Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks

Designing and implementing long-term management plans is difficult both because of the complexity of the fisheries system, and the behaviour of humans. We compared four alternative management plans for the Baltic salmon stocks through approaching experts who interpreted and expressed the views of different stakeholder groups on the options. The focus of the study was on stakeholders’ commitment to the alternative management plans. Committing enhances the probability of achieving the ultimate objective of a plan, while if stakeholders do not commit, the effects of the plan may be less predictable. Thus commitment is an important part of implementation uncertainty in fisheries management. We present how we coupled qualitative analysis with probabilistic Bayesian networks in analysing expert knowledge related to alternative long term management plans in terms of group commitment. Using a Bayesian net provides potential for creating a holistic picture of a fishery by combining the data describing fishers’ commitment with biological data regarding fish stock dynamics and with economic data analyzing economically sound fisheries management.     

The added value of participatory modelling in fisheries management – what has been learnt?

How can uncertain fisheries science be linked with good governance processes, thereby increasing fisheries management legitimacy and effectiveness? Reducing the uncertainties around scientific models has long been perceived as the cure of the fisheries management problem. There is however increasing recognition that uncertainty in the numbers will remain. A lack of transparency with respect to these uncertainties can damage the credibility of science. The EU Commission's proposal for a reformed Common Fisheries Policy calls for more self-management for the fishing industry by increasing fishers' involvement in the planning and execution of policies and boosting the role of fishers' organisations. One way of higher transparency and improved participation is to include stakeholders in the modelling process itself. The JAKFISH project (Judgment And Knowledge in Fisheries Involving StakeHolders) invited fisheries stakeholders to participate in the process of framing the management problem, and to give input and evaluate the scientific models that are used to provide fisheries management advice. JAKFISH investigated various tools to assess and communicate uncertainty around fish stock assessments and fisheries management. Here, a synthesis is presented of the participatory work carried out in four European fishery case studies (Western Baltic herring, North Sea Nephrops, Central Baltic Herring and Mediterranean swordfish), focussing on the uncertainty tools used, the stakeholders' responses to these, and the lessons learnt. It is concluded that participatory modelling has the potential to facilitate and structure discussions between scientists and stakeholders about uncertainties and the quality of the knowledge base. It can also contribute to collective learning, increase legitimacy, and advance scientific understanding. However, when approaching real-life situations, modelling should not be seen as the priority objective. Rather, the crucial step in a science–stakeholder collaboration is the joint problem framing in an open, transparent way.