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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.

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We found an extraordinary level of bacterial biodiversity in the tree leaf canopy of a tropical Atlantic forest by using culture-independent molecular methods. Our survey suggests that each tree species selects for a distinct microbial community. Analysis of the bacterial 16S ribosomal RNA gene sequences revealed that about 97% of the bacteria were unknown species and that the phyllosphere of any one tree species carries at least 95 to 671 bacterial species. The tree canopies of tropical forests likely represent a large reservoir of unexplored microbial diversity.

Forest restoration requires strategies such as passive restoration to balance financial investments and ecological outcomes. However, the ecological outcomes of passive restoration are traditionally regarded as uncertain. We evaluated technical and legal strategies for balancing economic costs and ecological outcomes of passive versus active restoration in agricultural landscapes. We focused in the case of Brazil, where we assessed the factors driving the proportion of land allocated to passive and active restoration in 42 programs covering 698,398 hectares of farms in the Atlantic Forest, Atlantic Forest/cerrado ecotone and Amazon; the ecological outcomes of passive and active restoration in 2955 monitoring plots placed in six restoration programs; and the legal framework developed by some Brazilian states to balance the different restoration approaches and comply with legal commitments. Active restoration had the highest proportion of land allocated to it (78.4%), followed by passive (14.2%) and mixed restoration (7.4%). Passive restoration was higher in the Amazon, in silviculture, and when remaining forest cover was over 50 percent. Overall, both restoration approaches showed high levels of variation in the ecological outcomes; nevertheless, passively restored areas had a smaller percentage canopy cover, lower species density, and less shrubs and trees (dbh > 5 cm). The studied legal frameworks considered land abandonment for up to 4 years before deciding on a restoration approach, to favor the use of passive restoration. A better understanding of the biophysical and socioeconomic features of areas targeted for restoration is needed to take a better advantage of their natural regeneration potential.Abstract in Portuguese is available with online material.

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