Rev. biol. mar. oceanogr. 50(1): 25-38


Multi-model inference for growth parameter estimation of the Bigeye Croaker Micropogonias megalops in the Upper Gulf of California

E. Alberto Aragón-Noriega1, Edgar Alcántara-Razo1, Wenceslao Valenzuela-Quiñónez2 and Gerardo Rodríguez-Quiroz2

1Centro de Investigaciones Biológicas del Noroeste, Unidad Sonora, Km 2.35 Camino al Tular, Estero Bacochibampo, Guaymas, Sonora 85454, México
2Departamento de Acuacultura, Instituto Politécnico Nacional-CIIDIR, Unidad Sinaloa, Boulevard Juan de Dios Bátiz Paredes # 250, Guasave, Sinaloa 81101, México

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Bigeye Croaker (Micropogonias megalops) is caught in the Upper Gulf of California (UGC) by local community fishermen from San Felipe in Baja California, Golfo de Santa Clara and Puerto Peñasco in Sonora, Mexico. For the sustainable management of this fishery, it is necessary to understand its growth cycle. We modeled the individual growth of M. megalops from the UGC using 4 growth models: von Bertalanffy growth model (VBGM), Logistic, Gompertz and Schnute. The parameters of each model and their confidence intervals (CI) were computed using the maximum-likelihood method. The best-fit model was selected using Akaike´s information criterion (AIC). According to AIC, the VBGM model fit best the data. The parameter estimated and CI were: 1) mean asymptotic length (L¥) in males 429 mm total length TL (CI 426-432 mm TL) and in females 461 mm TL (CI 457-464 mm TL); 2) the growth coefficient (k) in males 0.419 (CI 0.412-0.426) and in females 0.377 (CI 0.370-0.384). In conclusion, the VBGM adequately described the individual mean growth for M. megalops in the UGC.

Key words:  Growth, Multi-Model inference, Akaike information theory, Upper Gulf of California, Micropogonias megalops, von Bertalanffy