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Foraminifera play an important role in oceanographic and paleoceanographic research. The test morphology and chemistry within species, as well as the presence or absence of certain species, are affected by environmental conditions. Classification of different species of foraminifera is a crucial yet tedious task for researchers. Deep-learning approaches can help with morphological studies and aid in species classification; however, they require large-scale datasets that are challenging to obtain and annotate because of the extremely small size and delicate handling of these microorganisms. In this work, we expand on an existing mathematical model for foraminifera shell growth to generate 3D synthetic models to aid in these studies. We define parameter spaces for the model which are intended to approximate seven randomly chosen foraminifera taxa. Along with providing an open-source code base to support other researchers in generating models and studying growth patterns, we further extend the synthetic data generation to include a rendering component that mimics two existing robotic imaging systems. We provide two use cases for our synthetic dataset. First, we show how orientation can affect the automated classification of different species and how incorporating aleatoric uncertainty indicators can help select the next views of the samples to significantly improve classification accuracy from 82% to 89%. Next, we show how a sparse set of synthetic 2D images can be used to extract 3D morphology of foraminifera using Neural Radiance Fields (NeRFs). 

Abstract The delivery of nutrients from intermediate waters that form in the Southern Ocean is thought to be a key control on tropical ocean surface productivity. In this paper, we present geochemical evidence that an increase in low‐latitude productivity during the Last Interglacial (LIG) was driven by an increase in the preformed nutrient content of Subantarctic Mode Water (SAMW). We generated records of benthic foraminiferal δ¹³C, δ¹⁸O, Cd/Ca and Mg/Li which are used to reconstruct seawater cadmium, dissolved oxygen, and temperature from a core site in the Florida Straits. The Florida Straits is a location of mixing between SAMW and Northern Component Water, the ratio of which is dependent on the strength of the Atlantic Meridional Overturning Circulation. We find that Late LIG seawater cadmium—which in today's ocean is correlated to phosphate—was substantially higher than the Late Holocene (LH) average at this location, while apparent oxygen utilization was similar during these two periods. Thus, we invoke higher preformed phosphate in the Florida Straits during the Late LIG relative to the LH. Increased SAMW preformed phosphate could be the result of reduced Antarctic Zone winter mixed layer residence time and greater Southern Ocean surface nutrient supply during the Late LIG compared to the LH, as supported by published reconstructions of Southern Ocean biogeochemistry and dynamics. We therefore hypothesize that higher SAMW preformed phosphate would cause an increase in the transport of nutrients into the low latitudes, thereby increasing productivity there. 

Two collocal cores were recovered at approx. 542 meters depth in the Bahamas side of the Florida Straits. Benthic foraminifera species Planulina ariminensis and Hoeglundina elegans, as well as Globobulimina spp., were picked from the greater-than 250-micron size fraction. Mass spectrometry methods were used to analyze P. ariminensis and Globobulimina spp. tests for carbon and oxygen isotopic ratios while H. elegans tests were analyzed for the cadmium/calcium, magnesium/calcium, and lithium/calcium ratios. The records extend from the Late Holocene to the Penultimate Glacial Maximum (Marine Isotope Stage [MIS] 6), with high sedimentation rates during peak interglacial periods (MIS 1 and 5e). Elemental ratios were measured by reductively and oxidatively cleaning the samples following Boyle and Rosenthal (1996), and then using a Thermo Finnigan Element2 Magnetic Sector Inductively Coupled Plasma-Mass Spectrometer (ICP-MS) at the Institute of Alpine and Arctic Research, University of Colorado, Boulder (INSTAAR) according to the methods of Marchitto (2006).Stable oxygen and carbon isotopic ratio data (δ18O and δ13C, respectively) for all samples of P. ariminensis and 51 out of 70 total samples of Globobulimina spp. were acquired using a Thermo MAT 253 with Kiel carbonate preparation device at the Georgia Institute of Technology (GT). 19 replicate samples of Globobulimina were analyzed at the University of Arizona with the same methods.The temperature reconstruction uses the Mg/Li-based calibration proposed by Marchitto et al. (2018)The oxygen content reconstruction uses the benthic foraminiferal epifaunal-infaunal δ13C gradient proxy, specifically the recently updated calibration described in Hoogakker et al. (2025). 

We present a novel space‐time Bayesian hierarchical model (BHM) to reconstruct annual Sea Surface Temperature (SST) over a large domain based on SST at limited proxy (i.e., sediment core) locations. The model is tested in the equatorial Pacific. The BHM leverages Principal Component Analysis to identify dominant space‐time modes of contemporary variability of the SST field at the proxy locations and employs these modes in a Gaussian process framework to estimate SSTs across the entire domain. The BHM allows us to model the mean field and covariance, varying in space and time in the process layers of the hierarchy. Using the Markov Chain Monte Carlo (MCMC) method and suitable priors on the model parameters, posterior distributions of the model parameters and, consequently, posterior distributions of the SST fields and the attendant uncertainties are obtained for any desired year. The BHM is calibrated and validated in the contemporary period (1854–2014) and subsequently applied to reconstruct SST fields during the Holocene (0–10 ka). Results are consistent with prior inferences of La Niña‐like conditions during the Holocene. This modeling framework opens exciting prospects for modeling and reconstruction of other fields, such as precipitation, drought indices, and vegetation. 

The high rate of biological productivity in the North Atlantic is stimulated by the advective supply of nutrients into the region via the Gulf Stream (nutrient stream). It has been proposed that the projected future decline in the Atlantic Meridional Overturning Circulation (AMOC) will cause a reduction in nutrient supply and resulting productivity. In this work, we examine how the nutrient stream changed over the Younger Dryas climate reversal that marked the transition out of the last ice age. Gulf Stream nutrient content decreased, and oxygen content increased at the Florida Straits during this time of weakened AMOC. The decreased nutrient stream was accompanied by a reduction in biological productivity at higher latitudes in the North Atlantic, which supports the link postulated in theoretical and modeling studies. 

Earth system models suggest that anthropogenic climate change will influence marine phytoplankton over the coming century with light-limited regions becoming more productive and nutrient-limited regions less productive. Anthropogenic climate change can influence not only the mean state but also the internal variability around the mean state, yet little is known about how internal variability in marine phytoplankton will change with time. Here, we quantify the influence of anthropogenic climate change on internal variability in marine phytoplankton biomass from 1920 to 2100 using the Community Earth System Model 1 Large Ensemble (CESM1-LE). We find a significant decrease in the internal variability of global phytoplankton carbon biomass under a high emission (RCP8.5) scenario and heterogeneous regional trends. Decreasing internal variability in biomass is most apparent in the subpolar North Atlantic and North Pacific. In these high-latitude regions, bottom-up controls (e.g., nutrient supply, temperature) influence changes in biomass internal variability. In the biogeochemically critical regions of the Southern Ocean and the equatorial Pacific, bottom-up controls (e.g., light, nutrients) and top-down controls (e.g., grazer biomass) affect changes in phytoplankton carbon internal variability, respectively. Our results suggest that climate mitigation and adaptation efforts that account for marine phytoplankton changes (e.g., fisheries, marine carbon cycling) should also consider changes in phytoplankton internal variability driven by anthropogenic warming, particularly on regional scales.