Scientists at the U.S. Department of Agriculture’s Agricultural Research Service (ARS) and the University of Montana have developed a method for predicting which has the greatest potential for a grassland fire among the more than 60 million acres of the Great Basin.
The predictions come from a model the researchers developed that combines measures of accumulated annual and perennial herbaceous plants that are potential fuels for the fires with recent weather and climate data. When combined, this information can be translated into maps showing the potential for a large wildfire – greater than 1,000 acres – across the Great Basin. These forecasts can also be scaled back to predict fire risks for counties or even individual pastures.
Great Basin rangeland fire probability maps for the rangeland fire season, approximately June through September, are published on the Grassland Analysis Platform. Two new research articles discussing the details and utility of the new model are part of a special issue of Pasture environment and management. The first paper used vegetation data from the Grassland Analysis platform combined with historical fire data from the Burn Severity dataset’s Monitoring Trends dataset to build fire prediction models for the Great Basin using 32 years of historical weather, vegetation and fire data. The second paper expands the work of fire probability from analysis to how practitioners use this information to make decisions for the fire season.
Pasture scientist Chad S. explained. and co-leader in developing the model.
Wildfires usually only need a ignition event, such as a lightning bolt, on most forest sites because they generally have enough plant fuel to burn each year.
“But with grassland fires, whether there’s enough fuel to start a large-scale fire really varies from place to place and year to year across the Great Basin,” Boyd added.
Until recently, prediction of grassland fires was limited by a lack of accurate measurements of how much annual and perennial grasses and grasses were produced each year. But satellite technology and remote sensing have made accurate data easily accessible.
“I was a little surprised that the buildup of herbaceous plants from the previous growing season was the best predictor of large-scale fires,” said Joe T. Smith, University of Montana research scientist and co-author of the model. “This gives something new to focus on combating the spread of invasive, fast-growing annual weeds such as kelp. Cheating in the Great Basin.”
While woody shrubs and trees such as juniper or pine do not increase the odds of a major fire, their place in the fire scene still matters. Shrubs burn hotter, causing more intense fire behavior that puts lives and property at risk and makes bushfires harder to put out.
Unlike weather and terrain, which are two major influencing factors on grassland fires, people can manage available fuel directly and preemptively. New fire probability maps will help land managers prioritize investment in fuel management.
“Maps can be used in conjunction with other planning tools to determine where to focus limited resources before the fire season begins,” Boyd explained. “They can also help guide annual efforts to reduce quality fuels such as weeds, which can reduce the effects of fires on area wildlife and work lands.”