Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design

Autores
Harford, William J.; Amoroso, Ricardo; Bell, Richard J.; Caillaux, Matias; Cope, Jason Marc; Dougherty, Dawn; Dowling, Natalie Anne; Hurd, Frank; Lomonico, Serena; Nowlis, Josh; Ovando, Dan; Parma, Ana María; Prince, Jeremy D.; Wilson, Jono R.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
As the world population grows, fisheries practitioners will be under increased pressure to address global challenges in data-limited fisheries management. With a focus on addressing localized and case-specific management needs, we provide a practical guide to the design and development of multi-indicator frameworks for fishery management. In a data-limited context, indicators are observations or estimates of the state of the fishery resource that are typically proxies for variables of interest, rather than quantities such as stock biomass estimated from data-rich stock assessments. Indicator frameworks structure the integration and interpretation of indicators to guide tactical fishery decision-making, often when the application of more formal analytical assessments is not feasible, yet where indicators in combination provide insight into stock status. With a focus on multi-indicator frameworks, we describe a pragmatic approach for their development via a set of organizational steps, considering a wide spectrum of types and severity of information limitations. We highlight where multi-indicator frameworks can be insightful and informative in relation to single indicator approaches but also point to potential pitfalls, with emphasis on critical evaluation and detection of performance flaws during the design phase using methods such as management strategy evaluation.
Fil: Harford, William J.. Nature Analytics; Canadá
Fil: Amoroso, Ricardo. University of Washington; Estados Unidos
Fil: Bell, Richard J.. The Nature Conservancy; Estados Unidos
Fil: Caillaux, Matias. The Nature Conservancy; Estados Unidos
Fil: Cope, Jason Marc. National Marine Fisheries Service; Estados Unidos
Fil: Dougherty, Dawn. The Nature Conservancy; Estados Unidos
Fil: Dowling, Natalie Anne. Commonwealth Scientific And Industrial Research Organization (CSIRO); Australia
Fil: Hurd, Frank. The Nature Conservancy; Estados Unidos
Fil: Lomonico, Serena. The Nature Conservancy; Estados Unidos
Fil: Nowlis, Josh. National Marine Fisheries Service; Estados Unidos
Fil: Ovando, Dan. University of Washington; Estados Unidos
Fil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina
Fil: Prince, Jeremy D.. Murdoch Univeristy; Australia
Fil: Wilson, Jono R.. The Nature Conservancy; Estados Unidos. University of California; Estados Unidos
Materia
FISHERY MANAGEMENT
INDICATOR
MANAGEMENT STRATEGY
FRAMEWORK
STOCK ASSESSMENT
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/166672
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and DesignHarford, William J.Amoroso, RicardoBell, Richard J.Caillaux, MatiasCope, Jason MarcDougherty, DawnDowling, Natalie AnneHurd, FrankLomonico, SerenaNowlis, JoshOvando, DanParma, Ana MaríaPrince, Jeremy D.Wilson, Jono R.FISHERY MANAGEMENTINDICATORMANAGEMENT STRATEGYFRAMEWORKSTOCK ASSESSMENThttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4As the world population grows, fisheries practitioners will be under increased pressure to address global challenges in data-limited fisheries management. With a focus on addressing localized and case-specific management needs, we provide a practical guide to the design and development of multi-indicator frameworks for fishery management. In a data-limited context, indicators are observations or estimates of the state of the fishery resource that are typically proxies for variables of interest, rather than quantities such as stock biomass estimated from data-rich stock assessments. Indicator frameworks structure the integration and interpretation of indicators to guide tactical fishery decision-making, often when the application of more formal analytical assessments is not feasible, yet where indicators in combination provide insight into stock status. With a focus on multi-indicator frameworks, we describe a pragmatic approach for their development via a set of organizational steps, considering a wide spectrum of types and severity of information limitations. We highlight where multi-indicator frameworks can be insightful and informative in relation to single indicator approaches but also point to potential pitfalls, with emphasis on critical evaluation and detection of performance flaws during the design phase using methods such as management strategy evaluation.Fil: Harford, William J.. Nature Analytics; CanadáFil: Amoroso, Ricardo. University of Washington; Estados UnidosFil: Bell, Richard J.. The Nature Conservancy; Estados UnidosFil: Caillaux, Matias. The Nature Conservancy; Estados UnidosFil: Cope, Jason Marc. National Marine Fisheries Service; Estados UnidosFil: Dougherty, Dawn. The Nature Conservancy; Estados UnidosFil: Dowling, Natalie Anne. Commonwealth Scientific And Industrial Research Organization (CSIRO); AustraliaFil: Hurd, Frank. The Nature Conservancy; Estados UnidosFil: Lomonico, Serena. The Nature Conservancy; Estados UnidosFil: Nowlis, Josh. National Marine Fisheries Service; Estados UnidosFil: Ovando, Dan. University of Washington; Estados UnidosFil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Prince, Jeremy D.. Murdoch Univeristy; AustraliaFil: Wilson, Jono R.. The Nature Conservancy; Estados Unidos. University of California; Estados UnidosFrontiers Media2021-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/166672Harford, William J.; Amoroso, Ricardo; Bell, Richard J.; Caillaux, Matias; Cope, Jason Marc; et al.; Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design; Frontiers Media; Frontiers In Marine Science; 8; 12-2021; 1-132296-7745CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fmars.2021.757877info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fmars.2021.757877/fullinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:57:25Zoai:ri.conicet.gov.ar:11336/166672instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:57:25.975CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
title Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
spellingShingle Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
Harford, William J.
FISHERY MANAGEMENT
INDICATOR
MANAGEMENT STRATEGY
FRAMEWORK
STOCK ASSESSMENT
title_short Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
title_full Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
title_fullStr Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
title_full_unstemmed Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
title_sort Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design
dc.creator.none.fl_str_mv Harford, William J.
Amoroso, Ricardo
Bell, Richard J.
Caillaux, Matias
Cope, Jason Marc
Dougherty, Dawn
Dowling, Natalie Anne
Hurd, Frank
Lomonico, Serena
Nowlis, Josh
Ovando, Dan
Parma, Ana María
Prince, Jeremy D.
Wilson, Jono R.
author Harford, William J.
author_facet Harford, William J.
Amoroso, Ricardo
Bell, Richard J.
Caillaux, Matias
Cope, Jason Marc
Dougherty, Dawn
Dowling, Natalie Anne
Hurd, Frank
Lomonico, Serena
Nowlis, Josh
Ovando, Dan
Parma, Ana María
Prince, Jeremy D.
Wilson, Jono R.
author_role author
author2 Amoroso, Ricardo
Bell, Richard J.
Caillaux, Matias
Cope, Jason Marc
Dougherty, Dawn
Dowling, Natalie Anne
Hurd, Frank
Lomonico, Serena
Nowlis, Josh
Ovando, Dan
Parma, Ana María
Prince, Jeremy D.
Wilson, Jono R.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv FISHERY MANAGEMENT
INDICATOR
MANAGEMENT STRATEGY
FRAMEWORK
STOCK ASSESSMENT
topic FISHERY MANAGEMENT
INDICATOR
MANAGEMENT STRATEGY
FRAMEWORK
STOCK ASSESSMENT
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv As the world population grows, fisheries practitioners will be under increased pressure to address global challenges in data-limited fisheries management. With a focus on addressing localized and case-specific management needs, we provide a practical guide to the design and development of multi-indicator frameworks for fishery management. In a data-limited context, indicators are observations or estimates of the state of the fishery resource that are typically proxies for variables of interest, rather than quantities such as stock biomass estimated from data-rich stock assessments. Indicator frameworks structure the integration and interpretation of indicators to guide tactical fishery decision-making, often when the application of more formal analytical assessments is not feasible, yet where indicators in combination provide insight into stock status. With a focus on multi-indicator frameworks, we describe a pragmatic approach for their development via a set of organizational steps, considering a wide spectrum of types and severity of information limitations. We highlight where multi-indicator frameworks can be insightful and informative in relation to single indicator approaches but also point to potential pitfalls, with emphasis on critical evaluation and detection of performance flaws during the design phase using methods such as management strategy evaluation.
Fil: Harford, William J.. Nature Analytics; Canadá
Fil: Amoroso, Ricardo. University of Washington; Estados Unidos
Fil: Bell, Richard J.. The Nature Conservancy; Estados Unidos
Fil: Caillaux, Matias. The Nature Conservancy; Estados Unidos
Fil: Cope, Jason Marc. National Marine Fisheries Service; Estados Unidos
Fil: Dougherty, Dawn. The Nature Conservancy; Estados Unidos
Fil: Dowling, Natalie Anne. Commonwealth Scientific And Industrial Research Organization (CSIRO); Australia
Fil: Hurd, Frank. The Nature Conservancy; Estados Unidos
Fil: Lomonico, Serena. The Nature Conservancy; Estados Unidos
Fil: Nowlis, Josh. National Marine Fisheries Service; Estados Unidos
Fil: Ovando, Dan. University of Washington; Estados Unidos
Fil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina
Fil: Prince, Jeremy D.. Murdoch Univeristy; Australia
Fil: Wilson, Jono R.. The Nature Conservancy; Estados Unidos. University of California; Estados Unidos
description As the world population grows, fisheries practitioners will be under increased pressure to address global challenges in data-limited fisheries management. With a focus on addressing localized and case-specific management needs, we provide a practical guide to the design and development of multi-indicator frameworks for fishery management. In a data-limited context, indicators are observations or estimates of the state of the fishery resource that are typically proxies for variables of interest, rather than quantities such as stock biomass estimated from data-rich stock assessments. Indicator frameworks structure the integration and interpretation of indicators to guide tactical fishery decision-making, often when the application of more formal analytical assessments is not feasible, yet where indicators in combination provide insight into stock status. With a focus on multi-indicator frameworks, we describe a pragmatic approach for their development via a set of organizational steps, considering a wide spectrum of types and severity of information limitations. We highlight where multi-indicator frameworks can be insightful and informative in relation to single indicator approaches but also point to potential pitfalls, with emphasis on critical evaluation and detection of performance flaws during the design phase using methods such as management strategy evaluation.
publishDate 2021
dc.date.none.fl_str_mv 2021-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/166672
Harford, William J.; Amoroso, Ricardo; Bell, Richard J.; Caillaux, Matias; Cope, Jason Marc; et al.; Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design; Frontiers Media; Frontiers In Marine Science; 8; 12-2021; 1-13
2296-7745
CONICET Digital
CONICET
url http://hdl.handle.net/11336/166672
identifier_str_mv Harford, William J.; Amoroso, Ricardo; Bell, Richard J.; Caillaux, Matias; Cope, Jason Marc; et al.; Multi-Indicator Harvest Strategies for Data-Limited Fisheries: A Practitioner Guide to Learning and Design; Frontiers Media; Frontiers In Marine Science; 8; 12-2021; 1-13
2296-7745
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3389/fmars.2021.757877
info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fmars.2021.757877/full
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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