Theories and behavioural drivers underlying fleet dynamics models

Fish and Fisheries - Tập 13 Số 2 - Trang 216-235 - 2012
Ingrid van Putten1, Sakari Kulmala2, Olivier Thébaud2, Natalie Dowling1, Katell G. Hamon1,3,4,5, Trevor Hutton2, Sean Pascoe2
1CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania 7001, Australia
2CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, EcoSciences Precinct, PO Box 2583, Brisbane QLD 4001, Australia
3IFREMER, UMR AMURE, Département d’économie maritime, BP 70, 29280 Plouzané, France
4Tasmania Aquaculture and Fisheries Institute, University of Tasmania, Marine Research Laboratories, Nubeena Crescent Taroona, GPO Box 252-49, Hobart, Tasmania 7001, Australia
5Université européenne de Bretagne, Université de Brest, UMR AMURE, IUEM, 12 rue de Kergoat, CS 93837, 29238 Brest Cedex 3, France

Tóm tắt

AbstractIn the domain of decision‐support tools for the management of marine fish resources, considerable attention has been paid to the development of models explaining how fish stocks change over space and time. In most models, fishing effort is assumed to be exogenous and determined by factors such as management. Increasingly, there has been a call for bio‐economic models to also account for the dynamics of fishing fleets, recognizing that fishers respond to changing environmental, institutional and economic conditions. A growing literature has sought to explicitly model the endogenous determinants of the capacity of fishing fleets, the intensity of its use and its temporal and spatial allocation across fishing opportunities. We review this literature, focusing on empirical applications of the behavioural models that have been put forward to explain and predict observed fleet dynamics. We find that although economic factors are usually included as a dominant driver in most studies, this is often based on the use of proxy variables for the key economic drivers, for which adequate data are lacking. Also, while many studies acknowledge that social and social–psychological factors play a significant role in explaining observed fishing behaviour, their inclusion in fishing fleet dynamic models is still very limited. Progress in this domain can only be achieved via the development of multidisciplinary research programmes focusing on applied quantitative analysis of the drivers of fishing fleet dynamics.

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