000059093 001__ 59093
000059093 005__ 20250221175158.0
000059093 0247_ $$2doi$$a10.22004/ag.econ.59093
000059093 037__ $$a421-2016-26813
000059093 041__ $$aeng
000059093 245__ $$aIntegration of biological, economic and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential Baltic salmon management plan
000059093 260__ $$c2010
000059093 269__ $$a2010
000059093 300__ $$a28
000059093 336__ $$aConference Paper/ Presentation
000059093 520__ $$aThere is a growing need to evaluate fisheries management plans in a comprehensive
interdisciplinary context involving stakeholders. In this paper we demonstrate a
probabilistic management model to evaluate potential management plans for Baltic
salmon fisheries. The analysis is based on several studies carried out by scientists
from respective disciplines. The main part consisted of biological and ecological stock
assessment with integrated economic analysis of the commercial fisheries.
Recreational fisheries were evaluated separately. Finally, a sociological study was
conducted aimed at understanding stakeholder perspectives and potential commitment
to alternative management plans. In order to synthesize the findings from these
disparate studies a Bayesian Belief Network (BBN) methodology is used.
The ranking of management options can depend on the stakeholder perspective. The
trade-offs can be analysed quantitatively with the BBN model by combining,
according to the decision maker’s set of priorities, utility functions that represent
stakeholders’ views. We show how BBN can be used to evaluate 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 fishermen to management plans is highlighted by modelling the link
between commitment and implementation success.
000059093 546__ $$aEnglish
000059093 650__ $$aResource/Energy Economics and Policy
000059093 6531_ $$aBaltic salmon
000059093 6531_ $$abio-economic modelling
000059093 6531_ $$aBayesian Belief Network
000059093 6531_ $$aexpert
knowledge
000059093 6531_ $$afisheries management
000059093 6531_ $$acommitment and implementation uncertainty
000059093 6531_ $$amanagement
plan
000059093 6531_ $$arecreational fisheries
000059093 6531_ $$astakeholders.
000059093 700__ $$aLevontin, Polina
000059093 700__ $$aKulmala, Soile
000059093 700__ $$aHaapasaari, Paivi
000059093 700__ $$aKuikka, Sakari
000059093 8564_ $$978a73721-6e4b-431f-b94b-208f628e1ead$$s237464$$uhttps://ageconsearch.umn.edu/record/59093/files/Kulmala_%20Soile%201.pdf
000059093 887__ $$ahttp://purl.umn.edu/59093
000059093 909CO $$ooai:ageconsearch.umn.edu:59093$$pGLOBAL_SET
000059093 912__ $$nSubmitted by Megan Watmuff (megan@aomevents.com) on 2010-03-10T02:26:24Z
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  Previous issue date: 2010
000059093 913__ $$aLicense granted by Megan Watmuff (megan@aomevents.com) on 2010-03-10T02:23:40Z (GMT):

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000059093 980__ $$a421
000059093 982__ $$gAustralian Agricultural and Resource Economics Society>2010 Conference (54th), February 10-12, 2010, Adelaide, Australia