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| Rockmann, Christine; Ulrich, Clara; Dreyer, Marion; Bell, Ewen; Borodzicz, Edward; Haapasaari, Paivi; Hauge, Kjellrun Hiis; Howell, Daniel; Mantyniemi, Samu; Miller, David; Tserpes, George; Pastoors, Martin. |
| 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... |
| Tipo: Text |
Palavras-chave: Participatory modelling; Fisheries management; Uncertainty; Post-normal science; Extended peer review; Problem framing. |
| Ano: 2012 |
URL: https://archimer.ifremer.fr/doc/00589/70104/68121.pdf |
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| Planque, Benjamin; Mullon, Christian. |
| Nearly 30 years ago, emerged the concept of deterministic chaos. With it came sensitivity to initial conditions, nonlinearities, and strange attractors. This constituted a paradigm shift that profoundly altered how numerical modellers approached dynamic systems. It also provided an opportunity to resolve a situation of mutual misunderstanding between scientists and non-scientists about uncertainties and predictability in natural systems. Our proposition is that this issue can be addressed in an original way which involves modelling based on the principles of chance and necessity (CaN). We outline the conceptual and mathematical principles of CaN models and present an application of the model to the Barents Sea food-web. Because CaN models rely on concepts... |
| Tipo: Text |
Palavras-chave: Chaos theory; Constraints; Nonlinear systems; Participatory modelling; Uncertainty; Viability theory. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00585/69686/67759.pdf |
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