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Precautionary risk methodology in fisheries

Final Report Summary - PRONE (Precautionary risk methodology in fisheries)

The PRONE project developed risk methodologies for fisheries management which became available to managers in the sector in order to help them confront the inherent risks of fisheries in the European Union. The developed methods provided improved quantitative and qualitative information on the biological, social and economic consequences of the currently applied and the alternative actions, embracing the full process from stock assessment, projection and advice, to the practical implementation of the management measures, including control. PRONE was expected to improve fisheries profitability around Europe if being successfully implemented.

Information on the stakeholders' risk perception was collected through the examination of four contrasting case studies in different countries. The project aimed to take advantage of relevant state of the art in a variety of fields and test the methodologies applicability to fisheries management. Risks were analysed both from management and advice points of view. The specific PRONE objectives were as follows:
1. review the current state of the art in fisheries science and management framework and identify weaknesses along with potentially useful risk approaches being used in other fields of applied sciences;
2. identify the knowledge requirements and link them to their ability to achieve management objectives by management tools;
3. identify the necessary controllable elements in different systems and their ability to manipulate the system in order to achieve management objectives;
4. develop risk assessment and management tools;
5. evaluate the level of understanding and the will to exploit risk related information in alternative management systems through the examination of the selected case studies, taking into account the cultural background of the fish farmers.

The methodological tools which were either developed or applied as part of the project were the following:
1. use of probabilistic Bayesian stock assessment tools to fish stocks;
2. risk management control tools to plan multi-disciplinary fisheries management;
3. game theory to analyse management implementation on international level;
4. informative stock-recruitment models addressed to specific European stocks;
5. human health risk methodology in fisheries context;
6. risk classification methods, supporting clearer actors' responsibilities.

PRONE was successful in providing high quality scientific methodology. It demonstrated in particular that risks were very specific for different fisheries, thus specific model structures and estimation procedures ought to be followed. Hierarchical Bayesian models seemed to serve as a valuable tool, especially in cases of increased uncertainty.

The project evaluated the currently applied uncertainty methodology, included theoretical and empirical sections on economic and social risks and provided and tested alternative tools. Decision analysis was applied only to biological parts of the modelling. In addition, first steps for an easily applicable risk classification were developed.

Finally, the current risk methodology was reviewed from both a theoretical and a practical point of view. The tested framework helped to produce a balanced evaluation of risk management systems, including a strong human dimension along with advice on the elements of international agreements controlling fisheries risks.

The project results were mainly disseminated via the production of scientific manuscripts sent to peer reviewed scientific journals. In addition, theme sessions were organised to comment on the multidisciplinary aspects of risk analysis in fisheries, while the findings of PRONE were actively applied by scientific organisations and included in universities teaching material.

It was proposed that future framework research should focus on the development of an ecosystem based risk framework for results based management in sustainable fisheries. In that way stakeholders could better understand and further use the relevant risk estimates for an effective and efficient management of more complex real world fisheries systems.

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