Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-20T13:33:31.001Z Has data issue: false hasContentIssue false
  • English
  • Français

The effect of restrictive policy instruments on Belgian fishing fleet dynamics

Published online by Cambridge University Press:  09 October 2008

Hendrik Stouten ,
Aimé Heene ,
Xavier Gellynck  and
Hans Polet
Hendrik Stouten
Affiliation:
Institute for Agriculture and Fisheries Research (ILVO)/Faculty of Economics and Business Administration, Ghent University Ankerstraat 1, 8400 Ostend, Belgium
Aimé Heene
Affiliation:
Department Management and Organization, Faculty of Economics and Business Administration, Ghent University Tweekerkentstraat 2, 9000 Ghent, Belgium
Xavier Gellynck
Affiliation:
Department of Agricultural Economics, Faculty of Bio-Science Engineering, Ghent University Coupure Links 653, 9000 Ghent, Belgium
Hans Polet
Affiliation:
Institute for Agriculture and Fisheries Research (ILVO) Ankerstraat 1, 8400 Ostend, Belgium
Get access

Abstract

Even with the rapid changes in the level of complexity and the uncertainty of the environment in which Belgian sea fisheries operate, fisheries management in Belgium is still mainly based on restrictive policy instruments founded in the biological approach of fisheries management science. Since they will continue to play an important role, this paper evaluated changes in three restrictive policy instruments and their effect on future fleet performance and dynamics, i.e. maximum fishing days, total quota-restrictions and licences. These effects are tested through scenarios in a microeconomic simulation model, including sensitivity analysis. This study opts for a dynamic simulation model based on a microeconomic approach of fleet dynamics using system dynamics as a modelling technique (operational base: Vensim®DSS). The results indicated that changes in maximum fishing days and total quota resulted in higher fluctuations in fleet performance and dynamics compared to changes in licences. Furthermore, changes in maximum fishing days and total quota had a direct impact on fleet performance, though not always as expected, whereas licences only affected fleet performance indirectly since they only limit the entry of new vessels to the fleet and they can block the growth of successful sub fleets. The outcomes of this study are translated into practical recommendations for improving fisheries management. Firstly, policy makers need to be more aware of misperceptions of feedback. Secondly, the results proved that altering only one type of restrictive policy instrument at a time often fails to meet desired outcomes. Therefore, policy makers need to find a balance in combining policy instruments. Finally, this paper opens the discussion on the future value of restrictive policy instruments in the rapidly changing, complex and uncertain fisheries environment. It suggests rethinking their use from “preserving a status quo and social peace” toward a driving factor in “stimulating fleet dynamics”.

Keywords

Fisheries managementRestrictive policy instrumentsSensitivity simulationSystem dynamicsFleet performanceFleet dynamics
Type
Research Article
Information
Aquatic Living Resources , Volume 21 , Issue 3: Special Issue (Advances in Fisheries Analysis and Modelling – Reversible and Irreversible Changes in Fish Resources and their usage) , July 2008 , pp. 247 - 258
Copyright
© EDP Sciences, IFREMER, IRD, 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, L.G., 1987, Expansion of the fisheries management paradigm to include institutional structure and function. Trans. Am. Fish. Soc. 116, 396–404. 2.0.CO;2>CrossRef
Anderson, L.G., 1985, Potential economic benefits from gear restrictions and licence limitation in fisheries regulation. Land Econ. 61, 409–419. CrossRef
Barber, W.E., 1988, Maximum sustainable yield lives on. North Am. J. Fish. Manage. 8, 153–157. 2.3.CO;2>CrossRef
Boude, J., Boncoeur, J., Bailly, D., 2001, Regulating the access to fisheries: learning from European experiences. Mar. Policy 25, 313–322. CrossRef
Charles, A.T., 1998, Living with uncertainty in fisheries: analytical methods, management priorities and the Canadian ground fishery experience. Fish. Res. 37, 37–50. CrossRef
Cochrane, K.L., 1999, Complexity in fisheries and limitations in the increasing complexity of fisheries management. ICES J. Mar. Sci. 56, 917–926. CrossRef
Crutchfield, J.A., 1956, Common property resources and factor allocation. Can. J. Econ. Polit. Sci. 22, 292–300. CrossRef
Crutchfield J., 1959, Biological and economic aspects of fishery management. Seattle, University of Washington Press.
Diehl, E., Sterman, J.D., 1995, Effects of feedback complexity on dynamic decision making. Organ. Behav. Hum. Decis. Process. 62, 198–215. CrossRef
Dudley R.G., 2003, A Basis for understanding fishery management complexities. In: Proc. International System Dynamics Conference, July 20-24, New York City.
Dudley R.G., 2006, Fisheries decision making and management failure: better answers require better questions. http://www.people.cornell.edu/pages/rgd6/PDF/fishlups.pdf.
Gordon, H., 1953, An economic approach to the optimum utilisation of fishery resources. J. Fish. Res. Board Can. 10, 442–457. CrossRef
Gordon, H., 1954, The economic theory of the common property resource: the fishery. J. Polit. Econ. 62, 124–142. CrossRef
Graham, M., 1935, Modern theory of exploiting a fishery, and application to North Sea trawling. ICES J. Mar. Sci. 10, 264–274. CrossRef
Healey, M.C., Hennessey, T., 1998, The paradox of fairness: The impact of escalating complexity on fishery management. Mar. Policy 22, 109–118. CrossRef
Lane, D.E., Stephenson, R.L., 1999, Fisheries-management science: a framework for the implementation of fisheries-management systems. ICES J. Mar. Sci. 56, 1059–1066. CrossRef
Larkin, P.A., 1996, Concepts and issues in marine ecosystem management. Rev. Fish. Biol. Fish. 6, 139–164. CrossRef
Mathiesen C., 2003, Analytical framework for studying fishers' behaviour and adaptation strategies. In: Proc. 8th Conference of the Circumpolar Arctic Social Sciences Ph.D. Network, August, 2003.
Moxnes, E., 1998a, Not only the tragedy of the commons: misperceptions of bioeconomics. Manage. Sci. 44, 1234–1248. CrossRef
Moxnes, E., 1998b, Overexploitation of renewable resources: The role of misperceptions. J. Econ. Behav. Organ. 37, 107–127. CrossRef
Moxnes E., 1999, Near-to-optimal harvesting strategies for a stochastic multicohort fishery. Report No. 56, Bergen, Centre for Fisheries Economics.
Moxnes, E., 2003, Uncertain measurements of renewable resources: approximations, harvesting policies and value of accuracy. J. Environ. Econ. Manage. 45, 85–108. CrossRef
Opaluch, J., Bockstael, N.E., 1984, Behavioral modeling and fisheries management. Mar. Resour. Econ. 1, 105–115. CrossRef
Polet H., Depestele J., Stouten H., Vanderperren E., 2006, Moving from beam trawls towards multi-rig otter trawls – and further... In: Proc. Conference on energy efficiency in fisheries, 11-12 May, Brussels.
Ruseski, G., 1998, International fish wars: the strategic roles for fleet licensing and effort subsidies. J. Environ. Econ. Manage. 36, 70–88. CrossRef
Russell, E.S., 1931, Some theoretical considerations on the “over-fishing” problem. ICES J. Mar. Sci. 6, 3–20. CrossRef
Salz P., 2006, Economic performance of EU fishing fleets and consequences of fuel price increase. In: Proc. Conference on energy efficiency in fisheries, 11–12 May, Brussels.
Scott, A., 1955, The fishery: the objectives of sole ownership. J. Polit. Econ. 63, 116–124. CrossRef
Senge P., 1990, The fifth discipline: the art of practice of the learning organization. London, Century business.
Sterman, J.D., 1989, Modeling managerial behavior: misperceptions of feedback in a dynamic decision making experiment. Manage. Sci. 35, 321–339. CrossRef
Stouten, H., Van Craeynest, K., Heene, A., Gellynck, X., Polet, H., 2007, The effect of fuel price scenarios on Belgian fishing fleet dynamics. In: Proc. 2007 ICES Annual Science Conference, Sept 17-21, Marina Congress Center, Helsinki, Finland.
Walters C.J., 1980, Systems principles in fisheries management. In: Fisheries management Science, New York, Wiley.