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Paleoceanographic studies often rely on abundance changes in microfossil species, with little consideration for characteristics such as organism size, which may also be related to environmental changes. Using a tropical Indian Ocean (TIO) core-top data set, we test the Optimum size-hypothesis (OSH), investigating whether relative abundance or environmental variables are better descriptors of planktonic foraminifera species' optimum conditions. We also investigate the environmental drivers of whole-assemblage planktonic foraminiferal test size variation in the TIO. We use an automated imaging and sorting system (MiSo) to identify planktonic foraminiferal species, analyze their morphology, and quantify fragmentation rate using machine learning techniques. Machine model accuracy is confirmed by comparison with human classifiers (97% accuracy). Data for 33 environmental parameters were extracted from modern databases and, through exploratory factor analysis and regression models, we explore relationships between planktonic foraminiferal size and oceanographic parameters in the TIO. Results show that the size frequency distribution of most planktonic foraminifera species is unimodal, with some larger species showing multimodal distributions. Assemblage size95/5 (95th percentile size) increases with increasing species diversity, and this is attributed to vertical niche separation induced by thermal stratification. Our test for the OSH reveals that relative abundance is not a good predictor of species' optima and within-species size95/5 response to environmental parameters is species-specific, with parameters related to carbonate ion concentration, temperature, and salinity being primary drivers. At the species and assemblage levels, our analyses indicate that carbonate ion concentration and temperature play important roles in determining size trends in TIO planktonic foraminifera. Key Points Optimum size-hypothesis holds true in planktonic foraminifera if one considers th

This paper looks at experiential feedback and the technical and scientific challenges tied to the MERITE-HIPPOCAMPE cruise that took place in the Mediterranean Sea in spring 2019. This cruise proposes an innovative approach to investigate the accumulation and transfer of inorganic and organic contaminants within the planktonic food webs. We present detailed information on how the cruise worked, including 1) the cruise track and sampling stations, 2) the overall strategy, based mainly on the collection of plankton, suspended particles and water at the deep chlorophyll maximum, and the separation of these particles and planktonic organisms into various size fractions, as well as the collection of atmospheric deposition, 3) the operations performed and material used at each station, and 4) the sequence of operations and main parameters analysed. The paper also provides the main environmental conditions that were prevailing during the campaign. Lastly, we present the types of articles produced based on work completed by the cruise that are part of this special issue.

Planktonic Foraminifera are ubiquitous marine protozoa inhabiting the upper ocean. During life, they secrete calcareous shells, which accumulate in marine sediments, providing a geological record of past spatial and temporal changes in their community structure. As a result, they provide the opportunity to analyze both current and historical patterns of species distribution and community turnover in this plankton group on a global scale. The FORCIS project aims to unlock this potential by synthesizing a comprehensive global database of abundance and diversity observations of living planktonic Foraminifera in the upper ocean over more than 100 years starting from 1910. The database will allow for unravelling the impact of multiple global-change stressors acting on planktonic Foraminifera in historical times, using an approach that combines statistical analysis of temporal diversity changes in response to environmental changes with numerical modeling of species response based on their ecological traits.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

We present here a study based on the Anisotropy of Magnetic Susceptibility (AMS) and magnetic mineralogy carried out on the composite core MD17&18taken from the eastern levee of the active channel of the middle Bengal Fan in the Indian Ocean. Based on C-14 dating, the sedimentary sequence covers 9.8 ka in 39 m of sediment. It therefore records at very high resolution the variations in continental material exported to the ocean by the Ganges-Brahmaputra river system during the Holocene. This sequence was divided into two units according to turbidite activity: Unit 1 from 9.8 to 9.2 ka cal. Representing 39 m of coarse-grained turbidite sequences (coarse silts to fine sands) and extremely high sedimentation rates. Unit 2 of 9.2 ka cal. BP to the present characterized by a sharp decrease in the sedimentation rate, the presence of fine-grained turbidites characterized by strong decrease in the ln(Ti/Ca) ratio. Our AMS results indicate that the magnetic fabric is highly sensitive to the mode of deposition. The turbidite sequences are clearly characterized by very high F and Pj values, not only of the coarse-grained turbidite levels in unit 1, but also of the fine turbidites in unit 2. We suggest that this strong degree of anisotropy is the result of the strong and rapid deposition during the turbidite sequences which induces an additional compaction effect. Furthermore, LT SIRM measurements revealed that the magnetic minerals representative of the Ganges and Brahmaputra drainage area are magnetite, hematite and goethite. A higher supply in fine-grained magnetite was observed during the turbidite sequences in phase with an increase in sediment grain size.

Manual identification of foraminiferal morphospecies or morphotypes under stereo microscopes is time consuming for micropalaeontologists and not possible for nonspecialists. Therefore, a long-term goal has been to automate this process to improve its efficiency and repeatability. Recent advances in computation hardware have seen deep convolutional neural networks emerge as the state-of-the-art technique for image-based automated classification. Here, we describe a method for classifying large foraminifera image sets using convolutional neural networks. Construction of the classifier is demonstrated on the publicly available Endless Forams image set with a best accuracy of approximately 90 %. A complete automatic analysis is performed for benthic species dated to the last deglacial period for a sediment core from the north-eastern Pacific and for planktonic species dated from the present until 180 000 years ago in a core from the western Pacific warm pool. The relative abundances from automatic counting based on more than 500 000 images compare favourably with manual counting, showing the same signal dynamics. Our workflow opens the way to automated palaeoceanographic reconstruction based on computer image analysis and is freely available for use.

Pollen grains are valuable paleoclimate and paleovegetation proxies which require extensive knowledge of morphotypes and long acquisition time under the microscope. The abundance of damaged, folded, and broken pollen grains in the fossil register and sometimes also in modern soil and sediment samples, has so far prevented automation of pollen identification. Recent improvements in machine learning, however, have allowed reconsidering this approach. Here we present an automated approach which is capable of assisting palynologists with poorly preserved pollen samples. Called multi-CNNs, this approach is based on multiple convolutional neural networks (CNNs) integrated in a decision tree system. To test it, we built a system designed for three botanical families very common in the modern and fossil pollen assemblages of Eastern Africa, namely Amaranthaceae, Poaceae, and Cyperaceae. Our system was tested on stacked optical images of 8 pollen types (6 Amaranthaceae, 1 Poaceae, 1 Cyperaceae) using a training dataset of 1102 intact pollen grains and three validation datasets of intact (276 grains), damaged (223 grains), and fossil pollen (97 grains). We show that our system successfully recognizes intact, damaged, and fossil pollen grains with very low misclassification rates of 0%, 2.8%, and 3.7%, respectively. The use of augmentation on stacked optical images during the training increases classification accuracy. Following a palynologist's approach, our system allows grains without obvious characters to be classified into a class of high taxonomic level or as indeterminable pollen. This is the first software able to process grains with a wide range of taphonomical stages, which makes it the first truly applicable to automated pollen identification of fossil material.

Identification of microfossils is usually done by expert taxonomists and requires time and a significant amount of systematic knowledge developed over many years. These studies require manual identification of numerous specimens in many samples under a microscope, which is very tedious and time-consuming. Furthermore, identification may differ between operators, biasing reproducibility. Recent technological advances in image acquisition, processing and recognition now enable automated procedures for this process, from microscope image acquisition to taxonomic identification. A new workflow has been developed for automated radiolarian image acquisition, stacking, processing, segmentation and identification. The protocol includes a newly proposed methodology for preparing radiolarian microscopic slides. We mount eight samples per slide, using a recently developed 3D-printed decanter that enables the random and uniform settling of particles and minimizes the loss of material. Once ready, slides are automatically imaged using a transmitted light microscope. About 4000 specimens per slide (500 per sample) are captured in digital images that include stacking techniques to improve their focus and sharpness. Automated image processing and segmentation is then performed using a custom plug-in developed for the ImageJ software. Each individual radiolarian image is automatically classified by a convolutional neural network (CNN) trained on a Neogene to Quaternary radiolarian database (currently 21 746 images, corresponding to 132 classes) using the ParticleTrieur software. The trained CNN has an overall accuracy of about 90 %. The whole procedure, including the image acquisition, stacking, processing, segmentation and recognition, is entirely automated via a LabVIEW interface, and it takes approximately 1 h per sample. Census data count and classified radiolarian images are then automatically exported and saved. This new workflow paves the way for the analysi

The planktonic foraminifera genus Globigerinoides provides a prime example of a species-rich genus in which genetic and morphological divergence are uncorrelated. To shed light on the evolutionary processes that lead to the present-day diversity of Globigerinoides, we investigated the genetic, ecological and morphological divergence of its constituent species. We assembled a global collection of single-cell barcode sequences and show that the genus consists of eight distinct genetic types organized in five extant morphospecies. Based on morphological evidence, we reassign the species Globoturborotalita tenella to Globigerinoides and amend Globigerinoides ruber by formally proposing two new subspecies, G. ruber albus n.subsp. and G. ruber ruber in order to express their subspecies level distinction and to replace the informal G. ruber “white” and G. ruber “pink”, respectively. The genetic types within G. ruber and Globigerinoides elongatus show a combination of endemism and coexistence, with little evidence for ecological differentiation. CT-scanning and ontogeny analysis reveal that the diagnostic differences in adult morphologies could be explained by alterations of the ontogenetic trajectories towards final (reproductive) size. This indicates that heterochrony may have caused the observed decoupling between genetic and morphological diversification within the genus. We find little evidence for environmental forcing of either the genetic or the morphological diversification, which allude to biotic interactions such as symbiosis, as the driver of speciation in Globigerinoides.

Planktonic foraminifer tests are major archives of environmental change and provide a multitude of proxies in paleoceanography and paleoclimatology. The application of such proxies is contingent upon a collaborative effort to better understand how the living organisms record the properties of their environment and how the resulting signals are recorded in marine sediments. In this contribution, we provide a review of the rapidly developing sub-fields of research, where new advances have been made possibleby technological developments, and by cross-disciplinary work of the scientific community. Following brief historical overviews of the sub-fields, we discuss the latest advances in planktonic foraminifer research and highlight the resulting new perspectives in ocean and climate research. Natural classification based on consistent species concepts forms the basis for analysis of any foraminifer-derived proxy. New approaches in taxonomy and phylogeny of Cenozoic planktonic foraminifers (Section 2) are presented, highlighting new perspectives on sensitivity and response of planktonic foraminifers to the changing climate and environment (Section 4). Calibration of foraminifer-specific data and environmental parameters is improving along with the technical development of probes and the access to samples from the natural environment (Section 3), enhancing our understanding of the ever-changing climate and ocean system. Comprehension of sedimentation and flux dynamics facilitates maximum gain of information from fossil assemblages (Section 5). Subtle changes in the physical (e.g., temperature), chemical (e.g., pH), and biological (e.g., food) conditions of ambient seawater affect the abundance of species and composition of assemblages as well as the chemical composition of the foraminifer shell and provide increasingly-detailed proxy data on paleoenvironments (Section 6).

Investigations of biodiversity, biogeography, and ecological processes rely on the identification of "species" as biologically significant, natural units of evolution. In this context, morphotaxonomy only provides an adequate level of resolution if reproductive isolation matches morphological divergence. In many groups of organisms, morphologically defined species often disguise considerable genetic diversity, which may be indicative of the existence of cryptic species. The diversity hidden by morphological species can be disentangled through genetic surveys, which also provide access to data on the ecological distribution of genetically circumscribed units. These units can be identified by unique DNA sequence motifs and allow studies of evolutionary and ecological processes at different levels of divergence. However, the nomenclature of genetically circumscribed units within morphological species is not regulated and lacks stability. This represents a major obstacle to efforts to synthesize and communicate data on genetic diversity for multiple stakeholders. We have been confronted with such an obstacle in our work on planktonic foraminifera, where the stakeholder community is particularly diverse, involving geochemists, paleoceanographers, paleontologists, and biologists, and the lack of stable nomenclature beyond the level of formal morphospecies prevents effective transfer of knowledge. To circumvent this problem, we have designed a stable, reproducible, and flexible nomenclature system for genetically circumscribed units, analogous to the principles of a formal nomenclature system. Our system is based on the definition of unique DNA sequence motifs collocated within an individual, their typification (in analogy with holotypes), utilization of their hierarchical phylogenetic structure to define levels of divergence below that of the morphospecies, and a set of nomenclature rules assuring stability. The resulting molecular operational taxonomic units remain outsi

The depth of equatorial Pacific thermocline is diagnostic of the main modes of tropical climates. Past estimates of Pacific thermocline dynamics have been reconstructed either for the Last Glacial Maximum or on longer timescales at low resolution. Here we document a new high-resolution set of reconstructed past sea surface and subsurface waters temperatures from the southwestern subequatorial Pacific, core MD05-2930, in the Gulf of Papua, over the last 800 ka. We used two morphotypes of Globigerinoides ruber known to live at different water depths to reconstruct past stratification. We estimated calcification temperature of each morphotypes by Mg/Ca paleothermometry. Our subequatorial Pacific thermocline paleotemperature record indicates a response of the thermocline to both direct orbital forcing and glacial-interglacial changes. Our stratification record shows a systematic shallower glacial thermocline, whereas sea surface temperatures are characterized by precessional forcing. The record is indicative of a progressive long-term shoaling of the thermocline during the glacial stages during the late Pleistocene. The shoaling of the subequatorial Pacific thermocline is consistent with regional estimates. An enhanced South Pacific shallow overturning wind-driven circulation could have driven this progressive shoaling. We speculate that this late Pleistocene glacial shoaling of the thermocline could be related to an increase in the amplitude of the obliquity.

The depth of equatorial Pacific thermocline is diagnostic of the main modes of tropical climates. Past estimates of Pacific thermocline dynamics have been reconstructed either for the Last Glacial Maximum or on longer timescales at low resolution. Here we document a new high-resolution set of reconstructed past sea surface and subsurface waters temperatures from the southwestern subequatorial Pacific, core MD05-2930, in the Gulf of Papua, over the last 800 ka. We used two morphotypes of Globigerinoides ruber known to live at different water depths to reconstruct past stratification. We estimated calcification temperature of each morphotypes by Mg/Ca paleothermometry. Our subequatorial Pacific thermocline paleotemperature record indicates a response of the thermocline to both direct orbital forcing and glacial-interglacial changes. Our stratification record shows a systematic shallower glacial thermocline, whereas sea surface temperatures are characterized by precessional forcing. The record is indicative of a progressive long-term shoaling of the thermocline during the glacial stages during the late Pleistocene. The shoaling of the subequatorial Pacific thermocline is consistent with regional estimates. An enhanced South Pacific shallow overturning wind-driven circulation could have driven this progressive shoaling. We speculate that this late Pleistocene glacial shoaling of the thermocline could be related to an increase in the amplitude of the obliquity.

The use of planktonic foraminifera in paleoceanography requires taxonomic consistency and precise assessment of the species biogeography. Yet, ribosomal small subunit (SSUr) DNA analyses have revealed that most of the modern morphospecies of planktonic foraminifera are composed of a complex of several distinct genetic types that may correspond to cryptic or pseudo-cryptic species. These genetic types are usually delimitated using partial sequences located at the 3'end of the SSUrDNA, but typically based on empirical delimitation. Here, we first use patristic genetic distances calculated within and among genetic types of the most common morpho-species to show that intra-type and inter-type genetic distances within morpho-species may significantly overlap, suggesting that genetic types have been sometimes inconsistently defined. We further apply two quantitative and independent methods, ABGD (Automatic Barcode Gap Detection) and GMYC (General Mixed Yule Coalescent) to a dataset of published and newly obtained partial SSU rDNA for a more objective assessment of the species status of these genetic types. Results of these complementary approaches are highly congruent and lead to a molecular taxonomy that ranks 49 genetic types of planktonic foraminifera as genuine (pseudo) cryptic species. Our results advocate for a standardized sequencing procedure allowing homogenous delimitations of (pseudo) cryptic species. On the ground of this revised taxonomic framework, we finally provide an integrative taxonomy synthesizing geographic, ecological and morphological differentiations that can occur among the genuine (pseudo) cryptic species. Due to molecular, environmental or morphological data scarcities, many aspects of our proposed integrative taxonomy are not yet fully resolved. On the other hand, our study opens up the potential for a correct interpretation of environmental sequence datasets.

The planktonic foraminiferal morpho-species Globoconella inflata is widely used as a stratigraphic and paleoceanographic index. While G. inflata was until now regarded as a single species, we show that it rather constitutes a complex of two pseudo-cryptic species. Our study is based on SSU and ITS rDNA sequence analyses and genotyping of 497 individuals collected at 49 oceanic stations covering the worldwide range of the morpho-species. Phylogenetic analyses unveil the presence of two divergent genotypes. Type I inhabits transitional and subtropical waters of both hemispheres, while Type II is restricted to the Antarctic subpolar waters. The two genetic species exhibit a strictly allopatric distribution on each side of the Antarctic Subpolar Front. On the other hand, sediment data show that G. inflata was restricted to transitional and subtropical environments since the early Pliocene, and expanded its geographic range to southern subpolar waters similar to 700 kyrs ago, during marine isotopic stage 17. This datum may correspond to a peripatric speciation event that led to the partition of an ancestral genotype into two distinct evolutionary units. Biometric measurements performed on individual G. inflata from plankton tows north and south of the Antarctic Subpolar Front indicate that Types I and II display slight but significant differences in shell morphology. These morphological differences may allow recognition of the G. inflata pseudo-cryptic species back into the fossil record, which in turn may contribute to monitor past movements of the Antarctic Subpolar Front during the middle and late Pleistocene.