ITHACA, N.Y. -- As small earthquakes can be omens of larger ones andlandslides can be precursors to avalanches, Cornell University geologistshave shown in a computer simulation that forest fires display the samenatural behavior. Their findings, they believe, could be used to predictwhere large forest fires can occur -- and how to prevent them.
The researchers' findings appear in the latest issue of the journal Science (Sept. 18, 1998).
"What is surprising to me is that an event like a forest fire is so similarto other natural events," says Donald L. Turcotte, the M.M. UpsonProfessor of Engineering in the Cornell Department of Geology. "Andhumanity really plays a small role in these events."
Turcotte and his fellow researchers, Bruce D. Malamud, a Fulbright Scholarand visiting lecturer in geology at Cornell, and Gleb Morein, a Cornellgraduate student, built their computer model of forest fires and analyzeddata sets from a number of forests and wildfires from around the world,including Yellowstone National Park.
Until 1972 Yellowstone had a policy of suppressing forest fires. Thisresulted in a large accumulation of dead trees, undergrowth and very oldtrees that became perfect tinder for fires. The researchers contend thatthe large Yellowstone fire of 1988, which burned 800,000 acres, could havebeen prevented if the policy of letting smaller fires burn to completionhad been in place before 1972. The smaller fires would have eliminated theunderbrush and dead wood earlier, thus reducing the likelihood of a largefire, they say.
In analyzing how forest fires start and propagate, the researchers foundthat the frequency distribution of small and medium fires can be used toassess the risk of larger fires, as small tremors are routinely used toassess the risk of larger earthquakes.
Turcotte explains that for natural occurrences there is a return period forevents of different magnitudes. For example, meteorologists classifystorms as 5-year, 10-year, 50-year or 100-year. This is an example ofbehavior on the part of weather. "It's an interesting class of phenomena,"he says. "Small landslides build up to large landslides, and I supposethis model can be applied to something like the stock market, which alsoshows a degree of self-organized critical behavior."
To model forest fires, the scientists developed a computer grid of aforest, then simulated dropping a match. If the match landed on a tree,the tree and its neighbors would burn. If the match landed on an areawithout trees, no fire ensued. Where the grid was packed with trees, alarge fire ensued. The scientists say that the only previous applicationof this type of model was to study measles epidemics in isolatedpopulations.
The scientists ran the model under different scenarios of forest density.Interestingly, for each scenario, the researchers found a range of small tolarge fires and many more small fires than larger ones, which correlateswith the law of a fractal distribution. (Fractal distribution is themagnification of certain things, like the size of a fire, in proportion totheir original size.)
Large forest fires are dominant when the forest is densely populated. Thiswas demonstrated by the researchers when the computer grid was filled withtrees: The fires spanned the grid. This is what happened in YellowstoneNational Park in 1988. The scientists say that forest-fire professionalsnow recognize that the best way to prevent the largest fires is to allowthe small and medium fires to burn.
The scientists found that actual forest fires have fractal distributionsover many orders of magnitude. However, the environmental- andhuman-related variables that affect the size of wildfires are many,including the proximity and type of combustible materials, weatherconditions and firefighting efforts to extinguish certain fires, theresearchers say.
"Despite these complexities, the predicition capability of the forest firemodel appears to be robust," says Turcotte.
The Science article is titled "Forest Fires: An Example of Self-OrganizedCritical Behavior." Funding for the research was provided by a grant fromthe National Aeronautics and Space Administration (NASA).
Materials provided by Cornell University. Note: Content may be edited for style and length.
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