Files and links (1)
Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project
Earth's Future, Vol.13(4), pp.1-18
2025
Abstract
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 modeling 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 characterize 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.
Details
- Title
- A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project
- Authors
- Nina Rynne (Corresponding Author) - Queensland University of TechnologyCamilla Novaglio (Author) - University of TasmaniaJulia Blanchard (Author) - University of TasmaniaDaniele Bianchi (Author) - University of California, Los AngelesVilly Christensen (Author) - University of British ColumbiaMarta Coll (Author) - Ecopath International InitiativeJerome Guiet (Author) - University of California, Los AngelesJeroen Steenbeek (Author) - Ecopath International InitiativeAndrea Bryndum-Buchholz (Author) - Memorial University of NewfoundlandTyler D. Eddy (Author) - Memorial University of NewfoundlandCheryl S. Harrison (Author) - Louisiana State UniversityOlivier Maury (Author) - Université de MontpellierKelly Ortega-Cisneros (Author) - University of Cape TownColleen M. Petrik (Author) - Scripps Institution of OceanographyDerek P Tittensor (Author) - Dalhousie UniversityRyan Heneghan - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Earth's Future, Vol.13(4), pp.1-18
- Publisher
- John Wiley & Sons Ltd.
- Date published
- 2025
- DOI
- 10.1029/2024EF004868
- ISSN
- 2328-4277
- Copyright note
- © 2025. The Author(s). This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
- Data Availability
- No new data was produced as part of this manuscript.
- Grant note
- MC acknowledges support from the Spanish project ProOceans (Plan Estatal de Investigación Científica, Técnica y de Innovación, 2020, PID2020‐118097RBI00) and the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019‐000928‐S) to the Institute of Marine Science (ICM‐CSIC). CMP acknowledges support from NOAA grants NA20OAR4310438, NA20OAR4310441,and NA20OAR4310442. KOC acknowledges support from the National Research Foundation of South Africa (Grant 136481). OM acknowledges support from the European Union's Horizon 2020 research and innovation program under grant agreement No. 817806.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991121752302621
- Output Type
- Journal article
Metrics
17 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Environmental Sciences
- Geosciences, Multidisciplinary
- Meteorology & Atmospheric Sciences
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites