.48 m<br>(57.35-140.30 m)</td>
    <td>62.29±3.86 m<br>(39.41-88.33 m)</td>
    <td>59.69±3.92 m<br>(37.20-110.28 m)</td>
    <td>62.76±3.84 m<br>(7.56-150 m)</td>
  </tr>
</table>
<table><tr><td>Neogloboquadrina pachyderma</td><td>61.36±1.92 m (11.74–150 m)</td><td>67±2.85 m (51.15–92.80 m)</td><td>110.07±7.24 m (88.96–131.17 m)</td><td>66.07±2.51 m (41.33–86.01 m)</td><td>50.35±2.71 m (18.16–113.67 m)</td></tr><tr><td>Globigerinella calida</td><td>62.93±2.58 m (10–150 m)</td><td>34.81±3.20 m (10–60.19 m)</td><td>57.08±5.99 m (27.50–99.57 m)</td><td>-</td><td>58.45±3.74 m (10–140 m)</td></tr><tr><td>Globovorotalia inflata</td><td>63.17±2.81 m (10–150 m)</td><td>60.33±3.56 m (27.51–79.17 m)</td><td>92.96±11.23 m (60.21–125.70 m)</td><td>-</td><td>77.61±6.43 m (30–150 m)</td></tr><tr><td>Globoquadrina conglomerata</td><td>-</td><td>-</td><td>64.32±7.43 m (15–90 m)</td><td>-</td><td>47.53±3.10 m (21.43–70 m)</td></tr><tr><td>Globovorotalia scitula</td><td>76.6±2.40 m (10–159 m)</td><td>105.4±2.34 m (90–117.5 m)</td><td>73.79±10.77 m (46.36–125 m)</td><td>61.8±4.14 m (40–90 m)</td><td>76.62±5.51 m (10–150 m)</td></tr><tr><td>Hastigerina pelagica</td><td>93.59±2.65 m (15.68–150 m)</td><td>43.92±5.25 m (21.64–66.19 m)</td><td>59.1±6.82 m (35.05–90 m)</td><td>-</td><td>63.5±5.93 m (14.21–150 m)</td></tr><tr><td>Turborotalita humilis</td><td>81.01±3.13 m (19.55–150 m)</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Globovorotalia hirsuta</td><td>81.54±2.17 m (36.60–150 m)</td><td>-</td><td>-</td><td>-</td><td>85±8.29 m (10–150 m)</td></tr><tr><td>Globovorotalia truncatulinoides</td><td>102.07±3.47 m (10–150 m)</td><td>94.19±2.14 m (77.37–108.63 m)</td><td>-</td><td>-</td><td>85.65±2.71 m (70–110.36 m)</td></tr><tr><td>Globovorotalia crassaformis</td><td>111.88±2.75 m (10–150 m)</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Globovorotaloides hexagona</td><td>-</td><td>-</td><td>132.48±13.59 m (50–175 m)</td><td>-</td><td>80.85±5.72 m (36.37–150 m)</td></tr></table>

1049

1050

1051

1052 Supplementary material

1053

1054 Figures

1055
**Figure S1. Sensitivity analysis of alpha values for threshold determination in species presence.** Sensitivity test conducted across all species to evaluate the impact of varying alpha values (0.10, 0.15, 0.20, 0.25, 0.30) on the number of significant latitudinal bands representing species presence.

**Figure S2. Sensitivity analysis of alpha values and their effect on the number of significant latitudinal bands.** Violin plots show the distribution of significant latitudinal bands in species presence across different alpha values (0.10, 0.15, 0.20, 0.25, 0.30). The width of each violin represents the density of observations, with individual data points overlaid to illustrate variability. Red dots indicate the mean number of significant bands for each alpha value. A decreasing trend suggests that higher alpha values lead to a more stringent threshold for species presence, reducing the number of latitudinal bands deemed significant.

**Figure S3. Latitudinal Shannon diversity index of planktonic Foraminifera at different ocean basins.** Latitudinal patterns in Shannon diversity Index for PF, spanning from -80° (more than 70° South) to 80° (more than 80° North) in 10° intervals. Derived from samples collected using plankton net, pump, and CPR, the analyses encompass data from the surface 200 m of the water column since 1970. This comprehensive examination offers insights into the latitudinal distribution of PF diversity across ocean basins.

**Figure S4. Latitudinal Diversity Gradient of the major 26 Planktonic Foraminifera species across ocean basins.** Relationship between latitude and PF species richness, across different ocean basins. Each dot represents the observed species richness at a sampling location, color-coded by the corresponding ocean basin. The overall latitudinal diversity gradient is derived from species richness data aggregated between 1970 and 2018. The analysis is restricted to samples from depths shallower than 200 meters to capture near-surface habitat diversity.

**Figure S5. Temperature tolerance of planktonic Foraminifera in different ocean basins.** Temperature-related preferences of PF across various oceanic basins and ecological provinces (global, polar, subpolar, temperate, subtropical, and tropical). The dataset covers water depth ranges from the sea surface to 100 m, starting from 1970. Mean in-situ temperatures are computed from minimum and maximum temperature values extracted from the Reanalysis Data Hadley EN 4.2.1 analysis g10 dataset, providing temperature information at a 1x1° resolution
1086 in (A) North Atlantic Ocean, (B) South Atlantic Ocean, (C) North Pacific Ocean, (D) Indian Ocean, (E) Southern Ocean and in (F) Arctic Ocean.

1088

1089 Table

1090

1091 Supplementary Table 1. Planktonic Foraminifera species names in FORCIS and their corresponding ecological provinces, adult test size, and dissolution susceptibility.

1093

<table><thead><tr><td>Species name</td><td>Habitat*</td><td>Number of significant bands</td><td>Adult size category**</td><td>New habitat</td><td>Sensitivity***</td></tr></thead><tbody><tr><td>G. bulloides</td><td>Global</td><td>14</td><td>Medium</td><td>Global</td><td>Moderate</td></tr><tr><td>G. glutinata</td><td>Global</td><td>14</td><td>Medium</td><td>Global</td><td>Moderate</td></tr><tr><td>G. inflata</td><td>Global</td><td>12</td><td>Medium</td><td>Global</td><td>Moderate</td></tr><tr><td>T. quinqueloba</td><td>Global</td><td>12</td><td>Small</td><td>Global</td><td>Moderate</td></tr><tr><td>N. pachyderma</td><td>Polar</td><td>9</td><td>Medium</td><td>Polar</td><td>Resistant</td></tr><tr><td>G. uvula</td><td>Subpolar</td><td>7</td><td>Small</td><td>Subpolar to global</td><td>-</td></tr><tr><td>G. crassaformis</td><td>Temperate</td><td>5</td><td>Medium</td><td>Tropical to temperate</td><td>Resistant</td></tr><tr><td>G. hirsuta</td><td>Temperate</td><td>8</td><td>Medium</td><td>Temperate</td><td>Moderate</td></tr><tr><td>G. scitula</td><td>Temperate</td><td>10</td><td>Medium</td><td>Temperate to subpolar</td><td>Moderate</td></tr><tr><td>N. incompta</td><td>Temperate</td><td>11</td><td>Medium</td><td>Temperate to subpolar</td><td>Resistant</td></tr><tr><td>T. humilis</td><td>Temperate</td><td>5</td><td>Small</td><td>Temperate</td><td>-</td></tr><tr><td>G. calida</td><td>Subtropical</td><td>5</td><td>Large</td><td>Subtropical to temperate</td><td>Moderate</td></tr><tr><td>G. cultrata</td><td>Subtropical</td><td>7</td><td>Large</td><td>Subtropical</td><td>Resistant</td></tr></tbody></table>
<table><tr><td>G. ruber</td><td>Subtropical</td><td>10</td><td>Medium</td><td>Subtropical to temperate</td><td>Sensitive</td></tr><tr><td>G. rubescens</td><td>Subtropical</td><td>6</td><td>Small</td><td>Subtropical</td><td>Sensitive</td></tr><tr><td>G. siphonifera</td><td>Subtropical</td><td>10</td><td>Large</td><td>Subtropical to temperate</td><td>Sensitive</td></tr><tr><td>G. truncatulinoides</td><td>Subtropical</td><td>7</td><td>Large</td><td>Subtropical</td><td>Moderate</td></tr><tr><td>H. pelagica</td><td>Subtropical</td><td>9</td><td>Large</td><td>Subtropical to temperate</td><td>-</td></tr><tr><td>N. dutertrei</td><td>Subtropical</td><td>10</td><td>Medium</td><td>Subtropical to temperate</td><td>Resistant</td></tr><tr><td>O. universa</td><td>Subtropical</td><td>11</td><td>Large</td><td>Subtropical to temperate</td><td>Moderate</td></tr><tr><td>T. sacculifer</td><td>Subtropical</td><td>10</td><td>Medium</td><td>Subtropical to temperate</td><td>Sensitive</td></tr><tr><td>G. conglobatus</td><td>Tropical</td><td>9</td><td>Medium</td><td>Tropical to subtropical</td><td>Sensitive</td></tr><tr><td>G. conglomerata</td><td>Tropical</td><td>4</td><td>Medium</td><td>Tropical</td><td>-</td></tr><tr><td>G. hexagona</td><td>Tropical</td><td>5</td><td>Medium</td><td>Tropical</td><td>-</td></tr><tr><td>G. ruber ruber</td><td>Tropical</td><td>7</td><td>Medium</td><td>Tropical</td><td>Sensitive</td></tr><tr><td>P. obliquiloculata</td><td>Tropical</td><td>6</td><td>Medium</td><td>Tropical</td><td>Resistant</td></tr></table>

* According to Bé and Tolderlund, 1971 and, Vincent and Berger 1981.

** From Chaabane et al. 2024 based on Brummer & Kucera, 2022, Schiebel and Hemleben, 2017, Meilland et al. 2021, Meilland et al. 2022.

*** Kucera et al. 2007

1094

1095

1096

1097

1098

1099

1100

1101

1102

**Supplementary Table 2.** Latitudinal ranges of primary and transitional ecological provinces, as well as the distribution of ubiquitous species of planktonic Foraminifera.

<table><thead><tr><th>Ecological province</th><th>Latitude Range</th></tr></thead><tbody><tr><td colspan="2"><strong>Primary provinces</strong></td></tr><tr><td>Tropical Zone</td><td>0° – 20° N/S</td></tr><tr><td>Subtropical Zone</td><td>20° – 40° N/S</td></tr><tr><td>Temperate Zone</td><td>40° – 60° N/S</td></tr></tbody></table>
<table><tr><td>Subpolar Zone</td><td>60° – 70° N/S</td></tr><tr><td>Polar Zone</td><td>70° – 90° N/S</td></tr><tr><td colspan="2">Transitional provinces</td></tr><tr><td>Tropical-to-Subtropical</td><td>0° – 40° N/S</td></tr><tr><td>Subtropical-to-Temperate</td><td>20° – 60° N/S</td></tr><tr><td>Temperate-to-Subpolar</td><td>40° – 70° N/S</td></tr><tr><td>Subpolar-to-Polar</td><td>>70° N/S</td></tr><tr><td>Ubiquitous Species</td><td>Present across all latitudes</td></tr></table>

1103

1104

1105
<figure><img src="image_32.png" /><figcaption>Globigerinita glutinata</figcaption></figure>

<figure><img src="image_33.png" /><figcaption>Turborotalita humilis</figcaption></figure>

<figure><img src="image_34.png" /><figcaption>Globorotalia hirsuta</figcaption></figure>

<figure><img src="image_35.png" /><figcaption>Neogloboquadrina dutertrei</figcaption></figure>

<figure><img src="image_36.png" /><figcaption>Turborotalita quinqueloba</figcaption></figure>

<figure><img src="image_37.png" /><figcaption>Neogloboquadrina pachyderma</figcaption></figure>

<figure><img src="image_38.png" /><figcaption>Neogloboquadrina incompta</figcaption></figure>

<figure><img src="image_39.png" /><figcaption>Globorotalia crassaformis</figcaption></figure>

<figure><img src="image_40.png" /><figcaption>Globigerinella siphonifera</figcaption></figure>

<figure><img src="image_41.png" /><figcaption>Globigerina bulloides</figcaption></figure>

<figure><img src="image_42.png" /><figcaption>Globigerinita uvula</figcaption></figure>

<figure><img src="image_43.png" /><figcaption>Globorotalia scitula</figcaption></figure>

<figure><img src="image_44.png" /><figcaption>Orbulina universa</figcaption></figure>

<figure><img src="image_45.png" /><figcaption>Globoturborotalita rubescens</figcaption></figure>

<figure><img src="image_46.png" /></figure>
<figure><img src="image_47.png" /></figure>

<figure><img src="image_48.png" /></figure>

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<figure><img src="image_50.png" /><figcaption>Fig. 1</figcaption></figure>
<figure><img src="image_51.png" /><figcaption>Fig. 2</figcaption></figure>
<figure><img src="image_52.png" /><figcaption>Fig. 3</figcaption></figure>
<figure><img src="image_53.png" /><figcaption>Fig. 4</figcaption></figure>
<figure><img src="image_54.png" /><figcaption>Fig. 5</figcaption></figure>
<figure><img src="image_55.png" /><figcaption>Fig. S1</figcaption></figure>
<figure><img src="image_56.png" /><figcaption>Fig. S2</figcaption></figure>
<figure><img src="image_57.png" /><figcaption>Fig. S3</figcaption></figure>
<figure><img src="image_58.png" /><figcaption>Fig. S4</figcaption></figure>
<figure><img src="image_59.png" /><figcaption>Fig. S5</figcaption></figure>