Just released analyses by USDA Forest Service researchers reveal underlying patterns in wildland arson. Research forester Jeff Prestemon and economist David Butry, both from the FS Southern Research Station economics unit at Research Triangle Park, NC, have developed a model that can help law enforcement agencies better predict where and when fires might be set in wildland areas and adopt strategies to reduce the risk of arson.
Over 1.5 million fires are set by arsonists each year in the United States, resulting in over $3 billion in damages. Arson is a leading cause of wildfire in several heavily populated states, including California and Florida. Since wildland arsonists often set fires near homes and roads, arson wildfires cause a disproportionate amount of the damage attributed to wildfire in general. Several recent large wildfires were intentionally set, including the Hayman fire near Denver in 2002, which caused damages exceeding $100 million.
Criminals often commit multiple crimes in a short time frame, a documented phenomenon that researchers call temporal clustering. Temporal clustering of arson events can also be a result of copycat behavior. Property and violent crimes often have a spatial clustering component, also, with crime concentrated in neighborhoods. In a pair of studies, Prestemon and Butry set out to test whether spatio-temporal clustering also appeared in wildland arson. Their research, which described the firesetting process in the context of the economics of crime, also examined whether socioeconomic factors are related to wildland arson in ways identified by criminologists.
"Even though the economic damages created by wildland arsonists are often staggering, research into the factors that contribute to it has been limited to a few published studies," says Prestemon. "Models of wildland arson have mostly related firesetting to weather, seasonal trends, and law enforcement, ignoring the role of the socioeconomic variables used to predict other types of crime."
"At the same time, no one has been able to identify the spatio-temporal dimensions of wildland arson that we found," declared colleague David Butry. "Our findings have uncovered a new avenue of fire research, deepened our understanding of arsonists' behaviors, and revealed another way in which humans and society interact with our environment."
In one study, the researchers evaluated wildland arson as both an annual and a daily process. Their annual model revealed the influence of law enforcement, fuels, poverty, and labor conditions on the rates of ignitions observed in all of the counties in Florida during the period 1995 to 2001. The researchers uncovered the fine temporal pattern of arson by analyzing arson in nine high-arson counties scattered across the state over the same time frame, but sliced into days instead of years. This model identified temporal clustering that lasted up to 11 days--implying higher risk of repeat arson ignitions for 11 days following the initial fire. This kind of pattern had never before been found in any research into human-ignited wildfires.
In the second study, Prestemon and Butry measured the spatial as well as temporal clustering of arson wildfires using daily information for the six Census tracts in Florida with the greatest arson activity. Their statistical results showed that an arson event in one Census tract was related to arson in the previous two days in neighboring tracts and the previous ten days in the same tract.
"So not only did we confirm our finding from the previous study, that arson clusters in time, but we also showed that it clusters in space over time," adds Butry. "In other words, arson events in one tract may be used to predict future ignitions in the same or adjacent tracts for several days." When the two studies are taken together, a principal finding is that wildland arson has spatio-temporal clustering similar to patterns found for other types of crime.
"Combining this principal finding with our data on law enforcement led to our second finding, that there are strategies that law enforcement can use to prevent wildland arson," says Prestemon. "They can closely monitor areas where fires have been set before. They can also increase arson enforcement on days of the year when events are more common, and during droughts."
A third finding was that locations with difficult economic conditions--low wages and high poverty rates--have higher rates of wildland arson, which is consistent with an economic model of crime. Fourth, forest management activities are also related to wildland arson, with fuel reductions from prescribed burning and other wildfires correlated with lower arson rates. "This finding is also consistent with an economic model of wildland arson crime, where lower fuels increase the cost of successfully starting fires," says Prestemon.
The next step is to test the model in other locations to see if the statistical results hold true outside of Florida and to conduct new research into arsonists' behavior. "While we have examined and found similar firesetting patterns in California, we think we need to direct some of our effort into understanding who arsonists are and what, precisely, makes them behave as they do," says Butry. "If we could add feedback from convicted wildland arsonists, we could really enhance our understanding of how they choose where and when to set fires. Incorporating this information into the model would raise its predictive value to law enforcement."
"Time to Burn: Modeling Wildland Arson as an Autoregressive Crime Function," by Jeffrey P. Prestemon and David T. Butry was published in the August 2005 issue of the American Journal of Agricultural Economics, and is available in full text at http://www.srs.fs.usda.gov/pubs/20631
"Spatio-temporal wildland arson crime functions," by David T. Butry and Jeffrey P. Prestemon, was presented at the Annual Meeting of the American Agricultural Economics Association, July 26-29, 2005, Providence, Rhode Island, is available in full text at http://www.srs.fs.usda.gov/pubs/9537
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