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A Concept of Bayesian Regulation in Fisheries Management
University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.ORCID iD: 0000-0003-3000-8786
University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.ORCID iD: 0000-0002-2055-4284
University of Tartu, Estonia.
University of Helsinki, Finland.
2014 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 11, e111614Article in journal (Refereed) Published
Abstract [en]

Stochastic variability of biological processes and uncertainty of stock properties compel fisheries managers to look for tools to improve control over the stock. Inspired by animals exploiting hidden prey, we have taken a biomimetic approach combining catch and effort in a concept of Bayesian regulation (BR). The BR provides a real-time Bayesian stock estimate, and can operate without separate stock assessment. We compared the performance of BR with catch-only regulation (CR), alternatively operating with N-target (the stock size giving maximum sustainable yield, MSY) and F-target (the fishing mortality giving MSY) on a stock model of Baltic Sea herring. N-targeted BR gave 3% higher yields than F-targeted BR and CR, and 7% higher yields than N-targeted CR. The BRs reduced coefficient of variance (CV) in fishing mortality compared to CR by 99.6% (from 25.2 to 0.1) when operated with F-target, and by about 80% (from 158.4 to 68.4/70.1 depending on how the prior is set) in stock size when operated with N-target. Even though F-targeted fishery reduced CV in pre-harvest stock size by 19–22%, it increased the dominant period length of population fluctuations from 20 to 60–80 years. In contrast, N-targeted BR made the periodic variation more similar to white noise. We discuss the conditions when BRs can be suitable tools to achieve sustainable yields while minimizing undesirable fluctuations in stock size or fishing effort.

Place, publisher, year, edition, pages
PLoS , 2014. Vol. 9, no 11, e111614
National Category
Ecology
Research subject
Natural sciences
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URN: urn:nbn:se:his:diva-10449DOI: 10.1371/journal.pone.0111614ISI: 000345558100088PubMedID: 25365071Scopus ID: 2-s2.0-84909619978OAI: oai:DiVA.org:his-10449DiVA: diva2:773291
Available from: 2014-12-18 Created: 2014-12-18 Last updated: 2017-12-05Bibliographically approved

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