A New Method of Estimating Gillnet Selectivity, with an Example for Spotted Seatrout, Cynocion nehulosus

Abstract

This study proposes a new method of estimating the selectivity of gill nets. Using data on the distribution of fish lengths from the catches of various meshes in an experimental gill net, a system of m equations and n unknown coefficients is simultaneously solved describing the functional relationship of the moments from an assumed mathematical model across mesh size and size-class of fish. The solution to the model is a response surface describing the probability of capture of fish of size-class j in mesh i. This new method is applied to spotted seatrout (Cynocion nehulosus) in coastal Louisiana and used to estimate the relative abundance of the various size-classes of fish in the population. We suggest that this approach for estimating gillnet selectivity has several advantages over other methods: it is very flexible in terms of choosing a mathematical model which would best represent the data; it takes full advantage of the empirical data allowing catch information, nij, to contribute to the final solution both as a function of mesh size and size-class; and it offers simplicity and elegance in its overall iterative least squares approach and is tractable in terms of assessing the reliability of the parameters and model used.