BLM REA COP 2010 LANDFIRE - Percent Mixed Severity Fire (version 1.0)

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 simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions.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 Simulated Historical Percent of Mixed Severity Fires data layer quantifies the percent of all fires that were of mixed severity. Mixed severity fires cause between 25 and 75% average replacement of dominant overstory aboveground biomass within a typical fire perimeter. This data layer is derived from vegetation and disturbance dynamics simulations using LANDSUM (Keane et al. 2002, Keane et al. 2003, Keane et al. 2005, Pratt et al. 2005). LANDSUM simulates fire dynamics as a function of vegetation dynamics, topography, and spatial context in addition to variability introduced by dynamic wind direction and speed, frequency of extremely dry years, and landscape-level fire size characteristics. This layer is intended to describe one component of simulated historical fire regime characteristics in the context of the broader historical time period represented by the LANDFIRE Biophysical Settings layer and LANDFIRE Biophysical Settings Model Documentation.The percent of mixed severity fires is calculated from the number of mixed severity fires relative to the total number of fires that affect a given pixel. The simulations used to produce this layer were 10,000 years in duration to observe the most complete representation of the fire regime characteristics within spatially complex landscapes, given computational limitations. However, it is important to note that these simulations are not intended to accurately represent the last 10,000 years of measurable history, which includes spatially and temporally dynamic factors such as climate change, vegetation species dispersal, and anthropogenic influences on vegetation and fire characteristics.Simulated historical percents of mixed severity fires were classified into 20 categories using 5% increments. 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.Keane, R.E., R. Parsons, and P. Hessburg. 2002. Estimating historical range and variation of landscape patch dynamics: limitations of the simulation approach. Ecological Modeling 151: 29-49.Keane, R.E., G.J. Cary, and R. Parsons. 2003. Using simulation to map fire regimes: an evaluation of approaches, strategies, and limitations. International Journal of Wildland Fire 12: 309-322.Keane, R.E., L. Holsinger, and S. Pratt. 2006. Simulating historical landscape dynamics using the landscape fire succession model LANDSUM version 4.0. USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory. RMRS-GTR-171CD.Pratt, S.D., L. Holsinger, and R.E. Keane. 2005. Modeling historical reference conditions for vegetation and fire regimes using simulation modeling. Chapter 10 in: The LANDFIRE Prototype Project: nationally consistent and locally relevant geospatial data and tools for wildland fire management. M.G. Rollins, Technical Editor. USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory. RMRS-GTR-[In prep.]