AtlantECO-KER-AM-2

The Benguela Upwelling System is one of the most productive marine coastal ecosystems globally, driven by wind-induced upwelling of cold, nutrient-rich deep waters. However, the system’s complexity, combined with data scarcity, has left its dynamics and long-term response to a warming climate insufficiently understood. This study employs a high-resolution coupled physical-biogeochemical modeling system, using a two-way nesting strategy, to investigate the dynamics of the Benguela Upwelling System over a four-decade period (1980–2020). The physical model component, the Nucleus for European Modeling of the Ocean (NEMO), is coupled with the Biogeochemical Flux Model (BFM) to reproduce both physical and biogeochemical dynamics within a high-resolution Benguela domain. The physical component demonstrates good skill in replicating observational annual and seasonal climatologies of seawater temperature, salinity, and near-surface currents. The simulated biogeochemical fields satisfactorily compare with observational datasets available in the Benguela region for inorganic nutrients, dissolved oxygen, and upper ocean Chlorophyll-a (Chl-a) concentrations. Model outcomes were then used to investigate the long-term sea surface temperature and Chl-a trends by focusing on the upwelling zone, where a cooling trend was detected in both the northern and southern Benguela subregions, suggesting the occurrence of an upwelling intensification in recent decades. Although a positive Chl-a trend was observed in both subregions, the loose correspondence in either location or timing with the surface temperature signal indicates that algal growth is only partly influenced by the upwelling intensity. This coupled modeling framework provides valuable insights into the Benguela Upwelling System and could serve as a basis for improving our understanding of the variability in physical and ecological processes over recent decades.

Sexual reproduction is a nearly universal characteristic of the eukaryotic life cycle, yet it is rarely observed in natural populations of micro-eukaryotes. Sex is particularly relevant for diatoms, a key group of marine and freshwater phytoplankton, where sexual reproduction counters a progressive cell size reduction due to cellular division. Here, we leveraged controlled sex transcriptome experiments of four diatom species to develop a robust method for in situ monitoring of sexual reproduction events. The resulting panel of conserved marker genes was validated for specificity and sensitivity using metatranscriptomic profiling of a natural estuarine community undergoing massive sexual reproduction of multiple species in response to increased salinity. Analysis of metatranscriptomic data linked with Metagenome-Assembled Genomes from the Tara Oceans expedition revealed widespread and coordinated expression of these markers across nine diatom genera, complemented by observations of sexual stages in automated imaging resources. Our results reveal that diatom sexual reproduction is more widespread in the global ocean than previously thought, encompassing both dominant bloom-forming species and rare taxa. Our panel of markers to detect sexual reproduction in natural environments paves the road to better understand the interplay between endogenous and environmental controls of this pivotal process, essential for the diatoms’ evolutionary success.

Microbial competition for scarce resources shapes biodiversity patterns and ecosystem function across global biomes, yet quantifying this process from genomic data has remained elusive. Here, we introduce CaCo, a scalable metric that transforms metagenomic carbohydrate-active enzyme profiles into precise measures of niche overlap and competition potential (Resource Partitioning Score, RPS). Analyzing 14,691 high-quality metagenome-assembled genomes spanning Ocean, freshwater, soil, and human gut microbiomes, we reveal a striking macroecological pattern: Niche overlap increases from partitioned specialists in oligotrophic oceans to overlapping generalists in carbon-rich environments, including the human gut. This gradient aligns with classic niche theory, as phylogenetic signals indicate that closely related taxa may compete most intensely. Multitiered validation, spanning BIOLOG phenotypes, synthetic cocultures, and interaction gradients, confirms CaCo’s predictive power and captures competitive exclusion. CaCo bridges genomic potential and ecological reality, providing niche-breadth metrics and enabling testable predictions of how resource availability shapes microbial competition and community structure.

Latitudinal diversity gradients (LDGs), which typically decline from the equator to the poles, are a pervasive macroecological pattern. However, 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 exhibit diversity peaks at (sub)tropical latitudes and a poleward decline, whereas mesopelagic communities (200–1,000 m) show no latitudinal diversity structuring. Taxonomic resolution reveals that the mixed-layer LDG is underpinned by Alphaproteobacteria and Cyanobacteriia, while other taxa exhibit distinct or contrasting LDGs. Diversity structuring also varies by seasons and regions and is governed by temperature and nutrient availability. Together, these findings highlight that, within the ocean microbiome, LDGs are not universal but reflect 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.

Dimethylsulfoniopropionate (DMSP) is a highly abundant marine organosulfur compound, with important roles in stress protection and climate-cooling gases production. Polar regions, particularly seawater and sea ice interfaces, are critical yet understudied DMSP cycling hotspots. Here, we reveal up to 38-fold higher DMSP concentrations in Southern Ocean sea ice versus seawaters, identifying sea ice as a concentrated reservoir of DMSP with implications for microbial stress tolerance and sulfur recycling. Eukaryotic algae harboring DSYB and DSYE genes were predicted to dominate DMSP production, but diverse and previously unidentified bacterial producers were also detected. This elevated abundance of algal biosynthetic genes likely underpins the higher DMSP concentrations in sea ice. Notably, DMSP catabolism, particularly the dmdA demethylase and dddD and dddK lyase genes, were more abundant than biosynthesis genes. Taken together, these findings reveal the widespread metabolism for DMSP cycling and underscore a dynamic reservoir and transformation hub influencing polar climate-cooling sulfur fluxes.

We conducted a high-resolution analysis of diatom populations in the microphytoplankton size range using data collected at 30-min intervals over a 20-month period by an automated imaging system deployed near the mouth of Baía de Todos os Santos (BTS), Brazil. Seven diatom taxa were identified and quantified through automated classification using a Convolutional Neural Network (CNN). Frequency-domain analysis revealed distinct environmental drivers acting across different temporal scales. At high-frequency scales (53 h), solar radiation was the predominant factor influencing diatom abundances. At intermediate to monthly scales (53 h–13 days, neap-spring cycles of 13–15 days, and monthly scales), canonical correspondence analysis (CCA) indicated that dissolved oxygen, temperature, and salinity were the primary environmental drivers. Multiple linear regression (MLR) models highlighted colored dissolved organic matter (CDOM) and the north-south wind component as key predictors for Coscinodiscus wailesii abundances. K-strategist marine taxa, including Rhizosolenia robusta and the Rhizosolenia–Proboscia complex, exhibited peak densities during neap tides, coinciding with stronger intrusion events of oligotrophic oceanic waters into the bay. Conversely, r-strategist coastal and estuarine taxa, including C. wailesii, Bacteriastrum-Chaetoceros complex, and Guinardia striata, reached maximum abundances during spring tides, associated with enhanced river discharge and pronounced ebb flow conditions. These taxon-specific distribution patterns demonstrate the influence of environmental forcing across multiple temporal scales on diatom populations. Our findings show the effectiveness of frequency-domain analytical approaches in resolving the complex interactions between environmental variability and phytoplankton dynamics, enhancing understanding of bottom-up regulatory processes and inter-taxa ecological interactions in coastal tropical ecosystems.

Marine heat waves affect ocean ecosystems and are expected to become more frequent and intense. Earth system models’ ability to reproduce extreme ocean temperature statistics has not been tested quantitatively, making the reliability of their future projections of marine heat waves uncertain. We demonstrate that annual maxima of detrended anomalies in daily mean sea surface temperatures (SSTs) over 39 years of global satellite observations are described excellently by the generalized extreme value distribution. If models can reproduce the observed distribution of SST extremes, this increases confidence in their marine heat wave projections. 14 CMIP6 models' historical realizations reproduce the satellite-based distribution and its parameters’ spatial patterns. We find that maximum ocean temperatures will become warmer (by 1.07° ± 0.17°C under 2°C warming and 2.04° ± 0.18°C under 3.2°C warming). These changes are mainly due to mean SST increases, slightly reinforced by SST seasonality increases. Our study quantifies ocean temperature extremes and gives confidence to model projections of marine heat waves.