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Improved estimation of size-transition matrices using tag-recapture data

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Lloyd-Jones, L. R., Nguyen, H. D., Wang, Y.-G. and O'Neill, M. F. (2014) Improved estimation of size-transition matrices using tag-recapture data. Canadian Journal of Fisheries and Aquatic Sciences . ISSN 0706-652X

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Article Link: http://dx.doi.org/10.1139/cjfas-2014-0080


We derive a new method for determining size-transition matrices (STMs) that eliminates probabilities of negative growth and accounts for individual variability. STMs are an important part of size-structured models, which are used in the stock assessment of aquatic species. The elements of STMs represent the probability of growth from one size class to another, given a time step. The growth increment over this time step can be modelled with a variety of methods, but when a population construct is assumed for the underlying growth model, the resulting STM may contain entries that predict negative growth. To solve this problem, we use a maximum likelihood method that incorporates individual variability in the asymptotic length, relative age at tagging, and measurement error to obtain von Bertalanffy growth model parameter estimates. The statistical moments for the future length given an individual’s previous length measurement and time at liberty are then derived. We moment match the true conditional distributions with skewed-normal distributions and use these to accurately estimate the elements of the STMs. The method is investigated with simulated tag–recapture data and tag–recapture data gathered from the Australian eastern king prawn (Melicertus plebejus).

Item Type:Article
Business groups:Animal Science
Subjects:Aquaculture and Fisheries > Fisheries > Fishery research
Science > Statistics > Mathematical statistics
Live Archive:19 Aug 2014 05:51
Last Modified:03 Sep 2021 16:49

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