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Simulation of Long-Term Landscape-Level Fuel Treatment Effects on Large WildfiresAuthor(s): Mark A. Finney; Rob C. Seli; Charles W. McHugh; Alan A. Ager; Berni Bahro; James K. Agee
Source: In: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 125-147
Publication Series: Proceedings (P)
Station: Rocky Mountain Research Station
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DescriptionA simulation system was developed to explore how fuel treatments placed in random and optimal spatial patterns affect the growth and behavior of large fires when implemented at different rates over the course of five decades. The system consists of a forest/fuel dynamics simulation module (FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel treatment optimization program, and spatial fire growth and behavior model to evaluate the performance of the treatments in modifying large fires. Simulations were performed for three study areas: Sanders County in western Montana, the Stanislaus National Forest in California, and the Blue Mountains in eastern Oregon. Response variables reported here include: (1) fire size distributions, (2) large fire spread rates, and (3) burn probabilities, and all revealed the same trends. For different spatial treatment strategies, our results illustrate how the rate of fuel treatment (percentage of land area treated per decade) competes against the rates of fuel recovery to determine how fuel treatments accrue multi-decade cumulative impacts on the response variables. Using fuel treatment prescriptions that involve thinning and prescribed burning, even optimal treatment arrangements (designed to disrupt the growth of large fires) require at least 10% to 20% of the landscape to be treated each decade. Randomly arranged units with the same treatment prescriptions require about twice that rate to produce the same effectiveness. The results also show that the fuel treatment optimization tends to balance maintenance of previous units with treatment of new units. For example, with 20% landscape treatment, fewer than 5% of the units received 3 or more treatments in 5 decades with most being treated only once or twice and about 35% remaining untreated the entire planning period.
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CitationFinney, Mark A.; Seli, Rob C.; McHugh, Charles W.; Ager, Alan A.; Bahro, Berni; Agee, James K. 2006. Simulation of Long-Term Landscape-Level Fuel Treatment Effects on Large Wildfires. In: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 125-147
Keywordsfire, fire ecology, fuels management, simulation system, large wildfires, forest/fuel dynamics simulation module, FVS, fuel treatment prescriptions
- Simulation of long-term landscape-level fuel treatment effects on large wildfires
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