ESSDD Earth System Science Data Discussions ESSDD Earth Syst. Sci. Data Discuss. Göttingen, Germany 10.5194/essd-2026-633 TreeMap 2020, 2022, and 2023: Improved species range mapping in a tree-level forest dataset for the conterminous United States Riley Karin https://orcid.org/0000-0001-6593-5657 1 Houtman Rachel https://orcid.org/0000-0003-2097-9423 1 Zimmer Scott 1 Leatherman Lila https://orcid.org/0009-0007-8849-8964 2 Peeler Jamie 3 4 Shaw John 5 Grenfell Isaac 1 Borja Arboleda Maria 2 Shrestha Abhinav https://orcid.org/0009-0007-1904-7457 2 6 Housman Ian 2 Finney Mark 1 Missoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, 5775 W Highway 10, Missoula, Montana 59808, USA RedCastle Resources, 3556 S 5600 W Suite #1-1102, Salt Lake City, UT 84120, USA Oak Ridge Institute for Science and Education, Oak Ridge Associated Universities,1299 Bethel Valley Road, Oak Ridge, Tennessee 37830, USA Department of Ecosystem and Conservation Sciences, University of Montana, 32 Campus Drive, Missoula, Montana 59812, USA Forest Inventory and Analysis, US Forest Service, 507 25th St., Ogden, Utah 84401, USA Chair of Ecosystem Dynamics and Forest Management in Mountain Landscapes, School of Life Sciences, Technical University of Munich, Freising, Germany 11 10 2026 2026 1 33 Copyright: © 2026 Karin Riley et al. 2026 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://essd.copernicus.org/preprints/essd-2026-633/ The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-633/essd-2026-633.pdf

TreeMap is a tree-level model of the forests of the conterminous United States (CONUS) that provides a spatially continuous, 30 m resolution representation of forest structure and composition. It uses a random forests imputation approach to assign the most similar Forest Inventory and Analysis (FIA) plot to each forested pixel in gridded LANDFIRE data based on a suite of predictor variables that include vegetation, topographic, biophysical, and disturbance characteristics. By linking every mapped pixel to an FIA plot identifier for all forested areas in CONUS, TreeMap bridges localized inventory measurements with national-scale analyses and provides high-resolution estimates of forest structure and composition. In this update, TreeMap 2020, 2022, and 2023 incorporate climatic variables from Daymet in place of LANDFIRE biophysical variables. Further, we refined the independent validation by limiting the analysis to FIA plots where heterogeneity was administrative rather than ecological, excluding plots previously used to validate TreeMap versions that spanned heterogeneous forest conditions.&nbsp; TreeMap 2020, 2022, and 2023 also implement a new process constraining the pool of FIA plots available for imputation within each LANDFIRE zone to species documented within that zone and its adjacent zones, thereby reducing implausible species assignments across CONUS. TreeMap 2020, 2022, and 2023 are publicly available at <a href="https://doi.org/10.2737/RDS-2025-0031" target="_blank" rel="noopener">https://doi.org/10.2737/RDS-2025-0031</a> (Zimmer et al., 2025) and <a href="https://doi.org/10.2737/RDS-2025-0032" target="_blank" rel="noopener">https://doi.org/10.2737/RDS-2025-0032</a> (Houtman et al., 2025), and <a href="https://doi.org/10.2737/RDS-2026-0038" target="_blank" rel="noopener">https://doi.org/10.2737/RDS-2026-0038</a> (Zimmer et al., 2026), respectively.