A recently completed multi-state study at Mississippi State will help forest managers better predict fire risks and patterns in the South.
The analysis by the university's Forest and Wildlife Research Center covered more than 100 million acres in Alabama, Arkansas, Louisiana, Mississippi, Tennessee, and eastern Oklahoma and Texas. The finished project is expected to provide a powerful planning instrument in the arsenal of fire fighting tools for forest managers.
"The study area includes young pine and mixed pine and hardwood under 10 years old, which have the highest potential for wildfires," said project investigator Ian Munn.
The professor of forestry said the 2002 fire season alone caused more than seven million acres lost in flames nationwide. While most fires occur in the West, the South also is at high risk for potentially destructive fires, he added.
"We wanted to look at fire potential over several Southern states, as forest fires know no boundaries,” Munn said. "Few studies have looked at fire occurrence over multi-state regions.”
To analyze the area, the MSU researchers developed a geographic information system with both forest inventory analysis data collected by the USDA Forest Service and U.S. census data that provided demographic characteristics of the region.
"The geographic information system helps organize and analyze the complex spatial relationships among multiple factors of importance,” said associate professor David Evans, project co-investigator.
"Variables such as vegetation, topography, weather, management activity, residential pattern, and location all can have an impact on fires,” Evans explained.
Their conclusion: highest-risk areas in the South are public forests, urban-forest interface locations and young pine and mixed stands, each with potentially serious hazard and damage consequences in the event of major fires.
Evans said the team gave particular attention to the distance between forest and urbanized areas using GIS. Wildfires are more likely to occur near developed areas where human activity, either accidental or deliberate, can lead to high rates of fire.
To analyze the data, the MSU scientists classified forest fires into three categories: natural fires, accidental and/or arson fires, and person-controlled fires or prescribed fires.
Munn said person-caused forest fires--whether prescribed or accidental/arson--represent "more than two-thirds of all forest fires.” By combining the forest service and census data into GIS, the university team developed an equation to predict fire probability.
"The geographic information system technology, combined with the modeling equation, can identify and map the levels of fire potential,” Evans said.
Added Munn: "Using readily available data, we were able to identify where efforts are most needed to limit the impact of wildfires.”
For more information on the study, contact Munn at (662) 325-4546 or email@example.com.