Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon

<qd> Levontin, P., Kulmala, S., Haapasaari, P., and Kuikka, S. 2011. Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon. – ICES Journal of Marine Science, 68: . </qd>...

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Bibliographic Details
Published in:ICES Journal of Marine Science
Main Authors: Levontin, Polina, Kulmala, Soile, Haapasaari, Päivi, Kuikka, Sakari
Format: Text
Language:English
Published: Oxford University Press 2011
Subjects:
Online Access:http://icesjms.oxfordjournals.org/cgi/content/short/68/3/632
https://doi.org/10.1093/icesjms/fsr004
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Summary:<qd> Levontin, P., Kulmala, S., Haapasaari, P., and Kuikka, S. 2011. Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon. – ICES Journal of Marine Science, 68: . </qd>There is a growing need to evaluate fisheries management plans in a comprehensive interdisciplinary context involving stakeholders. The use of a probabilistic management model to evaluate potential management plans for Baltic salmon fisheries is demonstrated. The analysis draws on several scientific studies: a biological stock assessment with integrated economic analysis of the commercial fisheries, an evaluation of recreational fisheries, and a sociological study aimed at understanding stakeholder perspectives and potential commitment to alternative management plans. A Bayesian belief network is used to synthesize the findings from these separate studies and to evaluate the robustness of management decisions to different priorities and various sources of uncertainty. In particular, the importance of sociological studies in quantifying uncertainty about the commitment of fishers to management plans is highlighted by modelling the link between commitment and implementation success. Such analyses, relying on prior knowledge, can forewarn of the consequences of management choices before they are implemented.