Individual Growth Parameterization Models Using the Observed Variance in Organisms Subject to Aquaculture

Parameterizing nonlinear models presents an ongoing challenge in fisheries and aquaculture research. While additive and multiplicative error structures have been traditionally applied, a more recent alternative—the observed error structure—is gaining increasing acceptance. This study aimed to analyze the variability of individual growth during the early developmental stages of totoaba (Totoaba macdonaldi), shrimp (Penaeus vannamei), and pearl oyster (Pteria sterna). The observed variance was incorporated as a central component for parameterizing individual growth models. All three datasets were derived from controlled laboratory conditions. Information theory was applied to identify the most appropriate variance criterion (observed, additive, or multiplicative). The Schnute model, case 1, was utilized to estimate the growth curve for each species. Distinct growth patterns were observed: sigmoid in totoaba, rectilinear in shrimp, and exponential in pearl oyster. These findings indicate that incorporating observed variability at each age enhances the parameterization of individual growth models across diverse taxonomic groups, including fish, crustaceans, and mollusks.