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.

Lumpfish, or lumpsucker, Cyclopterus lumpus (Linnaeus, 1758) is widely distributed in the North Atlantic Ocean. It has a considerable economic value and substantial fisheries occur in several North Atlantic regions owing to the use of its fully ripe internal egg masses in the ovaries as an alternative to sturgeon caviar. Despite being intensively fished in several locations, biological knowledge is limited and no genetic structure information is available. In this study, the stock structure of C. lumpus was investigated across the North Atlantic using ten microsatellite loci. Out of ten loci, two exhibited higher level of differentiation but their inclusion/exclusion from the analyses did not drastically change the observed genetic pattern. A total of three distinct genetic groups were detected: Maine–Canada–Greenland, Iceland–Norway and Baltic Sea. These results, discussed in terms of origin of differentiation, gene flow, and selection, showed that gene flow was rather limited among the detected groups, and also between Greenland and Maine–Canada.

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Objective This study examined the feasibility and comparison of two styles of yoga within the context of a standard behavioral weight‐loss intervention (SBWI). Methods Fifty adults with obesity (BMI: 31.3 ± 3.8 kg/m2) participated in this 6‐month study that included a SBWI and a calorie‐ and fat‐reduced diet. Randomization was to restorative Hatha (SBWI+RES) or Vinyasa (SBWI+VIN) yoga. Yoga was prescribed to increase from 20 to 40 to 60 minutes per session across the intervention. Weight was assessed at baseline and 6 months. Perceptions of yoga were assessed at the completion of the intervention. Results Adjusted weight loss was −3.4 kg (95% CI: −6.4 to −0.5) in SBWI+RES and −3.8 kg (95% CI: −6.8 to −0.9) in SBWI+VIN (P < 0.001), with no difference between groups. Of all participants, 74.4% reported that they would continue participation in yoga after the SBWI. Session duration was a barrier as yoga increased from 20 to 40 to 60 minutes per day, with 0%, 7.5%, and 48.8% reporting this barrier, respectively. Conclusions Among adults with obesity, yoga participation, within the context of a SBWI, appears to be feasible, with weight loss not differing by style of yoga. Progressing to 60 minutes per session appears to be a barrier to engagement in yoga in this population.