Assessing stocks in data-poor African fisheries: a case study on the white grouper Epinephelus aeneus of Mauritania

Abstract

The lack of reliable stock assessment for numerous exploited stocks in West Africa often results from poor-quality data, high multi-specificity of captures, and the heterogeneity of exploitation methods. However, many signs of overexploitation exist, particularly for demersal resources, highlighting the urgent need for a more quantitative and comprehensive evaluation of these resources. This study aims to show how, in such a context of poor-quality data and high uncertainty, a multi-method approach for stock assessment can generate a consistent diagnosis of the condition of a resource. As a case study, several methods were combined to assess the stock status of the white grouper Epinephelus aeneus, a flagship species in West Africa that is exploited by industrial and small-scale fisheries in Mauritania. These were estimation of abundance indices using delta generalised linear models; a biomass production model using a pseudo-equilibrium method and including an environmental effect of upwelling intensity; a dynamic biomass production model fitted in a Bayesian framework also including an environmental effect; and an age-structured model based on a modified pseudo-cohort analysis. Sensitivity analyses were performed for most of these assessment methods. Results show that the white grouper stock is highly overexploited due to an excess in the fishing effort estimated at between 30% and 50%, depending on the model used to estimate the effort at maximum sustainable yield.

Keywords: age-structured model, Bayesian approaches, diagnosis, production model, stock assessment

African Journal of Marine Science 2013, 35(2): 253–267