Growth of Plagioscion squamosissimus (Perciformes: Sciaenidae) according to multiple model inference in of the mid Orinoco basin, Venezuela
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| Autores: | , |
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| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2020 |
| Descripción: | Introduction: The prior use of von Bertalanffy's model has been generally used in the study of fish growth, without considering the existence of other growth models that can produce a better adjustment of the data used; considering the use of multiple growth models as a better alternative, to select the one that produces a better adjustment. Objective: Due to uncertainty of the results obtained in a previous work on the growth of Plagioscion squamosissimus (Heckel 1840) in the middle Orinoco region in Venezuela, applying a priori the model of von Bertalanffy, the same data were adjusted to other models of growth to select the best adjustment. Methods: The models evaluated were the U-von Bertalanffy, the U-Logistics and the U-Gompertz, derived from the global U-Richards model, then the best adjustment was selected using the Akaike Information Criteria (AIC). Results: Contradicting the prior use of von Bertalanffy's model in the previous study, the model that actually produces a better adjustment of the data used was the U-Gompertz. Conclusions: It is necessary to evaluate the stock of P. squamosissimus in the middle Orinoco region using growth parameters estimated from an inference of multiple models, in order to validate the existing information of a moderately exploited resource. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español Inglés |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/38915 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/rbt/article/view/38915 |
| Palabra clave: | river fish Plagioscion squamosissimus Middle Orinoco population dynamicss growth information theory peces de río Orinoco medio din´´amica de poblaciones crecimiento teoría de la información |