Invited Review
Operational research models and the management of fisheries and aquaculture: A review

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Abstract

This paper reviews the role that the operational research (OR) discipline has played in the understanding and management of renewable resources in the areas of fisheries and aquaculture. The analysis is undertaken with two purposes. First, to assess the past performance of the OR models in this field. Second, to highlight current problems and future directions of research.

Introduction

The understanding and management of fisheries and aquaculture is a very complex problem. This complexity is mainly due to the issue of the required sustainability of the underlying natural system. In fact, when we talk about renewable resources, sustainability implies imposing constraints on the model to secure that the harvest rate of the resource does not surpass its natural regenerative capacity. It is clear that the accommodation of such constraints requires the use of suitable operational research (OR) methods.

After more than 40 years of applications of OR models to the management of fisheries, it seems sensible to review the most successful cases in order to evaluate the past performance as well as to highlight current problems and future directions of research. The paper aims to give the reader a clear idea of which are the important issues in fisheries and aquaculture, what has been accomplished in research and applications, and what are current and future research areas.

Applications of operations research to fisheries and aquaculture have been developed extensively in the last decades. Initial efforts were dedicated towards promoting stock conservation in the case of severely overexploited species. OR has since explored diverse issues in fisheries management, both at a national and international level. In doing so, bioeconomic models integrating biological growth of stock and industry behaviour have played a crucial role. Similarly, OR in aquaculture has combined modelling experiences from fisheries and other disciplines like agriculture and forestry to improve efficiency and economic gain at the farm and industry level.

In Section 2 applications of OR to capture fisheries are explored. Influential contributions to biological and in particular economic modelling are described. Economic modelling of capture fisheries is further divided into descriptive mathematical modelling, mathematical programming and optimisation, statistical analysis and estimation procedure, computer simulation, and decision theory. Section 3 gives an extensive overview of applications of operations research to aquaculture. The section distinguishes between biological and economic modelling, and the economic models are further categorised according to their approach or technique.

Section snippets

Applications in fisheries

The fundamental problem of fisheries management is twofold as it has to take into account both the conservation of the resource base, as well as the exploitation of the resource by the harvesting/processing sector. Larkin (1988) makes the distinction between biological constraints and social objectives as he claims that the approach to fisheries problem solving must be anthropocentric, i.e., based on social welfare. For stock exploitation this requires a multidisciplinary definition of the

Application to aquaculture

Work in related fields such as agriculture and fisheries management has influenced the development of modelling applications to aquaculture. Conceptually, aquaculture is more related to forestry or animal husbandry than to capture fisheries. OR in aquaculture integrates a biological model of growth of the species as a function of body weight, water temperature, feed etc., and an economic model linking the biological production process to the market through input and output prices and resource

Concluding remarks

Management of renewable natural resources is one of the first fields of successful applications of different OR models. It seems sensible to conjecture that the impressive past performance of OR models in this field will keep its pace in the near future. In fact, the emergence of global, competitive markets has increased the need to derive efficient production processes, to reduce investment and operational costs, and to increase productivity. Consequently, better management practices will play

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