Key Expoitable Results (KERs)

The ocean plays a central role in the global carbon cycle. It regulates atmospheric CO₂ through long-term sequestration in coastal and deep-sea systems. Blue Carbon Ecosystems (BCEs)—mangroves, salt marshes, seagrass meadows, and tidal flats—are recognized for their high carbon burial efficiency per unit area and their growing relevance in climate policy. In contrast, the open ocean, driven by the Biological Carbon Pump (BCP), dominates large-scale carbon storage but is rarely considered alongside coastal systems in carbon budget assessments. Here, we present a basin-scale assessment of carbon sequestration across the Atlantic coastal and open-ocean domains. To do so, we quantified carbon fluxes and long-term stocks by harmonizing and integrating spatial datasets, Earth System Model outputs, and a data-assimilated biogeochemical framework. Coastal ecosystems show high sequestration efficiency per unit area. The open ocean, however, accounts for most of the total carbon storage due to its depth, extent, and circulation-driven redistribution of remineralized carbon. By creating a unified framework that allows to combine coastal burial processes with pelagic carbon transfer in a consistent way, this study clarifies how different definitions of sequestration shape basin-scale estimates. The results provide a robust basis for improving representation of marine carbon processes in regional and global carbon budgets, marine conservation strategies, and climate mitigation planning.

Understanding the complexity of food webs is crucial for assessing ecosystem dynamics. However, the high number of trophic interactions in typical food webs complicates the identification of clear top-down or bottom-up regulatory effects. In this study, we applied interaction asymmetry analysis to examine causality within food webs, allowing for the identification of critical interactions based on topological importance (TI) metrics, which incorporate indirect interactions. We evaluated this method using 34 food web models from the Ecobase database and compared its performance with widely used network metrics. By constructing asymmetry graphs, we transformed original, undirected binary food webs into directed networks highlighting strong causal interactions. Pairwise correlation analyses revealed that ecosystems with higher total biomass indicated stronger bottom-up causal links and greater consumer diversity. Our findings suggest that asymmetry-based metrics provide robust quantitative indicators of causality, offering a straightforward yet powerful tool for assessing ecosystem functioning and health.

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.