Model uncertainty and Bayesian estimation of growth parameters of Yellowtail Snapper (Ocyurus chrysurus) from Veracruz, Mexico

Authors

  • Jesús Jurado Molina Departamento de El Hombre y su Ambiente, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Unidad Xochimilco. Calzada del Hueso 1100, Col. Villa Quietud, Coyoacán, Ciudad de México, 04960. México
  • Osvaldo Gutiérrez Benitez Posgrado de Ecología y Pesquerías, Universidad Veracruzana. Calle Independencia 30 (antes 38), Piso 1 y 2 Colonia Centro, Boca del Río, Veracruz, 94290. México
  • Alejandro Roldan Heredia Posgrado de Ecología y Pesquerías, Universidad Veracruzana. Calle Independencia 30 (antes 38), Piso 1 y 2 Colonia Centro, Boca del Río, Veracruz, 94290. México

DOI:

https://doi.org/10.24275/uam/izt/dcbs/hidro/2018v28n2/Jurado

Keywords:

Bayesian estimation, growth, likelihood, Ocyurus chrysurus, Veracruz

Abstract

Background. Most growth analyses of Yellowtail Snapper neglect consideration of model and parameter uncertainty. Goals. In this paper, we explore model uncertainty using three models (von Bertalanffy, logistic, and Gompertz) as well as the Akaike criterion for model selection. We also estimate growth parameters and its uncertainty using the maximum likelihood estimation approach (under different assumptions of error variance) and Bayesian methods. Methods. Models were fitted to length-at-age data from organisms caught in Antón Lizardo, Veracruz. Regarding the Bayesian methods, a prior distribution for the asymptotic length was built based on data gathered from literature. We used Monte Carlo Markov Chains (MCMC) methods to fit the logistic model. Results. The Akaike criterion results suggest that the logistic model provided the best fit for the observed data (lowest AIC = 31.4). Parameter estimates included asymptotic length (L? = 64.9 ± 5.43), growth rate (K = 0.49 ± 0.07), and age at the curve inflection point (I = 3.28 ± 0.42). Regarding the Bayesian analysis, MCMC simulations suggest that the most probable value for the asymptotic length was 64.3 cm with an interval of 95% probability (58.7,70.1). The most probable value for the growth rate was 0.48 with an interval of 95% probability (0.42, 0.55). Last, the most probable value for the age at the curve inflection point was 1.7 years with a range of 95% probability (1.31, 2.16). Conclusions. The maximum likelihood estimation (MLE) and the Bayesian framework should be considered basic statistical techniques in the evaluation of individual growth of the species of interest, as they provide a robust analysis of available information of the species and the opportunity to incorporate such analysis to sustainable management practices.

 

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Author Biographies

Jesús Jurado Molina, Departamento de El Hombre y su Ambiente, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Unidad Xochimilco. Calzada del Hueso 1100, Col. Villa Quietud, Coyoacán, Ciudad de México, 04960. México

Profesor-Investigador, Departamento del Hombre y su Ambiente

Osvaldo Gutiérrez Benitez, Posgrado de Ecología y Pesquerías, Universidad Veracruzana. Calle Independencia 30 (antes 38), Piso 1 y 2 Colonia Centro, Boca del Río, Veracruz, 94290. México

Estudiante de doctorado, Posgrado de Ecología y Pesquerías

Alejandro Roldan Heredia, Posgrado de Ecología y Pesquerías, Universidad Veracruzana. Calle Independencia 30 (antes 38), Piso 1 y 2 Colonia Centro, Boca del Río, Veracruz, 94290. México

Estidiante de Posgrado, Posgrado de Ecología y Pesqurías

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Published

2018-08-31

How to Cite

Jurado Molina, J., Gutiérrez Benitez, O., & Roldan Heredia, A. (2018). Model uncertainty and Bayesian estimation of growth parameters of Yellowtail Snapper (Ocyurus chrysurus) from Veracruz, Mexico. HIDROBIOLÓGICA, 28(2). https://doi.org/10.24275/uam/izt/dcbs/hidro/2018v28n2/Jurado

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