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.

Abstract.On

Humans have elevated global extinction rates and thus lowered global scale species richness. However, there is no a priori reason to expect that losses of global species richness should always, or even often, trickle down to losses of species richness at regional and local scales, even though this relationship is often assumed. Here, we show that scale can modulate our estimates of species richness change through time in the face of anthropogenic pressures, but not in a unidirectional way. Instead, the magnitude of species richness change through time can increase, decrease, reverse, or be unimodal across spatial scales. Using several case studies, we show different forms of scale‐dependent richness change through time in the face of anthropogenic pressures. For example, Central American corals show a homogenization pattern, where small scale richness is largely unchanged through time, while larger scale richness change is highly negative. Alternatively, birds in North America showed a differentiation effect, where species richness was again largely unchanged through time at small scales, but was more positive at larger scales. Finally, we collated data from a heterogeneous set of studies of different taxa measured through time from sites ranging from small plots to entire continents, and found highly variable patterns that nevertheless imply complex scale‐dependence in several taxa. In summary, understanding how biodiversity is changing in the Anthropocene requires an explicit recognition of the influence of spatial scale, and we conclude with some recommendations for how to better incorporate scale into our estimates of change.

Climate change and other anthropogenic drivers of biodiversity change are unequally distributed across the world. Overlap in the distributions of different drivers have important implications for biodiversity change attribution and the potential for interactive effects. However, the spatial relationships among different drivers and whether they differ between the terrestrial and marine realm has yet to be examined. We compiled global gridded datasets on climate change, land‐use, resource exploitation, pollution, alien species potential and human population density. We used multivariate statistics to examine the spatial relationships among the drivers and to characterize the typical combinations of drivers experienced by different regions of the world. We found stronger positive correlations among drivers in the terrestrial than in the marine realm, leading to areas with high intensities of multiple drivers on land. Climate change tended to be negatively correlated with other drivers in the terrestrial realm (e.g. in the tundra and boreal forest with high climate change but low human use and pollution), whereas the opposite was true in the marine realm (e.g. in the Indo‐Pacific with high climate change and high fishing). We show that different regions of the world can be defined by Anthropogenic Threat Complexes (ATCs), distinguished by different sets of drivers with varying intensities. We identify 11 ATCs that can be used to test hypotheses about patterns of biodiversity and ecosystem change, especially about the joint effects of multiple drivers. Our global analysis highlights the broad conservation priorities needed to mitigate the impacts of anthropogenic change, with different priorities emerging on land and in the ocean, and in different parts of the world.