期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 132, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2020.104806
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资金
- NSF [DEB-1441737]
- NASA [80NSSC17K0282, 80NSSC18K0435]
- Natural Environment Research Council (U.K.) [NE/M014533/1]
- NERC [NE/M014533/1] Funding Source: UKRI
Global biodiversity indicators are often derived by intersecting observed or projected changes in anthropogenic pressures with underlying patterns in the distribution of biodiversity. However these patterns are typically delineated at a coarser resolution than the key ecological processes shaping both land-use and biological distributions. The 'Biogeographic modelling Infrastructure for Large-scaled Biodiversity Indicators' (BILBI) integrates advances in macroecological modelling, informatics, remote sensing and high-performance computing to assess spatio-temporal change in collective properties of biodiversity, particularly beta diversity, at similar to 1 km grid resolution across the entire terrestrial surface of the planet. BILBI greatly refines the mapping of biodiversity patterns relative to more traditional surrogates such as ecoregions and species range maps. This capability is already proving of considerable value in informing global assessments through: 1) generation of indicators of past-to-present change in biodiversity resulting from habitat transformation or protection; and 2) projection of potential future change in biodiversity resulting from alternative global-change scenarios.
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