Bayesian modeling of individual growth variability using back-calculation: Application to pink cusk-eel (Genypterus blacodes) off Chile
| Autor: | Rodrigo Wiff, Javier E. Contreras-Reyes, Freddy Omar López Quintero |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
biology 010604 marine biology & hydrobiology Ecological Modeling Gaussian Bayesian probability Information Criteria Genypterus blacodes Random effects model Bayesian inference biology.organism_classification 010603 evolutionary biology 01 natural sciences symbols.namesake Bayes' theorem Student's t-distribution Statistics symbols Mathematics |
| Zdroj: | Ecological Modelling. 385:145-153 |
| ISSN: | 0304-3800 |
| DOI: | 10.1016/j.ecolmodel.2018.07.002 |
| Popis: | The von Bertalanffy growth function (VBGF) with random effects has been widely used to estimate growth parameters incorporating individual variability of length-at-age. Trajectories of individual growth can be inferred using either mark-recapture or back-calculation of length-at-age from growth marks in hard body parts such as otoliths. Modern statistical methods evaluate individual variation usually from mark-recapture data, and the parameters describing this function are estimated using empirical Bayes methods assuming Gaussian error. In this paper, we combine recent studies in non-Gaussian distributions and a Bayesian approach to model growth variability using back-calculated data in harvested fish populations. We presumed that errors in the VBGF can be assumed as a Student-t distribution, given the abundance of individuals with extreme length values. The proposed method was applied and compared to the standard methods using back-calculated length-at-age data for pink cusk-eel (Genypterus blacodes) off Chile. Considering several information criteria, and comparing males and females, we have found that males grow significantly faster than females, and that length-at-age for both sexes exhibits extreme length observations. Comparisons indicated that a Student-t model with mixed effects describes best back-calculated data regarding pink cusk-eel. This framework merged the strengths of different approaches to estimate growth parameters in harvested fish populations, considering modeling of individual variability of length-at-age, Bayesian inference, and distribution of errors from the Student-t model. |
| Databáze: | OpenAIRE |
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