Drought and Disturbances as Drivers of Long-Term Ecological Transformation and Risk

Science Center Objects

Forested areas in the Western U.S. that are impacted by disturbances such as fire and drought have increased in recent decades. This trend is likely to continue, with the increase in frequency and extent of wildfire activity being especially concerning. Resource managers need reliable scientific information to better understand wildfire occurrence, which can vary substantially across landscapes...

Forested areas in the Western U.S. that are impacted by disturbances such as fire and drought have increased in recent decades. This trend is likely to continue, with the increase in frequency and extent of wildfire activity being especially concerning. Resource managers need reliable scientific information to better understand wildfire occurrence, which can vary substantially across landscapes and throughout time. However, few scientific models capture this variability, and projections of future potential changes in fire occurrence can include some uncertainty. This uncertainty can limit our ability to anticipate potential wildfire impacts on society and ecological systems. Another method to help managers prepare for the future is to examine post-fire conditions and asses how and if forests might transition to different landscape types after wildfires (e.g. a change from conifer to deciduous forest). Some studies show that post-fire tree regeneration has been limited in many of the areas burned, especially in large high-severity patches, changing the composition of the landcover. However, it is also unclear how common this post-fire state transition is and what thresholds (e.g., fire severity, burn patch size, post-fire weather conditions) predict such transitions.



This research will investigate the impacts that fire disturbances and drought have on the structure and composition of forest ecosystems across the Western U.S. There will be three main areas of focus: 1) simulating interactions among climate, drought, vegetation, and disturbances, like fire; 2) monitoring and predicting post-fire forest vegetation recovery using remote sensing and simulation models, and 3) modeling wildfire occurrence and risk using historical data. This project builds off work previously done under the former USGS LandCarbon program.  



Products from this project will be used to assess past patterns of wildfire risk to homes and project future potential changes in fire occurrence and risk across the conterminous U.S. Outputs from this project will also inform fire management decision-making and can also be used to advance existing predictive technology, including landscape simulation models such as LANDIS-II, to help resource manager better prepare for future conditions.