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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 uncer- tainty 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.

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 ...

Stakeholder involvement is perceived as an important development in the European Common Fisheries Policy. But 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 project Judgement and Knowledge in Fisheries Involving Stakeholders (JAKFISH) was a 3 year project with 10 partners from the EU and Norway. It provided an integrated approach to stakeholder involvement into fisheries management and examined the institutions, practices and tools that allow complexity, uncertainty and ambiguity to be dealt with. The JAKFISH project reviewed the general literature on participatory modelling in natural resource management and derived a number of key recommendations from that review. The project also developed a fisheries management simulation game that was successfully applied in a number of occasions. In four different case studies, the JAKFISH project 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. We conclude 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. Modelling should not be seen as the priority objective. The crucial step in a science-stakeholder collaboration is the joint problem framing. The JAKFISH project also carried out social network analyses of the institutions and networks involved in six fisheries management systems (four in Europe, one in Australia and one in the USA). The results suggest that management systems with high participation in decision-making tended to have more disagreement about facts and values. When experts discuss matters more with colleagues from other stakeholder groups, their values, interests, opinions, and knowledge tend to differ. Consensus within a stakeholder group seems to be higher if the most important discussion partners are selected within the group. The discussion about the role of uncertainty in natural resource management and decision-making often assumes that it is the scientists that help other stakeholder better understand uncertainties and that this happens after the uncertainties have been identified. Our research refuted both assumption. Communication about uncertainty is clearly a two-way process and it already is happening during the problem framing and research process. An important difference has been identified between scientific proof-making and scientific justification. Scientific proof-making is evaluated against set of internal scientific criteria. Scientific justification is evaluated by a broader community consisting of scientific peers, government officials, industry stakeholders and environmental NGOs. Whether scientific uncertainty becomes an issue in a policy making context, not only depends on the amount of uncertainty, but also on the stakes involved and the burden of proof placed on the science. The claim in the EU Habitats Directive that site designation is an exclusively scientific exercise places all the burden of proof on the science which then triggers disproportionate attention to scientific complexity and uncertainty, particularly where stakes are high. The JAKFISH project has shown that participatory modelling requires an effective facilitation strategy where scientists, stakeholders and policy-makers actively connect and discuss. There is a need to train the participants in these process. It needs the realization that participatory modelling both builds trust and is built on trust, that it takes time and effort and that the outcome is more than the individual parts.