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RESEARCH ARTICLE

A simple approach for dealing with dynamics and uncertainty in fisheries with heterogeneous resource and effort distribution

J. C. Seijo A D , E. P. Pérez B and J. F. Caddy C
+ Author Affiliations
- Author Affiliations

A Universidad Marista de Mérida, Periférico Norte Tablaje 13941 Carretera Mérida-Progreso Mérida 97300, Yucatán, México.

B Universidad Católica del Norte, Facultad de Ciencias del Mar, Casilla 117, Coquimbo, Chile.

C T. W. Huxley School of Environment, Earth Sciences and Engineering, University of London, Senate House Malet Street, London WC1EHU, UK.

D Corresponding author. Email: jseijo@marista.edu.mx

Marine and Freshwater Research 55(3) 249-256 https://doi.org/10.1071/MF04040
Submitted: 24 February 2004  Accepted: 19 March 2004   Published: 19 May 2004

Abstract

Most fisheries models are based on dynamic pool assumptions. For sedentary and sessile species, these assumptions are inadequate, because they are spatially distributed in patches that vary in size, density and age structure. A simple bioeconomic model, negative binomial (NEGBIN), is proposed; this model relaxes the dynamic pool assumption without entering into the complexities of a geographically structured model. NEGBIN assumes a probability density function (the negative binomial), to describe heterogeneity in the density distribution over the population range. The model incorporates decision theory and different levels of risk aversion in resource management. The uncertainty associated with alternative fishing strategies, given imperfect knowledge about virgin stock biomass, is also included in the analysis. The model is applied to the Mesodesma donacium (surf clam) fishery in the central northern zone of Chile (South America). Alternative management strategies are evaluated with different levels of risk aversion. In the fisheries literature to date, this approach to evaluating the uncertainty associated with spatial allocation decisions has been rare. It is suggested that this kind of analysis, whether accompanied by quantitative probabilities of alternative states of nature or not, is an alternative way of dealing with risk and uncertainty in spatial allocation decisions.

Extra keywords: bioeconomic simulation, decision theory, risk, spatial allocation of effort, spatial heterogeneity, uncertainty.


Acknowledgment

We wish to express our gratitude to Miguel Angel Cabrera, Daniel Hernandez and Marian Hylkema for their useful comments on the first draft of this manuscript. We also thank Gabriel Novelo for his assistance in developing the figures.


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