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A new bioeconomic simulation tool for small scale fisheries based on game theory: GAMEFISTO model

Published online by Cambridge University Press:  27 October 2007

Gorka Merino ,
Francesc Maynou  and
Antonio García-Olivares
Gorka Merino
Affiliation:
Instituto de Ciencias del Mar (ICM-CSIC), Paseo Marítimo de la Barceloneta 37-49, 08003 Barcelona, Spain
Francesc Maynou
Affiliation:
Instituto de Ciencias del Mar (ICM-CSIC), Paseo Marítimo de la Barceloneta 37-49, 08003 Barcelona, Spain
Antonio García-Olivares
Affiliation:
Instituto de Ciencias del Mar (ICM-CSIC), Paseo Marítimo de la Barceloneta 37-49, 08003 Barcelona, Spain
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Abstract

GAMEFISTO simulation model is presented as a tool to improve the small scale fisheries bioeconomic simulation techniques. The main novelty of the current model is the implementation of game theoretic techniques for forecasting the fishing effort trends and consequently, the fish population levels and the economic outcome, including landings, income and net profits. The model assigns individual fishing strategies to individual vessels according to their technical characteristics. The fishermen within a fishing fleet exploiting a single stock are assumed to be the decision agents, who share not only a fish population (modelled through stock externality) but also a market, through an offer-demand function (market externality). Mediterranean fisheries need to be analysed at vessel level due to the heterogeneity of its fishing fleets. A ten year simulation on red shrimp, Aristeus antennatus, is presented as an application of the presented GAMEFISTO model.

Keywords

Game theoryStochastic simulationBioeconomic modelMediterranean fisheriesAristeus antennatus
Type
Research Article
Information
Aquatic Living Resources , Volume 20 , Issue 3 , July 2007 , pp. 223 - 230
Copyright
© EDP Sciences, IFREMER, IRD, 2007

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References

Arnason, R., Magnusson, G., Agnarsson, S., 2001, The Norwegian Spring-spawning herring fishery: a stylised game model. Mar. Resour. Econ. 15, 293-319. CrossRef
Babcock, E.A, Pikitch, E.K, 2000, A dynamic programming model of fishing strategy choice in a multispecies trawl fishery with trip limits. Can. J. Fish. Aquat. Sci. 57, 357-370. CrossRef
Bas C, Maynou F., Sardá F., Lleonart J., 2003, Variacions Demogràfiques a les Poblacions d'espècies Demersals Explotades. Els Darrers Quaranta Anys a Blanes i Barcelona, Barcelona, Institut d'Estudis Catalans.
Camerer, C.F., Fehr, E., 2006, When does “economic man” dominate social behaviour? Science 311, 47-52. CrossRef
Carbonell A., Bruno J., Gaza M., Fernández J.L., 2003, Stock assessment of the red shrimp (Aristeus antennatus) in the management unit 5. Balearic zone, Northern Spain. Working doc. No. 3 to the GFCM SAC Working Group on the assessment of demersal stocks.
Carbonell, A., Carbonell, M., Demestre, M., Grau, A., Montserrat, S., 1999, The red shrimp Aristeus antennatus (Risso, 1816) fishery and biology in the Balearic islands, western Mediterranean. Fish. Res. 44, 1-13. CrossRef
Demestre, M., Lleonart, J., 1993, Population dynamics of Aristeus antennatus (Decapoda: Dendrobranchiata) in the Northwestern Mediterranean. Sci. Mar. 57, 183-189.
Demestre, M., Martin, P., 1993, Optimum exploitation of a demersal resource in the western Mediterranean: the fishery of the deep-water shrimp Aristeus antennatus (Risso, 1816). Sci. Mar. 57, 175-182.
ESRI, 2004, ArcGIS 9.0.
FAO, 2004, The State of World Fisheries and Aquaculture, Rome, Food and Agriculture Organization of the United Nations.
Finlayson A.C., 1994, Fishing for truth: A sociological analysis of northern cod stock assessments from 1977-1990. St. John's, Newfoundland, Canada. Memorial University of Newfoundland.
Fudenberg D., Tirole J., 1991, Game Theory, Cambridge, MIT Press.
Grant, W.E., Isakson, K.G., Griffin, W.L., 1981, A general bioeconomic simulation model for annual-crop marine fisheries. Ecol. Model. 13, 195-219. CrossRef
Griffin W.L., 2003, A General Bioeconomic Fisheries Simulation Model: Description, Calibration, Validation, and Application. Proc. 1st North Am. Fish. Econ. Forum pp. 97-112.
Grønbæk L., 2000, Fishery Economics and Game Theory, Esberj, University of Southern Denmark.
Haddon M., 2001, Modelling and quantitative methods in fisheries, Boca Ratón, Florida, Chapman and Hall.
Hannesson, R., 1995, Sequential fishing: cooperative and non-cooperative equilibria. Nat. Res. Model. 9, 51-59. CrossRef
Hannesson, R., 1997, Fishing as a supergame. J. Environ. Econ. Manage. 32, 309-322. CrossRef
Hardin, G., 1968, The tragedy of the commons. Science 162, 1243-1248.
Hilborn R., Walters C.J., 1992, Quantitative Fisheries Stock Assessment: Choice, Dynamics and Uncertainty. London. Chapman and Hall.
Isakson, K.G., Grant, W.E., Griffin, W.L., 1982, General Bioeconomic Fisheries Simulation Model: A detailed model documentation. J. Int. Soc. Ecol. Model. 4, 61-85.
Kaitala, V.T., Lindroos, M., 1998, Sharing the benefits of cooperation in high seas fisheries: A characteristic function game approach. Nat. Res. Model. 11, 275-299. CrossRef
Levhari, D., Mirman, L.J., 1980, The great fish war: An example using a dynamic Cournot-Nash solution. Bell J. Econ. 11, 322-334. CrossRef
Lleonart J., 1999, Precautionary approach and Mediterranean fisheries. Precautionary approaches to local fisheries and species introductions in the Mediterranean. CIESM Workshop.
Lleonart, J., Maynou, F., 2003, Fish stock assessments in the Mediterranean: state of the art. Sci. Mar. 67, 37-49. CrossRef
Lleonart, J., Maynou, F., Franquesa, R., 1999, A bioeconomic model for Mediterranean fisheries, the hake off Catalonia (western Mediterranean) as a case study. Fish. Econ. Newsl. 48, 1-16.
Lleonart, J., Maynou, F., Recasens, L., Franquesa, R., 2003, A bioeconomic model for Mediterranean fisheries, the hake off Catalonia (western Mediterranean) as a case study. Sci. Mar. 67, 337-351. CrossRef
Luce R.D., Raiffa H., 1989, Games and Decisions. Introduction and Critical Survey, New York. John Wiley and Sons, Inc.
Mardle, S., Pascoe, S., 2002, Modelling the effects of trade-offs between long and short-term objectives in fisheries management. J. Environ. Manage. 65, 49-62. CrossRef
Merino G., 2006, Simulation techniques for the bioeconomic analysis of Mediterranean fisheries. Game theory and effort dynamics. GAMEFISTO model , PhD thesis, Barcelona, Universitat Politécnica de Catalunya.
Merino G., Maynou F., García-Olivares A., 2007, Effort dynamics in a fisheries bioeconomic model: A vessel level approach through game theory, Sci. Mar. 71(3), 537-550.
Mesterton-Gibbons, M., 1993, Game-Theoretic resource modeling. Nat. Res. Model. 7, 93-147. CrossRef
Munro G.R., 2006, Game Theory and the development of resource management policy: The case of international fisheries. 6th meeting on game Theory and Practice Dedicated to Development, Natural Resources and the Environment, Zaragoza.
Nash, J.F., 1951, Non-cooperative games. Ann. Math. 54, 286-295. CrossRef
Oakerson R.J., 1992, Analyzing the commons: A framework. In: Bromley D.W. (Eds.) Making the commons work: Theory, practice and policy. San Francisco, ICS Press, pp. 41-59.
Pauly, D., Christensen, U.V., Guénette, S., Pitcher, T., Sumaila, U.R., Walters, C.J., Watson, R., Zeller, D., 2002, Toward sustainability in world fisheries. Nature 428, 689-695. CrossRef
Pella J.J., 1967, A study of methods to estimate the Schaefer model parameters with special reference to the yellowfin tuna fishery in the eastern tropical Pacific ocean, Seattle. University of Washington.
Placenti V., Rizzo G., Spagnolo M., 1995, A Bio-Economic model for the Mediterranean Fisheries, Final report. Directorate General XIV Fisheries (MA-2.585), IREPA.
Polacheck, T., Hilborn, R., Punt, A.E., 1993, Fitting surplus production models: Comparing methods and measuring uncertainty. Can. J. Fish. Aquat. Sci. 50, 2597-2607. CrossRef
Sardá, F., 1993, Bio-ecological aspects of the decapod crustacean fisheries in the Western Mediterranean. Aquat. Living Resour. 6, 299-305. CrossRef
Sardá F., 2000, Analysis of the Mediterranean (including North Africa) deep-sea shrimp fishery: evolution, catches, efforts and economics. DG XIV/97/0018. Final report.
Sardá, F., Company, J.B., Maynou, F., 2003, Deep-sea Shrimp Aristeus antennatus Risso 1816 in the Catalan Sea, a review and perspectives. J. Northwest. Atl. Fish. Soc. 31, 127-136.
Schaefer, M.B., 1954, Some aspects of the dynamics of populations important to the management of commercial marine fisheries. Bull. IATTC. 1, 27-56.
Schaefer, M.B., 1957, A study of the dynamics of fishery for yellowfin tuna in the Eastern Tropical Pacific Ocean. Bull. IATTC. 2, 247-285.
Sparre P.J., 2001, Simulation model for evaluation of effort and catch quota management regimes using the methodology of ICES. , Charlottenlund. Danish Institute for Fisheries Research.
Sparre P.J., Willman R., 1993, Software for bio-economic analysis of fisheries. BEAM 4. Analytical Bio-economic Simulation of Space-structured Multispecies and Multi-fleet Fisheries. Vol. 1. Description of the model. Computerized information series (Fisheries).
Sumaila, U.R., 1997, Cooperative and non-cooperative exploitation of the Arcto-Norwegian cod stock. Environ. Res. Econ. 10, 147-165. CrossRef
Sumaila, U.R., 1998, Protected marine reserves as fisheries management tools: a bioeconomic analysis. Fish. Res. 37, 287-296. CrossRef
Sumaila, U.R., 1999, A review of game theoretic models of fishing. Mar. Policy 23, 1-10. CrossRef
Ulrich C., Le Gallic B., Dunn M.R., 1999, Bioeconomic modelling of English Channel fisheries and their technical interactions: presentation of the simulation model BECHAMEL (BioEconomic CHAnnel ModEL). ICES CM 199/S:04.
Ulrich, C., Gascuel, D., Dunn, M.R., Le Gallic, B., Dintheer, C., 2001, Estimation of technical interactions due to the competition for resource in a mixed-species fishery, and the typology of fleets and métiers in the English Channel, Aquat. Living Resour. 14, 267-281. CrossRef
Ulrich, C., Le Gallic, B., Dunn, M.R., Gascuel, D., 2002, A multi-species, multi-fleet bioeconomic simulation model for the English Channel artisanal fisheries. Fish. Res. 58, 379-401. CrossRef