Performance of methods for estimating size–transition matrices using tag–recapture data
André E. Punt A B F , Rik C. Buckworth C , Catherine M. Dichmont D and Yimin Ye D EA CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tas. 7001, Australia.
B School of Aquatic and Fishery Sciences, Box 355020, University of Washington, Seattle, WA 98195-5020, USA.
C Fisheries, Department of Regional Development, Fisheries and Resources, GPO Box 3000, Darwin, NT 0810, Australia.
D CSIRO Marine and Atmospheric Research, PO Box 120, Cleveland, Qld 4163, Australia.
E Current address: Fishery Management & Conservation Service, FAO of the United Nations, Viale delle Termi diCaracalla, 00153, Rome, Italy.
F Corresponding author. Email: andre.punt@csiro.au
Marine and Freshwater Research 60(2) 168-182 https://doi.org/10.1071/MF08217
Submitted: 25 July 2008 Accepted: 25 October 2008 Published: 20 February 2009
Abstract
Management advice for hard-to-age species such as prawns, crabs and rock lobsters are usually based on size-structured population dynamics models. These models require a size–transition matrix that specifies the probabilities of growing from one size-class to the others. Many methods exist to estimate size–transition matrices using tag–recapture data. However, they have not been compared in a systematic way. Eight of these methods are compared using Monte Carlo simulations parameterised using the data for the tiger prawn (Penaeus semisulcatus). Four of the methods are then applied to tag–recapture data for three prawn species in Australia’s Northern Prawn Fishery to highlight the considerable sensitivity of model outputs to the method for estimating the size–transition matrix. The simulations show that not all methods perform equally well and that some methods are extremely poor. The ‘best’ methods, as identified in the simulations, are those that allow for individual variability in the parameters of the growth curve as well as the age-at-release. A method that assumes that l∞ rather than k varies among individuals tends to be more robust to violations of model assumptions.
Additional keywords: Australia, prawns, size-structured models, tagging data.
Acknowledgements
This work was supported by FRDC project 2004/022 and CSIRO Marine and Atmospheric Research. Bill Venables, Nick Ellis and Shijie Zhou (CSIRO Marine and Atmospheric Research), Richard McGarvey (SARDI), Malcolm Haddon (TAFI), and an anonymous reviewer are thanked for their comments on an earlier version of this paper.
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