How do distribution mapping methods perform in estimating beta diversity at macroecological scales? A case study with Neotropical anurans.

Species distribution mapping methods have their advantages and limitations concerning their use on theoretical and/or applied macroecological approaches. However, it remains underexplored how the estimates of community ecology metrics vary across the distributions generated by different mapping methods. Here, we mapped the distribution patterns of the anuran beta diversity in the Atlantic Forest and Cerrado hotspots generated by three mapping methods: point-to-grid (PTG), extent-of-occurrence (EOO), and ecological niche modelling (ENM) maps, so we were able to compare the congruence of the local contribution to beta diversity index (LCBD) among them, as well as their turnover and nestedness components. PTGs generated the most divergent LCBD values probably due to the more resolved spatial scale in which species' presence are considered, so EEO and ENM generated similar beta diversity estimates for both hotspots. High LCBD values in the Cerrado were recorded in ecotone regions, whereas in the Atlantic Forest the highest beta diversity values were found along the Atlantic coast. The structure of beta diversity of PTG showed way too high values of importance for the turnover component compared to the EEO and ENM maps, which also recorded higher importance for the turnover than for the nestedness component.

Expected impacts of climate change threaten the anuran diversity in the Brazilian hotspots.

We performed Ecological Niche Models (ENMs) to generate climatically suitable areas for anurans in the Brazilian hotspots, the Atlantic Forest (AF), and Cerrado (CER), considering the baseline and future climate change scenarios, to evaluate the differences in the alpha and beta diversity metrics across time. We surveyed anuran occurrence records and generated ENMs for 350 and 155 species in the AF and CER. The final predictive maps for the baseline, 2050, and 2070 climate scenarios, based on an ensemble approach, were used to estimate the alpha (local species richness) and beta diversity metrics (local contribution to beta diversity index and its decomposition into replacement and nestedness components) in each ~50 × 50 km grid cell of the hotspots. Climate change is not expected to drastically change the distribution of the anuran richness gradients, but to negatively impact their whole extensions (i.e., cause species losses throughout the hotspots), except the northeastern CER that is expected to gain in species richness. Areas having high beta diversity are expected to decrease in northeastern CER, whereas an increase is expected in southeastern/southwestern CER under climate change. High beta diversity areas are expected to remain in the same AF locations as the prediction of the baseline climate, but the predominance of species loss under climate change is expected to increase the nestedness component in the hotspot. These results suggest that the lack of similar climatically suitable areas for most species will be the main challenge that species will face in the future. Finally, the application of the present framework to a wide range of taxa is an important step for the conservation of threatened biomes.

Biogeographic distribution patterns and their correlates in the diverse frog fauna of the Atlantic Forest hotspot.

Anurans are a highly diverse group in the Atlantic Forest hotspot (AF), yet distribution patterns and species richness gradients are not randomly distributed throughout the biome. Thus, we explore how anuran species are distributed in this complex and biodiverse hotspot, and hypothesize that this group can be distinguished by different cohesive regions. We used range maps of 497 species to obtain a presence/absence data grid, resolved to 50×50 km grain size, which was submitted to k-means clustering with v-fold cross-validation to determine the biogeographic regions. We also explored the extent to which current environmental variables, topography, and floristic structure of the AF are expected to identify the cluster patterns recognized by the k-means clustering. The biogeographic patterns found for amphibians are broadly congruent with ecoregions identified in the AF, but their edges, and sometimes the whole extent of some clusters, present much less resolved pattern compared to previous classification. We also identified that climate, topography, and vegetation structure of the AF explained a high percentage of variance of the cluster patterns identified, but the magnitude of the regression coefficients shifted regarding their importance in explaining the variance for each cluster. Specifically, we propose that the anuran fauna of the AF can be split into four biogeographic regions: a) less diverse and widely-ranged species that predominantly occur in the inland semideciduous forests; b) northern small-ranged species that presumably evolved within the Pleistocene forest refugia; c) highly diverse and small-ranged species from the southeastern Brazilian mountain chain and its adjacent semideciduous forest; and d) southern species from the Araucaria forest. Finally, the high congruence among the cluster patterns and previous eco-regions identified for the AF suggests that preserving the underlying habitat structure helps to preserve the historical and ecological signals that underlie the geographic distribution of AF anurans.