Título

Using Observed Residual Error Structure Yields the Best Estimates of Individual Growth Parameters

Autor

Marcelo Vidal Curiel Bernal

EUGENIO ALBERTO ARAGON NORIEGA

MIGUEL ANGEL CISNEROS MATA

LAURA SANCHEZ VELASCO

SYLVIA PATRICIA ADELHEID JIMENEZ ROSENBERG

ALEJANDRO FRANCISCO PARES SIERRA

Nivel de Acceso

Acceso Abierto

Licencia

http://creativecommons.org/licenses/by-nc-nd/4.0

Referencia de publicación

doi: DOI: 10.3390/fishes6030035

ISSN/ISSN: 2410-3888

URL/URL: https://www.mdpi.com/2410-3888/6/3/35

Materias

multimodel inference, error structure, totoaba, growth performance - (AUTOR) BIOLOGÍA Y QUÍMICA - (CTI) CIENCIAS DE LA VIDA - (CTI) BIOLOGÍA ANIMAL (ZOOLOGÍA) - (CTI) FISIOLOGÍA ANIMAL - (CTI) FISIOLOGÍA ANIMAL - (CTI)

Resumen o descripción

"Obtaining the best possible estimates of individual growth parameters is essential in studies of physiology, fisheries management, and conservation of natural resources since growth is a key component of population dynamics. In the present work, we use data of an endangered fish species to demonstrate the importance of selecting the right data error structure when fitting growth models in multimodel inference. The totoaba (Totoaba macdonaldi) is a fish species endemic to the Gulf of California increasingly studied in recent times due to a perceived threat of extinction. Previous works estimated individual growth using the von Bertalanffy model assuming a constant variance of length-at-age. Here, we reanalyze the same data under five different variance assumptions to fit the von Bertalanffy and Gompertz models. We found consistent significant differences between the constant and nonconstant error structure scenarios and provide an example of the consequences using the growth performance index _0 to show how using the wrong error structure can produce growth parameter values that can lead to biased conclusions. Based on these results, for totoaba and other related species, we recommend using the observed error structure to obtain the individual growth parameters."

Editor

Multidisciplinary Digital Publishing Institute

Fecha de publicación

2021

Tipo de publicación

Artículo

Versión de la publicación

Versión publicada

Recurso de información

http://cibnor.repositorioinstitucional.mx/jspui/handle/1001/2470

Formato

application/pdf

Fuente

Fishes

Idioma

Inglés

Sugerencia de citación

Curiel-Bernal, M.V.; Aragón-Noriega, E.A.; Cisneros-Mata, M.Á.; Sánchez-Velasco, L.; Jiménez-Rosenberg, S.P.A.; Parés-Sierra, A. Using Observed Residual Error Structure Yields the Best Estimates of Individual Growth Parameters. Fishes 2021, 6, 35. https://doi.org/10.3390/fishes6030035

Repositorio Orígen

Repositorio Institucional CIBNOR

Descargas

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