Growth of Plagioscion squamosissimus (Perciformes: Sciaenidae) according to multiple model inference in of the mid Orinoco basin, Venezuela

 

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Autores: González, Angel, Márquez, Arístide
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
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OAI Identifier:oai:portal.ucr.ac.cr:article/38915
Acceso en línea:https://revistas.ucr.ac.cr/index.php/rbt/article/view/38915
Access Level:acceso abierto
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