Long Term Recovery After Wildfire



Many large fires have occurred in recent decades across the western U.S. and projections predict this trend to continue due to warmer and drier climate conditions. Extensive areas have and will burn severely with high overstory mortality. Long term (> 10 years) response in fuel loads and vegetation composition after large and severe wildfires has not been widely researched.  Accurate estimates of fuel conditions and vegetation recovery rates of various ecosystems with time since the last burn can assist fuel and fire management decisions, and understanding vegetation response trajectories based upon burn severity and other post-burn indicators can increase our ability to effectively prioritize management options to address long-term fuel and fire management objectives.

We are sampling post-fire fuel and vegetation, stratified by burn severity, across five fire-adapted ecosystems in the western U.S. including Alaska. The 15 wildfires selected for field sampling occurred 7-15 years previous; decomposing snags are currently falling at rapid rates to alter fuel loading conditions and reburn potential. We are linking these field measures of fuel and vegetation with map products generated from analysis of 1984-2012 Landsat image time series using the Trends in Disturbance and Recovery (LandTrendr) technique to infer fuel and vegetation response at the landscape level. Our results will provide fuel and fire managers with spatially explicit maps regarding fuel loads, reburn potential, invasive species establishment, and plant species diversity 7-15 years post-fire. Our project will deliver improved geospatial information needed by forest managers to manage post-fire ecosystem recovery and by fuel and fire managers to plan for and respond to future fires. Further, we will use these data in a workshop with land managers focused on fire extent and burn severity of subsequent fires under alternative landscape-scale fire management scenarios based on our data, and share broader implications of our work via webinars and publications. Accurate estimates of post-fire succession and fuel build-up becomes particularly important to wildland fire management via the Landscape Fire and Resource management Planning Tools Project (LANDFIRE, www.landfire.gov), which is a long-term, multi-partner project providing nation-wide spatial data layers of vegetation and fuel characteristics. LANDFIRE spatial data are instrumental for fire behavior predictions on every fire in the U.S. via the Wildland Fire Decision Support System (WFDSS, www.wfdss.gov). The data collected via this project will contribute immensely to the scheduled bi-annual updates of the LANDFIRE database, models, and spatial layers and will inform fire behavior predictions decision making in incident management via WFDSS.

03-Hayman-fire.jpgAreas within the 2003 Hayman fire of Colorado that burned at low (left), moderate (mid), and high (right) severity. The photos were taken in June 2015.