Baltic Herring Fisheries Management
Stakeholder Views to Frame the Problem
Bibliographic Data
| ID | 4239678 |
|---|---|
| Authors | Päivi Haapasaari (0000-0001-9342-5195, University of Helsinki), Samu Mäntyniemi (0000-0002-3367-6280, University of Helsinki), Sakari Kuikka (0000-0001-8802-8013, University of Helsinki) |
| Year | 2012 |
| Volume | 17 |
| Issue | 3 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Conservation Ecology (JOURNAL) |
| Journal identifiers | ISSN: 1195-5449 • E-ISSN: 1708-3087 |
| Publisher | Resilience Alliance (PUBLISHER • CA) |
| DOI | 10.5751/es-04907-170336 |
| OpenAlex | W2063901051 |
| Language | EN |
| Citations received | 6 |
| References cited | 13 |
Comprehensive problem framing that includes different perspectives is essential for holistic understanding of complex problems and as the first step in building models. We involved five stakeholders to frame the management problem of the Central Baltic herring fishery. By using the Bayesian belief networks (BBNs) approach, the views of the stakeholders were built into graphical influence diagrams representing variables and their dependencies. The views of the scientists involved concentrated on biological concerns, whereas the fisher, the manager, and the representative of an environmental nongovernmental organization included markets and fishing industry influences. Management measures were considered to have a relatively small impact on the development of the herring stock; their impact on socioeconomic objectives was greater. Overall, the framings by these stakeholders propose a focus on socioeconomic issues in research and management and explicitly define management objectives, not only in biological but also in social and economic terms. We find the approach an illustrative tool to structure complex issues systematically. Such a tool can be used as a forum for discussion and for decision support that explicitly includes the views of different stakeholder groups. It enables the examination of social and biological factors in one framework and facilitates bridging the gap between social and natural sciences. A benefit of the BBN approach is that the graphical model structures can be transformed into a quantitative form by inserting probabilistic information
Bayesian network · Business · Economics · Environmental resource management · Fisheries management · Fishery · Fishing · Fishing industry · Geography · Herring · Political science · Probabilistic logic · Public relations · Stakeholder · Stock assessment · Bayesian Modeling and Causal Inference · Cognitive Science and Mapping · Computer Science · Marine and fisheries research
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| Unique citing works | 6 |
|---|---|
| Citations per year | 0,46 |
| Citation span | 2013 - 2025 (13) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 5 |