Summer 2004

CURRENT RESEARCH
Research Helps Analyze, Minimize Forest Fire Risks

A recently completed multi state study at Mississippi State University (MSU) will help forest and wildlife 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 the Southeast. 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 to be lost in flames nationwide. While most fires occur in the West, the South is also at high risk for potentially destructive fires, he added.

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 United States 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.
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.

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 Geographic Information Systems, the university team developed an equation to predict fire probability.

“Using readily available data, we were able to identify where efforts are most needed to limit the impact of wildfires,” added Munn.