La pesca de sardina, Sardinella aurita (Teleostei: Clupeidae) asociada con la variabilidad ambiental del ecosistema de surgencia costera de Nueva Esparta, Venezuela / Association of sardine fishery, Sardinella aurita (Teleostei: Clupeidae) and environmental variability of the coastal upwelling ecosystem of Nueva Esparta, Venezuela

The present research is an analysis of Spanish sardine fishing (Sardinella aurita) associated with some climatic and meteorologic parameters of the ecosystem from El Morro Nueva Esparta, Venezuela. The catch and environmental data from the area were taken in the period 1996-2000. Catch data as a function of wind speed, sea surface temperature, air temperature and rain were analyzed by means of simple lineal regression and multiple models. We found a positive correlation of catch with wind speed, and a negative correlation with sea surface temperature, air temperature, and rain. The multiple regression model with intercept had a poor fit, therefore, we made a model without intercept, which improve greatly the fit. A selection of the variables using the forward procedure verified that the independent variables "wind speed" and "air temperature" have a significant relation with catch (p < 0.001) at real time. This method suggests that sea surface temperature and rain have little influence on the catch, and suggests a major availability of resources in the months with low air temperature and the highest wind speed (January-June). Rev.

[Association of sardine fishery, Sardinella aurita (Teleostei: Clupeidae) and environmental variability of the coastal upwelling ecosystem of Nueva Esparta, Venezuela]. / La pesca de sardina, Sardinella aurita (Teleostei: Clupeidae) asociada con la variabilidad ambiental del ecosistema de surgencia costera de Nueva Esparta, Venezuela.

The present research is an analysis of Spanish sardine fishing (Sardinella aurita) associated with some climatic and meteorologic parameters of the ecosystem from El Morro Nueva Esparta, Venezuela. The catch and environmental data from the area were taken in the period 1996-2000. Catch data as a function of wind speed, sea surface temperature, air temperature and rain were analyzed by means of simple lineal regression and multiple models. We found a positive correlation of catch with wind speed, and a negative correlation with sea surface temperature, air temperature, and rain. The multiple regression model with intercept had a poor fit, therefore, we made a model without intercept, which improve greatly the fit. A selection of the variables using the forward procedure verified that the independent variables "wind speed" and "air temperature" have a significant relation with catch (p < 0.001) at real time. This method suggests that sea surface temperature and rain have little influence on the catch, and suggests a major availability of resources in the months with low air temperature and the highest wind speed (January-June). Rev.