We herein present FactorsR, an RWizard application which provides tools for the identification of the most likely causal factors significantly correlated with species richness, and for depicting on a map the species richness predicted by a Support Vector Machine (SVM) model. As a demonstration of FactorsR, we used an assessment using a database incorporating all species of terrestrial carnivores, a total of 249 species, distributed across 12 families. The model performed with SVM explained 91.9% of the variance observed in the species richness of terrestrial carnivores. Species richness was higher in areas with both higher vegetation index and patch index, i.e., containing higher numbers of species whose range distribution is less fragmented. Lower species richness than expected was observed in Chile, Madagascar, Sumatra, Taiwan, and Sulawesi.

In contrast to several studies presented in the literature which analyze how different political elements affect specific aspects of financial management of public institutions, we have investigated from a comprehensive perspective how various political factors influence the financial situation of the municipalities. To do this, we use diverse multivariate techniques, the concept of financial condition and a large sample of Spanish municipalities. By isolating the electoral cycle and analyzing the essence of political factors, our main findings are that conservative and progressive parties do not present different behavior in relation to any of the financial dimensions. The territoriality of political parties influences the relationship between fund transfers received by the municipalities and certain expenses and investments. Furthermore, we did not detect that, in Spain, a partisan alignment exists between municipalities and the upper-level institutions