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Increasing rates of habitat loss and human occupation are creating demands for optimum strategies that maximize conservation efforts, despite the lack of detailed data required for implementation. Broad scale biogeographical data may furnish initial guidelines for conservation planning in a hierarchical framework for establishing conservation priorities and helping guide future research programmes. This approach may be critical in regions for which few detailed data on diversity, abundance and distribution are available, such as in the Cerrado biome of central Brazil. We used a macroecological approach, based on the extent of occurrence of 127 species of terrestrial vertebrates endemic to the Cerrado, to design a regional network of potential areas that represent all species at least once. The final network has a total of 24 regions widely distributed throughout the biome. We also evaluated these regions in terms of their human occupation by adding a cost for each cell based on 23 variables expressing variation in agricultural, demographic and cattle-ranching patterns on the Cerrado. Our analyses showed that conservation efforts should be concentrated in the south and south-east of the biome. This macro- ecological approach can provide broad guidelines for conservation and define the focus for more local and realistic conservation efforts. [ABSTRACT FROM AUTHOR]

Abstract: At lower spatial scales, richness spatial patterns probably lead to more complex ecological–evolutionary interactions. In this paper, we used a “deconstruction” approach to evaluate the Cerrado breeding bird''s richness, according to their habitat use categories (independent, semi-dependent and dependent on forest habitats). Six environmental variables and current human population size were used as predictors of species richness. Moran''s I coefficients revealed strong spatial autocorrelation in ordinary least squares multiple regression residuals, and thus a Principal Coordinate of Neighbour Matrices (PCNM) was used to evaluate the influence of richness predictors, minimizing the problems caused by spatial autocorrelation. Models generated for total richness and for species richness by habitat categories were compared. We showed that, despite the total richness being more concentrated in south and southeast regions of Cerrado, these patterns changed when analysing semi-dependent and dependent forest habitat species, demonstrating a spatial variation in richness for these categories. The PCNM analyses demonstrated that, for total species richness, only partial coefficients of AET and temperature were significant. For independent forest richness, significant partial regression coefficients were found for AET, PET, TEMP and PREC, whereas for semi-dependent forest habitats richness, only AET was significant. On the other hand, for dependent of forest richness, a significant positive coefficient was found for precipitation and for human population. Most spatial variation in richness can be explained by joined effects of geographic structure and environmental predictors. These analyses reveal that deconstruction can be a step to a more effective understanding of richness patterns and their environmental drivers. [Copyright &y& Elsevier]