You are here

Fire, Fuel and Smoke

Projects

The ecological, economic and health and safety concerns surrounding wildland fires are driving the need to better understand climate-fire interactions.
The ecological, economic, and health and safety concerns surrounding wildland fires are driving the need to better understand climate-fire interactions.
Exploring linkages between live wildland fuels, ignition, combustion and potential fire behavior.
Many large fires have occurred in recent decades across the western United States and projections predict this trend to continue with increasingly warmer and drier conditions, meaning extensive areas have and will burn severely. Accurate estimates of fuel conditions and vegetation recovery rates of various ecosystems with time since last burn would assist fuel and fire management decisions. Understanding vegetation response trajectories based upon burn severity and other post-burn indicators will increase our ability to effectively prioritize management options and planning to address long-term fuel and fire management objectives.
The cumulative area of LiDAR collections across multiple ownerships in the northwestern United States has reached the point that land managers of the U.S. Forest Service (USFS) and other stakeholders would greatly benefit from a strategy for how to utilize LiDAR for regional aboveground biomass inventory. The need for Carbon Monitoring Systems (CMS) can be more robustly addressed by using not only available NASA satellite data products, but also commercial airborne LiDAR data collections.
This project seeks to address two key scientific questions: (1) Are emission factors for CO2, CO, CH4, NOX, PM2.5, and BC significantly dependent on either fuel moisture or fuel bed structure? and (2) Can fuel moisture and fuel bed structure serve as independent variables for empirical models that reliably predict these emission factors?
In this study, we determined the locations of wildfire-derived emissions and their aggregate impacts on Salt Lake City, Utah, a major urban center downwind of the fires. The USFS Rocky Mountain Research Station’s new Wildland Fire Emission Inventory Version 2 model was used to determine the location and timing of wildfire emissions.
Over the past 20 years, we have been monitoring mortality rates for ponderosa pine trees in the Blue Mountains of northeastern Oregon since we removed a fire-scarred partial cross-section from them. We suggest that sampling live, fire-scarred ponderosa pine trees remains an important and generally non-lethal method of obtaining information about historical fires that can supplement the information obtained from dead fire-scarred trees.
In 2015, analysts with Fire Modeling Institute (FMI) continued to be involved with application of a wildfire risk assessment framework developed largely by RMRS scientists from both the Fire, Fuel, and Smoke Science Program and the Human Dimensions Program. The risk assessment framework is useful for multiple reasons: it provides a means to assess the potential risk posed by wildfire to specific highly valued resources and assets (HVRAs) across large landscapes, and it also provides a scientifically-based foundation for fire managers to think strategically and proactively about how to best manage fire and fuels on their landscapes in a way that integrates with broader land and resource management goals.  
Many scientists from the Rocky Mountain Research Station Fire, Fuel, and Smoke (FFS) program are intimately involved with various aspects of fire management, including both prescribed fires and wildfires. These activities provide operational experience and the opportunity to observe fire in many different vegetation types. FFS employees have worked on lands managed by the National Park Service (NPS), U.S. Fish and Wildlife Service (FWS), Bureau of Land Management (BLM), Forest Service (USFS), Colville Agency, Yakama Agency, State of Idaho, State of Alaska, and the Clearwater-Potlatch Timber Protective Association. Explore the work that each of our FFS employees participated in.

Pages