Understanding Extreme Wildfire Events to Manage for Fire-Resistant and Resilient Landscapes Active
Increasing wildfire activity in the western US poses profound risks for human communities and ecological systems. Recent fire years are characterized not only by expanding area burned but also explosive fire growth. In 2020, several fires grew by >100,000 acres within a 24-hour period. Extreme single-day fire spread events such as these are poorly understood but disproportionately responsible for wildfire impacts: just the top 1% of fire spread events account for 20% of annual area burned. Extreme events are linked to warmer and drier conditions, and we project that their frequency could double under future climate.
Extreme fire spread events defy suppression and overcome traditional fuels reductions treatments, compelling new approaches to management. Earlier studies have shown that fire itself can be an effective treatment to reduce subsequent fire spread. Further, observations suggest that some forest types such as aspen can impede fire spread. Thus, managers may be able to strategically use prescribed fire to reduce fuels and promote aspen forests in ways that reduce the likelihood of extreme burning, safeguarding forests and reducing risks to nearby human communities.
The purpose of our research is twofold. First, we will use new satellite-based maps of daily fire spread to examine associations with environmental factors (weather, climate, vegetation/fuels, topography, and management) to understand what conditions promote or inhibit extreme fire spread events. Second, we will use this understanding to work with land management partners in the headwaters of the Colorado River to create maps and models to better design prescribed fire treatments to reduce the risk of extreme fire spread. These approaches could be applied elsewhere, and we will host a workshop with land managers to identify opportunities and barriers across the region. Fire may be inevitable, but we have the opportunity to choose when, where, and how it burns.
- Source: USGS Sciencebase (id: 626c53c2d34e76103cd2d1ee)
Increasing wildfire activity in the western US poses profound risks for human communities and ecological systems. Recent fire years are characterized not only by expanding area burned but also explosive fire growth. In 2020, several fires grew by >100,000 acres within a 24-hour period. Extreme single-day fire spread events such as these are poorly understood but disproportionately responsible for wildfire impacts: just the top 1% of fire spread events account for 20% of annual area burned. Extreme events are linked to warmer and drier conditions, and we project that their frequency could double under future climate.
Extreme fire spread events defy suppression and overcome traditional fuels reductions treatments, compelling new approaches to management. Earlier studies have shown that fire itself can be an effective treatment to reduce subsequent fire spread. Further, observations suggest that some forest types such as aspen can impede fire spread. Thus, managers may be able to strategically use prescribed fire to reduce fuels and promote aspen forests in ways that reduce the likelihood of extreme burning, safeguarding forests and reducing risks to nearby human communities.
The purpose of our research is twofold. First, we will use new satellite-based maps of daily fire spread to examine associations with environmental factors (weather, climate, vegetation/fuels, topography, and management) to understand what conditions promote or inhibit extreme fire spread events. Second, we will use this understanding to work with land management partners in the headwaters of the Colorado River to create maps and models to better design prescribed fire treatments to reduce the risk of extreme fire spread. These approaches could be applied elsewhere, and we will host a workshop with land managers to identify opportunities and barriers across the region. Fire may be inevitable, but we have the opportunity to choose when, where, and how it burns.
- Source: USGS Sciencebase (id: 626c53c2d34e76103cd2d1ee)