Synthesising biological, economic and sociological knowledge using Bayesian Belief Networks to support broadly based fisheries policy:the case of devising a new Baltic salmon management plan
Polina Levontin, Soile Kulmala, Päivi Haapasaari, Katja Parkkila · Figshare · 2009
No abstracts are to be cited without prior reference to the author.In order to develop a new management plan for Baltic salmon fisheries the European Commission has asked for a comprehensive impact assessment. The resulting analysis comprised several studies carried out by scientists from respective disciplines. These included: biological and ecological assessment, economic analysis of the commercial fisheries sector and a separate socio-economic data analysis of the recreational fisheries, and, finally, a sociological impact assessment was conducted aimed at understanding stakeholder perspectives and possible commitment to a new management plan. In order to synthesize the findings from these disparate studies a Bayesian Belief Network (BBN) methodology is used. BBN is a tool that can support decision making by allowing a computation of utilities of different decisions in the light of diverse sources of evidence. Additionally, BBN provides a convenient way to summarise information in one model that represents the management problem that includes all of the evidence available. We demonstrate how this methodology can be used to support decision making in fisheries that relies not just on stock assessments but also on a broader range of expert opinion, data and research from ecological, economical and sociological fields.