No abstract

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.

In our study of bat diversity in the Amazon Basin, we captured bats in undisturbed continuous forest and in forest fragments at the Biological Dynamics of Forest Fragments Project (BDFFP) near Manaus, Brazil, from January 1996 until July 1999. We recorded 72 species of bats in a sample of more than 7700 individuals caught during 29,900 mistnet hours in terra-firme forest. Species accumulation curves and mathematical estimates of species numbers based on the number of species captured with standardized methodology suggest that we sampled about 95% of the entire expected bat fauna of the area, including aerial insectivorous bats. Our results are similar to those of other mistnetting inventories of Amazonian bat assemblages in terms of species composition and number of species per bat family. Some species considered widespread in Central Amazonia and expected at our study site were not recorded. We interpret their absence as effects of sampling bias and of local ecological conditions. We know from acoustic monitoring (i.e., identification of bats by their echolocation calls) that our mistnet data are incomplete for aerial insectivorous species. We conclude that the development of comprehensive inventories of key vertebrate taxa such as bats derived from a combination of several standardized sampling procedures is essential to develop meaningful, conservation-oriented plans for land-use and management of protected areas.