Title:

Linking TreeMap and FuelMap to growth, yield, and disturbance modeling: an FVS-ready database for the conterminous United States (30m) circa 2020 landscapes

Author(s):

Houtman, Rachel M.; Riley, Karin L.; Shaw, John D.; Ager, Alan A.

Publication Year:

2026

How to Cite:

These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Houtman, Rachel M.; Riley, Karin L.; Shaw, John D.; Ager, Alan A. 2026. Linking TreeMap and FuelMap to growth, yield, and disturbance modeling: an FVS-ready database for the conterminous United States (30m) circa 2020 landscapes. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2026-0057

Abstract:

TreeMap, a CONUS-wide gridded dataset of Forest Inventory and Analysis (FIA) plots imputed to spatially-explicit LANDFIRE and DAYMET data, provides a unique opportunity to connect spatially contiguous tree-level data with the Forest Vegetation Simulator (FVS), enabling users to model landscape-wide forest and fuels management, growth, and disturbance effects. Surface fuel data are an optional input into FVS and are of particular value when modeling fire behavior and effects, including carbon emissions. FIA plot measurements include all the data required for modeling forest growth and management, but complete fuel data are not measured for every plot. FuelMap, a dataset that complements TreeMap through the imputation of fuels data to FIA plots in TreeMap, fills this gap.

The data in this package include a 30 meter (m) resolution raster that identifies each unique combination of FVS variant and TreeMap and FuelMap FIA plot control numbers (CNs), circa landscape conditions in 2020, as well as a set of FVS-ready SQLite databases that contain the FIA-derived tree and stand-level variables for each unique combination. Also included in this package is the R script used to build the FVS input databases. Users of the FIA Database (FIADB), which is more recently referred to as the FIA DataMart, should be aware that these databases differ from the FVS-ready tables available in the FIADB in two key ways. First, the FIADB tables do not include fuels for FIA plots for which fuels are not measured. Second, the FIADB tables include the FVS variant in which each FIA plot originates, rather than the FVS variant within which the FIA plots are imputed in TreeMap.

Keywords:

biota; environment; Natural Resource Management & Use; Forest management; Landscape management; Restoration; Forest & Plant Health; forest modeling; landscape modeling; TreeMap; FuelMap; Forest Vegetation Simulator; Forest Inventory and Analysis; FIADB; FIA DataMart; conterminous United States; United States; CONUS

Related publications:

• Ager, Alan A.; Houtman, Rachel M.; Day, Michelle A.; Ringo, Chris; Palaiologou, Palaiologos. 2019. Tradeoffs between US national forest harvest targets and fuel management to reduce wildfire transmission to the wildland urban interface. Forest Ecology and Management. 434: 99-109. https://doi.org/10.1016/j.foreco.2018.12.003 https://research.fs.usda.gov/treesearch/57897
• Aparício, Bruno A.; Day, Michelle A.; Davis, Raymond; Houtman, Rachel M.; Krawchuk, Meg A. 2026. Exposure and carbon risk for mature and old-growth forests from severe wildfire in the Pacific Northwest, U.S.A. Natural Hazards. 3: 1. https://doi.org/10.1038/s44304-025-00160-w https://research.fs.usda.gov/treesearch/80018
• Houtman, Rachel M.; Riley, Karin L.; Finney, Mark A.; Ager, Alan A. 2026. Spatial datasets of wildfire risk to forest carbon for the conterminous United States (30m) circa 2014 landscapes. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2026-0014

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