Lessons learned from actual implementations of landscape fuel treatment projects: Modeled fire behavior impacts and implications for future forest landscape planning

Background/Question/Methods

The regional assessment of fire hazard and fuel loads in the 2004 Sierra Nevada Forest Plan Amendment identifies modifying wildland fire behavior as a management priority. The preferred alternative is to apply strategic fuel management at the landscape level. One of the objectives of the Sierra Nevada Adaptive Management Project (SNAMP) is to evaluate the effectiveness of strategic fuel treatments (known as SPLATs) in reducing potential fire behavior and improving forest health. The defining characteristic of a SPLAT is that each treatment is part of a strategic pattern which slows and moderates the wildfire. Some factors influencing SPLAT location include: severe fire behavior potential, proximity of threatened and endangered species habitat (i.e., California spotted owl and Pacific fisher), and the presence of economic values.

We used two mixed conifer forest sites in the northern (Last Chance) and southern (Sugar Pine) Sierra Nevada, California. Fuel reduction treatments were implemented at both sites, including thinning, mastication, and prescribed fire, dependent upon forest conditions and wildlife habitat requirements. We used a network of geo-referenced field plots, measuring pre- (2007-2008) and post-treatment (2012-2013) forest conditions, and airborne discrete Lidar to develop landscape vegetation classification, forest structure, and fuel model maps required for our fire behavior modeling.

Our analytic approach was to simulate forest vegetation development and fire interactions for several decades into the future. ArcFuels, a fuels treatment planning tool, integrates a few widely used models for: 1) forest stand dynamics – Forest Vegetation Simulator, and 2) fire simulations – Farsite/FlamMap, to quantify the effects of fuel treatments on forest structure and potential fire behavior over time. 

Results/Conclusions

Fuel treatments effectively reduced landscape-level simulated fire behavior, more so at Last Chance compared to Sugar Pine. Some reasons for this include amount of treated area (14.4% for Last Chance and 5% for Sugar Pine), intensity of treatments (e.g., more basal area removed at Last Chance), and spatial arrangement of treatments. Similarly, treatments had a larger and longer impact on reducing fire behavior through 30 years of simulated forest growth at Last Chance.

Fuel treatment scale and intensity should have the capacity to modify landscape fire behavior for several years, and monitoring is required to realize full impacts to resources. Opposing priorities may complicate such landscape scale projects involving multiple agencies, stakeholders, and scientific disciplines. Integration enables multiple objectives to be assessed and tradeoffs evaluated, allowing for more informed land management decisions.