Annual data analysis finds optimal models for spawning stock-recruitment relationships, guiding fishery management.
Determining the relationship between spawning stock biomass and recruitment (SS-R) in exploited populations is one of the most important biological and ecological aspects for sustainable management. It requires identification of optimal models that qualitatively and quantitatively represents this relationship for specific stocks. In the present study, annual SS-R abundance data (1995–2020) for Bigeye croaker Micropogonias megalops in the Gulf of California were analyzed using a multi-model approach. Time series of different lengths were used for model fitting to examine how time series lengths influenced SS-R estimation. The tested models were: Beverton-Holt, Ricker, Cushing and Shepherd, which have structural differences and are frequently used in fisheries science. Results showed that there is no single ‘best’ model to describe the SS-R relationship of the species. However, there were models with relative higher descriptive power such as the Cushing and Shepherd density-dependent models according to the Akaike Information Criterion; the difference between models was more evident for longer time series (18 to 26 yr). Mean recruitment was similar for all models in each time series, ranging from 57.76 to 58.23 million individuals in the full 1995–2020 series. Recruitment was variable with a positive trend over time, showing lowest levels in 2002 and highest in 2010 and 2015. Estimates of the steepness parameter ranged from h = 0.25 to 0.29. The multi-model approach helped to better understand the SS-R relationship of M. megalops, which can be considered for subsequent fishery assessments and management decisions.
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Arzola-Sotelo et al. (2025) studied this question.
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