Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

BILBI: supporting global biodiversity assessment through high-resolution macroecological modelling

Hoskins, A. J. et al

Environ. Model. Softw. 132, 104806 (2020) · 2020

Read source ↗ All evidence

Summary

Abstract 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 ~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.

Outcomes reported

Referenced by Nature Communications British biodiversity scenarios as citation 131; likely supports topic area: biodiversity / conservation; methods / modelling / statistics. Topics: biodiversity / conservation; methods / modelling / statistics Evidence type: Modelling / projection Source report: Nature Communications British biodiversity scenarios Ref#: Nature Communications British biodiversity scenarios #131 Original: Hoskins, A. J. et al. BILBI: supporting global biodiversity assessment through high-resolution macroecological modelling. Environ. Model. Softw. 132, 104806 (2020).

Theme
Farming systems, soils & land use
Subject
Other / interdisciplinary
Study type
Research
Source type
Peer-reviewed research
Status
Published
Geography
United Kingdom
System type
Other
DOI
10.1016/j.envsoft.2020.104806
Catalogue ID
IRmoq83nfn-671f23
Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.