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dc.contributor.authorFernandes, Jose A.
dc.contributor.authorRutterford, Louise
dc.contributor.authorSimpson, Stephen D. and Butenschon, Momme
dc.contributor.authorFrolicher, Thomas L.
dc.contributor.authorYool, Andrew
dc.contributor.authorCheung, William W. L.
dc.contributor.authorGrant, Alastair
dc.date.accessioned2021-07-02T08:12:52Z-
dc.date.available2021-07-02T08:12:52Z-
dc.date.issued2020
dc.identifierISI:000530660300001
dc.identifier.citationGLOBAL CHANGE BIOLOGY, 2020, 26, 3891-3905
dc.identifier.issn1354-1013
dc.identifier.urihttp://dspace.azti.es/handle/24689/1125-
dc.description.abstractLarge-scale and long-term changes in fish abundance and distribution in response to climate change have been simulated using both statistical and process-based models. However, national and regional fisheries management requires also shorter term projections on smaller spatial scales, and these need to be validated against fisheries data. A 26-year time series of fish surveys with high spatial resolution in the North-East Atlantic provides a unique opportunity to assess the ability of models to correctly simulate the changes in fish distribution and abundance that occurred in response to climate variability and change. We use a dynamic bioclimate envelope model forced by physical-biogeochemical output from eight ocean models to simulate changes in fish abundance and distribution at scales down to a spatial resolution of 0.5 degrees. When comparing with these simulations with annual fish survey data, we found the largest differences at the 0.5 degrees scale. Differences between fishery model runs driven by different biogeochemical models decrease dramatically when results are aggregated to larger scales (e.g. the whole North Sea), to total catches rather than individual species or when the ensemble mean instead of individual simulations are used. Recent improvements in the fidelity of biogeochemical models translate into lower error rates in the fisheries simulations. However, predictions based on different biogeochemical models are often more similar to each other than they are to the survey data, except for some pelagic species. We conclude that model results can be used to guide fisheries management at larger spatial scales, but more caution is needed at smaller scales.
dc.language.isoEnglish
dc.publisherWILEY
dc.subjectbiological feedback
dc.subjectclimate change
dc.subjecterror estimation
dc.subjectmarine fisheries
dc.subjectmodel validation
dc.subjectmodelling
dc.subjectsize spectrum
dc.subjectspecies interactions
dc.subjectEUROPEAN CONTINENTAL-SHELF
dc.subjectNORTH-SEA
dc.subjectNATURAL MORTALITY
dc.subjectMARINE ECOSYSTEMS
dc.subjectCHANGE IMPACTS
dc.subjectREGIME SHIFTS
dc.subjectPART I
dc.subjectOCEAN
dc.subjectMODEL
dc.subjectFISHERIES
dc.titleCan we project changes in fish abundance and distribution in response to climate?
dc.typeArticle
dc.identifier.journalGLOBAL CHANGE BIOLOGY
dc.format.page3891-3905
dc.format.volume26
dc.contributor.funderHorizon 2020 program [678193, 820989, 641816]
dc.contributor.funderEuropean UnionEuropean Commission
dc.contributor.funderSwiss National Science FoundationSwiss National Science Foundation (SNSF)European Commission [PP00P2\_170687]
dc.contributor.funderNatural Environment Research CouncilUK Research \& Innovation (UKRI)Natural Environment Research Council (NERC) [NE/H017372/1]
dc.contributor.funderNational Capability in Ocean Modelling
dc.identifier.e-issn1365-2486
dc.identifier.doi10.1111/gcb.15081
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