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Information transfer, behavior of vessels and fishing efficiency: an individual-based simulation approach

Published online by Cambridge University Press:  01 April 2006

Laurent Millischer  and
Didier Gascuel
Laurent Millischer
Affiliation:
Agrocampus Rennes, Département Halieutique UPR Mesh, 65 rue de Saint-Brieuc, CS 84215, 35042 Rennes Cedex, France
Didier Gascuel
Affiliation:
Agrocampus Rennes, Département Halieutique UPR Mesh, 65 rue de Saint-Brieuc, CS 84215, 35042 Rennes Cedex, France
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Abstract

A simulator dedicated to the modeling of individual search behaviors of fishing vessels has been built using multi-agents systems methodology. The harvesting activity of a virtual fleet is simulated and applied to a static virtual fish population, distributed in a bi-dimensional spatially explicit environment. The resource population can differ depending on different degrees of aggregation. Each vessel of the fleet is modeled as a singular and autonomous agent of the fishery system. The model focuses on the representation of information transfer among vessels, which results in an orientation of search effort. The informative search behavior is compared to a stochastic search, in order to estimate efficiency gains allowed by information transfers. Results show a strong dependence of the fleet's efficiency towards the level of aggregation of the resource. For higher levels of aggregation the informative behavior results in important gains in efficiency. Conversely, a misleading effect of information appears in the weakest aggregations. The informative behavior leads to the progressive convergence and the gathering of the agents. When the aggregation is strong, this “pack effect” is stable in time and enables the vessels to make quick catches. For the weakest aggregation levels, the “pack effect” is unstable and leads the ships to a perpetual pursuit state, without catches. Thus, the size of existing networks appears as a key parameter of vessel behaviors. This approach, using an individual-based simulator, seems quite appropriate to connect individual behaviors to the dynamics of the fishing efficiency, which are generally studied in an aggregated manner. It allows to quantify the effects of the exchange of information among vessels, which is commonly considered as a qualitative phenomenon. Such an approach should be enlarged to a more global modeling of all of the components of the individual search behaviors of vessels.

Keywords

Fishing behaviorFishing efficiencyFish aggregationIndividual-based modelMulti-agent systemsSimulation
Type
Research Article
Information
Aquatic Living Resources , Volume 19 , Issue 1 , January 2006 , pp. 1 - 13
Copyright
© EDP Sciences, IFREMER, IRD, 2006

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References

Abrahams, M.V., Healey, M.C., 1990, Variation in the competitive abilities of fishermen and its influence on the spatial distribution of the British Columbia salmon troll fleet. Can. J. Fish. Aquat. Sci. 47, 1116-1121. CrossRef
Allen P.M., 1991, Fisheries: models of learning and uncertainty. In: Cury P., Roy C. (Eds.), Pêcheries ouest-africaines. Variabilité, instabilité et changement, Colloques et séminaires, Paris, Orstom, pp. 377-389.
Allen, P.M., McGlade, J.M., 1986, Dynamics of discovery and exploitation: the case of the Scottian shelf ground fish fisheries. Can. J. Fish Aquat. Sci. 43, 1187-1200. CrossRef
Bouju S., 1995, Anthropologie et halieutique : réflexions sur l'élaboration d'une typologie et sur l'intérêt de l'utilisation de la notion de technotope. In: Laloë F., Durand J.L., Rey H. (Eds.), Questions sur la dynamique de l'exploitation halieutique, Colloques et séminaires, Paris, Orstom, pp. 245-262.
Bousquet F., 1995, Les systèmes multi-agents et la modélisation de la pêche dans le delta central du Niger : remarques sur une expérimentation. In: Laloë F., Durand J.L., Rey H. (Eds.), Questions sur la dynamique de l'exploitation halieutique, Colloques et séminaires, Paris, Orstom, pp. 141-166.
Breton, Y., 1981, L'anthropologie sociale et les sociétés de pêcheurs. Réflexions sur la naissance d'un sous-champ disciplinaire. Anthropol. Soc. 5, 7-27.
Clark, M., Mangel, C.W., 1979, Aggregation and fishery dynamics: a theoretical study of schooling and the purse seine tuna fisheries. Fish. Bull. 77, 317-337.
Coquillard P., Hill R.C.D., 1997, Modélisation et simulation d'écosystèmes. Des modèles déterministes aux simulations à évènements discrets. Paris, Masson.
DeAngelis D.L., Gross M.J. (Eds.), 1992, Individual-based models and approaches in ecology: populations, communitites and ecosytems. New York, Chapman & Hall.
Dorn, W.M., 1998, Fine-scale fishing strategies of factory trawlers in a midwater trawl fishery for Pacific hake (Merluccius productus). Can. J. Fish. Aquat. Sci. 55, 180-198. CrossRef
Dreyfus-Leon, M.J., 1999, Individual-based modeling of fishermen search behavior with neural networks and reinforcement learning. Ecol. Model. 120, 287-297. CrossRef
Dreyfus-Leon, M., Kleiber, P., 2001, A spatial individual behavior-based model approach of the yellowfin tuna fishery in the eastern Pacific Ocean. Ecol. Model. 146, 47-56. CrossRef
Ferber J., 1995, Les systèmes multi-agents. Vers une intelligence collective. Paris, InterEditions.
Ferber J., 1997, La modélisation multi-agents : un outil d'aide à l'analyse de phénomènes complexes. Tendances nouvelles en modélisation pour l'environnement. Paris, Journées du Programme Environnement, Vie et Société du CNRS, pp. 113-133.
Fonteneau A., Gascuel D., Pallares P., 1998, Vingt-cinq ans d'évaluation des ressource thonières dans l'Atlantique : quelques réflexions méthodologiques. Proc. ICCAT Tuna Symposium, Madrid, pp. 523-561.
Gaertner, D., Pagavino, M., Marcano, J., 1999, Influence of fishers'behaviour on the catchability of surface tuna schools in the Venezuelan purse-seiner fishery in the Caribbean Sea. Can. J. Fish. Aquat. Sci. 56, 394-406.
Gascuel D., 1995, Efforts et puissances de pêche : redéfinition des concepts et exemple d'application. In: Gascuel D., Durand J.L., Fonteneau A. (Eds.), Les recherches françaises en evaluation quantitatives et modélisation des resources et des systèmes halieutiques, Colloques et séminaires, Paris, Orstom, pp. 159-181.
Gascuel, D., Fonteneau, A., Foucher, E., 1993, Analyse de l'évolution des puissances de pêche par l'analyse des cohortes : application aux senneurs exploitant l'albacore (Thunnus albacares) dans l'Atlantique Est. Aquat. Living Resour. 6, 15-30. CrossRef
Gauthiez F., 1996, Multiplicité d'échelles dans l'organisation spatiale des poissons marins : modélisation des schémas locaux, couplage avec le comportement du pêcheur et conséquences sur l'observation d'une ressource halieutique. Tendances nouvelles en modélisation pour l'environnement. Paris, Journées du Programme Environnement, Vie et Société du CNRS, pp. 223-230.
Gillis, M.G., Peterman, R.M., 1998, Implications of interference among fishing vessels and the ideal free distribution to the interpretation of CPUE. Can. J. Fish. Aquat. Sci. 55, 37-46. CrossRef
Grimm, V., 1999, Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future? Ecol. Model. 115, 129-148. CrossRef
Hancock, J., Hart, J.B.P., Antezana, T., 1995, Searching behavior and catch of horse mackerel (Trachurus murphyi) by industrial purse-seiners off south-central Chile. ICES J. Mar. Sci. 52, 991-1004. CrossRef
Hilborn, R., 1985, Fleet dynamics and individual variations: why some people catch more fish than others. Can. J. Fish. Aquat. Sci. 42, 2-13. CrossRef
Hilborn, R., Ledbetter, M., 1985, Determinants of catching power in the British Columbia salmon purse seine fleet. Can. J. Fish. Aquat. Sci. 42, 51-56. CrossRef
Hilborn, R., Walters, C.J., 1987, A general model for simulation of stock and fleet dynamics in spatially heterogeneous fisheries. Can. J. Fish Aquat. Sci. 44, 1366-1369. CrossRef
Hilborn R., Walters C.J., 1992, Quantitative Fisheries Stock Assessment. Choice, dynamics and uncertainty. New York, Chapman and Hall.
Laurec, A., 1977, Analyse et estimations des puissances de pêche. J. Cons. Int. Explor. Mer 37, 173-185. CrossRef
Lomnicki, A., 1999, Individual-based models and the individual-based approach to population ecology. Ecol. Model. 115, 191-198. CrossRef
Maury O., Millischer L., Gascuel D., Fonteneau A., 1998, Le GAM, un outil d'estimation des biomasses locales. Application au thon albacore (Thunnus albacares) de l'Atlantique. In: Biométrie et Halieutique, Duby C., Gouet J.P., Laloë F. (Eds.), Paris, IRD pp. 11-20.
Millischer L., 2000, Modélisation individu-centrée des comportements de recherche des navires de pêche. Approche spatialement explicite par systèmes multi-agents. Intérêts pour l'analyse des stratégies et des puissances de pêche. Thèse de doctorat de l'ENSAR, Rennes.
Millischer, L., Gascuel, D., Biseau, A., 1999, Estimation of the overall fishing power: a study of the dynamics and fishing strategies of Brittany's industrial fleets. Aquat. Living Resour. 12, 89-103. CrossRef
Pichon J., 1992, Les zones de pêche des chalutiers bigoudens. Thèse de doctorat de géographie de l'Université de Bretagne occidentale, Brest.
Poulard, J.C., Léauté, J.P., 2002, Interaction between marine populations and fishing activities: temporal patterns of landings of La Rochelle trawlers in the Bay of Biscay. Aquat. Living Resour. 15, 197-210. CrossRef
Powell, E.N., Bonner, A.J, Muller, B., Bochenek, E.A., 2003, Vessel time allocation in the US Illex illecebrosus fishery. Fish. Res. 6, 35-55. CrossRef
Robson, D.S., 1966, Estimation of the relative Fishing Power of individual ships. ICNAF Res. Bull. 3, 5-15.
Salthaug, A., 2001, Adjustment of commercial trawling effort for Atlantic cod, Gadus morhua, due to increasing catching efficiency. Fish. Bull. 99, 338-342.
Salthaug, A., Aanes, S., 2003, Catchability and spatial distribution of fishing vessels. Can. J. Fish. Aquat. Sci. 60, 259-268 CrossRef
Squires, D., Kirkley, J., 1999, Skipper skill and panel data in fishing industries. Can. J. Fish. Aquat. Sci. 56, 2011-2018. CrossRef
Swain, D.P., Wade, E.J., 2003, Spatial distribution of catch and effort in a fishery for snow crab (Chionoecetes opilio): test of predictions of the ideal free distribution. Can. J. Fish. Aquat. Sci. 60, 987-909. CrossRef
Thorlindsson T., 1988, The skipper effect in the Icelandic herring fishery. Human Org. 47,199-212.
Vignaux, M., 1996, Analysis of vessel movements and strategies using commercial catch and effort data from the New Zealand hoki fishery. Can. J. Fish. Aquat. Sci. 53, 2126-2136. CrossRef
Xiao, Y., 2004, Modelling the learning behavior of fishers: learning more from their successes than from their failures. Ecol. Model. 171, 3-20. CrossRef