The value of private properties for the conservation of biodiversity in the Brazilian Cerrado.

Areas set aside for conservation within private lands may be key to enhancing biodiversity-friendly landscapes. This conservation strategy should be especially effective in highly threatened regions that are poorly protected by public lands, such as the Brazilian Cerrado. Brazil's Native Vegetation Protection Law has included set-aside areas within private properties, but their relevance to conservation has not been evaluated. We assess whether private lands are contributing to biodiversity in the Cerrado, a global biodiversity conservation priority and major region for food production, where land use conflicts are often at odds with conservation objectives. We determined that private protected areas accommodate up to 14.5% of threatened vertebrate species ranges, which increases to 25% when considering the distribution of remaining native habitat. Moreover, the spatial spread of private protected areas benefits a large number of species. Ecological restoration of private protected lands would improve the benefits of this protection system, especially in the Southeastern Cerrado, where a large economic hub meets a threat hotspot.

Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation.

The increasing use of species distribution modeling (SDM) has raised new concerns regarding the inaccuracies, misunderstanding, and misuses of this important tool. One of those possible pitfalls - collinearity among environmental predictors - is assumed as an important source of model uncertainty, although it has not been subjected to a detailed evaluation in recent SDM studies. It is expected that collinearity will increase uncertainty in model parameters and decrease statistical power. Here we use a virtual species approach to compare models built using subsets of PCA-derived variables with models based on the original highly correlated climate variables. Moreover, we evaluated whether modelling algorithms and species data characteristics generate models with varying sensitivity to collinearity. As expected, collinearity among predictors decreases the efficiency and increases the uncertainty of species distribution models. Nevertheless, the intensity of the effect varied according to the algorithm properties: more complex procedures behaved better than simple envelope models. This may support the claim that complex models such as Maxent take advantage of existing collinearity in finding the best set of parameters. The interaction of the different factors with species characteristics (centroid and tolerance in environmental space) highlighted the importance of the so-called "idiosyncrasy in species responses" to model efficiency, but differences in prevalence may represent a better explanation. However, even models with low accuracy to predict suitability of individual cells may provide meaningful information on the estimation of range-size, a key species-trait for macroecological studies. We concluded that the use of PCA-derived variables is advised both to control the negative effects of collinearity and as a more objective solution for the problem of variable selection in studies dealing with large number of species with heterogeneous responses to environmental variables.

Gerromorpha (Hemiptera: Heteroptera) of eastern Mato Grosso State, Brazil: checklist, new records, and species distribution modeling.

The infraorder Gerromorpha comprises semiaquatic bugs, most of which spend much of their lifetime on the water surface, between floating plants, or on the margins of water bodies. Based on literature and collections made on streams and lakes on municipalities of eastern Mato Grosso, Brazil, a list has been elaborated with 52 species, including several new records. Out of the recorded species, 26 belong to the family Veliidae, 20 to Gerridae, three to Hydrometridae, two to Mesoveliidae, and one to Hebridae. The modeling of the potential geographical distribution is also presented for the 20 species that have been recorded for the first time from the state.