Individual growth modeling of the penshell Atrina maura (Bivalvia: Pinnidae) using a multi model inference approach
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Autor: | |
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Formato: | artículo original |
Estado: | Versión publicada |
Fecha de Publicación: | 2013 |
Descripción: | Growth models of marine animals, for fisheries and/or aquaculture purposes, are based on the popular von Bertalanffy model. This tool is mostly used because its parameters are used to evaluate other fisheries models, such as yield per recruit; nevertheless, there are other alternatives (such as Gompertz, Logistic, Schnute) not yet used by fishery scientists, that may result useful depending on the studied species. The penshell Atrina maura, has been studied for fisheries or aquaculture supplies, but its individual growth has not yet been studied before. The aim of this study was to model the absolute growth of the penshell A. maura using length-age data. For this, five models were assessed to obtain growth parameters: von Bertalanffy, Gompertz, Logistic, Schnute case 1 and Schnute and Richards. The criterion used to select the best models was the Akaike information criterion, as well as the residual squared sum and R2 adjusted. To get the average asymptotic length, the multi model inference approach was used. According to Akaike information criteria, the Gompertz model better described the absolute growth of A. maura. Following the multi model inference approach the average asymptotic shell length was 218.9mm (IC 212.3-225.5) of shell length. I concluded that the use of the multi model approach and the Akaike information criteria represented the most robust method for growth parameter estimation of A. maura and the von Bertalanffy growth model should not be selected a priori as the true model to obtain the absolute growth in bivalve mollusks like in the studied species in this paper. |
País: | Portal de Revistas UCR |
Institución: | Universidad de Costa Rica |
Repositorio: | Portal de Revistas UCR |
Lenguaje: | Español |
OAI Identifier: | oai:portal.ucr.ac.cr:article/11911 |
Acceso en línea: | https://revistas.ucr.ac.cr/index.php/rbt/article/view/11911 |
Palabra clave: | multi model inference akaike information criteria atrina maura growth models inferencia multi modelo criterio de información de akaike modelos de crecimiento |