Modelling chance and necessity in natural systems

Type Article
Date 2020-07
Language English
Author(s) Planque Benjamin1, Mullon Christian2
Affiliation(s) 1 : Institute of Marine Research, Ecosystem Processes Research Group, Tromsø, Norway
2 : MARBEC, IRD; Université de Montpellier; IFREMER; CNRS; Sète, France
Source Ices Journal Of Marine Science (1054-3139) (Oxford University Press (OUP)), 2020-07 , Vol. 77 , N. 4 , P. 1573-1588
DOI 10.1093/icesjms/fsz173
WOS© Times Cited 3
Note Contribution to the Themed Section: ‘Science in support of a nonlinear non-equilibrium world’ Food for Thought
Keyword(s) chaos theory, constraints, nonlinear systems, participatory modelling, uncertainty, viability theory
Abstract

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 easily grasped by all actors, because they are explicit about knowns and unknowns and because the interpretation of their results is simple without being prescriptive, they can be used in a context of participatory management. We propose that, three decades after the emergence of chaos theories, CaN can be a practical step to reconcile scientists and non-scientists around the modelling of structurally and dynamically complex natural systems, and significantly contribute to ecosystem-based fisheries management.

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