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Our study found that fire perimeter source and fireline buffer width had the largest impact on quantified fireline effectiveness metrics. Misclassification of firelines produced dramatic erroneous results which artificially increased the effectiveness and decreased suppression effort. High-severity fires were shown to be less effective across all fireline types and required higher suppression than most low- and moderate-severity fires.
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Users indicated that the program is viewed as efficient for sharing information about wildfires and documenting management decision rationale. They identified emerging gaps in technical proficiency and the need for specialised training that creates high-level users to help guide teams using the program.
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We developed and applied a spatial optimization algorithm to prioritize forest and fuel management treatments within a proposed linear fuel break network on a 0.5 million ha Western US national forest. The large fuel break network, combined with the logistics of conducting forest and fuel management, requires that treatments be partitioned into a sequence of discrete projects, individually implemented over the next 10–20 years. The original plan for the network did not consider how linear segments would be packaged into projects and how projects would be prioritized for treatments over time, as the network is constructed. Using our optimization algorithm, we
analyzed 13 implementation scenarios where size-constrained projects were prioritized based on predicted wildfire hazard, treatment costs, and harvest revenues.
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Although fire is a fundamental ecological process in western North American forests, climate warming and accumulating forest fuels due to fire suppression have led to wildfires that burn at high severity across larger fractions of their footprint than were historically typical. These trends have spiked upwards in recent years and are particularly pronounced in the Sierra Nevada–Southern Cascades ecoregion of California, USA, and neighboring states. We assessed annual area burned (AAB) and percentage of area burned at high and low-to-moderate severity for seven major forest types in this region from 1984 to 2020. We compared values for this period against estimates for the pre-Euro-American settlement (EAS) period prior to 1850 and against a previous study of trends from 1984 to 2009.
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Black gravel increased mean temperatures of the surface soil by 1.6 and 2.6 °C compared to white gravel in Cheyenne and Boise, respectively, causing 21–24 more days with soil temperatures > 0 °C, earlier cheatgrass germination, and up to 2.8-fold increases in cheatgrass height. Higher seeding density of cheatgrass led to 1.4-fold taller plants on black gravel plots at both sites, but not white gravel at the Boise site, indicating a possible thermal benefit or reduction of water demand due to plant clustering in warmer treatments.
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Here, we examine how the ventenata invasion alters simulated fire across forest-mosaic landscapes of the 7 million ha Blue Mountains Ecoregion using the large fire simulator (FSim) with custom fuel landscapes: present-day invaded versus historic uninvaded. Invasion increased simulated mean fire size, burn probability, and flame lengths throughout the ecoregion, and the strength of these impacts varied by location and scale. Changes at the ecoregion scale were relatively modest given that fine fuels increased in only 2.8% of the ecoregion where ventenata invaded historically fuel-limited vegetation types. However, strong localized changes were simulated
within invaded patches (primarily dwarf-shrublands) and where invasion facilitated fire spread into nearby forests.
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Interactions among species can strongly affect how plant communities reassemble after disturbances, and variability among native and invasive species across environmental gradients must be known in order to manage plant-community recovery. The stress-gradient hypothesis (SGH) predicts species interactions will be more positive in abiotically stressful conditions and conversely, more negative in benign conditions, and the resistance-resilience concept (RRC) may predict where and when invasions will complicate ecosystem recovery. We evaluated how abiotic stress and biotic interactions determine native bunchgrass abundances across environmental gradients using additive models of cover data from over 500 plots re-measured annually for 5 years as they recovered naturally (untreated) after a megafire (>100,000 ha) in sagebrush steppe threated by the invasive-grass and fire cycle.
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Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.
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Wildfire is a natural phenomenon with substantial economic consequences, and its management is complex, dynamic, and rife with incentive problems. This article reviews the contribution of economics to our understanding of wildfire and highlights remaining knowledge gaps. We first summarize economic impacts to illustrate scale and trends. We then focus on wildfire management in three phases: mitigation before fires occur, response during fires, and response after fires. The literature highlights economic interdependencies and spillover effects across fire-prone landscapes as the source of economic inefficiencies and motivation for public institutional response. The literature illustrates the complexity of this problem with its myriad threads, including the trade-offs of living in fire-prone environments, the prospects for using controlled fire and mechanical fuel removal for reducing wildfire severity, the decision-making environment that firefighters face, and the economic consequences of wildfire smoke on health. Economics provides valuable insights, but fundamental questions remain unanswered.
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We examined the financial efficiency and effectiveness of landscape versus community protection fuel treatments to reduce structure exposure and loss to wildfire on a large fire-prone area of central Idaho. The study area contained 63,707 structures distributed in 20 rural communities and resorts, encompassing 13,804 km2. We used simulation modeling to estimate expected structure loss based on burn probability and characteristics of the home ignition zone. We then designed three fuel management strategies that targeted treatments to: 1) the surrounding areas predicted to be the source of exposure to communities from large fires, 2) the home ignition zone, and 3) a combination of the landscape and home ignition zone. We evaluated each treatment scenario in terms of exposure and expected structure loss compared to a no-treatment scenario. The potential revenue from wood products was estimated for each scenario to assess the cost-efficiency. We found that the combined landscape and home ignition zone treatment scenario which treated 5.7% of the study area resulted in the highest overall reduction in predicted exposure (47.5%, 100 structures yr- 1) and predicted loss (69.1%, 57 structures yr- 1). Home ignition zone treatments provided the best predicted economic and per area treated performance where exposure and loss were reduced by one structure by treating 89 and 111 ha per year, respectively, with an annual cost of $33,645 and $73,672. Revenue from thinning was the highest for landscape fuel treatments and covered 16% of the required investment. This work highlighted economic and risk tradeoffs associated with alternative fuel treatment strategies to protect developed areas from large wildland fires.