AN ALTERNATIVE METHODOLOGY FOR FITTING SELECTIVITY CURVES TO PREDEFINED DISTRIBUTIONS

A non-linear least-squares methodology for simultaneously estimating p arameters of selectivity curves with a pre-defined functional form, ac ross size classes and mesh sizes, using catch size frequency distribut ions, was developed based on the model of Kirkwood and Walker [Kirkwoo d, G.P., Walker, T.L, 1986. Gill net selectivities for gummy shark, Mu stelus antarcticus Gunther, taken in south-eastern Australian waters. Aust. J. Mar. Freshw. Res. 37, 689-697] and [Wulff, A., 1986. Mathemat ical model for selectivity of gill nets. Arch. Fish Wiss. 37, 101-106] . Observed catches of fish of size class I in mesh m are modeled as a function of the estimated numbers of fish of that size class in the po pulation and the corresponding selectivities. A comparison was made wi th the maximum likelihood methodology of [Kirkwood, G.P., Walker, T.I. , 1986. Gill net selectivities for gummy shark, Mustelus antarcticus G unther, taken in south-eastern Australian waters. Aust. J. Mar. Freshw . Res. 37, 689-697] and [Wulff, A., 1986. Mathematical model for selec tivity of gill nets. Arch. Fish Wiss; 37, 101-106], using simulated ca tch data with known selectivity curve parameters, and two published da ta sets. The estimated parameters and selectivity curves were generall y consistent for both methods, with smaller standard errors for parame ters estimated by non-linear least-squares. The proposed methodology i s a useful and accessible alternative which can be used to model selec tivity in situations where the parameters of a pre-defined model can b e assumed to be functions of gear size; facilitating statistical evalu ation of different models and of goodness of fit. (C) 1998 Elsevier Sc ience B.V.