An Abstract submitted to: The 2nd International Wildland Fire Ecology and Fire Management Congress, November 16-20, 2003

by Evan Mercer, Jeff Prestemon, David Butry, John Pye*

Recently, wildfires in the United States have resulted in total damages and costs that exceed billions of dollars annually. This has resulted in controversial proposals by land managers and policy makers to dramatically increase the amount of prescribed burning and other kinds of vegetation management to reduce the risk of wildfire. Yet, to date, there have been very few empirical studies of the impacts of fuel reduction treatments on actual wildfire risk. Most studies of the efficacy of fuels reduction for wildfire risk reduction are derived from extrapolations of how fires burn at fine scales. Rarely, have studies examined how wildfire risk relates to human activities, vegetation management, and land use patterns. We use a cross-sectional, time series data set of wildfires and prescribed burning permits for the state of Florida to estimate two wildfire risk functions that estimate the risk of wildfire acreage and severity as a function of weather/climate, prescribed burning history, wildfire history, timber harvest history, ecosystem type and housing density. Then, we apply this wildfire risk function to develop an economic optimization model to estimate the optimal amount of prescribed burning to minimize the total costs of wildfire (suppression and damages) plus prescribed burning costs across a landscape. Using Monte Carlo simulations of 20 fuels reductions policies, we apply the model to estimate the optimal amount of prescribed burning to produce the lowest net cost of wildfire for Florida counties.

*All authors are members of the Economics of Forest Protection and Management Work Unit, Southern Research Station, USDA Forest Service, PO Box 12254, 3041 Cornwallis Road, Research Triangle Park, NC.