MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.

Aim  The diversity of reproductive modes among amphibians constitutes a striking example of how differences in the biology of species provide important explanations for species distribution patterns on a broad scale. We hypothesize that sites with a higher humidity level will support more modes of reproduction than drier sites and will consequently exhibit a higher phylogenetic diversity. Furthermore, if there is a gradient in the tolerance of reproductive modes to desiccation, there will be a nested pattern in the composition of reproductive modes among sites. Location  Twenty‐seven forest sites in the Brazilian Atlantic Forest. Methods  Through a path analysis approach, we evaluated the direct and indirect effects of the humidity level on the number of reproductive modes, as well as the relative importance of both variables on amphibian phylogenetic diversity. A nestedness analysis was used to quantify the extent to which the compositions of both species and reproductive modes in drier sites correspond to subsets of those in sites with higher annual precipitation. Results  We found that the reproductive modes present in drier sites are non‐random subsets of those present in sites with higher humidity levels. Because reproductive modes are phylogenetically conserved among amphibians, sites with a greater number of reproductive modes supported greater phylogenetic diversity. Sites with high precipitation throughout the year provided suitable environmental conditions for a larger number of reproductive modes, whereas sites with low precipitation and typical seasonal climates supported only those reproductive modes specialized to resist desiccation. Main conclusions  Our results show that humidity‐related variables are key environmental factors related to both the richness of reproductive modes and phylogenetic diversity. Our results support the hypothesis that the higher phylogenetic diversity found in moister sites reflects differences in the tolerance to desiccation among different reproductive modes. Given that reproductive modes are associated with susceptibility to desiccation, their incorporation into explanatory models may trigger a significant advance in the understanding of the mechanisms regulating the species richness and composition of amphibian communities.

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.

We evaluated five non-mutually exclusive hypotheses driving the biogeographic regions of anuran species in the Amazonia. We overlaid extent-of-occurrence maps for anurans 50 × 50 km cells to generate a presence–absence matrix. This matrix was subjected to a cluster analysis to identify the pattern and number of biogeographic regions for the dataset. Then, we used multinomial logistic regression models and deviance partitioning to explore the relative importance of contemporary and historical climate variables, topographic complexity, riverine barriers and vegetation structure in explaining the biogeographic regions identified. We found seven biogeographic regions for anurans in the Amazonia. The major rivers in the Amazonia made the largest contribution to explaining the variability in anuran biogeographic regions, followed by climate variables and topography. The barrier effect seems to be strong for some rivers, such as the Amazon and Madeira, but other Amazonia rivers appear to not be effective barriers. Furthermore, climate and topographical variables provide an environmental gradient driving the species richness and anuran range-size distributions. Therefore, our results provide a spatially explicit framework that could be used to address conservation and management issues of anuran diversity for the largest tropical forests in the world.

In the Neotropics, conversion of natural habitats into agricultural areas is occurring at a high rate, with consequent reduction of habitat complexity in anuran breeding ponds. Identifying features of farmland ponds that allow them to support a high diversity of species is fundamental for successful management and conservation policies and is especially important in Neotropical regions that harbor the highest anuran species richness in the world. Here, we aimed to investigate which environmental descriptors correlate the occurrence of anuran species in tropical farmland ponds in southeastern Brazil. We found that environmental descriptors reflecting the complexity of vegetation in farmland ponds primarily predict the diversity of anuran species in these habitats. Species richness was correlated mainly by vegetation height in the margin, with ponds that exhibit greater stratification harboring a larger number of species. Vegetation height in the interior of ponds, diversity of vegetation in the margin, pond area and hydroperiod were also important variables predicting the abundance of six of 10 anuran species analyzed. Our results show that features of farmland ponds representing increased habitat complexity are key factors in maintaining a high diversity of species, providing a greater variety of microhabitats, both in vertical and horizontal strata, and thus meeting diverse speciesspecific requirements.