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Title: Bayesian modeling of individual growth variability using back-calculation: Application to pink cusk-eel Authors:  Freddy Omar Lopez Quintero - Telefónica-UTFSM-UV-PUCV (Chile) [presenting]
Abstract: The von Bertalanffy growth function with random effects has been widely used to estimate growth parameters incorporating individual variability of length at age. Inferred trajectories of individual growth can be assessed from growth marks in hard body parts such as otoliths using either mark-recapture or back-calculation of length-at-age. 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 ({\it 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 skew distribution of errors from the Student-$t$ model.