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.
Onega Bay is the largest bay in the White Sea, characterised by shallow depth, a range of sediment types and strong tidal currents. All these factors provide conditions for high species richness and biomass. This study reviews data from three surveys of sublittoral macrobenthos undertaken by Russian institutes: the benthic survey covering the entire Onega Bay in 1952; the survey performed in the northern part of the area in 1981/90, and a study carried out in 2006 in the eastern part of the bay. In total, data from 107 stations were analysed. The data in different surveys were collected by different grab types. The datasets of both 1981/90 and 2006 overlap the 1952 survey area. The pattern of biomass distribution was consistent between the years of survey and was characterised by the low biomass at the northern periphery of the bay and the highest biomass observed in the coastal waters of the Solovetsky Islands. Bivalves and cirripeds (mostly Modiolus modiolus, Arctica islandica, Balanus balanus and Verucca stroemia) dominated in biomass. Neither the biomass share of dominant species nor the frequency of occurrence of several common species in these groups changed markedly between 1952 and 1981/90. Although the results of the 2006 survey appear somewhat different from the patterns of previous years, this does not indicate major changes in the benthic communities, because the survey in 2006 was designed in a different way and its overlap with the 1952 survey was minimal. However, the dominant species (by biomass) –A. islandica, M. modiolus and V. stroemia– held their leading positions. Results of the multidimensional scaling analysis based on the biomass data for all taxa encountered in the 1952 survey indicate considerable mixing of the samples from all surveys. This may be interpreted as the absence of major shifts in the sublittoral communities of the macrobenthos of Onega Bay at decadal scale. This kind of stability may be explained by an oceanographical regime resilient to climate variation and a relatively low anthropogenic environmental impact when compared to other shallow European seas.
Despite the dynamic nature of spatial pattern, the temporal variation of spatial structure of marine benthic assemblages is rarely assessed using several temporal scales. We quantified the variability of density and biomass of main benthic species in the intertidal soft-bottom flats at two bights in Chupa Inlet (Kandalaksha Bay, the White Sea). The data cover the 21-year period (1987-2008) of a long-term monitoring survey (1987-present) using a hierarchical sampling design with two temporal (year, season within a year) and three spatial scales (bights-7 km, stations within a bight-10-100 m, and replicate samples-10 s cm apart). We used nested ANOVA to test significance and variance components to compare the relative contribution of different scales of variability of density and biomass of 18 most occurring macrobenthic species. Some species demonstrated high large-scale variability, however, the majority showed high smallscale variability and residual variance. The interactive variability was at least as important as the temporal effects, indicating that the spatial pattern changes through time. The assemblages were more variable at small scales and more stable at larger scales. Potential implications for sampling design are discussed.
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