Estimating relative abundance from catch and effort data, using neural networks

We develop and test a method to estimate relative abundance from catch and effort data using neural networks. Most stock assessment models use time series of relative abundance as their major source of information on abundance levels. These time series of relative abundance are frequently derived from catch-per-unit-of-effort (CPUE) data, using general linearized models (GLMs). GLMs are used to attempt to remove variation in CPUE that is not related to the abundance of the population. However, GLMs are restricted in the types of relationships between the CPUE and the explanatory variables. An alternative approach is to use structural models based on scientific understanding to develop complex non-linear relationships between CPUE and the explanatory variables. Unfortunately, the scientific understanding required to develop these models may not be available. In contrast to structural models, neural networks uses the data to estimate the structure of the non-linear relationship between CPUE and the explanatory variables. Therefore neural networks may provide a better alternative when the structure of the relationship is uncertain. We use simulated data based on a habitat based-method to test the neural network approach and to compare it to the GLM approach. Cross validation and simulation tests show that the neural network performed better than nominal effort and the GLM approach. However, the improvement over GLMs is not substantial. We applied the neural network model to CPUE data for bigeye tuna (Thunnus obesus) in the Pacific Ocean.

Choix d'une unité d'effort de pêche pour les flottilles sardinières sémi-industrielles et artisanales au Sénégal

Different catches per unit of effort available for industrial and artisanal sardinella fisheries of Senegal have been analysed and compared in order to determine whether they are acceptable indices of abundance. Among the four units of fishing effort studied (total number of sets, number of trips, time spent on fishing ground, searching time), the first and the second seem inadequate in the studied fleets. The two other units, particularly the searching time, allow the calculation of catches per unit of effort which best reflect variations in abundance, although they are not completely free of usual deficiencies.