CMAT Centro de Matemática, Universidade do Minho, Braga, Portugal
Scientific tools capable of identifying the distribution patterns of species are important as they contribute to improve knowledge of causes of species fluctuations which can contribute to improve the species management, and consequently conserve biodiversity. Species distribution data often implies residual spatial autocorrelation and temporal variability, so both time and space are important components to study the evolution of species distribution from an ecological point of view. This study aims to estimate the spatio-temporal distribution of sardine (Sardina pilchardus) in the western and southern Iberian waters, relating the spatio-temporal variability of the biomass indicator with the environmental conditions. With this objective, a hierarchical two-part model is suggested capable of dealing with data specificities, namely zero-inflated, and with different sources of uncertainty. This work proposes to incorporate environmental covariates with time-lags, not under the usual approach of being fixed, but considering kernel weights.