Research by the US Department of Agriculture (USDA) Forest Service’s Southern Research Station finds that the addition of fine-scale data into existing forest management tools could create useful, dynamic fire-behavior models to help forest managers determine where and how to deliberately set fires to help reduce wildland fires, promote forest restoration, and improve wildlife habitat. To make these prescribed fires most effective, land managers must accurately identify and prioritize burn areas as a result of budget constraints and increased public concerns. Although there are tools available for these tasks, they aren’t sufficiently detailed for use other than at the state or regional levels. The tools traditionally rely on sparse plot inventories – which are typically used in forestry to estimate tree stands -- and data from satellites, which are inadequate for use with smaller managed areas. The USDA researchers developed fuel-load equations -- estimates of how living vegetation and debris in a forest, such as leaves, underbrush, deadwood, and duff, could feed a fire -- to create custom models based on actual data. They also created an easy-to-use statistical tool that lets land managers prioritize prescribed-burn areas. They published their work in several articles in a special edition of Forest Ecology and Management. (EurekAlert)(USDA Forest Service Southern Research Station)(Forest Ecology and Management)
