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  Journal of the International Association of Wildland Fire
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Article << Previous     |     Next >>   Contents Vol 16(6)

Simulation of long-term landscape-level fuel treatment effects on large wildfires

Mark A. Finney A E, Rob C. Seli A, Charles W. McHugh A, Alan A. Ager B, Bernhard Bahro C, James K. Agee D

A USDA Forest Service, Missoula Fire Sciences Laboratory, PO Box 8089, Missoula, MT 59808, USA.
B USDA Forest Service, Pacific Northwest Research Station, Western Wildland Environmental Threat Assessment Center, 3160 3rd Street NE, Prineville, OR 97754, USA.
C USDA Forest Service, Pacific Southwest Region – FAMSAC, 3237 Peacekeeper Way McClellan, CA 95652, USA.
D University of Washington, College of Forest Resources, Seattle, WA 98195, USA.
E Corresponding author. Email: mfinney@fs.fed.us
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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.

Keywords: fire modelling.

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