Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Allan, James R; Watson, James E M; Di Marco, Moreno; O'Bryan, Christopher J; Possingham, Hugh P; Atkinson, Scott C; Venter, Oscar (2019): Supporting data for hotspots of human impact on threatened terrestrial vertebrates [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.897391, Supplement to: Allan, JR et al. (2019): Hotspots of human impact on threatened terrestrial vertebrates. PLoS Biology, https://doi.org/10.1371/journal.pbio.3000158

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX Citation

Abstract:
Conserving threatened species requires identifying where across their range they are being impacted by threats, yet this remains unresolved across most of Earth. Here we present a global analysis of cumulative human impacts on threatened species by using a spatial framework that jointly considers the co-occurrence of eight threatening processes and the distribution of 5,457 terrestrial vertebrates. We show that impacts to species are widespread, occurring across 84% of Earth's surface, and identify hotspots of impacted species richness, and coolspots of unimpacted species richness. Almost one quarter of assessed species are impacted across > 90% of their distribution, and ~7% are impacted across their entire range. These results foreshadow localized extirpations, and potential extinctions, without conservation action. The spatial framework developed here offers a tool for defining strategies to directly mitigate the threats driving species declines, providing essential information for future national and global conservation agendas.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1File nameFile nameAllan, James R
2File formatFile formatAllan, James R
3File sizeFile sizekByteAllan, James R
4Uniform resource locator/link to fileURL fileAllan, James R
Size:
16 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML