Climate based multi-year predictions of the Barents Sea cod stock.
Predicting fish stock variations on interannual to decadal time scales is one of the major issues in fisheries science and management. Although the field of marine ecological predictions is still in its infancy, it is understood that a major source of multi-year predictability resides in the ocean....
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ftdoajarticles:oai:doaj.org/article:d888960fdf1e46b1b55d2aec38a99d68 2023-05-15T15:38:30+02:00 Climate based multi-year predictions of the Barents Sea cod stock. Marius Årthun Bjarte Bogstad Ute Daewel Noel S Keenlyside Anne Britt Sandø Corinna Schrum Geir Ottersen 2018-01-01T00:00:00Z https://doi.org/10.1371/journal.pone.0206319 https://doaj.org/article/d888960fdf1e46b1b55d2aec38a99d68 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC6200261?pdf=render https://doaj.org/toc/1932-6203 1932-6203 doi:10.1371/journal.pone.0206319 https://doaj.org/article/d888960fdf1e46b1b55d2aec38a99d68 PLoS ONE, Vol 13, Iss 10, p e0206319 (2018) Medicine R Science Q article 2018 ftdoajarticles https://doi.org/10.1371/journal.pone.0206319 2022-12-31T07:11:22Z Predicting fish stock variations on interannual to decadal time scales is one of the major issues in fisheries science and management. Although the field of marine ecological predictions is still in its infancy, it is understood that a major source of multi-year predictability resides in the ocean. Here we show the first highly skilful long-term predictions of the commercially valuable Barents Sea cod stock. The 7-year predictions are based on the propagation of ocean temperature anomalies from the subpolar North Atlantic toward the Barents Sea, and the strong co-variability between these temperature anomalies and the cod stock. Retrospective predictions for the period 1957-2017 capture well multi-year to decadal variations in cod stock biomass, with cross-validated explained variance of over 60%. For lead times longer than one year the statistical long-term predictions show more skill than operational short-term predictions used in fisheries management and lagged persistence forecasts. Our results thus demonstrate the potential for ecosystem-based fisheries management, which could enable strategic planning on longer time scales. Future predictions show a gradual decline in the cod stock towards 2024. Article in Journal/Newspaper Barents Sea North Atlantic Directory of Open Access Journals: DOAJ Articles Barents Sea PLOS ONE 13 10 e0206319 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Medicine R Science Q |
spellingShingle |
Medicine R Science Q Marius Årthun Bjarte Bogstad Ute Daewel Noel S Keenlyside Anne Britt Sandø Corinna Schrum Geir Ottersen Climate based multi-year predictions of the Barents Sea cod stock. |
topic_facet |
Medicine R Science Q |
description |
Predicting fish stock variations on interannual to decadal time scales is one of the major issues in fisheries science and management. Although the field of marine ecological predictions is still in its infancy, it is understood that a major source of multi-year predictability resides in the ocean. Here we show the first highly skilful long-term predictions of the commercially valuable Barents Sea cod stock. The 7-year predictions are based on the propagation of ocean temperature anomalies from the subpolar North Atlantic toward the Barents Sea, and the strong co-variability between these temperature anomalies and the cod stock. Retrospective predictions for the period 1957-2017 capture well multi-year to decadal variations in cod stock biomass, with cross-validated explained variance of over 60%. For lead times longer than one year the statistical long-term predictions show more skill than operational short-term predictions used in fisheries management and lagged persistence forecasts. Our results thus demonstrate the potential for ecosystem-based fisheries management, which could enable strategic planning on longer time scales. Future predictions show a gradual decline in the cod stock towards 2024. |
format |
Article in Journal/Newspaper |
author |
Marius Årthun Bjarte Bogstad Ute Daewel Noel S Keenlyside Anne Britt Sandø Corinna Schrum Geir Ottersen |
author_facet |
Marius Årthun Bjarte Bogstad Ute Daewel Noel S Keenlyside Anne Britt Sandø Corinna Schrum Geir Ottersen |
author_sort |
Marius Årthun |
title |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_short |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_full |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_fullStr |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_full_unstemmed |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_sort |
climate based multi-year predictions of the barents sea cod stock. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2018 |
url |
https://doi.org/10.1371/journal.pone.0206319 https://doaj.org/article/d888960fdf1e46b1b55d2aec38a99d68 |
geographic |
Barents Sea |
geographic_facet |
Barents Sea |
genre |
Barents Sea North Atlantic |
genre_facet |
Barents Sea North Atlantic |
op_source |
PLoS ONE, Vol 13, Iss 10, p e0206319 (2018) |
op_relation |
http://europepmc.org/articles/PMC6200261?pdf=render https://doaj.org/toc/1932-6203 1932-6203 doi:10.1371/journal.pone.0206319 https://doaj.org/article/d888960fdf1e46b1b55d2aec38a99d68 |
op_doi |
https://doi.org/10.1371/journal.pone.0206319 |
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PLOS ONE |
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13 |
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10 |
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e0206319 |
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