Multi-criteria decision models for management of tropical coastal fisheries. A review
Institute of Fisheries Policy and Development Studies, College of
Fisheries and Ocean Sciences, University of the Philippines Visayas,
* Corresponding author:
Accepted: 19 October 2009
The crisis in the world’s fisheries is attributed to excessive fishing pressure, long-term mismanagement, increased population growth, development and improvement of fishing technologies, uncertainty in global fisheries catch data, economic incentives and subsidies, and increasing demand for fish meal. For the coastal fisheries of developing countries, the problem is aggravated by coastal habitat degradation, widespread poverty in coastal communities, inshore encroachment of commercial fishing vessels, use of illegal and destructive fishing methods, resource use conflicts, pollution from uplands, and weak institutional arrangements. In response to these problems and in the hope of reversing their negative effects, fisheries management strategies have emerged for tropical coastal fisheries during at least the past 30 years. In fisheries, it is crucial to determine the outcomes of management strategies, especially when public money has to be accounted for. However, efforts to assess their impacts or measure progress are usually directed towards a single disciplinary approach, which fails to consider the multi-dimensionality of tropical fisheries including concomitant multi-level and conflicting goals and objectives. This article explores the utility of a multi-criteria type of evaluation as a potential analytical approach in impact evaluation for tropical fisheries management. The general framework of a multi-criteria evaluation method is a two-dimensional matrix composed of different choice possibilities including the set of criteria and indicators that will serve as bases in assessing these choice possibilities. The literature presents various criteria and indicators in fisheries management evaluation, the kinds and number of which would depend on stated goals and objectives of fisheries and the availability of resources to acquire the information. The type of measurement, i.e., quantitative or qualitative, and the weighing of criteria and indicators are crucial in the evaluation process because they determine the multi-criteria aggregation approach to be used. Moreover, the participation of stakeholders and coastal resource users is crucial in complementing scientific information, in developing acceptable solutions, and in reducing conflicts and distrust in the evaluation and decision-making process. While many aggregation models in multi-criteria analysis in natural resource management exist, this article limits its review to only six models: the analytic hierarchy process, the weighted sum model, the ordination technique, concordance analysis, the regime method and Evamix; which are viewed to be applicable to the structure of decision-making in tropical fisheries management. This article also examines the performance of some of these models through a case study that determines the impacts of fisheries management strategies in San Miguel Bay, Philippines. The review reveals the following: (1) among the aggregation approaches, the analytic hierarchy process and ordination technique had the highest number of applications in fisheries while none was found for concordance analysis, the regime method or Evamix; (2) the application of hybrid models in multi-criteria analysis is increasing and found to be effective in many environmental decision problems including fisheries; (3) the application of multi-criteria decision models to fisheries management is relatively scarce during the last 10 years; only 26 papers were found in peer-reviewed journals; and (4) in the choice of model, its technical assumptions and limitations, its appropriateness for a specific decision-making problem, and its ability to handle the situation correctly vis-à-vis contextual, technical and political concerns should be considered.
Key words: multi-criteria decision models / fisheries management / impact evaluation / indicators / criteria / preference system / San Miguel Bay
© INRA, EDP Sciences, 2010