IIMYC   23581
INSTITUTO DE INVESTIGACIONES MARINAS Y COSTERAS
Unidad Ejecutora - UE
artículos
Título:
Evaluating the role of endogenous and exogenous features on larval hake nutritional condition
Autor/es:
DO SOUTO, MARINA; SCHIARITI, AGUSTÍN; MACCHI, GUSTAVO J.; DIAZ, MARINA V.; TEMPERONI, BRENDA; BROWN, DANIEL R.; BETTI, PAOLA; MACHINANDIARENA, LAURA
Revista:
FISHERIES OCEANOGRAPHY
Editorial:
WILEY-BLACKWELL PUBLISHING, INC
Referencias:
Lugar: Londres; Año: 2020 vol. 29 p. 584 - 596
ISSN:
1054-6006
Resumen:
Evaluating the nutritional condition of fish larvae is imperative to establish the importance of starvation, understanding the causes of larval mortality and determining favorable zones for growth and survival within nursery areas. We assessed the nutritional condition of Merluccius hubbsi larvae employing RNA/DNA index (sRD) and its derived index of growth performance (Gpf). Larvae (N=395) were collected during the reproductive peak in 2010 and 2011. Principal Component Analysis and Generalized Linear Models were used to study the relationship between larval condition and endogenous factors (size, weight, growth rate, trophic incidence and carbon content per stomach) and exogenous variables (temperature, chlorophyll concentration, potential prey availability, ctenophore biomass, and hake larvae density). The year of sampling was also considered as a variable. The significant variables in the model selection were size, temperature, the density of hake larvae, and year. The larval size was positively related to the condition while larval density and temperature showed a negative relationship with the sRD index. The year was also a significant variable, with higher larval sRD values in 2010. The negative relationship between sRD and larval density suggests the existence of mechanisms of density‐dependence operating upon larval condition. On the other hand, the lower temperatures occurred in stratified waters (with greater availability of food) a fact that might explain the negative relationship between sRD and temperature. The fitting of the models suggests that other explanatory variables might be considered to improve the understanding of the nutritional condition index nature.