The Obj 1 has established a novel analytical protocol based on a clustering algorithm to generate a hierarchical system of biogeographical regions for mammals with four levels (1128, 141, 27 and 9 bioregions) showing that global biodiversity patterns can be cohesively shaped from local to regional and realm scales. These bioregions were used in the Obj 2 to identify the determinants that best predict taxonomic differences among bioregions within the framework of two hypothesised scenarios. Differentiation between large bioregions require longer evolutionary times, so both scenarios assume that historical determinants of speciation and extinction will be most important to explain taxonomic dissimilarities. As bioregions decrease in size processes related to tolerances to given habitats, past and present climates, and past and present human impact would gain importance. The scenarios differ in how this process may occur: linearly or nested. Models show the existence of a nested effect across time and space of the determinants tested. Events occurring millions of years ago, as tectonic movements or orographic barriers, remained apparent from the largest to the smallest bioregions, while recent past and current determinants acquired importance at smaller scales. For the smaller bioregions, a combination of multiple determinants, with a particular influence of Quaternary climate changes, was critical to predict biogeographical assemblages. Models also showed a prevalent footprint of past anthropogenic impacts, particularly human land use 2000 years ago, across the hierarchical bioregionalisation. Interestingly, this variable was the most important determinant behind the plate tectonics for the largest bioregions. On the contrary, current human land use was unimportant, consistent with the hypothesis that human impact has been extensive and started longer ago than is often recognised. So far, the Obj 3 has computed preliminary ecological models to assess the performance of the human appropriation of net primary productivity (HANPP) as a direct proxy of current human impacts predicting extinction risk. HANPP is an integrated socio-ecological indicator quantifying the effects of human-induced changes in productivity and harvest on ecological biomass flows. Models including HANPP were not good predicting extinction risk, but the alternatively use of the energy that remains in the system, in terms of biomass after the human harvest (NPP0) resulted successful to predict extinction risk. This unexpected result opens the door to new conservation-related questions to predict vulnerability to extinction risk. Actions carried out so far have allowed to increase the scientific impact of DRIVE by presenting the main results to some of the most relevant international meetings in biogeography and ecology (IBS meetings, MEDECOS). Data and results will be uploaded to the project website once accepted for publication.