• Rocky Mountain Research Station
• 240 West Prospect
• Fort Collins, CO 80526
• (970) 498-1100

Integrated Modeling for Forest Health and Fuel Reduction Decision Support

The first step in this process was to use landscape models to map and assess current fuel conditions, likelihood of fire, and how these conditions are expected to change in the future as a result of vegetation growth and the presence of insects, disease, and wildland fire. The fire behavior models, FARSITE, FLAMMAP, and MTT were used predict fire spread and intensity for the existing landscape conditions for two fire scenarios. Both scenarios assumed burning conditions at the 95 percentile, one assumed ignition from lightning on the western edge of the study area with wind from the west, while the other assumed ignition points in the southern portion of the area with wind from the south. SIMPPLLE was used in this process to predict the spatial likelihood of fire across the landscape for the current conditions and how these conditions will change in the future if there are no management treatments. Changes in vegetation due to bark beetles and other insect and disease disturbances that affect future fuels are included in these simulations. These analyses were initially conducted for the 465,000 Bitterroot Front landscape to identify the Trapper-Bunkhouse area as the area most in need of fuel and forest health restoration treatments. Results were also used to inform treatment locations within the project area.

MAGIS was used to schedule optimal treatment scenarios and calculate resource and economic trade-offs where managing for multiple resource objectives. In developing these treatment schedules, MAGIS integrates input from the fire behavior and disturbance process and balances treatments to modify fire behavior with the location of valued resources - homes, sensitive habitats, and streams while estimating costs and possible revenues over a range of treatment options. These treatment locations guided fieldwork for ground verification and development of the project alternatives.

The next modeling step is to simulate the effects of project alternatives using both SIMPPLLE and the fire behavior models FARSITE, FLAMMAP, and MTT. The results from simulating the treatment alternatives will be compared to the no treatment simulations to predict the effectiveness of treatments in terms of change in fire spread rates and intensity and the likelihood of fire at specific locations across the landscape.

This project gives researchers and managers an opportunity to work together to investigate how to best integrate the use of these diverse models in an Interdisciplinary Team environment to plan and document an integrated project that addresses fuel and forest restoration objectives while considering the economic viability of the project and environmental effects.

More information can be found in: "Integrating Fuel Treatments into Comprehensive Ecosystem Management," Fuels Management - How to Measure Success: Conference Proceedings 2006, 28-30 March; Portland, OR. Proceedings RMRS-P-41, Ft. Collins, CO: USDA Forest Service, Rocky Mountain Research Station. Model information is found at the following websites: FARSITE, FLAMMAP, and MTT (http://farsite.org/); SIMPPLLE (); and MAGIS.