Climate-driven ecosystem changes are increasingly affecting the world’s ocean ecosystems, necessitating urgent guidance on adaptation strategies to limit or prevent catastrophic impacts. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) is a network and framework that provides standardised ensemble projections of the impacts of climate change and fisheries on ocean life and the benefits that it provides to people through fisheries. Since its official launch in 2013 as a small, self-organised project within the larger Inter-Sectoral Impact Model Intercomparison Project, the FishMIP community has grown substantially and contributed to key international policy processes, such as the IPCC AR5 and AR6, and the IPBES Global Biodiversity Assessment. While not without challenges, particularly around comparing heterogeneous ecosystem models, integrating fisheries scenarios, and standardising regional-scale ecosystem models, FishMIP outputs are now being used across a variety of applications (e.g., climate change targets, fisheries management, marine conservation, Sustainable Development Goals). Over the next decade, FishMIP will focus on improving ecosystem model ensembles to provide more robust and policy-relevant projections for different regions of the world under multiple climate and societal change scenarios, and continue to be open to a broad spectrum of marine ecosystem models and modellers. FishMIP also intends to enhance leadership diversity and capacity-building to improve representation of early- and mid-career researchers from under-represented countries and ocean regions. As we look ahead, FishMIP aims to continue enhancing our understanding of how marine life and its contributions to people may change over the coming century at both global and regional scales.

A document by Tyler Eddy. Click on the document to view its contents.

The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) has dedicated a decade to unravelling the future impacts of climate change on marine animal biomass. FishMIP is now preparing a new simulation protocol to assess the combined effects of both climate and socio-economic changes on marine fisheries and ecosystems. This protocol will be based on the Ocean System Pathways (OSPs), a new set of socio-economic scenarios derived from the Shared Socioeconomic Pathways (SSPs) widely used by the Intergovernmental Panel on Climate Change (IPCC). The OSPs extend the SSPs to the economic, governance, management and socio-cultural contexts of large pelagic, small pelagic, benthic-demersal and emerging fisheries, as well as mariculture. Comprising qualitative storylines, quantitative model driver pathways and a “plug-in-model” framework, the OSPs will enable a heterogeneous suite of ecosystem models to simulate fisheries dynamics in a standardised way. This paper introduces this OSP framework and the simulation protocol that FishMIP will implement to explore future ocean social-ecological systems holistically, with a focus on critical issues such as climate justice, global food security, equitable fisheries, aquaculture development, fisheries management, and biodiversity conservation. Ultimately, the OSP framework is tailored to contribute to the synthesis work of the IPCC. It also aims to inform ongoing policy processes within the United Nations Food and Agriculture Organisation (FAO). Finally, it seeks to support the synthesis work of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), with a particular focus on studying pathways relevant for the United Nations Convention on Biological Diversity (CBD).

Understanding climate change impacts on global marine ecosystems and fisheries requires complex marine ecosystem models, forced by global climate projections, that can robustly detect and project changes. The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) uses an ensemble modelling approach to fill this crucial gap. Yet FishMIP does not have a standardised skill assessment framework to quantify the ability of member models to reproduce past observations and to guide model improvement. In this study, we apply a comprehensive model skill assessment framework to a subset of global FishMIP models that produce historical fisheries catches. We consider a suite of metrics and assess their utility in illustrating the models’ ability to reproduce observed fisheries catches. Our findings reveal improvement in model performance at both global and regional (Large Marine Ecosystem) scales from the Coupled Model Intercomparison Project Phase 5 and 6 simulation rounds. Our analysis underscores the importance of employing easily interpretable, relative skill metrics to estimate the capability of models to capture temporal variations, alongside absolute error measures to characterise shifts in the magnitude of these variations between models and across simulation rounds. The skill assessment framework developed and tested here provides a first objective assessment and a baseline of the FishMIP ensemble’s skill in reproducing historical catch at the global and regional scale. This assessment can be further improved and systematically applied to test the reliability of FishMIP models across the whole model ensemble from future simulation rounds and include more variables like fish biomass or production.

Climate change could irreversibly modify Southern Ocean ecosystems. Marine ecosystem model (MEM) ensembles can assist policy making by projecting future changes and allowing the evaluation and assessment of alternative management approaches. However, projected future changes in total consumer biomass from the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) global MEM ensemble highlight an uncertain future for the Southern Ocean, indicating the need for a region-specific ensemble. A large source of model uncertainty originates from the Earth system models (ESMs) used to force FishMIP models, particularly future changes to lower trophic level biomass and sea ice coverage. To build confidence in regional MEMs as ecosystem-based management tools in a changing climate that can better account for uncertainty, we propose the development of a Southern Ocean Marine Ecosystem Model Ensemble (SOMEME) contributing to the FishMIP 2.0 regional model intercomparison initiative. One of the challenges hampering progress of regional MEM ensembles is achieving the balance of global standardised inputs with regional relevance. As a first step, we design a SOMEME simulation protocol, that builds on and extends the existing FishMIP framework, in stages that include: detailed skill assessment of climate forcing variables for Southern Ocean regions, extension of fishing forcing data to include whaling, and new simulations that assess ecological links to sea-ice processes in an ensemble of candidate regional MEMs. These extensions will help advance assessments of urgently needed climate change impacts on Southern Ocean ecosystems.

As the urgency to evaluate the impacts of climate change on marine ecosystems increases, there is a need to develop robust projections and improve the uptake of ecosystem model outputs in policy and planning. Standardising input and output data is a crucial step in evaluating and communicating results, but can be challenging when using models with diverse structures, assumptions, and outputs that address region-specific issues. We developed an implementation framework and workflow to standardise the climate and fishing forcings used by regional models contributing to the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) and to facilitate comparative analyses across models and a wide range of regions, in line with the FishMIP 3a protocol. We applied our workflow to three case study areas-models: the Baltic Sea Mizer, Hawai’i-based Longline fisheries therMizer, and the southern Benguela ecosystem Atlantis marine ecosystem models. We then selected the most challenging steps of the workflow and illustrated their implementation in different model types and regions. Our workflow is adaptable across a wide range of regional models, from non-spatially explicit to spatially explicit and fully-depth resolved models and models that include one or several fishing fleets. This workflow will facilitate the development of regional marine ecosystem model ensembles and enhance future research on marine ecosystem model development and applications, model evaluation and benchmarking, and global-to-regional model comparisons.

Laura Kaikkonen1,2, Rebecca J Shellock3,4, Samiya Ahmed Selim5, Renis Auma Ojwala6, Beatriz S. Dias7, Shenghui Li8, Charles I. Addey9, Ignacio Gianelli10,11, Katherine M Maltby12, Sara Garcia-Morales13,14, Juliano Palacios-Abrantes15, Shan Jiang16, Marta Albo-Puigserver17, Virginia A. García Alonso18, Chelsey A. Baker19, Colleen B. Bove20, Stephanie Brodie21, Lol Iana Dahlet22,23, Jewel Das22,24, Aislinn Dunne25, Sebastian C.A. Ferse22,26, Ellen Johannesen6, Julia Jung27, Eugenia Merayo Garcia28, Denis B. Karcher29,   Sarah Mahadeo6, Lucia Millan30, Kasali Oladepo Lawal31, Ayodele Oloko32, Kelly Ortega-Cisneros33, Stephanie Otoabasi-Akpan34, Durlave Roy35, Samina Sharmin Rouf36, Szymon Smoliński37, Natasa Vaidianu38,39, Chris Whidden40, Mia Strand41National Institute of Water and Atmospheric Research, New ZealandUniversity of Helsinki, FinlandInstitute for Marine and Antarctic Studies, Hobart, Tasmania, AustraliaCentre for Marine Socioecology, University of Tasmania, AustraliaCenter for Sustainable Development, University of Liberal Arts BangladeshWorld Maritime University-Sasakawa Global Ocean Institute, Malmö, SwedenCollege of Fisheries and Ocean Sciences, University of Alaska Fairbanks, USGuangdong Ocean University, ChinaDepartment of Oceanography, University of Hawaii at Manoa, USEqualSea Lab-CRETUS. Department of Applied Economics, Universidade de Santiago de Compostela, SpainSouth American Institute for Resilience and Sustainability Studies (SARAS), UruguayGulf of Maine Research Institute, Maine, USMarine Environmental and Sciences Centre (MARE-ARNET), University of Lisbon, PortugalEcology and Biodiversity Institute (IEB), ChileInstitute for the Oceans and Fisheries, The University of British Columbia, Vancouver CanadaState Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, ChinaCentro Oceanográfico de Baleares, Instituto Español de Oceanografía (IEO‑CSIC), Ecosystem Oceanography Group, Palma, SpainInstituto de Biodiversidad y Biología Experimental y Aplicada (IBBEA, CONICET-UBA)National Oceanography Centre, Marine Systems Modelling, Southampton, UKUrsinus College; Biology Department; Collegeville, United StatesEnvironment, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, AustraliaLeibniz Centre for Tropical Marine Research (ZMT), GermanyInstituto de Estudos Costeiros, Universidade Federal do Pará (UFPA), Bragança, BrazilInstitute of Marine Sciences, University of Chittagong, Chattogram, BangladeshRed Sea Research Center, King Abdullah University of Science and Technology, Saudi ArabiaDepartment of Marine Ecology, Faculty of Biology and Chemistry, University of Bremen, Bremen, GermanyCobra Collective, Egham, United KingdomJoint Nature Conservation Committee, UKAustralian National Centre for the Public Awareness of Science, Australian National University, Canberra, AustraliaInstitut de Ciències del Mar - CSIC, Barcelona, SpainDepartment of Marine Science and Technology, Federal University of Technology Akure, NigeriaInstitute for the Oceans and Fisheries, The University of British Columbia,CanadaDepartment of Biological Sciences, University of Cape Town, Cape Town, South AfricaFederal University of Technology, AkureBangladesh Open UniversityBertarelli Foundation’s Marine Science Programme, Zoological Society of London, UKNational Marine Fisheries Research Institute, Gdynia, PolandFaculty of Natural and Agricultural Sciences, Ovidius University of ConstantaInterdisciplinary Center of Advanced Research on Territorial Dynamics, University of Bucharest, RomaniaFaculty of Computer Science, Dalhousie UniversityDepartment of Development Studies, Nelson Mandela University, Gqeberha, South Africa

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.