One-year high-frequency environmental and behavioral data from ALAN experience in a French coastal area
Despite the widespread exposure to artificial light at night (ALAN) on coastal ecosystems, its effects are poorly studied, and data remain scarce compared to terrestrial ecosystems. Coastal areas are critical for ecosystem services, providing biodiversity, social, and commercial benefits. To acquire high-quality data on ALAN impacts on coastal ecosystems, we conducted a one-year in situ study in the “Ile aux Oiseaux” site, part of the Arcachon Bay (France), from December 2023 to November 2024. The experimental platforms consisted of two oyster tables: one for the control condition exposed to natural light and one exposed to a skyglow ALAN intensity using underwater LEDs. The impacts of ALAN were assessed using two oyster species (Crassostrea gigas and Ostrea edulis) as sentinel organisms, recording continuously their valve behavior using high-frequency non-invasive valvometer biosensors. To characterize the local environment, the experimental platform was also equipped with multiple sensors for the long-term measurement of light irradiance and additional physical parameters (temperature, water level, salinity, turbidity, conductivity, and low-frequency sound).
(Scientific Data. vol. 12, n° 2052-4463, pp. 1808, 18/11/2025)
EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS, GEODE, UT2J, Comue de Toulouse, CNRS
Shallow benthic invertebrate communities in relation to substrate types in coastal environments of the sub-Antarctic Crozet archipelago.
Coastal ecosystems of sub-Antarctic islands are threatened by increasing climate-driven changes and direct anthropogenic pressures. Significant effects on marine communities are expected, but benthic ecosystems of these isolated islands remain largely under-explored. Effective preservation of these nearshore environments requires deeper ecological assessments and comprehensive biodiversity knowledge. In this regard, this study reports findings from a survey carried out in 2021 at two sites – Baie du Marin and Crique du Sphinx – located on the eastern coast of Ile de la Possession (sub-Antarctic Crozet archipelago, Southern Ocean). We investigated the composition and structure of nearshore benthic faunal communities using a quantitative fieldwork protocol and an integrative molecular- and morphology-based taxonomic approach. A total of 124 morphotypes were identified, including a high proportion (72%) of rare species. Both sites exhibited similar benthic invertebrate communities. Structurally complex habitats such as hard substrates or areas dominated by macroalgae exhibited higher species richness and diversity. The investigated benthic invertebrate communities are typical of the sub-Antarctic area but featured unique structures, including dense tube-dwelling polychaete colonies. This study will provide a baseline for future monitoring programs and for the preservation of sub-Antarctic coastal benthic ecosystems.
(Frontiers in Marine Science. vol. 12, n° 2296-7745, pp. 1692217, 14/11/2025)
BGS, EPHE, PSL, CNRS, UBE, LBM, ULB, LECOB, SU, CNRS, OOB, SU, CNRS, ULiège, ULiège, UMAG, CHIC, BASE, EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS, IMR, UiB, UIB, UAM
Développement de nouveaux algorithmes d’apprentissage statistique pour coupler projections climatiques et observations passées en vue de réduire les incertitudes du changement climatique à venir
Le climat change à cause des émissions humaines de gaz à effet de serre. Les modèles climatiques permettent de projeter son évolution selon des scénarios futurs d’émissions humaines (SSP). Cependant, les résultats des différents modèles climatiques développés dans le monde sont quantitativement divergents, générant une grande incertitude appelée par la suite incertitude modèle.Cette incertitude modèle est particulièrement forte pour la circulation méridienne de retournement en Atlantique (AMOC), un système de courants océaniques qui affecte les conditions climatiques de nombreuses régions du globe. En effet, même si tous les modèles climatiques CMIP6 prévoient un ralentissement de l’AMOC, l’ampleur varie fortement : en moyenne, ils projettent un ralentissement AMOC de 33 ± 36% d’ici 2100 (confiance 90%, scénario SSP2-4.5).Pour réduire l’incertitude modèle, les méthodes dites de contraintes observationnelles (COs) ont été récemment développées. Elles contraignent les projections des modèles par l'observation réelle d'une (univarié) ou de plusieurs (multivarié) variables. Ces approches sont cependant difficiles à utiliser car dans la littérature (i) les fondements statistiques sur lesquels elles reposent ne sont pas toujours identiques et manquent souvent de clarté, (ii) les approches sont très diversifiées et souvent univariées, et (iii) le choix des variables observables est subjectif. Cette thèse se compose de trois articles qui traitent chacune de ces trois problématiques.(i) Le premier article propose un modèle statistique rigoureux pour une CO linéaire multivariée, appelé ClimLoco1.0. Il prend en compte l’incertitude sur l'observation réelle et l'incertitude provenant du nombre limité de modèles climatiques, toutes deux souvent négligées ou mal considérées dans la littérature. Dans un souci de pédagogie, l’article détaille progressivement la construction de ClimLoco1.0 et fournit des interprétations graphiques des résultats mathématiques obtenus.(ii) Le second article compare les performances de quatre approches de CO, par validation croisée. L’AMOC future y est contrainte soit par l’AMOC passée (univarié), soit par l’AMOC passée, la température et la salinité de surface de différentes régions océaniques choisies subjectivement (multivarié). L’approche la plus performante est la régression Ridge dans le cas multivarié, qui est particulièrement adaptée à notre étude. Elle fournit une estimation du ralentissement AMOC d’ici 2100 de 51 ± 8% (SSP2-4.5). Ce ralentissement plus important que celui estimé par la moyenne multi-modèle (33%) résulte principalement de la considération du biais des modèles climatiques concernant la salinité de surface en Atlantique sud. Cela est en accord avec la littérature reliant ce biais à la rétroaction positive d’advection de salinité, un mécanisme clé pour la stabilité de l’AMOC.(iii) Le troisième article utilise une méthode spécifique de clustering pour créer des groupes de régions associées à de nombreuses variables climatiques. Ces groupes sont interprétés pour identifier les mécanismes qui expliquent l’incertitude modèle de l’AMOC future. Ils sont également résumés par des variables synthétiques qui sont utilisées dans la méthode ClimLoco1.0 pour contraindre cette incertitude modèle. Cette méthode suggère que l’incertitude modèle est notamment expliquée par la rétroaction positive d’advection de salinité et les remontées d’eaux profondes, en accord avec la littérature. Contrainte par l’observation de ces variables synthétiques, l'estimation du ralentissement AMOC d'ici 2100 est de 45 ± 10% (SSP2-4.5).Les deux derniers articles estiment un ralentissement AMOC similaire, qui est plus important et moins incertain que celui estimé par la simple moyenne multi-modèles. Il semble donc opportun que ce résultat soit pris en compte afin d’améliorer les projections climatiques et les stratégies d'adaptation associées.
(14/11/2025)
ASTRAL, IMB, UB, Bordeaux INP, CNRS, Inria, UB, Bordeaux INP, EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS
Global Carbon Budget 2025
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data. Emissions from land-use change (ELUC) are estimated by bookkeeping models based on land-use and land-use change data. Atmospheric CO2 concentration is measured at surface stations, and the global atmospheric CO2 growth rate (GATM) is computed from the annual changes in concentration. The global net uptake of CO2 by the ocean (SOCEAN, called the ocean sink) is estimated with global ocean biogeochemistry models and observation-based fCO2products. The global net uptake of CO2 by the land (SLAND, called the land sink) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. The sum of all sources and sinks results in the carbon budget imbalance (BIM), a measure of imperfect data and incomplete understanding of the contemporary of 2023-2024 in the Northern Hemisphere. The ocean CO2 sink was 3.2 ± 0.4 GtC yr -1 during
(13/11/2025)
CICERO, UiO, UEA, GKSS, VLIZ, MPI-M, WUR, LMU, LMU, LMU, CSIRO, LSCE, UVSQ, INSU - CNRS, CNRS, DRF (CEA), CEA, BIOGEO, LSCE, UVSQ, INSU - CNRS, CNRS, DRF (CEA), CEA, UiO, PMEL, NOAA, KIT, CIMAS, RSMAS, BIOS, UOR, MFRI, BSC-CNS, LMD, INSU - CNRS, X, IP Paris, SU, CNRS, ENS-PSL, PSL, ENPC, IP Paris, CSIRO, JAMSTEC, SATINV, LSCE, UVSQ, INSU - CNRS, CNRS, DRF (CEA), CEA, JMA, LGENS, INSU - CNRS, CNRS, ENS-PSL, PSL, EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS
Investigation of the combined influence of salinity and particle concentration on the adsorption of anionic and zwitterionic PFAS onto estuarine sediment using the RSM modelling approach
Salinity (S) and suspended particulate matter (SPM) are key factors influencing the sorption of micropollutants in estuaries, due to strong gradients in these ecosystems. Previous laboratory or field-based studies have typically investigated the impact of S or SPM separately. Thus, the combined effects of S and SPM as well as their interactions on the sorption of micropollutants such as per- and polyfluoroalkyl substances (PFAS) in estuarine environments still remain poorly understood. We initially investigated the adsorption kinetics of 11 anionic and zwitterionic PFAS onto estuarine sediment under one S/SPM combination in laboratory-controlled conditions, as well as their adsorption isotherms under two S/SPM combinations. We also determined their distribution coefficients (K d ) across 35 S/SPM combinations covering a wide range of estuarine conditions. The adsorption kinetics of PFAS could be described by a pseudo-second-order model (equilibrium time <24h). Sorption isotherms were fitted by both linear and Freundlich models; the linear sorption range was in the range 0.12–1.31 nM and K d varied between 0.6 and 55271 L/kg. Based on response surface modelling, both S and SPM were significant factors, i.e. K d was positively related to S (salting-out effect), while it was negatively related to SPM concentration (third-phase effect). SPM had a stronger effect than S for short-chain carboxylates, whereas S was the dominant factor for most other compounds. We also present, for the first time, evidence of a significant negative interaction between these two factors. This study therefore provides a new perspective to model the fate of PFAS at the land-sea interface.
(Peer Community Journal. vol. 5, n° 2804-3871, pp. e124, 12/11/2025)
EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS
Deep learning for carbonate rocks petrography
This project aims to investigate deep learning capacity to enhance the identification of factors that may impact the dynamic behavior of carbonate reservoirs. This is achieved through the integration of comprehensive datasets comprising images acquired over decades from hydrocarbon carbonate reservoirs and identified outcrop analogues. Convolutional neural networks represent natural candidates for analyzing the thousands of available thin sections. This thesis developed a suite of complementary methods for their quantitative and automated description. An optimal subdivision strategy for high-resolution images was established to enable multi-scale characterization of this data type, closely approximating traditional microscopic analysis methods. The approach combines representation learning through a rotation-invariant variational autoencoder with automatic clustering, achieving a two-fold acceleration in labeling time while forming geologically coherent groups based primarily on R. Dunham's classifications for limestones, R. Folk's classifications for dolomites, and the incorporation of secondary minerals such as anhydrite facies. The model can then be refined for these subsidiary classification tasks, enabling semantic description of the samples studied (>88% mAP). To address the heterogeneity of existing petrographic descriptions and the lack of precise quantification on real data, two methods were developed: SynSection procedurally generates training data by simulating depositional processes (+20% mAP) in grain limestones, while SynSection2 unifies synthetic-to-realistic transformation with segmentation (+5% additional mAP). These approaches jointly enable automatic segmentation of elements (bioclasts, intraclasts, ooids, and peloids) and the creation of a homogeneous quantified database. Deep semantic segmentation applied to granular limestones provides access to quantification of relative proportions and grain size distribution analysis. The developed metrics achieve determination coefficients (R²) of 0.78 for mean grain size and 0.72 for sorting. This integrated methodology enables standardized and reproducible description following established petrographic nomenclatures and can be superimposed on pore network analysis. Automated quantification of pore types reveals heterogeneities that facilitate comparative analysis between samples. This approach constitutes a powerful tool for quantitative petrographic analysis, capable of incorporating local refinements to fully exploit deep learning's potential in characterizing carbonate systems and understanding associated petrophysical responses.
(10/11/2025)
EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS
Combined Atmospheric and Marine Heatwaves Exacerbate the Impacts of a Non-Indigenous Species, the Asian Date Mussel Arcuatula Senhousia, on Benthic Ecosystem Functioning
Climate change is predicted to increase the frequency, severity, and duration of extreme climatic events such as heatwaves. Benthic organisms inhabiting intertidal flats are subjected to both marine and atmospheric heatwaves and can experience extreme temperature variations over relatively short periods of time. Non-indigenous species are generally capable to cope with extreme events more efficiently that native species. The Arcachon bay, a lagoon located along the French Atlantic coast is currently colonised by the invasive mussel, Arcuatula senhousia. In this study, we investigated how these two stressors (non-indigenous species colonisation and heatwaves) affect soft-bottom ecosystem functioning. We conducted two seasonal laboratory experiments to investigate the effects of combined marine and atmospheric heatwaves on the biogeochemical dynamics of sediments colonised by A. senhousia at different densities. More precisely, we assessed the community scale responses by measuring nutrients (NOx, NH4+, PO43-) and oxygen fluxes across the sediment-water interface. The results highlight that (1) heatwaves affect oxygen and nutrient exchanges across the sediment-water interface, (2) the magnitude of these effects can be strongly enhanced by increasing densities of A. senhousia, and (3) a marked seasonal-dependence. These results emphasise that the interaction between the seasonality of heatwave occurrence, its intensity and the level of colonisation by non-indigenous ecosystem engineers likely shape their consequences for ecosystem functioning. Our results thus reinforce previous findings suggesting that climate change may profoundly exacerbate the effects of biological invasions.
(Marine Environmental Research. vol. 212, n° 0141-1136, pp. 107560, 01/11/2025)
EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS, PatriNat, MNHN, IRD, CNRS, OFB - DSUED, OFB, LERAR, COAST, IFREMER
Epigenetic regulation of sex: the role of DNA methylation and zbtb38 in zebrafish sex differentiation and heat-induced masculinization
There is increasing evidence that global change can threaten biodiversity by inducing skewed sex ratios. Accumulating evidences support a role of epigenetics, mainly DNA methylation, in sex differentiation. The aim of the present work was to investigate the potential role of zbtb38, a transcriptional factor that binds to methylated promoters, in sex differentiation and/or maintenance in zebrafish. We analyzed the methylation and transcription level of zbtb38 in males, females and undifferentiated individuals raised at standard or high temperature, a masculinizing factor. Results were compared to those obtained for genes already known to be involved in sex differentiation/maintenance (cyp19a1a, foxl2a, dmrt1). All genes presented a sex-specific pattern of DNA methylation and transcription but the most significant differences between sexes were observed for zbtb38. Moreover, a highly significant positive correlation was observed between the methylation level of zbtb38 and cyp19a1a, which encodes an enzyme that converts androgens into estradiol. However, while the hypermethylation of cyp19a1a was associated with its down-regulation, an inverse relationship was observed for zbtb38, providing a basis for mutual antagonism. Furthermore, zbtb38 was the only gene for which its transcription level was affected by temperature, being up-regulated in females that escaped to masculinization. Finally, despite embryos presented a paternal methylome, zbtb38 was the only gene for which its methylation level rapidly changed during early development to reach intermediate values between males and females at the larval stage, ie a bi-potential state. Our results strongly support a strategic role of DNA methylation and zbtb38 in sex differentiation and maintenance.
(Molecular and Cellular Endocrinology. vol. 609, n° 0303-7207, pp. 112636, 01/11/2025)
EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS
It’s about time: integrating micro- and macro-evolutionary perspectives into ecotoxicology for improved predictions and long-term assessment of ecosystem health
Whilst ecology has served as a foundational inspiration for risk assessment in ecotoxicology, far less attention has been given to evolution, despite its importance. As the need for a new paradigm in ecotoxicology is becoming increasingly evident in the face of Global change, the consideration of evolutionary processes and patterns should provide a way to progress towards this objective. This review draws on the recent literature to feed this idea, with a particular attention to the interplay between evolutionary paces. Doing so, we recast ecotoxicology as an innovative, exciting discipline, conceptually equipped to meet the challenges of the Anthropocene era.
(Current Opinion in Environmental Science & Health. vol. 48, pp. 100688, 01/11/2025)
LIENSs, INSU - CNRS, ULR, CNRS, EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS, DECOD, IFREMER, INRAE, Institut Agro, Institut Agro
New insights on the regional architecture and dynamics of mixed fluvio-aeolian deposits from Middle Buntsandstein in the southern margin of the German Basin
(pp. 658920, 27/10/2025)
EPOC, EPHE, PSL, UB, INSU - CNRS, CNRS, IFPEN, Bordeaux INP, GR, UR, INSU - CNRS, CNRS