Patrice Brehmer

This study, conducted on the Cap-Vert peninsula (Dakar, Senegal), examines the epifaunal communities associated with macroalgae, revealing significant variations depending on the species of algae. In 2023 (in situ samples), amphipods dominated most macroalgae, particularly Coralina officinalis (29.40%) (Rhodophyceae), Chlorophyceae (30.38%), and Codium sp. (29.38%) (Chlorophyceae). In 2022, copepods (76–92%) were most abundant on Sargassum spp. and Ulva spp., which had washed up on the beach. A significant link between epifaunal abundance and macroalgae species highlighted their ecological interdependence. These findings are of relevant interest for West Africa’s blue economy, where the growing exploitation of wild macroalgae could disrupt these ecosystems. Sustainable management must take into account epifaunal species, particularly those found on structurally important macroalgae (e.g., Corallina sp., Codium sp.). The study recommends including macroalgae-epifauna associations in biodiversity inventories, particularly in marine protected areas, and continuing research on influencing factors (e.g., algal morphology, environmental conditions). Mass strandings of Sargassum spp. and Ulva spp. can cause mortality in marine larvae and eggs, leading to a local reduction in recruitment. Future research integrating these conclusions could allow a more detailed analysis of the epifauna on macroalgae. Ecosystem approach is essential to strike a balance between economic development and biodiversity conservation.

Sustainable freshwater aquaculture is crucial for food security and economic development in Africa, particularly in North West Africa’s less advanced countries. Existing complex monitoring methods are often impractical for these contexts due to technical and resource limitations. We developed and tested a localised tool to evaluate the sustainability of tilapia farms across diverse agroecological zones in Senegal. The approach involved engaging farmers in a participatory process to identify context-relevant indicators for the environmental, social, and economic dimensions of tilapia farming. These indicators were scored to create a composite sustainability index. Key sustainability challenges identified included a lack of technical support, profitability issues, inadequate environmental management, and social welfare concerns. However, we found promising potential for integrated community-based farms. The sustainability indicators inform policies and practices that promote localised sustainability in sub-Saharan Africa, while considering smallholder farms’ unique needs and characteristics. These assessments contribute to implementing targeted interventions, improved resource management, and enhanced social and environmental outcomes in the freshwater farming industry. Collaboration and knowledge sharing among stakeholders can significantly contribute to developing sustainable aquaculture practices, though successful implementation requires specific, medium-term practice programmes. The tool successfully discriminated between farm types, with intensive private farms scoring highest overall (up to 73% of the maximum sustainability score), while extensive farms in the southern region scored lowest (≈40%). The study demonstrates the value of participatory, context-specific tools for diagnosing sustainability and guiding improvements in African aquaculture.

The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multidecadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only 3 years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: (1) developing km-scale Earth system models with small errors in the energy and water balance, (2) performing km-scale climate simulations with a throughput greater than 1 simulated year per day, and (3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The hackathon participants included experts from climate science, software engineering, and high-performance computing as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations with ICON and IFS-FESOM, spanning the period 2020–2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its time frame, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.

This study from Cap-Vert (Dakar, Senegal) examines epifaunal communities associated with macroalgae, revealing key variations based on algal species and sampling period. In 2023 (in situ samples), amphipods (24–30%) dominated, particularly on Corallina officinalis (Rhodophyceae), while 2022 (beached samples) showed copepods (76–92%) as the most abundant on Sargassum and Ulva spp. The highest epifaunal density was recorded on 2023 Ulva spp. (Chlorophyceae). Univariate analysis confirmed a significant link between epifaunal abundance and macroalgae species, highlighting their ecological interdependence. These findings are critical for West Africa’s blue economy, where expanding macroalgae exploitation could disrupt these ecosystems. Sustainable management should account for species-specific epifaunal dependencies, particularly for structurally important algae (Corallina, Codium). The study recommends integrating macroalgae-epifauna associations into biodiversity inventories, especially in marine protected areas, and further research on influencing factors (algal morphology, environmental conditions). An ecosystem-based approach is essential to balance economic development and biodiversity conservation.

The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multi-decadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only three years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: 1) developing km-scale Earth system models with small errors in the energy and water balance, 2) performing km-scale climate simulations with a throughput greater than one simulated year per day, and 3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The participants in hackathons included experts from climate science, software engineering, and high-performance computing, as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations of ICON and IFS-FESOM, spanning the period 2020–2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its timeframe, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.

The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multi-decadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only three years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: 1) developing km-scale Earth system models with small errors in the energy and water balance, 2) performing km-scale climate simulations with a throughput greater than one simulated year per day, and 3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The participants in hackathons included experts from climate science, software engineering, and high-performance computing, as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations of ICON and IFS-FESOM, spanning the period 2020–2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its timeframe, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.

The association of epifaunal communities with marine macroalgae has not yet been studied on the Cape Verde Peninsula (Dakar, Senegal). Macroalgae were collected at sea during the warm season (July) from stations around the Cape Verde Peninsula to investigate their association with epifaunal organisms. A predominance of amphipods was noted across the entire epifaunal community. The abundance of this order was higher on the macroalgae Corallina officinalis. The highest epifaunal density was observed on the genus Ulva sp. A significant relationship was observed between the diversity and abundance of epifaunal communities and macroalgal species. However, there was no significant relationship between the biomass of the macroalgae and the biomass of the epifauna. The methodology used in this study could be replicated on a larger spatial and temporal scale. This would provide deeper insights into the communities hosted by macroalgae within the context of the growing blue economy, encouraging future exploitation of macroalgae and addressing biodiversity loss.Keywords: Epifauna, Macroalgae, Dakar, Senegal.

The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multi-decadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only three years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: 1) developing km-scale Earth system models with small errors in the energy and water balance, 2) performing km-scale climate simulations with a throughput greater than one simulated year per day, and 3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The participants in hackathons included experts from climate science, software engineering, and high-performance computing, as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations of ICON and IFS-FESOM, spanning the period 2020–2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its timeframe, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.

In 2020–2021, a “mysterious illness” struck Senegalese fishermen, causing severe acute dermatitis in over one thousand individuals following exposure through drift-net fishing activity. Here, by performing deep analysis of the environmental samples we reveal the presence of the marine dinoflagellate Vulcanodinium rugosum and its associated cyclic imine toxins. Specifically, we show that the toxin PortimineA, strongly enriched in environmental samples, impedes ribosome function in human keratinocytes, which subsequently activates the stress kinases ZAKα and P38 and promotes the nucleation of the human NLRP1 inflammasome, leading to the release of IL-1β/IL-18 pro-inflammatory cytokines and cell death. Furthermore, cell-based models highlight that naturally occurring mutations in the P38-targeted sites of human NLRP1 are unable to respond to PortimineA exposure. Finally, the development and use of human organotypic skins and zebrafish models of PortimineA exposure demonstrate that the ZAKα-NLRP1 axis drives skin necrosis and inflammation. Our results exemplify the threats to human health caused by emerging environmental toxins and identify ZAKα and NRLP1 as important pharmacological targets to mitigate PortimineA toxicity.