Motivation: The 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... Show moreMotivation: The 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 included: The 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 grain: BioTIME 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 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)).Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Show less
East Asian migratory waterfowl have greatly declined since the 1950s, especially the populations that winter in China. Conservation is severely hampered by the lack of primary information about... Show moreEast Asian migratory waterfowl have greatly declined since the 1950s, especially the populations that winter in China. Conservation is severely hampered by the lack of primary information about migration patterns and stopover sites. This study utilizes satellite tracking techniques and advanced spatial analyses to investigate spring migration of the greater white-fronted goose (Anser albifrons) and tundra bean goose (Anser serrirostris) wintering along the Yangtze River Floodplain. Based on 24 tracks obtained from 21 individuals during the spring of 2015 and 2016, we found that the Northeast China Plain is far-out the most intensively used stopover site during migration, with geese staying for over 1month. This region has also been intensely developed for agriculture, suggesting a causal link to the decline in East Asian waterfowl wintering in China. The protection of waterbodies used as roosting area, especially those surrounded by intensive foraging land, is critical for waterfowl survival. Over 90% of the core area used during spring migration is not protected. We suggest that future ground surveys should target these areas to confirm their relevance for migratory waterfowl at the population level, and core roosting area at critical spring-staging sites should be integrated in the network of protected areas along the flyway. Moreover, the potential bird-human conflict in core stopover area needs to be further studied. Our study illustrates how satellite tracking combined with spatial analyses can provide crucial insights necessary to improve the conservation of declining Migratory species. Show less
Pollinator communities exhibit variable responses to changing landscape composition. A general expectation is that a decreasing cover of semi-natural habitats negatively affects pollinator... Show morePollinator communities exhibit variable responses to changing landscape composition. A general expectation is that a decreasing cover of semi-natural habitats negatively affects pollinator reproduction, population size and pollination services, but few studies have investigated the simultaneous effects of landscape complexity on different aspects of pollinator communities and functioning.In 20 agricultural landscape plots the size of an average Dutch farm, we studied how changing landscape complexity affected wild bee abundance, species richness and reproduction. To measure pollination, we placed potted strawberry plants as phytometers in landscapes. Landscape complexity was characterized as the area of semi-natural habitats. In addition, we estimated floral resource abundance in each landscape plot. We expected that i) bee species richness, reproduction and pollination would be positively related to area of semi-natural habitats and flower abundance, and that ii) species richness and reproduction would be positively related to pollination.An increase in semi-natural habitats in landscapes increased both the abundance of cavity-nesting bees colonizing trap nests, and the growth rates of experimental Bombus terrestris L. colonies, but not the species richness of wild bees measured by pan traps. There was only a tendency for higher pollination levels of strawberry plants with higher cover of semi-natural habitats. There was no relationship between species richness and bee reproduction in a landscape and the pollination services. Estimated flower abundance in landscape had a positive effect on bumblebee colony growth only and not on the other variables.Our results suggest that, by improving habitat quality on their farms through establishing more semi-natural habitats or enhancing the flower availability in semi-natural habitats, farmers can promote reproduction of a number of functionally important bee species and the pollination services they provide. Bee species richness, however, seems to be More difficult to enhance and requires more than just creating more of the same type of habitats or flowers. Show less
