Modelling geographic patterns of population density of the white‐tailed deer in central Mexico by implementing ecological niche theory

Abstract

Conservation and management of species require basic knowledge on their geographic distribution and abundance. Here, we propose a novel approach, based on the theory of the ecological niche, to model the spatial patterns of the white‐tailed deer Odocoileus virginianus population density in two regions of central Mexico (Balsas Basin and Tehuacán‐Cuicatlán Valley). We used an ecological niche model to generate binary geographic distribution maps of the white‐tailed deer in each region based on occurrence data and a set of environmental variables. Then, the centroid of the distributions was calculated in ecological space (niche centroid) and the multidimensional Euclidian ecological distance of each pixel to the niche centroid was estimated. Finally, for each region the distance to the niche centroid (DNC) was regressed against 14 independent occurrence points in each site containing white‐tailed deer density information to determine the function describing the DNC‐density relationship, which was used to generate maps describing the distribution of white‐tailed deer density. Our results indicated an inverse DNC‐density relationship in both regions (Balsas Basin: r2 = 0.90 and Tehuacán‐Cuicatlán: r2 = 0.76) that was validated via bootstrapping resulting in a predicting capacity of near 62% for Balsas Basin and 65% for Tehuacán‐Cuicatlán Valley. Our results suggest that the distance to the niche centroid method is a robust, science‐based correlative approach that resulted useful to predict the population density of the white‐tailed deer in a spatially explicit fashion. The proposed approach is suitable for predicting the distribution of density for white‐tailed deer for which occurrence data with accompanying density information exists, but relative abundance can also be estimated when no abundance data are available.