Economic Impacts of Fire and Fire Management

Wildfire processes are spatially and temporally dynamic across long time and large spatial scales, but published theoretical models of wildfire economics have not characterized these dynamics. Spatial and temporal dynamics are important if wildfires consume significant fuels, creating a situation of temporal and spatial dependence. Such dependence implies that current wildfire levels in one location depend on past wildfire levels in the same or neighboring locations, in addition to current time and local space factors. Some recent empirical studies at broad landscape and temporal scales document the magnitude of temporal dependence, manifested statistically as negative temporal autocorrelation. One implication of negative autocorrelation of wildfire processes is that the short-run effects of wildfire management, such as fuels management, fire prevention, and suppression, are larger than their long-run effects. This implies that calculations of economically optimal intervention levels ignoring such autocorrelation would be larger than levels that recognize it. In parts of the US, circumstantial evidence suggests that wildfires were “over-suppressed,” in effect, ignoring the negative autocorrelation of wildfire processes. The end result of over-suppression is that future costs would be much higher than they would have been, had negative autocorrelation been built into decisions at the time of suppression. There is less evidence that fuels have been over-reduced through fuel treatments or that fire prevention education and other prevention activities (e.g., targeted closures of high hazard locations) have been over-applied. The complication for the land management agencies, in adjusting to these realities, is that society has intervened, accepting the reduced annual fire risks created by over-suppression, making it very costly to back away from an over-suppression policy. Typical wildfire damages, excluding suppression, probably exceed $2,000 per hectare in forests near built-up areas, but suppression costs per unit area decline with size. The optimal policy, given current values at risk and suppression costs that vary by fire size, then, may therefore be increased use of fire prevention education that reduces the frequency of some fires near built-up areas, targeted fuel treatments in places with highest values at risk that allow “herding” of wildfires, and a greater focus on point protection of key values. Other opportunities exist in larger scale multiple fire management—strategies to allocate within-season suppression resources across fires within a large management unit. These strategies would be designed to increase the area burned by less intense but fuel-consuming fires over a season and therefore increase the long-run economic productivity of the suppression resources used. Perhaps a great challenge, however, is identifying the policies and programs to achieve this in a way that is political palatable.