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Mesozooplankton play a key role in marine ecosystems as they modulate the transfer of energy from phytoplankton to large marine organisms. In addition, they directly influence the oceanic cycles of carbon and nutrients through vertical migrations, fecal pellet production, respiration, and excretion. Mesozooplankton are mainly made up of metazoans, which undergo important size changes during their life cycle, resulting in significant variations in metabolic rates. However, most marine biogeochemical models represent mesozooplankton as protists-like organisms. Here, we study the potential caveats of this simplistic representation by using a chemostat-like zero-dimensional model with four different Nutrient-Phytoplankton-Zooplankton configurations in which the description of mesozooplankton ranges from protist-type organisms to using a size-based formulation including explicit reproduction and ontogenetic growth. We show that the size-based formulation strongly impacts mesozooplankton. First, it generates a delay of a few months in the response to an increase in food availability. Second, the increase in mesozooplankton biomass displays much larger temporal variations, in the form of successive cohorts, because of the dependency of the ingestion rate to body size. However, the size-based formulation does not affect smaller plankton or nutrient concentrations. A proper assessment of these top-down effects would require implementing our size-resolved approach in a 3-dimensional biogeochemical model. Furthermore, the bottom-up effects on higher trophic levels resulting from the significant changes in the temporal dynamics of mesozooplankton could be estimated in an end-to-end model coupling low and high trophic levels.

As the volume of accessible marine pelagic observations increases exponentially, incorporating diverse data types such as metagenomics and quantitative imaging, the need for standardized modelling frameworks becomes critical to predict biogeographic patterns in space and time and across the diverse range of emergent sampling methods. In response, we introduce CEPHALOPOD (Comprehensive Ensemble Pipeline for Habitat modelling Across Large‐scale Ocean Pelagic Observation Datasets), a standardized, highly automated and flexible framework designed to integrate and analyse heterogeneous marine data for multi‐species habitat modelling following best practices in the field. CEPHALOPOD is built on observational data from federating initiatives such as AtlantECO, OBIS, GBIF, associated with already existing statistical and machine learning methods that enable to extract and model information from heterogeneous, scarce and biased field observations. It is highly automated and follows explicit quality checks informing the user of the predictive accuracy and interpretability of the results. Here, we document our statistical ensemble modelling approach and then assess its strengths and limitations with a virtual ecologist approach. We show how our framework performs in reproducing a range of distributions from biased field samples. Our modelling framework serves as a foundation for the consistent generation of Essential Biodiversity and Ocean Variables (EBVs and EOVs) and carries the potential to significantly advance our comprehension of biodiversity and marine ecosystem functioning. Finally, it provides an unprecedented opportunity to foster collaborations in the field of marine science, sustainable ecological practices, and ultimately contribute to the preservation of global marine biodiversity.

The giant kelp Macrocystis pyrifera is a cosmopolitan species of cold-temperate coasts. Its South-American distribution ranges from Peru to Cape Horn and Argentina, encompassing a considerable temperature gradient, from 3 to 20°C. Temperature is known to strongly affect survival, growth and reproduction of many kelp species, and ongoing global warming is already eroding their range distribution. Their response to thermal variability was shown to vary among genetically differentiated regions and populations, suggesting a possible adaptive divergence in thermal tolerance traits. This study aimed at testing the existence of local adaptation in the giant kelp, in regions separated by up to 4000km and strong thermal divergence. Two complementary experiments mimicked reciprocal transplants through a common garden approach, each habitat being represented by a given temperature corresponding to the regional average of the sampled populations. Several proxies of fitness were measured in the haploid stage of the kelp, and sympatric versus allopatric conditions (i.e. individuals at the temperature of their region of origin versus in a different temperature and versus individuals from other regions in that temperature) were compared. Additionally, a heat wave at 24°C was applied to measure the tolerance limits of these gametophytes. A significant interaction between experimental temperature and region of origin revealed that temperature tolerance varied among regions. However, depending on the fitness parameter measured, high latitude populations from the sub-Antarctic region were not always less heat resilient than populations from the warmer region of Peru. Even at 24°C, a temperature that is exceptionally reached in the southernmost part of the kelp’s natural habitat, all the gametophytes survived, although with strong differences in other traits among regions and populations within regions. This large range of temperature tolerance supports the idea of kelp gametophytes being a resistant stage. Finally, local adaptation sensu stricto was not detected. Fertility was more influenced by the geographic origin than by temperature, with possible effects of marginal conditions at the extremes of the distribution range. The latter results also suggest that stochastic dynamics such as genetic drift restricts adaptive processes in some populations of M. pyrifera.

Filter-feeding gelatinous macrozooplankton (FFGM), namely salps, pyrosomes and doliolids, are increasingly recognized as an essential component of the marine ecosystem. Unlike crustacean zooplankton (e.g., copepods) that feed on prey that are an order of magnitude smaller, filter feeding allows FFGM to have access to a wider range of organisms, with predator-over-prey size ratios as high as 105:1. In addition, most FFGM produce carcasses and/or fecal pellets that sink 10 times faster than those of copepods. This implies a rapid and efficient export of organic matter to depth. Even if these organisms represent < 5 % of the overall planktonic biomass, their associated organic matter flux could be substantial. Here we present a first estimate of the influence of FFGM on the export of particulate organic matter to the deep ocean based on the marine biogeochemical model NEMO-PISCES (Nucleus for European Modelling of the Ocean, Pelagic Interaction Scheme for Carbon and Ecosystem Studies). In this new version of PISCES, two processes characterize FFGM: the preference for small organisms due to filter feeding and the rapid sinking of carcasses and fecal pellets. To evaluate our simulated FFGM distribution, we compiled FFGM abundance observations into a monthly biomass climatology using a taxon-specific biomass–abundance conversion. Model–observation comparison supports the model's ability to quantify the global and large-scale patterns of FFGM biomass distribution but reveals an urgent need to better understand the factors triggering the boom-and-bust FFGM dynamics before we can reproduce the observed spatio-temporal variability of FFGM. FFGM substantially contribute to carbon export at depth (0.4 Pg C yr−1 at 1000 m), particularly in low-productivity regions (up to 40 % of organic carbon export at 1000 m), where they dominate macrozooplankton biomass by a factor of 2. The FFGM-induced export increases in importance with depth, with a simulated transfer efficiency close to 1.

The impact of anthropogenic climate change on marine net primary production (NPP) is a reason for concern because changing NPP will have widespread consequences for marine ecosystems and their associated services. Projections by the current generation of Earth system models have suggested decreases in global NPP in response to future climate change, albeit with very large uncertainties. Here, we make use of two versions of the Institut Pierre-Simon Laplace Climate Model (IPSL-CM) that simulate divergent NPP responses to similar high-emission scenarios in the 21st century and identify nitrogen fixation as the main driver of these divergent NPP responses. Differences in the way N fixation is parameterised in the marine biogeochemical component PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies) of the IPSL-CM versions lead to N-fixation rates that are either stable or double over the course of the 21st century, resulting in decreasing or increasing global NPP, respectively. An evaluation of these two model versions does not help constrain future NPP projection uncertainties. However, the use of a more comprehensive version of PISCES, with variable nitrogen-to-phosphorus ratios as well as a revised parameterisation of the temperature sensitivity of N fixation, suggests only moderate changes in globally averaged N fixation in the 21st century. This leads to decreasing global NPP, in line with the model-mean changes of a recent multi-model intercomparison. Lastly, despite contrasting trends in NPP, all our model versions simulate similar and significant reductions in planktonic biomass. This suggests that projected plankton biomass may be a more robust indicator than NPP of the potential impact of anthropogenic climate change on marine ecosystems across models.

Defended species are often conspicuous and this is thought to be an honest signal of defences, i.e. more toxic prey are more conspicuous. Neotropical butterflies of the large Ithomiini tribe numerically dominate communities of chemically defended butterflies and may thus drive the evolution of mimetic warning patterns. Although many species are brightly coloured, most are transparent to some degree. The evolution of transparency from a warning-coloured ancestor is puzzling as it is generally assumed to be involved in concealment. Here, we show that transparent Ithomiini species are indeed less detectable by avian predators (i.e. concealment). Surprisingly, transparent species are not any less unpalatable, and may in fact be more unpalatable than opaque species, the latter spanning a larger range of unpalatability. We put forth various hypotheses to explain the evolution of weak aposematic signals in these butterflies and other cryptic defended prey. Our study is an important step in determining the selective pressures and constraints that regulate the interaction between conspicuousness and unpalatability.

In recent years, the volume of accessible marine pelagic observations has increased exponentially and now incorporates a wealth of new data types, including information derived from metagenomics and quantitative imaging. This calls for standardized modelling protocol across taxonomically harmonized observations, to better predict biogeographic patterns in space and time, and thus investigate marine ecosystem structure and functioning on a macroecological scale. In this context, we introduce CEPHALOPOD (Comprehensive Ensemble Pipeline for Habitat modelling Across Large-scale Ocean Pelagic Observation Datasets), a standardized and flexible framework to perform multi-species marine habitat modelling across data types and data sources. We built this new framework on observational data from federating initiatives such as AtlantECO, OBIS, GBIF, associated with already existing statistical and machine learning methods that enable to extract and model information from heterogeneous, scarce, and biased field observations. Here, we first document our statistical ensemble modelling approach and then assess its strength and limitations with a virtual ecologist approach. We show how our framework performs in reproducing a range of distributions from biased field samples. Then, we illustrate its performance and comparability across data types by investigating the global diversity patterns of coccolithophores from both abundance and metagenomic data. Our modelling framework serves as a foundation for the consistent generation of Essential Biodiversity and Ocean Variables (EBVs and EOVs) and carries the potential to significantly advance our comprehension of biodiversity and marine ecosystems functioning. Finally, it provides an unprecedented opportunity to foster collaborations in the field of marine science, sustainable ecological practices, and, ultimately, contribute to the preservation of global marine biodiversity.

Latitudinal diversity gradients (LDGs), typically declining from equator to poles, are a pervasive macroecological pattern, yet their generality and drivers in the ocean microbiome remain widely unresolved. We integrated global-scale metagenomic data with habitat modeling to study marine microbial LDGs across seasons and depths. Surface mixed layer microbiomes exhibited diversity peaks at (sub)tropical latitudes and a poleward decline, whereas mesopelagic communities (200–1,000 m) showed no latitudinal diversity structuring. Taxonomic resolution revealed that the mixed layer LDG was underpinned by Alphaproteobacteria and Cyanobacteriia, while other taxa exhibited distinct or contrasting LDGs. Diversity structuring also varied by seasons and regions, governed by temperature and nutrient availability. Together, these findings highlight that within the ocean microbiome, LDGs are not universal, but lineage-specific ecological strategies and responses to environmental gradients. Our study provides fundamental insights into the structuring of ocean microbiome diversity and lays the foundation for predicting responses to environmental change.

Introduction. Computational modeling of the human pelvis using the finite elements (FE) method has become increasingly important to understand the mechanisms of load distribution under both healthy and pathologically altered conditions and to develop and assess novel treatment strategies. The number of accurate and validated FE models is however small, and given models fail resembling the physiologic joint motion in particular of the sacroiliac joint. This study is aimed at using an inverted validation approach, using in vitro load deformation data to refine an existing FE model under the same mode of load application and to parametrically assess the influence of altered morphology and mechanical data on the kinematics of the model. Materials and Methods. An osteoligamentous FE model of the pelvis including the fifth lumbar vertebra was used, with highly accurate representations of ligament orientations. Material properties were altered parametrically for bone, cartilage, and ligaments, followed by changes in bone geometry (solid versus 3 and 2 mm shell) and material models (linear elastic, viscoelastic, and hyperelastic isotropic), and the effects of varying ligament fiber orientations were assessed. Results. Elastic modulus changes were more decisive in both linear elastic and viscoelastic bone, cartilage, and ligaments models, especially if shell geometries were used for the pelvic bones. Viscoelastic material properties gave more realistic results. Surprisingly little change was observed as a consequence of altering SIJ ligament orientations. Validation with in vitro experiments using cadavers showed close correlations for movements especially for 3 mm shell viscoelastic model. Discussion. This study has used an inverted validation approach to refine an existing FE model, to give realistic and accurate load deformation data of the osteoligamentous pelvis and showed which variation in the outcomes of the models are attributed to altered material properties and models. The given approach furthermore shows the value of accurate validation and of using the validation data to fine tune FE models.