A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project
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 en...
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| Format: | Article |
| Language: | English |
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Wiley
2025-04-01
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| Series: | Earth's Future |
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| Online Access: | https://doi.org/10.1029/2024EF004868 |
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| author | Nina Rynne Camilla Novaglio Julia Blanchard Daniele Bianchi Villy Christensen Marta Coll Jerome Guiet Jeroen Steenbeek Andrea Bryndum‐Buchholz Tyler D. Eddy Cheryl Harrison Olivier Maury Kelly Ortega‐Cisneros Colleen M. Petrik Derek P. Tittensor Ryan F. Heneghan |
| author_facet | Nina Rynne Camilla Novaglio Julia Blanchard Daniele Bianchi Villy Christensen Marta Coll Jerome Guiet Jeroen Steenbeek Andrea Bryndum‐Buchholz Tyler D. Eddy Cheryl Harrison Olivier Maury Kelly Ortega‐Cisneros Colleen M. Petrik Derek P. Tittensor Ryan F. Heneghan |
| author_sort | Nina Rynne |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e07c4b9193de486cbc545d716b9bea88 |
| institution | DOAJ |
| issn | 2328-4277 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Earth's Future |
| spelling | doaj-art-e07c4b9193de486cbc545d716b9bea882025-08-20T03:07:58ZengWileyEarth's Future2328-42772025-04-01134n/an/a10.1029/2024EF004868A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison ProjectNina Rynne0Camilla Novaglio1Julia Blanchard2Daniele Bianchi3Villy Christensen4Marta Coll5Jerome Guiet6Jeroen Steenbeek7Andrea Bryndum‐Buchholz8Tyler D. Eddy9Cheryl Harrison10Olivier Maury11Kelly Ortega‐Cisneros12Colleen M. Petrik13Derek P. Tittensor14Ryan F. Heneghan15School of Mathematical Sciences Queensland University of Technology Brisbane QLD AustraliaInstitute for Marine and Antarctic Studies University of Tasmania Hobart TAS AustraliaInstitute for Marine and Antarctic Studies University of Tasmania Hobart TAS AustraliaDepartment of Atmospheric and Oceanic Sciences University of California Los Angeles Los Angeles CA USAInstitute for the Oceans and Fisheries University of British Columbia Vancouver BC CanadaEcopath International Initiative Barcelona SpainDepartment of Atmospheric and Oceanic Sciences University of California Los Angeles Los Angeles CA USAEcopath International Initiative Barcelona SpainCentre for Fisheries Ecosystem Research Fisheries & Marine Institute Memorial University St John's NL CanadaCentre for Fisheries Ecosystem Research Fisheries & Marine Institute Memorial University St John's NL CanadaDepartment of Ocean and Coastal Science and Center for Computation and Technology Louisiana State University Baton Rouge LA USAIRD University Montpellier Ifremer CNRS INRAE MARBEC Sète FranceDepartment of Biological Sciences University of Cape Town Cape Town South AfricaScripps Institution of Oceanography University of California San Diego La Jolla CA USADepartment of Biology Dalhousie University Halifax NS CanadaSchool of Mathematical Sciences Queensland University of Technology Brisbane QLD AustraliaAbstract 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.https://doi.org/10.1029/2024EF004868model skill assessmentFishMIPCSPSecosystem modelingglobal fisheries impactclimactic change |
| spellingShingle | Nina Rynne Camilla Novaglio Julia Blanchard Daniele Bianchi Villy Christensen Marta Coll Jerome Guiet Jeroen Steenbeek Andrea Bryndum‐Buchholz Tyler D. Eddy Cheryl Harrison Olivier Maury Kelly Ortega‐Cisneros Colleen M. Petrik Derek P. Tittensor Ryan F. Heneghan A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project Earth's Future model skill assessment FishMIP CSPS ecosystem modeling global fisheries impact climactic change |
| title | A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project |
| title_full | A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project |
| title_fullStr | A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project |
| title_full_unstemmed | A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project |
| title_short | A Skill Assessment Framework for the Fisheries and Marine Ecosystem Model Intercomparison Project |
| title_sort | skill assessment framework for the fisheries and marine ecosystem model intercomparison project |
| topic | model skill assessment FishMIP CSPS ecosystem modeling global fisheries impact climactic change |
| url | https://doi.org/10.1029/2024EF004868 |
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