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Fire, Fuel and Smoke

Projects

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.
In April, 2015 the Helena National Forest (HNF) requested that the Fire Modeling Institute conduct a wildfire probability modeling and risk assessment study to analyze proposed fuel treatments in the project area. The HNF requested this study include modeling the probability of burning, potential fire behavior, and identification of areas where large fires and/or fires potentially destructive to structures were most likely to originate.
Effective and efficient risk-based management requires integrated knowledge, systems and planning tools that explore the interaction of the full range of land and fire management activities. The Wildfire Risk Management team is working to develop and demonstrate the power of integrating fire-risk science across the full range of fire management activities. This work will include the first pilot study of changes in wildfire risk across time, using the prototype LANDFIRE time series dataset, created specifically for the study landscape.
Synergistic interactions of climate change, mountain pine beetle infestations, and wildfire are likely to catalyze landscape-scale changes in vegetation distributions, successional stage, forest structure, and wildlife habitat suitability. Our research will provide forest managers with information they need to project changes to habitat suitability for wildlife under a range of alternative climate and management scenarios.
This work provides an overview of sources of data for United States wildfire activity analyses and highlights major reporting biases, inconsistencies, and uncertainty within data source.  
The Fire Effects Information System (FEIS) provides scientific information for resource management, restoration, rehabilitation, and fire management. FEIS continues to improve its service to managers by providing new and updated products and a new user interface is currently under development.

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