Using Dynamic, Fuels-Based Fire Probability Maps to Reduce Large Wildfires in the Great Basin

Abstract

Spatial and temporal dynamics of rangeland fuels is a primary factor driving large wildfires. Yet detailed information capturing variation in fine fuels has largely been missing from rangeland fire planning and fuels management. New fuels-based maps of Great Basin rangeland fire probability help bridge this gap by coupling dynamic vegetation cover and production data from the Rangeland Analysis Platform with weather and climate data to provide annual forecasts of the relative probability of large wildfire. In this paper, we review these new fuels-based maps and discuss implications for prefire planning, preparedness, and strategic fuels management. Examining patterns of fire probability through time reveals high spatial and temporal variation in risk of large wildfires across the Great Basin. Certain areas are chronically impacted with high fire probability most years, while others have more sporadic or low probability of large fire annually. Maps confirm previous research that the recent increase in large fire risk in the region is highly associated with invasive annual grasses, but total aboveground herbaceous production (including perennials) continues to be a primary predictor of fire probability. Fuels-based fire probability maps can be used alongside existing data sources and prioritization frameworks by fire and fuels managers to inform questions of 1) what kind of fire year might this be, 2) where large fires are most likely to occur given an ignition, and 3) where resources should be focused. We provide examples of how maps can be used to improve prefire preparedness and planning to enhance suppression, facilitate annual targeting of fine fuels reductions, and support land use planning for implementation of landscape-scale fuels management. Proactively incorporating this new information into rangeland fire and fuels management can help address altered fire regimes threatening the region's wildlife and working lands.