Predicting fisher response to competition for space and resources in a mixed demersal fishery

Type Article
Date 2015-03
Language English
Author(s) Girardin Raphael1, Vermard YouenORCID2, Thebaud OlivierORCID3, 4, Tidd Alex5, Marchal PaulORCID1
Affiliation(s) 1 : IFREMER, Fishery Resource Lab, F-62321 Boulogne Sur Mer, France.
2 : IFREMER, Unit Fisheries Ecol & Modelling, Ctr Atlantique, F-44311 Nantes 03, France.
3 : IFREMER, UMR M101, AMURE, Unite Econ Maritime,Ctr Bretagne,ZI Pointe Diable, F-29280 Plouzane, France.
4 : Queensland Univ Technol, Sch Econ & Finance, Brisbane, Qld 4001, Australia.
5 : Cefas, Lowestoft NR33 0HT, Suffolk, England.
Source Ocean & Coastal Management (0964-5691) (Elsevier Sci Ltd), 2015-03 , Vol. 106 , P. 124-135
DOI 10.1016/j.ocecoaman.2015.01.017
WOS© Times Cited 9
Keyword(s) Effort allocation, Random Utility Model, Spatial competition, Demersal mixed fishery, Eastern English Channel, Spatial management
Abstract Understanding and modelling fleet dynamics and their response to spatial constraints is a prerequisite to anticipating the performance of marine ecosystem management plans. A major challenge for fisheries managers is to be able to anticipate how fishing effort is re-allocated following any permanent or seasonal closure of fishing grounds, given the competition for space with other active maritime sectors. In this study, a Random Utility Model (RUM) was applied to determine how fishing effort is allocated spatially and temporally by the French demersal mixed fleet fishing in the Eastern English Channel. The explanatory variables chosen were past effort i.e. experience or habit, previous catch to represent previous success, % of area occupied by spatial regulation, and by other competing maritime sectors. Results showed that fishers tended to adhere to past annual fishing practices, except the fleet targeting molluscs which exhibited within year behaviour influenced by seasonality. Furthermore, results indicated French and English scallop fishers share the same fishing grounds, and maritime traffic may impact on fishing decision. Finally, the model was validated by comparing predicted re-allocation of effort against observed effort, for which there was a close correlation.
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