Climate change is affecting ocean temperature, acidity, currents, and primary production, causing shifts in species distributions, marine ecosystems, and ultimately fisheries. Earth system models simulate climate change impacts on physical and biogeochemical properties of future oceans under varying emissions scenarios. Coupling these simulations with an ensemble of global marine ecosystem models indicates decreasing global fish biomass with warming. However, regional projections of these impacts remain much more uncertain. Here, we employ CMIP5 and CMIP6 climate change impact projections using two Earth system models coupled with four regional and nine global marine ecosystem models in ten ocean regions to evaluate model agreement at regional scales. We find that models developed at different scales can lead to stark differences in biomass projections. On average, global models projected greater biomass declines by the end of the 21st century than regional models. For both global and regional models, greater biomass declines were projected using CMIP6 than CMIP5 simulations. Global models projected biomass declines in 86% of CMIP5 simulations for ocean regions compared to 50% for regional models in the same ocean regions. In CMIP6 simulations, all global model simulations projected biomass declines in ocean regions by 2100, while regional models projected biomass declines in 67% of the ocean region simulations. Our analysis suggests that improved understanding of the causes of differences between global and regional marine ecosystem model climate change projections is needed, alongside observational evaluation of modelled responses.

There is an urgent need for models that can robustly detect past and project future ecosystem changes and risks to the services that they provide to people. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) was established to develop model ensembles for projecting long-term impacts of climate change on fisheries and marine ecosystems while informing policy at spatio-temporal scales relevant to the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. While contributing FishMIP models have improved over time, large uncertainties in projections remain, particularly in coastal and shelf seas where most of the world’s fisheries occur. Furthermore, previous FishMIP climate impact projections have mostly ignored fishing activity due to a lack of standardized historical and scenario-based human activity forcing and uneven capabilities to dynamically model fisheries across the FishMIP community. This, in addition to underrepresentation of coastal processes, has limited the ability to evaluate the FishMIP ensemble’s ability to adequately capture past states - a crucial step for building confidence in future projections. To address these issues, we have developed two parallel simulation experiments (FishMIP 2.0) on: 1) model evaluation and detection of past changes and 2) future scenarios and projections. Key advances include historical climate forcing, that captures oceanographic features not previously resolved, and standardized fishing forcing to systematically test fishing effects across models. FishMIP 2.0 is a key step towards a detection and attribution framework for marine ecosystem change at regional and global scales, and towards enhanced policy relevance through increased confidence in future ensemble projections.

Although zooplankton play a substantial role in the biological carbon pump and serve as a crucial link between primary producers and higher trophic level consumers, the skillful representation of zooplankton is not often a focus of ocean biogeochemical models. Systematic evaluations of zooplankton in models could improve their representation, but so far, ocean biogeochemical skill assessment of Earth system model (ESM) ensembles have not included zooplankton. Here we use a recently developed global, observationally-based map of mesozooplankton biomass to assess the skill of mesozooplankton in six CMIP6 ESMs. We also employ a biome-based assessment of the ability of these models to reproduce the observed relationship between mesozooplankton biomass and surface chlorophyll. The combined analysis found that most models were able to reasonably simulate the large regional variations in mesozooplankton biomass at the global scale. Additionally, three of the ESMs simulated a mesozooplankton-chlorophyll relationship within the observational bounds, which we used as an emergent constraint on future mesozooplankton projections. We highlight where differences in model structure and parameters may give rise to varied mesozooplankton distributions under historic and future conditions, and the resultant wide ensemble spread in projected changes in mesozooplankton biomass. Despite differences, the strength of the mesozooplankton-chlorophyll relationships across all models was related to the projected changes in mesozooplankton biomass globally and in regional biomes. These results suggest that improved observations of mesozooplankton and their relationship to chlorophyll will better constrain projections of climate change impacts on these important animals.