A comparative framework to support an ecosystem approach to fisheries in a global context

Although an ecosystem approach to fisheries has been recognized as a means of progressing toward sustainable fishing, successful implementation of this approach has been limited. However, one way in which progress has been made is through the use of suites of indicators. Decision tree frameworks can...

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Autores principales:	Emma M. Lockerbie, Lynne Shannon, Christopher P. Lynam, Marta Coll, Astrid Jarre
Formato:	article
Lenguaje:	EN
Publicado:	Resilience Alliance 2020
Materias:	comparative assessment decision support decision trees ecosystem approach to fisheries indicators Biology (General) QH301-705.5 Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/88914c44f03f49ee9b22066befaa462e
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spelling	oai:doaj.org-article:88914c44f03f49ee9b22066befaa462e2021-12-02T11:55:12ZA comparative framework to support an ecosystem approach to fisheries in a global context1708-308710.5751/ES-11508-250216https://doaj.org/article/88914c44f03f49ee9b22066befaa462e2020-06-01T00:00:00Zhttp://www.ecologyandsociety.org/vol25/iss2/art16/https://doaj.org/toc/1708-3087Although an ecosystem approach to fisheries has been recognized as a means of progressing toward sustainable fishing, successful implementation of this approach has been limited. However, one way in which progress has been made is through the use of suites of indicators. Decision tree frameworks can be used to incorporate trends in ecological, fishing, and environmental indicators into ecosystem assessments. A relatively generic decision tree framework has been developed and successfully applied to multiple ecosystems. This framework incorporates trends in indicators, as well as the impacts of fishing pressure and environmental variability on ecological indicators in order to assess the state of each ecosystem. The inclusion of ecosystem expert knowledge from the outset ensures trends are correctly interpreted and allows analyses to contribute to global comparisons in a robust and meaningful manner. Although ecological and environmental indicators are well developed, those addressing the human dimensions of marine ecosystems are less so. This framework holds the potential to incorporate such indicators in order to fully assess marine ecosystems in a comparative context. Such assessments could help ensure food security from marine resources into the future as well as ensuring the well-being of coastal communities. Here critical review of the potential value of this framework has been conducted, with its usefulness emphasized in the similarities it holds, and in the contribution it could make, to current global methods of ecosystem assessments.Emma M. LockerbieLynne ShannonChristopher P. LynamMarta CollAstrid JarreResilience Alliancearticlecomparative assessmentdecision supportdecision treesecosystem approach to fisheriesindicatorsBiology (General)QH301-705.5EcologyQH540-549.5ENEcology and Society, Vol 25, Iss 2, p 16 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	comparative assessment decision support decision trees ecosystem approach to fisheries indicators Biology (General) QH301-705.5 Ecology QH540-549.5
spellingShingle	comparative assessment decision support decision trees ecosystem approach to fisheries indicators Biology (General) QH301-705.5 Ecology QH540-549.5 Emma M. Lockerbie Lynne Shannon Christopher P. Lynam Marta Coll Astrid Jarre A comparative framework to support an ecosystem approach to fisheries in a global context
description	Although an ecosystem approach to fisheries has been recognized as a means of progressing toward sustainable fishing, successful implementation of this approach has been limited. However, one way in which progress has been made is through the use of suites of indicators. Decision tree frameworks can be used to incorporate trends in ecological, fishing, and environmental indicators into ecosystem assessments. A relatively generic decision tree framework has been developed and successfully applied to multiple ecosystems. This framework incorporates trends in indicators, as well as the impacts of fishing pressure and environmental variability on ecological indicators in order to assess the state of each ecosystem. The inclusion of ecosystem expert knowledge from the outset ensures trends are correctly interpreted and allows analyses to contribute to global comparisons in a robust and meaningful manner. Although ecological and environmental indicators are well developed, those addressing the human dimensions of marine ecosystems are less so. This framework holds the potential to incorporate such indicators in order to fully assess marine ecosystems in a comparative context. Such assessments could help ensure food security from marine resources into the future as well as ensuring the well-being of coastal communities. Here critical review of the potential value of this framework has been conducted, with its usefulness emphasized in the similarities it holds, and in the contribution it could make, to current global methods of ecosystem assessments.
format	article
author	Emma M. Lockerbie Lynne Shannon Christopher P. Lynam Marta Coll Astrid Jarre
author_facet	Emma M. Lockerbie Lynne Shannon Christopher P. Lynam Marta Coll Astrid Jarre
author_sort	Emma M. Lockerbie
title	A comparative framework to support an ecosystem approach to fisheries in a global context
title_short	A comparative framework to support an ecosystem approach to fisheries in a global context
title_full	A comparative framework to support an ecosystem approach to fisheries in a global context
title_fullStr	A comparative framework to support an ecosystem approach to fisheries in a global context
title_full_unstemmed	A comparative framework to support an ecosystem approach to fisheries in a global context
title_sort	comparative framework to support an ecosystem approach to fisheries in a global context
publisher	Resilience Alliance
publishDate	2020
url	https://doaj.org/article/88914c44f03f49ee9b22066befaa462e
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A comparative framework to support an ecosystem approach to fisheries in a global context

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