FN Archimer Export Format
PT J
TI Modelling chance and necessity in natural systems
BT 
AF Planque, Benjamin
   Mullon, Christian
AS 1:1;2:2;
FF 1:;2:;
C1 Institute of Marine Research, Ecosystem Processes Research Group, Tromsø, Norway
   MARBEC, IRD; Université de Montpellier; IFREMER; CNRS; Sète, France
C2 INST MAR RES, NORWAY
   IRD, FRANCE
UM MARBEC
IN WOS Cotutelle UMR
   copubli-europe
IF 3.593
TC 10
UR https://archimer.ifremer.fr/doc/00585/69686/67759.pdf
LA English
DT Article
DE ;chaos theory;constraints;nonlinear systems;participatory modelling;uncertainty;viability theory
AB 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. 
PY 2020
PD JUN
SO Ices Journal Of Marine Science
SN 1054-3139
PU Oxford University Press (OUP)
VL 77
IS 4
UT 000582718700026
BP 1573
EP 1588
DI 10.1093/icesjms/fsz173
ID 69686
ER

EF