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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.

Changes to the global nitrogen cycle affect human health well beyond the associated benefits of increased food production. Many intensively fertilized crops become animal feed, helping to create disparities in world food distribution and leading to unbalanced diets, even in wealthy nations. Excessive air‐ and water‐borne nitrogen are linked to respiratory ailments, cardiac disease, and several cancers. Ecological feedbacks to excess nitrogen can inhibit crop growth, increase allergenic pollen production, and potentially affect the dynamics of several vector‐borne diseases, including West Nile virus, malaria, and cholera. These and other examples suggest that our increasing production and use of fixed nitrogen poses a growing public health risk.

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Recent ecological studies suggest that the landscape context of native habitat remnants may significantly influence plant and animal abundance and distribution within those remnants. Other research has revealed a weak link between landscape context and native community composition. To understand the relative importance of local and regional habitat characteristics for grassland butterflies, we assessed butterfly community diversity in four types of grassland habitats surrounded by varying amounts of urban development near Boulder, Colorado ( U.S.A.). We recorded butterfly species abundance and composition in 66 grassland study plots on five sampling dates in 1999 and 2000. Grasslands were of four types: native shortgrass, native mixed grass, native tallgrass, and planted hayfields. Grasslands also varied in quality, determined by the abundance of native versus exotic plant species. We observed highly significant effects of grassland type on butterfly species richness and composition. For example, tallgrass plots supported significantly higher butterfly species richness than shortgrass plots ( p < 0.01). Habitat quality also affected butterfly species richness and composition. Low‐quality plots generally supported fewer species than moderate‐ or high‐quality plots (  p < 0.05). Landscape context—the percentage of urbanization in the surrounding landscape—did not significantly predict butterfly species richness or composition. Our observations suggest that for the grassland butterfly communities in our study, (1) grassland type was the primary determinant of species richness and composition, (2) habitat quality secondarily affected butterfly community diversity, and (3) landscape context did not significantly predict butterfly species composition. Our findings emphasize the importance of maintaining high‐quality grassland habitat to protect native butterfly diversity.