Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

Lloyd-Jones, L.R., Wang, Y-G., & Nash, W.J. (2014) Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra). Ecological Modelling, 272, pp. 311-322.

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This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected

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ID Code: 90426
Item Type: Journal Article
Refereed: Yes
Additional Information: ISI Document Delivery No.: 275WW
Times Cited: 1
Cited Reference Count: 38
Lloyd-Jones, Luke R. Wang, You-Gan Nash, Warwick J.
Queensland Department of Agriculture; Fisheries and Forestry and the Australian Research Council for the scholarship
The authors would like to thank the Queensland Department of Agriculture, Fisheries and Forestry and the Australian Research Council for the scholarship that funded this research. We also thank the Tasmanian government, the Australian Fisheries Research and Development Corporation and the Tasmania abalone research team for supporting the original study. We also thank and acknowledge the anonymous reviewers who took the time to review our work and who helped to improve the document.
Elsevier science bv
Keywords: Aquatic species growth, von Bertalanffy model, Gompertz model, Maximum, likelihood method, Multiple tag-recapture data, Tagging effect, tag-recapture data, maximum-likelihood approach, von bertalanffy, seasonal growth, parameters, gompertz, mollusks, curves
DOI: 10.1016/j.ecolmodel.2013.10.012
ISSN: 0304-3800
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Elsevier B.V.
Deposited On: 17 Nov 2015 06:44
Last Modified: 14 Jan 2016 05:39

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