Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution based on the BIOME 6000 data set (8057 modern pollen-based site reconstructions). Predicted at 250 m using Ensemble Machine Learning and relief and climate variables representing the climate for the last 20+ years. Processing steps are described in detail here. Maps with "_sd_" contain estimated model errors per class. Antartica is not included. 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 6:e5457 https://doi.org/10.7717/peerj.5457 To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://github.com/envirometrix/PNVmaps/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: pnv = theme: potential natural vegetation, biome.type = variable: biome type (e.g. troppical savana), biome00k = classification model: BIOME6000, c = factor, 250m = spatial resolution / block support: 250 m, b0..0cm = vertical reference: land surface, 2000..2017 = time reference: period 2000-2017, v0.2 = version number: 0.2,