Current and future global distribution of potential biomes under climate change scenarios ...

Probability and uncertainty maps showing the potential current and future natural vegetation on a global scale under three different climate change scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) predicted using ensemble machine learning. Current (2022 - 2023) conditions are calculated on historical long t...

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Bibliographic Details
Main Authors: Bonannella, Carmelo, Hengl, Tomislav, Leal Parente, Leandro, de Bruin, Sytze
Format: Dataset
Language:English
Published: Zenodo 2023
Subjects:
ensemble machine learning
climate change scenario
rcp
biomes
global
Antarc*
Antarctica
Online Access:https://dx.doi.org/10.5281/zenodo.7520814
https://zenodo.org/record/7520814
Description
Summary:Probability and uncertainty maps showing the potential current and future natural vegetation on a global scale under three different climate change scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) predicted using ensemble machine learning. Current (2022 - 2023) conditions are calculated on historical long term averages (1979 - 2013), while future projections cover two different epochs: 2040 - 2060 and 2061 - 2080. Files are named according to the following naming convention, e.g.: biomes_graminoid.and.forb.tundra.rcp85_p_1km_a_20610101_20801231_go_epsg.4326_v20230110 with the following fields: generic theme: biomes , variable name: graminoid.and.forb.tundra.rcp85 , variable type, e.g. probability (" p "), hard class (" c "), model deviation (" md ") spatial resolution: 1km , depth reference, e.g. below (" b "), above (" a ") ground or at surface (" s "), begin time (YYYYMMDD): 20610101 , end time: 20801231 , bounding box, e.g. global land without Antarctica (" go "), EPSG code: epsg.4326 , version code, e.g. ...

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