An improved method for estimating individual growth variability in fish, and the correlation between von Bertalanffy growth parameters

Pilling, Graham M. and Kirkwood, Geoffrey P. and Walker, Stephen G. (2002) An improved method for estimating individual growth variability in fish, and the correlation between von Bertalanffy growth parameters. Canadian Journal of Fisheries and Aquatic Sciences, 59 (3). pp. 424-432. ISSN 0706-652X. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1139/f02-022

Abstract

A new method for estimating individual variability in the von Bertalanffy growth parameters of fish species is presented. The method uses a nonlinear random effects model, which explicitly assumes that an individual's growth parameters represent samples from a multivariate population of growth parameters characteristic of a species or population. The method was applied to backcalculated length-at-age data from the tropical emperor, Lethrinus mahsena. Individual growth parameter variability estimates were compared with those derived using the current "standard" method, which characterizes the joint distribution of growth parameter estimates obtained by independently fitting a growth curve to each individual data set. Estimates of mean von Bertalanffy growth parameters from the two methods were similar. However, estimated growth parameter variances were much higher using the standard method. Using the random effects model, the estimated correlation between population mean values of L-infinity and K was -0.52 or -0.42, depending on the marginal distribution assumed for K. The latter estimate had a 95% posterior credibility interval of -0.62 to -0.17. These represent the first reliable estimate of this correlation and confirm the view that these parameters are negatively correlated in fish populations; however, the absolute correlation value is somewhat lower than has been assumed.

Item Type: Article
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 25 Oct 2008 17:24
Last Modified: 25 Jun 2014 10:54
Resource URI: http://kar.kent.ac.uk/id/eprint/10568 (The current URI for this page, for reference purposes)
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