Detecting, Attributing, and Projecting Global Marine Ecosystem and Fisheries Change: FishMIP 2.0 - Julia L. Blanchard; Camilla Novaglio; Olivier Maury; Cheryl S. Harrison; Colleen M. Petrik; Denisse Fierro‐Arcos; Kelly Ortega‐Cisneros; Andrea Bryndum‐Buchholz; Tyler D. Eddy; Ryan Heneghan; Kelsey Roberts; Jacob Schewe; et al. (Earth's Future)
Abstract 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 been limited by a lack of global standardized historical fishing data, low resolution of coastal processes, and uneven capabilities across the FishMIP community to dynamically model fisheries. These features are needed to evaluate how reliably the FishMIP ensemble captures past ecosystem states ‐ a crucial step for building confidence in future projections. To address these issues, we have developed FishMIP 2.0 comprising a two‐track framework for: (a) Model evaluation and attribution of past changes and (b) future climate and socioeconomic scenario projections. Key advances include improved historical climate forcing, which captures oceanographic features not previously resolved, and standardized global fishing forcing to test fishing effects systematically across models. FishMIP 2.0 is a crucial step toward a detection and attribution framework for changing marine ecosystems and toward enhanced policy relevance through increased confidence in future ensemble projections. Our results will help elucidate pathways toward achieving sustainable development goals.