A Model-Based Framework to Evaluate Alternative Wildfire Suppression Strategies

The complexity and demands of wildland firefighting in the western U.S. have increased over recent decades due to factors including the expansion of the wildland-urban interface, lengthening fire seasons associated with climate change, and changes in vegetation due to past fire suppression and timber harvest. In light of these changes, the use of more wildland fire on the landscape could reduce fuels and form barriers to the spread of future fires while performing forest restoration in some areas. However, the risks, costs and benefits of changing fire response strategy have not been quantified. Here, we identify gaps regarding the ability to simulate alternative wildfire suppression strategies, due to a number of factors including limited data collected on fireline construction, as well as synergies between firefighting resources and resource effectiveness. We present a fire management continuum: at one end lies full suppression of all fires under all circumstances, and at the opposite end lies no suppression of any fires regardless of location or time in season, with a wide array of managed fire options falling in between. Next, we demonstrate the proof-of-concept using a stochastic fire simulation model, FSim, to simulate two alternative fire suppression strategies close to opposite ends of this continuum for the Sierra National Forest of California: (1) business-as-usual, which equates to nearly full fire suppression; and (2) full suppression of human-caused fires and no suppression actions on lightning-caused fires. Results indicate that fire management strategy can substantially affect the number of large fires and landscape burn probabilities, both of which were shown to increase under the second scenario. However, temporal feedbacks are expected to play an important role: we show that increases in burned area substantially limit ignition potential and the extent of subsequent fires within the first five to ten years, especially under the second scenario. While subject to current data gaps and limitations in fire modeling, the methodology presented here can be used to simulate a number of alternative fire suppression strategies, including decisions to suppress or not suppress fires based on location, time of season or other factors. This method also provides basic inputs needed to estimate risks, costs and benefits of various alternative suppression strategies in future work. In future work, uncertainties resulting from current limitations in knowledge can be addressed using techniques such as scenario planning in order to provide land managers with a set of possible fire outcomes.