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

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

Alberto A. Aragón-Noriega, Edgar Alcántara-Razo, Wenceslao Valenzuela-Quiñónez, Gerardo Rodríguez-Quiroz

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Translated title of the contributionMulti-model inference for growth parameter estimation of the Bigeye Croaker Micropogonias megalops in the Upper Gulf of California
Original languageEnglish
Pages (from-to)25-38
Number of pages14
JournalRevista de Biologia Marina y Oceanografia
Volume50
Issue number1
DOIs
StatePublished - 2015

Keywords

  • Akaike information theory
  • Growth
  • Micropogonias megalops
  • Multi-Model inference
  • Upper Gulf of California
  • Von Bertalanffy

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