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Potential Natural Vegetation biomes global predictions of classes (based on predictions using the BIOMES 6000 dataset's 'current biomes' category.)
Potential Natural Vegetation (PNV) is the vegetation cover in equilibrium with climate that would exist at a given location non-impacted by human activities. PNV is useful for raising public awareness about land degradation and for estimating land potential. This dataset contains results of predictions of - (1) global distribution of biomes based on the BIOME 6000 data set (8057 modern pollen-based site reconstructions), - (2) distribution of forest tree species in Europe based on detailed occurrence records (1,546,435 ground observations), and - (3) global monthly Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) values (30,301 randomly-sampled points).
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Potential distribution of biomes
biome_type Class Table
|1||1c5510||tropical evergreen broadleaf forest|
|2||659208||tropical semi-evergreen broadleaf forest|
|3||ae7d20||tropical deciduous broadleaf forest and woodland|
|4||000065||warm-temperate evergreen broadleaf and mixed forest|
|8||009a18||cool evergreen needleleaf forest|
|9||caffca||cool mixed forest|
|13||55eb49||temperate deciduous broadleaf forest|
|14||65b2ff||cold deciduous forest|
|15||0020ca||cold evergreen needleleaf forest|
|16||8ea228||temperate sclerophyll woodland and shrubland|
|17||ff9adf||temperate evergreen needleleaf open woodland|
|28||e7e718||graminoid and forb tundra|
|30||798649||erect dwarf shrub tundra|
|31||65ff9a||low and high shrub tundra|
|32||d29e96||prostrate dwarf shrub tundra|
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Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC. (2018) Global Mapping of Potential Natural Vegetation: An Assessment of Machine Learning Algorithms for Estimating Land Potential. PeerJ Preprints. 10.7287/peerj.preprints.26811v1