Sensor-based Geoinformatics (geosense), Faculty of Environment and Natural Resources, University of Freiburg, Tennenbacherstr. 4, 79106 Freiburg, Germany
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Views and downloads (calculated since 20 Feb 2024)
Cumulative views and downloads
(calculated since 20 Feb 2024)
Total article views: 2,371 (including HTML, PDF, and XML)
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2,098
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EndNote: 79
Views and downloads (calculated since 11 Nov 2024)
Cumulative views and downloads
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Total article views: 523 (including HTML, PDF, and XML)
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400
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Views and downloads (calculated since 20 Feb 2024)
Cumulative views and downloads
(calculated since 20 Feb 2024)
Viewed (geographical distribution)
Total article views: 2,894 (including HTML, PDF, and XML)
Thereof 2,894 with geography defined
and 0 with unknown origin.
Total article views: 2,371 (including HTML, PDF, and XML)
Thereof 2,371 with geography defined
and 0 with unknown origin.
Total article views: 523 (including HTML, PDF, and XML)
Thereof 520 with geography defined
and 3 with unknown origin.
Biomes are widely used to map vegetation patterns at large spatial scales and to assess impacts of climate change, yet there is no consensus on a generally valid biome classification scheme. We used crowd-sourced species distribution data and trait data to assess whether trait information is suitable for delimiting biomes. Although the trait data were heterogeneous and had large gaps with respect to the spatial distribution, we found that a global trait-based biome classification was possible.
Biomes are widely used to map vegetation patterns at large spatial scales and to assess impacts...