Bioclimatic Classification of 55 Million Herbarium Specimens

Article in prep. Dataset and data descriptors provided here.ABSTRACT:<br>We have developed a comprehensive bioclimatic classification for 55 million georeferenced herbarium specimens, linking each record to a Holdridge Life Zone (HLZ) and a Köppen-Geiger climate type via its Global Biodiversity Information Facility occurrence ID. Classifications are based on bioclimatic variables at 1 km resolution or finer, with HLZ derived from the WorldClim2.1 dataset and Köppen-Geiger from CHELSA 2.1. We also provide the underlying climatic variables necessary for HLZ classification. This dataset significantly expands the usefulness of herbaria for building taxonomic revisions and conducting historical research, as demonstrated through selected applications. It is here made freely available for public use.<br><br>DATA REFERENCES:<br><br>Brun, P., Zimmermann, N. E., Hari, C., Pellissier, L., &amp; Karger, D. N. (2022a). <i>CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution</i> (Version 1.0) EnviDat. https://doi.org/10.16904/ENVIDAT.332<br>Brun, P., Zimmermann, N. E., Hari, C., Pellissier, L., &amp; Karger, D. N. (2022b). <i>Global climate-related predictors at kilometre resolution for the past and future</i>. ESSD – Land/Biogeosciences and biodiversity. https://doi.org/10.5194/essd-2022-212<br><br>Enikolopov, A. (2025). <i>High resolution implementation of the Holdridge Life Zone system with transitional zones and altitudinal belts</i> [Dataset]. figshare. https://doi.org/10.6084/M9.FIGSHARE.28236242.V1<br>Fick, S. E., &amp; Hijmans, R. J. (2017). WorldClim 2: New 1‐km spatial resolution climate surfaces for global land areas. <i>International Journal of Climatology</i>, <i>37</i>(12), 4302–4315. https://doi.org/10.1002/joc.5086<br>GBIF.Org. (2025). <i>Occurrence Download</i> The Global Biodiversity Information Facility. https://doi.org/10.15468/DL.3CS9U7<br>Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., &amp; Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. <i>Scientific Data</i>, <i>4</i>(1), 170122. https://doi.org/10.1038/sdata.2017.122<br>Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., &amp; Kessler, M. (2021). <i>Climatologies at high resolution for the earth’s land surface areasCHELSA V2.1 (current)</i> (Version 2.1) [Geotiff]. EnviDat. https://doi.org/10.16904/ENVIDAT.228.V2.1<br><br>Peel, M. C., Finlayson, B. L., &amp; McMahon, T. A. (2007). Updated world map of the Köppen-Geiger climate classification. <i>Hydrology and Earth System Sciences</i>, <i>11</i>(5), 1633–1644. https://doi.org/10.5194/hess-11-1633-2007<br><br>United States Geological Survey. (1996). <i>Global 30 Arc-Second Elevation Data Set (GTOPO30)</i> [Dataset]. Sioux Falls, South Dakota, 2000<br><br>Zomer, R. J., Xu, J., &amp; Trabucco, A. (2022). Version 3 of the Global Aridity Index and Potential Evapotranspiration Database. <i>Scientific Data</i>, <i>9</i>(1), 409. https://doi.org/10.1038/s41597-022-01493-1