This simulation research was conducted in order to develop a large-fire risk assessment system for the contiguous land area of the United States. The modeling system was applied to each of 134 Fire Planning Units (FPUs) to estimate burn probabilities and fire size distributions. To obtain stable estimates of these quantities, fire ignition and growth was simulated for 10,000 to 50,000 ''years'' of artificial weather. The fire growth simulations, when run repeatedly with different weather and ignition locations, produce burn probabilities and fire behavior distributions at each landscape location (e.g., number of times a ''cell'' burns at a given intensity divided by the total years). The artificial weather was generated for each land unit using (1) a fire danger rating index known as the Energy Release Component (ERC) which is a proxy for fuel moisture contents, (2) a time-series analysis of ERC to represent daily and seasonal variability, and (3) distributions of wind speed and direction from weather records. Large fire occurrence was stochastically modeled based on historical relationships to ERC. The simulations also required spatial data on fuel structure and topography which were acquired from the LANDFIRE project (http://www.landfire.gov). Fire suppression effects were represented by a statistical model that yields a probability of fire containment based on independent predictors of fire growth rates and fuel type. The simulated burn probabilities were comparable to observed patterns across the U.S. over the range of four orders of magnitude, generally falling within a factor of 3 or 4 of historical estimates. Close agreement between simulated and historical fire size distributions suggest that fire sizes are determined by the joint distributions of spatial opportunities for fire growth (dependent on fuels and ignition location) and the temporal opportunities produced by conducive weather sequences. The research demonstrates a practical approach to using fire simulations at very broad scales for purposes of operational planning and perhaps ecological research.

A simulation system was developed to explore how fuel treatments placed in topologically random and optimal spatial patterns affect the growth and behaviour of large fires when implemented at different rates over the course of five decades. The system consisted of a forest and fuel dynamics simulation module (Forest Vegetation Simulator, FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel treatment optimisation program, and a spatial fire growth and behaviour model to evaluate the performance of the treatments in modifying large fire growth. Simulations were performed for three study areas: Sanders County in western Montana, the Stanislaus National Forest in California, and the Blue Mountains in south-eastern Washington. For different spatial treatment strategies, the results illustrated that the rate of fuel treatment (percentage of land area treated per decade) competes against the rates of fuel recovery to determine how fuel treatments contribute to multidecade cumulative impacts on the response variables. Using fuel treatment prescriptions that simulate thinning and prescribed burning, fuel treatment arrangements that are optimal in disrupting the growth of large fires require at least 1 to 2% of the landscape to be treated each year. Randomly arranged units with the same treatment prescriptions require about twice that rate to produce the same fire growth reduction. The results also show that the topological fuel treatment optimisation tends to balance maintenance of previous units with treatment of new units. For example, with 2% landscape treatment annually, fewer than 5% of the units received three or more treatments in five decades with most being treated only once or twice and ~35% remaining untreated after five decades.

Performance of fuel treatments in modifying behavior and effects of the largest wildfires has rarely been evaluated, because the necessary data on fire movement, treatment characteristics, and fire severity were not obtainable together. Here we analyzed satellite imagery and prescribed fire records from two Arizona wildfires that occurred in 2002, finding that prescribed fire treatments reduced wildfire severity and changed its progress. Prescribed burning in ponderosa pine forests 1–9 years before the Rodeo and Chediski fires reduced fire severity compared with untreated areas, despite the unprecedented 1860-km2 combined wildfire sizes and record drought. Fire severity increased with time since treatment but decreased with unit size and number of repeated prescribed burn treatments. Fire progression captured by Landsat 7 enhanced thematic mapper plus (ETM+) clearly showed the fire circumventing treatment units and protecting areas on their lee side. This evidence is consistent with model predictions that suggest wildland fire size and severity can be mitigated by strategic placement of treatments.

Sampling of 1367 trees was conducted in the Side wildfire (4 May 1996), Bridger-Knoll wildfire (20 June 1996) and Dauber prescribed fire (9 September 1995) in northern Arizona ponderosa pine forests (Pinus ponderosa). Tree mortality was assessed for 3 years after each fire. Three-year post-fire mortality was 32.4% in the Side wildfire, 18.0% in the Dauber prescribed fire, and 13.9% in the Bridger-Knoll wildfire. In the Dauber and Side fires, 95% and 94% of 3-year post-fire mortality occurred by year 2, versus 76% in the Bridger-Knoll wildfire. Compared with trees that lived for 3 years after fire, dead trees in all fires had more crown scorch, crown consumption, bole scorch, ground char, and bark beetle attacks. Logistic regression models were used to provide insight on factors associated with tree mortality after fire. A model using total crown damage by fire (scorch + consumption) and bole char severity as independent variables was the best two-variable model for predicting individual tree mortality for all fires. The amount of total crown damage associated with the onset of tree mortality decreased as bole char severity increased. Models using diameter at breast height (dbh) and crown volume damage suggested that tree mortality decreased as dbh increased in the Dauber prescribed fire where trees were smallest, and tree mortality increased as dbh increased in the Side and Bridger-Knoll wildfires where trees were largest. Moreover, a U-shaped dbh–mortality distribution for all fires suggested higher mortality for the smallest and largest trees compared with intermediate-size trees. We concluded that tree mortality is strongly influenced by interaction between crown damage and bole char severity, and differences in resistance to fire among different-sized trees can vary among sites.

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and twodimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis is used to characterize the seasonal trend in ERC, autocorrelation of residuals, and daily standard deviation and stochastically generate artificial time series of afternoon fuel moisture. Daily wind speed and direction are sampled stochastically from joint probabilities of historical wind speed and direction for the date range of the fire simulation period. Hundreds or thousands of fire growth simulations are then performed using the synthetic fire weather sequences. The performance of these methods is evaluated in terms of the number of ensemble member simulations, one-versus twodimensional fire spread simulations, and comparison with results from 91 fires occurring from 2007 to 2009. Simulations were found to be in consistent agreement with observations, but trends indicate that the ensemble average of simulated fire sizes were consistently larger than actual fires whereas the farthest extent burned by fires was underestimated.