Fire & Economics
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To evaluate forest restoration and fuel treatment benefits and costs, we conducted a meta-analysis of benefit-cost ratios for restoration benefit types documented in the literature for Western U.S. dry mixed conifer forests at risk of uncharacteristic wildfires. A total of 120 observations were collated from 16 studies conducted over the last two decades, with benefits ranging from enhanced ecosystem services to extensively avoided wildfire costs. Significant variation in the value of restoration and fuel treatment benefit types was found, indicating that restoration benefits differ in value based on societal importance. Overall, 17 individual benefit types were aggregated to show that in the most valuable and at-risk watersheds, every dollar invested in forest restoration can provide up to seven dollars of return in the form of benefits and provide a return-on-investment of 600%.
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There is a compelling business case for additional investment in enhanced data acquisition and analysis to better assess the safety and effectiveness of wildfire management. As a result of long-standing data gaps, fire management organizations cannot recreate what happened during fire operations, leading to persistent challenges in: (1) demonstrating the nature and magnitude of suppression investments, (2) assessing what did and didn’t work, (3) improving future effectiveness based on what was learned, and (4) understanding and preventing firefighter injuries and deaths. Credible analysis of the safety and effectiveness of wildfire management requires a clearer understanding of strategic, tactical, and operational objectives. Further required is information on firefighting resource location and use at high-resolution spatial and temporal scales. To facilitate timely analysis, the relevant data need to be archived, digital, accessible, and searchable. In December 2021, RMRS entered into a Cooperative Research and Development Agreement (CRADA) with a private company, Ignis Technologies, interested in capturing and availing better real-time data and analytics around wildland firefighting response and resource use. We agreed on common goals of (1) enhancing situational awareness with cutting-edge technology and (2) amassing historically elusive data needed to advance research into suppression effectiveness and performance measurement in wildland fire management. This agreement provides a vehicle for greater collaboration with the interagency fire data community. We are currently working with interagency representatives of the National Wildfire Coordinating Group and Wildland Fire Information Technology to ensure that the data captured through our collaborative efforts are incorporated into the Interagency Data Management Environment (IDME), which is a modern architecture that enables governed, self-service analytics across wildland fire.
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Public agencies and organizations often deliver financial assistance through cost sharing, in which recipients contribute some portion toward total costs. However, cost sharing might raise equity concerns if it reduces participation among populations with lower incomes. Here, we revisit a past study using a richer dataset (n=1,689) to assess whether stated income levels affect survey respondents’ willingness to participate in a cost share program for vegetation reduction to mitigate wildfire risk in western Colorado. Results show that residents with lower incomes are less likely to participate even though they can choose to contribute 0% toward a cost share. Residents reporting incomes less than $50,000 are 11 percentage points less likely to participate than those reporting incomes of $200,000 or more. They also are willing to pay a lower share (26 percentage points less) if they do participate. Results indicate potential economic equity concerns from the use of such programs.
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We present an easily replicable approach to calculate the economic cost from carbon released instantaneously from wildfires at state and county level (US). Our approach is straightforward and relies exclusively on publicly available data that can be easily obtained for locations throughout the USA. We also describe how to apply social cost of carbon estimates to the carbon loss estimates to find the economic value of carbon released from wildfires. We demonstrate our approach using a case study of the 2017 Eagle Creek Fire in Oregon. Our estimated value of carbon lost for this medium-sized (19,400 ha) fire is $187.2 million (2020 dollars), which highlights the significant role that wildfires can have in terms of carbon emissions and their associated cost. The emissions from this fire were equivalent to as much as 2.3% of non-fire emissions for the state of Oregon in 2020.
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Costs associated with the Schultz Fire continued to accrue over 10 years, particularly those associated with post-wildfire flooding, totalling between US$109 and US$114 million. Suppression costs represented only 10% of total costs.
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The results project increases in the number of simultaneous 1000+ acre (4+ km2) fires in every part of the Western USA at multiple return periods. These increases are more pronounced at higher levels of simultaneity, especially in the Northern Rockies region, which shows dramatic increases in the recurrence of high return levels.
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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.
We systematically selected and reviewed 20 thinning studies to analyze key variables affecting machine productivity and harvesting costs. The average cost of forest thinning was lowest for a mechanized whole-tree thinning operation at $21.34/ton or $2,075/ha. Feller-bunchers and skidders showed the highest productivity in felling and extraction machines, respectively.
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This report describes the full range of costs associated with wildland fire in the Western United States (U.S.) to help inform leaders and policymakers working to improve wildfire response and mitigation. Wildfire cost information has, in the past, primarily focused on suppression costs and structure losses; however, as this report shows, there are many other types of costs relating to values such as human health, water supply, transportation, the labor market, and local economics, among others. These less-recognized costs are massive in aggregate.