A Comparison of von Bertalanffy and Polynomial Functions in Modelling Fish Growth Data

Abstract

We compared the von Bertalanffy growth function (VBGF) and five polynomial functions (PF) in modelling fish growth for 16 populations comprising six species of freshwater fishes. Ranked results of the variance explained by each growth function indicated that VBGF described growth data better than three- and four-parameter polynomial functions. Log-transforming length and age greatly improved the goodness-of-fit of the three-parameter polynomial function. Statistical comparison of growth between populations or sexes was done using a general linear model for polynomial functions. An analysis of residual sum of squares was proposed to compare the resultant VBGFs because the nonlinear formulation of the VBGF prevented traditional analysis of covariance procedures. Fitting of different growth functions to the same growth data set yielded the same result in the intra-species growth comparisons for three species (eight populations) but different results for two species (seven populations). Where ages of the fish were less than the maximum age in the samples, dL/dt were similar for all growth functions except the parabola based on the log-transformation of length alone. The VBGF proved to be the best growth model for all 16 populations.