LANDFIRE - Fire Regime Groups (LANDFIRE.US_130FRG)
Dates
Publication Date
2013-08-31
Citation
Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey, 20130831, LANDFIRE.US_130FRG: .
Summary
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of historical fire regimes and vegetation conditions using the disturbance dynamics model VDDT. LANDFIRE also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National Fire Plan, Federal Wildland Fire Management Policy, and the Healthy [...]
Summary
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of historical fire regimes and vegetation conditions using the disturbance dynamics model VDDT. LANDFIRE also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National Fire Plan, Federal Wildland Fire Management Policy, and the Healthy Forests Restoration Act. Data Summary: The Fire Regime Groups layer characterizes the presumed historical fire regimes within landscapes based on interactions between vegetation dynamics, fire spread, fire effects, and spatial context (Hann and others 2004). Fire regime group definitions have been altered from previous applications (Hann & Bunnell 2001; Schmidt and others 2002; Wildland Fire Communicator's Guide) to best approximate the definitions outlined in the Interagency FRCC Guidebook. These definitions were refined to create discrete, mutually exclusive criteria. This layer was created by linking the BpS layer to the Fire Regime Group rulesets. This geospatial product should display a reasonable approximation of Fire Regime Group, as documented in the Refresh Model Tracker. The Historical Fire Regime Groups data layer categorizes simulated mean fire return intervals and fire severities into five fire regimes defined in the Interagency Fire Regime Condition Class Guidebook. The classes are defined as follows: Fire Regime I: 0 to 35 year frequency, low to mixed severity Fire Regime II: 0 to 35 year frequency, replacement severity Fire Regime III: 35 to 200 year frequency, low to mixed severity Fire Regime IV: 35 to 200 year frequency, replacement severity Fire Regime V: 200+ year frequency, any severity Additional data layer values were included to represent Water (111), Snow / Ice (112), Barren (131), and Sparsely Vegetated (132). Vegetated areas that never burned during the simulations were included in the category "Indeterminate Fire Regime Characteristics" (133); these vegetation types either had no defined fire behavior or had extremely low probabilities of fire ignition.
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Fire Regime Groups.xml Original FGDC Metadata
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application/fgdc+xml
Purpose
LANDFIRE data products are designed to facilitate national- and regional-level strategic planning and reporting of management activities. Data products are created at a 30-meter grid spatial resolution raster data set; however, the applicability of data products varies by location and specific use. Principal purposes of the data products include providing, 1) national-level, landscape-scale geospatial products to support fire and fuels management planning, and, 2) consistent fuels data to support fire planning, analysis, and budgeting to evaluate fire management alternatives. Users are advised to evaluate the data carefully for their applications.