MODELING GROWTH OF THE PACIFIC SARDINE SARDINOPS CAERULEUS IN THE GULF OF CALIFORNIA, MEXICO, USING THE MULTIMODEL INFERENCE APPROACH

To evaluate growth of the Pacific sardine in the Gulf of California, fish samples were collected from the commercial fleet during the 2010-11, 2011-12 and 2012-13 fishing seasons. Sardine samples were measured in standard length (SL) and age was determined based on counting opaque and hyaline growth increments in the otoliths. Four growth models were fitted to the age and length data: von Bertalanffy Growth Model (VBGM), Gompertz, Logistic, and Schnute, using a maximum likelihood algorithm. Confidence intervals of each parameter were calculated through likelihood profiles. The model that best explained the species growth kinetics was selected by Akaike information criteria and Akaike's weight (w(i)), while growth parameter covariance was obtained by the likelihood contour method. The sardines obtained from catches ranged in age from 0.5-6 years; sizes varied from 98-218 mm (SL). The growth model that obtained the greatest weight was VBGM (w(i) = 73.11%) whose estimated parameters and confidence intervals (CI) for the Pacific sardine were L-infinity= 201.28 (200.70-201.80) mm SL, K = 0.581 (SD: 0.577-0.586) and t(0) = -0.839 (SD: -0.855 - -0.824), showing a more accelerated growth rate of the species in the Gulf of California compared to the same species inhabiting the coasts of Baja California and California.