Anthropogenic and environmental pressure on Sardina pilchardus stock

Several equations and models were used for the stock assessment and evaluation of anthropogenic and environmental pressure on Sardina pilchardus stock, to deal with the fisheries-management issue of measures. The first analyze of the correlation showed that effort and landings are positively correlated with SST (sea-surface temperature) and negatively correlated with rainfall. Whereas, the correlations between LPUE (landing per unit of effort) and environmental parameters (SST and rainfall) are not significant. However, the selection of the generalized additive mixed model (GAMM) was relevant for incorporating multiple factors. This non-parametric flexible model was chosen to handle a time series of environmental (SST) and fishery covariates (landing, effort), along with the abundance index estimated from LPUE as a predictor variable. This family of GAMs models proved highly useful in understanding and illustrating the interaction between climatic and fishery variables on the abundance index of Sardina pilchardus stock for the EAST of Tunisia (Sahel region). Results emphasized the nonlinear response of all parameters and their significant interactive relationships. Summer and winter, two critical seasons for the sardine stock, revealed how biologic (reproduction) and ecological (food) sardine behavior control fishery action, influenced by hydrographic factor (SST). In fact, during the summer, there is no need to increase the effort to caught sardine, however, in the winter; two scenarios have been exposed according to the fishing ground. The landing is increasing and the effort is less, so sardines are caught off the coast. While the landing is decreasing and the effort is increasing, sardines are caught offshore. Finally, our preliminary research should be continued over time and extended to other pelagic species because the integration of such results will be crucial for developing Tunisian fisheries-management strategies to ensure sustainability with the take into consideration the quality of data particularly of the fisheries database. Such data were always a source of error and should be the case of data-improvement project in future for accuracy analyze to deal with fisheries management in Tunisia and the worldwide.