Fuel treatment effectiveness at the landscape scale: a systematic review of simulation studies comparing treatment scenarios in North America

Abstract

Background The risk of destructive wildfire on fire-prone landscapes with excessive fuel buildup has prompted the use of fuel reduction treatments to protect valued resources from wildfire damage. The question of how to maximize the effectiveness of fuel reduction treatments at landscape scales is important because treating an entire landscape may be undesirable or unfeasible. We reviewed 86 simulation studies that examined landscape-scale fuel reduction treatment effectiveness for landscapes of the USA or Canada. Each of these studies tested effects of fuel reduction treatments on wildfire through comparisons of landscape scenarios differing by treatment design or other attributes. Results from these studies were summarized to assess what they reveal about factors determining fuel treatment effectiveness at landscape scales. Results Qualifying studies focused primarily but not exclusively on forested landscapes of the western USA and ranged in size from 200 to 3,400,000 ha. Most studies showed that scenarios with fuel reduction treatments had lower levels of wildfire compared to untreated scenarios. Damaging wildfire types decreased while beneficial wildfire increased as a result of treatments in most cases where these were differentiated. Wildfire outcomes were influenced by five dimensions of treatment design (extent, placement, size, prescription, and timing) and other factors beyond the treatments (weather, climate, fire/fuel attributes, and other management inputs). Studies testing factorial combinations showed that the relative importance of these factors varied across landscapes and contexts. Conclusions Simulation studies have highlighted general principles of effective fuel treatment design at landscape scales, including the desirability of treating extensive areas with appropriate prescriptions at sufficient frequency to reduce wildfire impacts even under extreme conditions that may be more prevalent in the future. More specific, context-dependent strategies have also been provided, such as a variety of placement schemes prioritizing the protection of different resources. Optimization algorithms were shown to be helpful for determining treatment placement and timing to achieve desired objectives under given constraints. Additional work is needed to expand the geographical scope of these studies, further examine the importance and interactions of driving factors, and assess longer-term effects of fuel reduction treatments under projected climate change.

The Potential for Fuel Reduction to Offset Climate Warming Impacts on Wildfire Intensity in California

“…There is substantial evidence that fuel reduction can be effective at mitigating wildfire risk 24,29 , but studies to date tend to be on small scales, for particular circumstances (e.g., refs. [30][31][32][33][34][35] ), and it is unclear if they generalize to broad spatial scales, if they are consistent for extreme and non-extreme fire weather conditions 36 and to what degree the effects of fuel reduction could counteract projected climate warming 37 .…”

Avoided wildfire impact modeling with counterfactual probabilistic analysis

“…However, the informational basis regarding fuel treatment effectiveness is mixed. Empirical analyses have found that treatments can be effective at reducing fire intensity and severity within treated areas, but evidence of their effectiveness at landscape scales is limited ( Fernandes, 2015 ; Kalies and Kent, 2016 ; McKinney et al, 2022 ; Ott et al, 2023 ; Urza et al, 2023 ). This gap is critical as many existing or proposed treatments are not directly located in the WUI but rather in proximal wildlands, based on the premise that treatments will interrupt fire spread and reduce WUI exposure.…”

“…This gap is critical as many existing or proposed treatments are not directly located in the WUI but rather in proximal wildlands, based on the premise that treatments will interrupt fire spread and reduce WUI exposure. Simulation modeling is widely used to fill that gap, showing how treatments can affect metrics such as landscape burn probability ( Ott et al, 2023 ). However, in almost all cases, simulation modeling is used to evaluate hypothetical future treatments (e.g., Benali et al, 2021 ; Alcasena et al, 2022 ), with few examples that analyze how prior treatment interactions with wildfires may have altered landscape outcomes (e.g., Cheney, 2010 ; Cochrane et al, 2012 ).…”

Wildfire Risk Assessment for Strategic Forest Management in the Southern United States: A Bayesian Network Modeling Approach

“…Prescribed fires are controlled applications of fire used to reduce woody and herbaceous fuels and suppress the potential for wildfires with far greater hazard potential. Prescribed fire is now widely used as a management tool to achieve the social, economic, and ecological benefits of fire while reducing the risks associated with uncontrolled wildfires [12][13][14][15]. Wildfires that burn in areas where prescribed fire has been used to suppress fuels can have lower intensities and extents, cause less damage, and be easier to control [16][17][18][19].…”

“…We collaborated with regional fire management experts to develop a BN model that integrated spatial data to estimate wildfire risk for forests across the Southeastern United States and evaluate the role that prescribed fire can play in managing risk. The Southeastern US serves as a model region for the widespread use of prescribed fire to manage wildfire risks and forest ecological conditions [14,33]. Enhanced investments in risk management, including active management to reduce fuels in forest landscapes, will be required to confront growing risks.…”