Who's onboard? A predictive analysis of cooperative formation in commercial fisheries.

Economic organization Fisheries management Fishing sectors Machine learning New institutional economics Random forest

Journal

Journal of environmental management
ISSN: 1095-8630
Titre abrégé: J Environ Manage
Pays: England
ID NLM: 0401664

Informations de publication

Date de publication:
01 Feb 2021
Historique:
received: 19 08 2020
revised: 18 11 2020
accepted: 21 11 2020
pubmed: 3 1 2021
medline: 14 1 2021
entrez: 2 1 2021
Statut: ppublish

Résumé

Fishing cooperatives around the world have increasingly taken on co-management of commercial fisheries in recent decades, with generally positive results in meeting management targets and increasing economic value. To better understand which commercial fisheries or fleets are likely to form cooperative associations in the future, we utilized a database of management and fleet-level attributes for 106 fisheries-mainly industrial fisheries from the United States, New Zealand, Canada, and the United Kingdom-to develop a predictive model. We considered two alternative definitions of cooperatives: a legal, operational definition that classified 51 of the fisheries as cooperatives, and a more stringent proactive definition that classified 35 of the fisheries as cooperatives. Random forest classification analyses showed that cooperatives of both types were most likely to form in fisheries with greater boat cost, greater level of participation in industry associations, and in fisheries with bycatch limits; strong regional effects were also observed. Cross-validation prediction accuracy levels were high: using 10 predictor variables, 86% and 91% of fisheries were correctly classified under the operational and proactive cooperative definitions, respectively. These predictions suggest which fisheries may be next to create cooperative fishing associations or engage in more proactive arrangements within cooperatives. These results point to which regulatory reforms, such as flexible bycatch restrictions, could lead to more cooperative behavior in fisheries.

Identifiants

pubmed: 33387866
pii: S0301-4797(20)31640-6
doi: 10.1016/j.jenvman.2020.111715
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

111715

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Michael De Alessi (M)

School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, WA, 98195, USA. Electronic address: dealessi@uw.edu.

Michael C Melnychuk (MC)

School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, WA, 98195, USA. Electronic address: mmel@u.washington.edu.

Edward Wort (E)

University of Plymouth, Plymouth, PL4 8AA, United Kingdom. Electronic address: ewort@outlook.com.

Ray Hilborn (R)

School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, WA, 98195, USA. Electronic address: rayh@uw.edu.

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Classifications MeSH