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This study explores the relationship between wildfire exposure, social vulnerability, and community resilience across the 26 states east of the Mississippi River. This work centers around one research question: are there spatial differences in wildfire exposure that disproportionately impact disadvantaged communities in the Eastern United States over the recent period (2000–2020)? Employing remotely sensed wildfire data and ancillary datasets, we analyze and map the extensive wildfire exposure in the Eastern United States and compare it with spatial metrics of social vulnerability and community resilience to examine the social burdens of wildfire exposure in the Eastern U.S. A discernible wildfire exposure pattern emerges, with the Southeast bearing the highest exposure levels, largely attributed to human-caused and prescribed burning. By establishing a measure of disadvantaged counties using social vulnerability and community resilience, we identify regions where wildfire exposures could have the most adverse impact—areas characterized by highly vulnerable populations and limited community capacity to respond effectively to potential events. In evaluating wildfire risk, we conclude that considering not only exposure levels but also the inclusion of disadvantaged areas (incorporating social vulnerability and community resilience) is essential for understanding the disparate impact of wildfires on individuals and the communities where they live. [ABSTRACT FROM AUTHOR]

Large wildfires are increasing across numerous regions of the globe. While the West has remained a primary focus of wildfire research and resources in the U.S., recent signals suggest that wildfire risk is increasing in the eastern U.S. as well. We conducted an in‐depth assessment of large (>200 ha) wildfire regime characteristics (size, number, total hectares burned, seasonality, probability of occurrence, and ignition source) over a 36‐year period across the Eastern Temperate Forests of the U.S. to quantify geographic patterns in large‐wildfire regime and identify changing spatio‐temporal large wildfire patterns. We found increases in large wildfire size, occurrence, number, and total hectares burned in the southern and eastern regions of the Eastern Temperate Forests. In contrast, large wildfires declined or were minimal in northern ecoregions. We demonstrate increasing large wildfires across some of the most populated regions of the United States. Plain Language Summary: Large wildfires are increasing across numerous regions of the globe. While the western U.S. has remained a primary focus for wildfire research and resources, recent signals suggest that wildfire risk is also increasing in the eastern U.S. We assess patterns and changes in large (>200 ha) wildfire size, number, total hectares burned, seasonality, probability of occurrence, and ignition source over 36 years in the Eastern Temperate Forests, a region comprising most of the eastern U.S. We found that large wildfire size, occurrence, number, and total hectares burned increased in the southern and eastern portions of the Eastern Temperate Forests. In contrast, large wildfires declined or there were too few wildfires to assess in northern portions of the Eastern Temperate Forests. Our findings suggest the potential for increasing wildfire risk across some of the most populated regions of the U.S. Key Points: Large wildfires are increasing in portions of the eastern U.S.The southern and eastern regions experienced the greatest increases in large wildfire number, occurrence, size, and total hectares burnedLarge wildfire seasonality shifted across the Eastern Temperate Forests [ABSTRACT FROM AUTHOR]

Wildfire occurrences have increased and are projected to continue increasing globally. Strategic, evidence-based planning with diverse stakeholders, making use of diverse ecological and social data, is crucial for confronting and mitigating the associated risks. Prescribed fire, when planned and executed carefully, is a key management tool in this effort. Assessing where prescribed fire can be a particularly effective forest management tool can help prioritize efforts, reduce wildfire risk, and support fire-resilient lands and communities. We collaborated with expert stakeholders to develop a Bayesian network model that integrated a large variety of biophysical, socioecological, and socioeconomic spatial information for the Southeastern United States to quantify where risk is high and where prescribed fire would be efficient in mitigating risk. The model first estimated wildfire risk based on landscape-scale interactions among the likelihoods of fire occurrence and severity and the people and resources potentially exposed—accounting for socioeconomic vulnerabilities as well as key ecosystem services. The model then quantified the potential for risk reduction through prescribed fire, given the existing fuel load, climate, and other landscape conditions. The resulting expected risk estimates show high risk concentrated in the coastal plain and interior highland subregions of the Southern US, but there was considerable variation among risks to different ecosystem services and populations, including potential exposure to smoke emissions. The capacity to reduce risk through fuel reductions was spatially correlated with risk; where these diverged, the difference was largely explained by fuel load. We suggest that both risk and the capacity for risk reduction are important in identifying priorities for management interventions. The model serves as a decision support tool for stakeholders to coordinate large-landscape adaptive management initiatives in the Southern US. The model is flexible with regard to both empirical and expert-driven parameterizations and can be updated as new knowledge and data emerge. The resulting spatial information can help connect active management options to forest management goals and make management more efficient through targeted investments in priority landscapes. [ABSTRACT FROM AUTHOR]

Research has shown that climate change creates warmer temperatures and drier conditions, leading to longer wildfire seasons and increased wildfire risks in the United States. These factors have, in turn, led to increases in the frequency, extent, and severity of wildfires in recent years. Given the danger posed by wildland fires to people, property, wildlife, and the environment, there is an urgent need to provide tools for effective wildfire management. Early detection of wildfires is essential to minimizing potentially catastrophic destruction. To that end, in this paper, we present our work on integrating multiple data sources into SmokeyNet, a deep learning model using spatiotemporal information to detect smoke from wildland fires. We present Multimodal SmokeyNet and SmokeyNet Ensemble for multimodal wildland fire smoke detection using satellite-based fire detections, weather sensor measurements, and optical camera images. An analysis is provided to compare these multimodal approaches to the baseline SmokeyNet in terms of accuracy metrics, as well as time-to-detect, which is important for the early detection of wildfires. Our results show that incorporating weather data in SmokeyNet improves performance numerically in terms of both F1 and time-to-detect over the baseline with a single data source. With a time-to-detect of only a few minutes, SmokeyNet can be used for automated early notification of wildfires, providing a useful tool in the fight against destructive wildfires. [ABSTRACT FROM AUTHOR]

We examine the determinants of firms' 10‐K disclosures on the threat of and exposure to wildfires. We match the location of wildfires in the United States to firms in the same county as the wildfire. We first establish that wildfire disclosure is far from widespread. On average, 6.1% of firms with wildfires in their headquarters county mention wildfire information in their 10‐Ks. Second, we find that the number of wildfire days in a company's headquarters county is a key determinant of wildfire disclosure. The sensitivity of wildfire disclosure to wildfire exposure has also increased in recent years, emanating mainly from firms having experienced wildfires impacting their past operations and in the western states and the utility and banking industries, and from those exhibiting a high level of tangible assets. Third, we find that wildfire exposure has no bearing on stock price, whereas more wildfire‐related disclosure lowers stock price. [ABSTRACT FROM AUTHOR]

This study develops a stochastic dynamic model to optimize site value from timber and non-timber benefits for a landowner in the southeast United States who integrates wildfire risk and fuel accumulation into forest management and fire prevention decisions. The derived model determines optimal fuel treatment frequencies, timing, and level simultaneously and as a function of fire risk and fuel biomass dynamics under a range of economic and biophysical conditions. The landowner's optimal prevention decisions are highly dependent on the type of fuel biomass growth and the association between fire arrival rate and fuel accumulation, which can vary across a broad forest landscape. Results indicate that policymakers should develop their management strategies based on their long-run objectives and fuel accumulation patterns, and these strategies should vary in timing and effort level within each rotation. [ABSTRACT FROM AUTHOR]

Managing wildfire risk across boundaries and scales is critical in fire-prone landscapes around the world, as a variety of actors undertake mitigation and response activities according to jurisdictional, conceptual and administrative boundaries, based on available human, organisational, technical and financial resources. There is a need to catalyse coordination more effectively to collectively manage wildfire risk. We interviewed 102 people across five large landscape case studies in the western United States to categorise how people and organisations were deployed in range and forestlands to collectively address wildfire risk. Across all cases, actors spanned boundaries to perform functions including: (1) convening meetings and agreements; (2) implementing projects; (3) community outreach; (4) funding support; (5) project planning; (6) scientific expertise. These functions fostered conducive boundary settings, concepts and objects to communicate and work across boundaries, navigating challenges to implementing work on the ground. This work highlights context-specific ways to advance cross-boundary wildfire risk reduction efforts and uses a boundary spanning lens to illustrate how collective action in wildfire management evolves in different settings. This research highlights prescribed fire as a gateway for future collective action on wildfire risk, including managing naturally ignited wildfires for resource benefits and improving coordination during wildfire suppression efforts. Actors must collectively manage wildfire risk across administrative, conceptual, organisational and other boundaries in fire-prone landscapes. We interviewed practitioners in five cases across the western United States, identifying how actors were engaging in collective action to address wildfire risk, organised through a typology of actor functions and boundary-spanning features. [ABSTRACT FROM AUTHOR]

The methodology used by the First Street Foundation Wildfire Model (FSF-WFM) to compute estimates of the 30-year, climate-adjusted aggregate wildfire hazard for the contiguous United States at 30 m horizontal resolution is presented. The FSF-WFM integrates several existing methods from the wildfire science community and implements computationally efficient and scalable modeling techniques to allow for new high-resolution, CONUS-wide hazard generation. Burn probability, flame length, and ember spread for the years 2022 and 2052 are computed from two ten-year representative Monte Carlo simulations of wildfire behavior, utilizing augmented LANDFIRE fuel estimates updated with all the available disturbance information. FSF-WFM utilizes ELMFIRE, an open-source, Rothermel-based wildfire behavior model, and multiple US Federal Government open data sources to drive the simulations. LANDFIRE non-burnable fuel classes within the wildland–urban interface (WUI) are replaced with fuel estimates from machine-learning models, trained on data from historical fires, to allow the propagation of wildfire through the WUI in the model. Historical wildfire ignition locations and NOAA's hourly time series of surface weather at 2.5 km resolution are used to drive ELMFIRE to produce wildfire hazards representative of the 2022 and 2052 conditions at 30 m resolution, with the future weather conditions scaled to the IPCC CMIP5 RCP4.5 model ensemble predictions. Winds and vegetation were held constant between the 2022 and 2052 simulations, and climate change's impacts on the future fuel conditions are the main contributors to the changes observed in the 2052 results. Non-zero wildfire exposure is estimated for 71.8 million out of 140 million properties across CONUS. Climate change impacts add another 11% properties to this non-zero exposure class over the next 30 years, with much of this change observed in the forested areas east of the Mississippi River. "Major" aggregate wildfire exposure of greater than 6% over the 30-year analysis period from 2022 to 2052 is estimated for 10.2 million properties. The FSF-WFM represents a notable contribution to the ability to produce property-specific, climate-adjusted wildfire risk assessments in the US. [ABSTRACT FROM AUTHOR]

Increased atmospheric evaporative demand has important implications for humans and ecosystems in water-scarce lands. While temperature plays a significant role in driving evaporative demand and its trend, other climate variables are also influential and their contributions to recent trends in evaporative demand are unknown. We address this gap with an assessment of recent (1980-2020) trends in annual reference evapotranspiration (ETo) and its drivers across the continental United States based on five gridded datasets. In doing so, we characterize the structural uncertainty of ETo trends and decompose the relative influences of temperature, wind speed, solar radiation, and humidity. Results highlight large and robust changes in ETo across much of the western United States, centered on the Rio Grande region where ETo increased 135-235 mm during 1980-2020. The largest uncertainties in ETo trends are in the central and eastern United States and surrounding the Upper Colorado River. Trend decomposition highlights the strong and widespread influence of temperature, which contributes to 57% of observed ETo trends, on average. ETo increases are mitigated by increases in specific humidity in non-water-limited regions, while small decreases in specific humidity and increases in wind speed and solar radiation magnify ETo increases across the West. Our results show increases in ETo across the West that are already emerging outside the range of variability observed 20-40 years ago. Our results suggest that twenty-first-century land and water managers need to plan for an already increasing influence of evaporative demand on water availability and wildfire risks. [ABSTRACT FROM AUTHOR]

Wildfires in the western United States (US) are increasingly expensive, destructive, and deadly. Reducing wildfire losses is particularly challenging when fires frequently start on one land tenure and damage natural or developed assets on other ownerships. Managing wildfire risk in multijurisdictional landscapes has recently become a centerpiece of wildfire strategic planning, legislation, and risk research. However, important empirical knowledge gaps remain regarding cross-boundary fire activity in the western US. Here, we use lands administered by the US Forest Service as a study system to assess the causes, ignition locations, structure loss, and social and biophysical factors associated with cross-boundary fire activity over the past three decades. Results show that cross-boundary fires were primarily caused by humans on private lands. Cross-boundary ignitions, area burned, and structure losses were concentrated in California. Public lands managed by the US Forest Service were not the primary source of fires that destroyed the most structures. Cross-boundary fire activity peaked in moderately populated landscapes with dense road and jurisdictional boundary networks. Fire transmission is increasing, and evidence suggests it will continue to do so in the future. Effective cross-boundary fire risk management will require cross-scale risk co-governance. Focusing on minimizing damages to high-value assets may be more effective than excluding fire from multijurisdictional landscapes. [ABSTRACT FROM AUTHOR]

Since their introduction two decades ago, Community Wildfire Protection Plans (CWPPs) have become a common planning tool for improving community preparedness and risk mitigation in fire-prone regions, and for strengthening coordination among federal and state land management agencies, local government, and residents. While CWPPs have been the focus of case studies, there are limited large-scale studies to understand the extent of, and factors responsible for, variation in stakeholder participation—a core element of the CWPP model. This article describes the scale and scope of participation in CWPPs across the western United States. We provide a detailed account of participants in over 1,000 CWPPs in 11 states and examine how levels of participation and stakeholder diversity vary as a function of factors related to planning process, planning context, and the broader geographic context in which plans were developed. We find that CWPPs vary substantially both by count and diversity of participants and that the former varies as a function of the geographic scale of the plan, while the latter varies largely as a function of the diversity of landowners within the jurisdiction. More than half of participants represented local interests, indicating a high degree of local engagement in hazard mitigation. Surprisingly, plan participation and diversity were unrelated to wildfire hazard. These findings suggest that CWPPs have been largely successful in their intent to engage diverse stakeholders in preparing for and mitigating wildfire risk, but that important challenges remain. We discuss the implications of this work and examine how the planning process and context for CWPPs may be changing. [ABSTRACT FROM AUTHOR]

Management of forest lands under climate warming poses challenges to managers, some of which are difficult to predict. Examining the trade‐offs associated with forest stewardship choices is essential to avoid consequences associated with loss of natural capital. We utilized LANDIS‐II process model simulations for three forested sites located in disparate parts of the United States with the purpose of understanding the trade‐offs imposed by management choices under climate warming and associated wildfire. There were only small trade‐offs that emerged from the simulations, between habitat area for threatened and endangered species (TES), net ecosystem exchange for CO2 (NEE), and risk of wildfire. Stand management in the form of thinning and prescribed burning typically increased NEE while simultaneously increasing habitat for TES, while reducing the risk of wildfire. These benefits were also observed under a climate warming scenario; however, the benefits were greatly outweighed by the negative impacts of warming on both TES habitat and NEE. Balancing these ecosystem services via thinning and burning treatments is a strategic approach to mitigate risks of wildfire both currently and under a warming future climate. [ABSTRACT FROM AUTHOR]

Massive Geo-tagged social media data provide new opportunities for disaster risk assessment, prevention, and management. This article presents a proof of concept for assessing wildfire risk using Geo-tagged social media data, by taking wildfire risk as a function of wildfire hazard and social–ecological vulnerability. The case study of the United States shows that the regions with the highest wildfire hazard are concentrated in the Western, while the most vulnerable areas are mainly distributed in the Eastern, the Western Coast, and the Southern parts of the nation. Areas with high wildfire risk are mainly located in the Northwestern and Southeastern United States. It shows that the wildfire risk level has significant linear relationship with population density. Massive and vulnerable population might result in significant increase in wildfire risk perception. We conclude that Geo-tagged social media data have great potential in disaster risk studies. [ABSTRACT FROM AUTHOR]

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. This work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow. • Analyzed wildfire impact on solar PV production at 53 utility sites in Western US. • Skilled random forest model predicts solar PV production with R 2 = 0. 91 and M S E = 0. 005. • Wildfire smoke in vicinity reduced solar PV production by 8.3% on average. [ABSTRACT FROM AUTHOR]

Growing human and ecological costs due to increasing wildfire are an urgent concern in policy and management, particularly given projections of worsening fire conditions under climate change. Thus, understanding the relationship between climatic variation and fire activity is a critically important scientific question. Different factors limit fire behavior in different places and times, but most fire-climate analyses are conducted across broad spatial extents that mask geographical variation. This could result in overly broad or inappropriate management and policy decisions that neglect to account for regionally specific or other important factors driving fire activity. We developed statistical models relating seasonal temperature and precipitation variables to historical annual fire activity for 37 different regions across the continental United States and asked whether and how fire-climate relationships vary geographically, and why climate is more important in some regions than in others. Climatic variation played a significant role in explaining annual fire activity in some regions, but the relative importance of seasonal temperature or precipitation, in addition to the overall importance of climate, varied substantially depending on geographical context. Human presence was the primary reason that climate explained less fire activity in some regions than in others. That is, where human presence was more prominent, climate was less important. This means that humans may not only influence fire regimes but their presence can actually override, or swamp out, the effect of climate. Thus, geographical context as well as human influence should be considered alongside climate in national wildfire policy and management. [ABSTRACT FROM AUTHOR]

Attaining fire-adapted human communities has become a key focus of collaborative planning on landscapes across the western United States and elsewhere. The coupling of fire simulation with GIS has expanded the analytical base to support such planning efforts, particularly through the 'fireshed' concept that identifies areas where wildfires could ignite and reach a human community. Previous research has identified mismatches in scale between localized community wildfire planning and the broader fireshed considering patterns of wildfire activity across landscapes. Here we expand upon this work by investigating the degree to which alternative geospatial characterizations of human communities could influence assessment of community exposure and characterization of the fireshed. We use three methods of mapping human communities (point, raster, and polygon) and develop three fireshed metrics (size, number of fires reaching houses, and number of houses exposed), and apply this analytical framework on a 2.3 million ha case study landscape encompassing the Sierra National Forest in California, USA. We simulated fire occurrence and growth using FSim for 10,000 iterations (fire seasons) at 180-m resolution. The simulation resulted in 3.9 large fires per million ha per year, with a mean size of 3432 ha. Results exhibit similarities and differences in how exposure is quantified, specifically indicating that polygons representing recognized community boundaries led to the lowest exposure levels. These results highlight how choice of the mapping approach could lead to misestimating the scope of the problem or targeting mitigation efforts in the wrong areas, and underscore the importance of clarity and spatial fidelity in geospatial data representing communities at risk. [ABSTRACT FROM AUTHOR]

This study examines the statistical association of wildfire risk with climatic conditions and non-climate variables in 48 continental US states. Because the response variable "wildfire risk" is a fractional variable bounded between zero and one, we use a non-linear panel data model to recognize the bounded nature of the response variable. We estimate the non-linear panel data model (fractional probit) using the Generalized Estimating Equation (GEE) approach to ensure that the parameter estimation is efficient. The statistical model, coupled with the future climates projected by Global Climate Models (GCMs), is then employed to assess the impact of global climate change on wildfire risk. Our regression results show that wildfire risk is positively related to spring, summer, and winter temperatures and human population density whereas it is negatively associated with precipitation. The simulation results based on GCMs and the regression model indicate that climate change will intensify wildfire risk throughout the entire US, especially in the South Central region, posing an increasing wildfire threat and thus calling for more effective wildfire management strategies. [ABSTRACT FROM AUTHOR]

Recent years have seen growing interest within the United States fire management community in exploring alternatives to the standard approach of evacuating entire populations that are threatened by a wildfire. There has been particular interest in what can be learned from the Australian approach, whereby residents choose whether or not to evacuate under the 'prepare, stay and defend or leave early' approach, also called Stay or Go. Given these developments, it is useful to understand what elements are taken into consideration by those who would be most affected by a new approach when they think through the pros and cons of mass evacuation v. an alternative strategy should a wildfire occur. This paper reports on findings from interviews in four communities in the United States where some alternative to mass evacuation during a wildfire was being considered. In each community, emergency responders and community members were asked for their perspective on the pros and cons of evacuation and the alternative being considered. The results show that opinions were mixed on whether evacuation or an alternative approach was more appropriate. Individuals who were primarily thinking of improving safety and reducing uncertainty for emergency responders tended to think mass evacuation was the best approach, whereas those who were primarily thinking of increasing safety and reducing uncertainty for homeowners were more likely to think that alternative responses were a valid option. These findings demonstrate the complicated nature of developing evacuation strategies that are beneficial to all parties involved. [ABSTRACT FROM AUTHOR]

Seasonal changes in the climatic potential for very large wildfires (VLWF ≥ 50,000 ac ~ 20,234 ha) across the western contiguous United States are projected over the 21st century using generalized linear models and downscaled climate projections for two representative concentration pathways (RCPs). Significant ( p ≤ 0.05) increases in VLWF probability for climate of the mid-21st century (2031-2060) relative to contemporary climate are found, for both RCP 4.5 and 8.5. The largest differences are in the Eastern Great Basin, Northern Rockies, Pacific Northwest, Rocky Mountains, and Southwest. Changes in seasonality and frequency of VLWFs d7epend on changes in the future climate space. For example, flammability-limited areas such as the Pacific Northwest show that (with high model agreement) the frequency of weeks with VLWFs in a given year is 2-2.7 more likely. However, frequency of weeks with at least one VLWF in fuel-limited systems like the Western Great Basin is 1.3 times more likely (with low model agreement). Thus, areas where fire is directly associated with hot and dry climate, as opposed to experiencing lagged effects from previous years, experience more change in the likelihood of VLWF in future projections. The results provide a quantitative foundation for management to mitigate the effects of VLWFs. [ABSTRACT FROM AUTHOR]

Frequently, models are required to combine information obtained from different data sources and on different scales. In this work, we are interested in estimating the risk of wildfire ignition in the USA for a particular time and location by merging two levels of data, namely, individual points and aggregate count of points into areas. The data for federal lands consist of the point location and time of each fire. Nonfederal fires are aggregated by county for a particular year. The probability model is based on the wildfire point process. Assuming a smooth intensity function, a locally weighted likelihood fit is used, which incorporates the group effect. A logit model is used under the assumption of the existence of a latent process, and fuel conditions are included as a covariate. The model assessment is based on a residual analysis, while the False Discovery Rate detects spatial patterns. A benefit of the proposed model is that there is no need of arbitrary aggregation of individual fires into counts. A map of predicted probability of ignition for the Midwest US in 1990 is included. The predicted ignition probabilities and the estimated total number of expected fires are required for the allocation of resources. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Policymakers seek ways to encourage fuel reduction among private forest landowners to augment similar efforts on federal and state lands. Motivating landowners to contribute to landscape-level wildfire protection requires an understanding of factors that underlie landowner behaviour regarding wildfire. We developed a conceptual framework describing landowners' propensity to conduct fuel reduction as a function of objective and subjective factors relating to wildfire risk. We tested our conceptual framework using probit analysis of empirical data from a survey of non-industrial private forest landowners in the ponderosa pine (Pinus ponderosa) region of eastern Oregon (USA). Our empirical results confirm the conceptual framework and suggest that landowners' perceptions of wildfire risk and propensity to conduct fuel treatments are correlated with hazardous fuel conditions on or near their parcels, whether they have housing or timber assets at risk, and their past experience with wildfire, financial capacity for conducting treatments and membership in forestry and fire protection organisations. Our results suggest that policies that increase awareness of hazardous fuel conditions on their property and potential for losses in residential and timber assets, and that enhance social networks through which awareness and risk perception are formed, could help to encourage fuel reduction among private forest landowners. [ABSTRACT FROM AUTHOR]

Wildfire is on the rise. The United States is witnessing a spectacular increase in acres lost to catastrophic wildfires, a phenomenon fed by the generally hotter and dryer conditions associated with climate change. In addition to losses in lives, property, and natural resources, wildfires contribute thousands of tons of air pollution each year. Ironically, one of the most effective tools to reduce the incidence and severity of unplanned wildfires is fire. Prescribed, or controlled, burning reduces the buildup of vegetation resulting from years of wildfire-suppression policy. At present, the number of acres subject to prescribed burns falls far short of the optimal number needed to restore natural ecosystems and reduce damages from unplanned wildfires. Air-pollution law and policy is an important factor contributing to the under-provision of prescribed fire that has so far escaped in-depth treatment in the law and policy literature. After setting forth the relevant air quality framework, this Article argues that decisions regarding planned wildfire are marred by an anachronistic and inaccurate distinction between "natural" and "anthropogenic " fire. Rationalizing that unplanned wildfires are "natural, " the federal government excludes pollutants from such fires from air quality compliance calculations at the same time it encourages states to vigorously control pollutants from "anthropogenic, " prescribed fires. The result contributes to an undervaluation of necessary, planned wildfire. Wildfire air pollution policy is also hindered by governance structures that place air quality and resource agencies at odds with each other, and by state nuisance authorities that enable narrow local interests to shut down prescribed fire, all of which trump the broader public interest in reduced wildfire risk and healthier forests. This Article suggests several solutions to remove these distortions, including adopting a default rule whereby all wildfire smoke, of whatever origin, "counts " for purposes of air quality compliance. Together with adopting mechanisms to require air pollution and resource agencies to both participate in planned burning decisions and de-emphasize the influence of nuisance standards, this "smoke is smoke" rule will ensure that the air pollution policy better reflects the true costs and benefits of prescribed fire. [ABSTRACT FROM AUTHOR]

National‐scale analyses of fire occurrence are needed to prioritize fire policy and management activities across the United States. However, the drivers of national‐scale patterns of fire occurrence are not well understood, and how the relative importance of human or biophysical factors varies across the country is unclear. Our research goal was to model the drivers of fire occurrence within ecoregions across the conterminous United States. We used generalized linear models to compare the relative influence of human, vegetation, climate, and topographic variables on fire occurrence in the United States, as measured by MODIS active fire detections collected between 2000 and 2006. We constructed models for all fires and for large fires only and generated predictive maps to quantify fire occurrence probabilities. Areas with high fire occurrence probabilities were widespread in the Southeast, and localized in the Mountain West, particularly in southern California, Arizona, and New Mexico. Probabilities for large‐fire occurrence were generally lower, but hot spots existed in the western and south‐central United States The probability of fire occurrence is a critical component of fire risk assessments, in addition to vegetation type, fire behavior, and the values at risk. Many of the hot spots we identified have extensive development in the wildland–urban interface and are near large metropolitan areas. Our results demonstrated that human variables were important predictors of both all fires and large fires and frequently exhibited nonlinear relationships. However, vegetation, climate, and topography were also significant variables in most ecoregions. If recent housing growth trends and fire occurrence patterns continue, these areas will continue to challenge policies and management efforts seeking to balance the risks generated by wildfires with the ecological benefits of fire. [ABSTRACT FROM AUTHOR]

Three causes have been identified for the spiraling cost of wildfire suppression in the United States: climate change, fuel accumulation from past wildfire suppression, and development in fire-prone areas. Because little is likely to be performed to halt the effects of climate on wildfire risk, and because fuel-management budgets cannot keep pace with fuel accumulation let alone reverse it, changing the behaviors of existing and potential homeowners in fire-prone areas is the most promising approach to decreasing the cost of suppressing wildfires in the wildland-urban interface and increasing the odds of homes surviving wildfire events. Wildfire education efforts encourage homeowners to manage their property to decrease wildfire risk. Such programs may be more effective with a better understanding of the factors related to homeowners' decisions to undertake wildfire risk-reduction actions. In this study, we measured whether homeowners had implemented 12 wildfire risk-mitigation measures in 2 Colorado Front Range counties. We found that wildfire information received from local volunteer fire departments and county wildfire specialists, as well as talking with neighbors about wildfire, were positively associated with higher levels of mitigation. Firsthand experience in the form of preparing for or undertaking an evacuation was also associated with a higher level of mitigation. Finally, homeowners who perceived higher levels of wildfire risk on their property had undertaken higher levels of wildfire-risk mitigation on their property. [ABSTRACT FROM AUTHOR]

It is increasingly important that natural resource managers understand residents' perceptions of wildfire risks, particularly as the wildland-urban interface expands. Risk perceptions influence resident risk reduction strategies that are crucial to effective hazard management. This study compares key informant responses about community wildfire risk from five areas of the eastern United States. Perceptions are influenced by ecological characteristics as well as economic and sociodemographic factors. These include, e.g., the proliferation of low-density housing and second home development, local values and norms, and the strength of public services. Despite federal designation of wildfire risk, most informants said their communities were relatively unconcerned about wildfire. In some places, informants noted awareness of wildfire but lack of concern. Findings illustrate how social and cultural characteristics of participants' communities intersected with biophysical elements of wildfire to attenuate risk perceptions. Implications for community wildfire risk mitigation policy are discussed. [ABSTRACT FROM AUTHOR]

Dense ponderosa pine forests in the southwestern United States inhibit understory production and diversity and are susceptible to high-severity wildfire. Restoration treatments involving overstory thinning and prescribed burning are being implemented to increase understory productivity and diversity and to reduce the risk of severe wildfire. However, disturbances associated with treatments may favor invasion of nonnative species, and the severity of the disturbance may be related to the level of nonnative species establishment. We examined understory community composition, species richness, and plant cover responses to 3 stand-scale replicates of 4 different tree-thinning intensities. Restoration treatments altered the composition of the understory community regardless of thinning intensity. Understory richness and cover were highly variable among experimental blocks, but we observed strong trends of increasing richness and cover in the treated stands. Immediately following restoration treatments, nonnative species cover comprised 6% of the total cover where treatment-induced disturbances were the greatest. However, the initial increase in nonnative species did not persist and was reduced by half 6 years after treatment. Plant community composition was still in flux by the sixth year after treatment, indicating that continued monitoring is necessary for evaluating whether restoration targets are maintained over time. [ABSTRACT FROM AUTHOR]

In recent years, the threat that wildfire poses to homes has received much attention in both the mainstream press and academic literature. However, little is known about how homebuyers consider wildfire risk during the home-purchase process. In the context of a unique wildfire education program, we consider two approaches to examining the relationship between wildfire risk and home purchases. Results from a market-level analysis using home sales price data are compared to household survey results. The household survey validates the market-level analysis and provides further insight into homebuyers and wildfire risk. Specifically, we find that while homebuyers prefer locations near dangerous topography, they also prefer less flammable building materials. However, most homebuyers were unaware of wildfire risk when they made their home-purchase decisions. [ABSTRACT FROM AUTHOR]

An important policy question receiving considerable attention concerns the risk perception–risk mitigation process that guides how individuals choose to address natural hazard risks. This question is considered in the context of wildfire. We analyze the factors that influence risk reduction behaviors by homeowners living in the wildland–urban interface. The factors considered are direct experience, knowledge of wildfire risk, locus of responsibility, full-time/seasonal status, and self-efficacy. Survey data from three homeowner associations in the western U.S. are used to estimate the direct and indirect effects of this relationship. Our results indicate that the effects of knowledge and locus of responsibility are mediated by homeowners'' risk perceptions. We also find that beliefs of self-efficacy and full-time/seasonal status have a direct influence on risk reduction behaviors. Finally, we find, surprisingly, that direct experience with wildfire does not directly influence the risk perception–risk mitigation process. [Copyright &y& Elsevier]

Wildfires in the wildland urban interface (WUI) are an increasing concern throughout the western United States and elsewhere. WUI communities continue to grow and thus increase the wildfire risk to human lives and property. Information such as a wildfire risk map can inform WUI residents of potential risks and may help to efficiently sort mitigation efforts. This study uses the survey-based contingent valuation (CV) method to examine annual household willingness to pay (WTP) for the provision of a wildfire risk map. Data were collected through a mail survey of the East Mountain WUI area in the State of New Mexico (USA). The integrated empirical approach includes a system of equations that involves joint estimation of WTP values, along with measures of a respondent's risk perception and risk mitigation behavior. The median estimated WTP is around U.S. $12 for the annual wildfire risk map, which covers at least the costs of producing and distributing available risk information. Further, providing a wildfire risk map can help address policy goals emphasizing information gathering and sharing among stakeholders to mitigate the effects of wildfires. [ABSTRACT FROM AUTHOR]

Wildfire is a dynamic ecological process with spatial patterns that reflect multiple influences on fire occurrence and spread. We used weights of evidence techniques to model spatial patterns of wildfire occurrence in relation to landscape-scale drivers of fire in the southern Great Basin. Weights of evidence is a quantitative, data-driven, Bayesian modeling method that can be applied to spatial data for producing maps of expected probability of occurrence. We applied this method to Lincoln County, Nevada, for the period from 1994 to 2005. Fire data were obtained from the National Fire Occurrence Database and from the Bureau of Land Management. Spatial data sets used as potential predictors of fire occurrence included elevation, topography (terrain slope, hillshade illumination, basin vs. range, topographic roughness), geological substrate, vegetation cover type, lightning strike density, annual maximum temperature and total precipitation, soil infiltration and soil water capacity, population and road density, and distance to highways. Because very few human-caused fires were recorded, models were developed and tested for lightning-caused fires over the entire county and in forested areas only. Lightning strike density was the first or second most important predictor of fire occurrence in the entire county and in forested areas. Higher fire density and higher lightning strike density were observed in the eastern half of the county compared to the western half. Overall, the spatial distribution of wildfire occurrence was controlled more by ignition mechanisms than by processes influencing fuel moisture, accumulation, or both. [ABSTRACT FROM AUTHOR]

Quantification of the downed woody materials that comprise forest fuels has gained importance in Caribbean forest ecosystems due to the increasing incidence and severity of wildfires on island ecosystems. Because large-scale assessments of forest fuels have rarely been conducted for these ecosystems, forest fuels were assessed at 121 US Department of Agriculture forest service inventory plots on Puerto Rico, Vieques, and the US Virgin Islands. Results indicated that fuel loadings averaged 24.05 Mg ha-1 in 2004-2006. Forest litter decreased from wetter to drier forest life zones. These island forests showed a paucity of coarse woody fuels (CWD) (2.91 Mg ha-1) and relatively greater quantities of smaller-sized fine woody fuels (FWD) (10.18 Mg ha-1 for FWD and 10.82 Mg ha-1 for duff/litter) when compared to continental tropical forests. Between 2001 and 2006, CWD fuel loads decreased, while fine fuels and litter increased, such that total fuel loads remained constant on a subset of plots on Puerto Rico. This trend indicates that continued decomposition of CWD deposited by the last severe hurricane is balanced by increasing inputs of FWD from recovering and maturing secondary forests. Forest disturbance cycles and successional development must be taken into account by agencies charged with fire protection and risk assessment. [ABSTRACT FROM AUTHOR]

Fuels reduction programs aimed at reducing wildfire risk are increasing on national forests of the American Southwest. Incorporating both mechanical thinning and prescribed burning, fuels reduction projects can decrease the intensity and frequency of wildfires hut also provide economic benefits to regional economies, businesses, and individuals. This article analyzes the economic impacts of national forest fuels reduction programs in the Southwest. Impacts, multipliers, and wood utilization rates were calculated for regions containing the Apache-Sitgreaves, Coconino, Gila, Kaibab, and San Juan National Forests. In total, fiscal year 2005 fuels reduction programs for these five national forests accounted for over $40 million of output and helped generate some 500 jobs, providing an economic stimulus to rural communities. [ABSTRACT FROM AUTHOR]

In 2003, Congress passed the Healthy Forest Restoration Act encouraging communities to develop Community Wildfire Protection Plans (CWPP) to guide wildfire mitigation efforts on both federal and nonfederal lands. This article provides a case study of the development and implementation of a CWPP for the at-risk communities of the Sitgreaves National Forest in Arizona. This case study reveals a past history of collaboration to address the issue of wildfire along with high levels of cooperation among all levels of government and community stakeholders. The communities of the Sitgreaves National Forest successfully established an inclusive and multijurisdictional planning process and effective procedures for intergovernmental cooperation to mitigate the wildfire risk. The Sitgreaves CWPP provides an excellent example of an effective community-based planning effort to mitigate the wildfire threat. [ABSTRACT FROM AUTHOR]

The United States has experienced an even longer and more intense wildfire season than normal in recent years, largely resulting from drought conditions and a buildup of flammable vegetation. The derived stochastic dynamic model in this study was utilized to evaluate the interaction of wildfire risk mitigation policies for two adjacent landowners under various scenarios of forest benefits while accounting for full awareness of fire externalities. This study also evaluated the effectiveness of cost-share programs and fuel stock regulation and investigated under which scenarios of forest management interests the implementation of these policies encourages risk mitigation behaviors and yields larger reductions in social costs. The findings revealed that social costs significantly reduced after the implementation of cost-share programs and fuel stock regulation. Market-oriented adjacent landowners were more responsive to policy instruments compared to other types of neighboring landowners, and their responsiveness was greater for fuel stock regulation policies than for cost-share programs. Policymakers may introduce extra financial incentives or more rigorous fuel stock regulations to induce nonmarket-oriented landowners to undertake increased fuel management activities. [ABSTRACT FROM AUTHOR]

The fluctuation of streamflow in snowmelt-dominated watersheds may be an indicator of climate change. However, the relationship between the start of growing season (SOS) and the streamflow in snowmelt-dominated watersheds is not clear. In this study, we update the Coupled Hydro-Ecological Simulation System (CHESS) model by incorporating the Growing Season Index (GSI) module to estimate the start of the growing season. The updated CHESS model is then used to calculate the streamflow in the Cleve Creek, Incline Creek and Twin River watersheds located in Nevada in the United States from 1981 to 2017. This updated CHESS can be applied in any regions that are suitable for deciduous vegetation. The streamflow in the static and dynamic scheme in the three watersheds have been simulated between 1981 and 2017 with the NS of 0.52 and 0.80 in the Cleve Creek, 0.46 and 0.75 in the Incline Creek, and 0.42 and 0.70 in the Twin River watersheds, respectively. The results illustrate that the SOS have come around 3–5 weeks earlier during the last 37 years. The results illustrate a high correlation between the temperature and the timing of the SOS. Early SOS leads to a substantial increase in total annual transpiration. An increase in annual transpiration can reduce aquifer recharge and increase cumulative growing season soil moisture deficit. Comparing to the streamflow without vegetation, the streamflow with vegetation is smaller due to transpiration. As the SOS comes earlier, the peaks of the streamflow with vegetation also come earlier. If the shifts in SOS continue, the effects on annual rates of transpiration can be significant, which may reduce the risk of flooding during snowmelt. On the other hand, earlier SOS may cause soil moisture to decline during summer, which would increase the drought stress in trees and the risk of wildfires and insect infestation. [ABSTRACT FROM AUTHOR]

Decision support systems (DSSs) are increasingly common in forest and wildfire planning and management in the United States. Recent policy direction and frameworks call for collaborative assessment of wildfire risk to inform fuels treatment prioritization using the best available science. There are numerous DSSs applicable to forest and wildfire planning, which can support timely and relevant information for decision making, but the use and adoption of these systems is inconsistent. There is a need to elucidate the use of DSSs, specifically those that support pre-wildfire, spatial planning, such as wildfire risk assessment and forest fuels treatment prioritization. It is important to understand what DSSs are in use, barriers and facilitators to their use, and recommendations for improving their use. Semi-structured interviews with key informants were used to assess these questions. Respondents identified numerous barriers, as well as recommendations for improving DSS development and integration, specifically with respect to capacity, communication, implementation, question identification, testing, education and training, and policy, guidance, and authorities. These recommendations can inform DSS use for wildfire risk assessment and treatment prioritization to meet the goals of national policies and frameworks. Lastly, a framework for organizing spatial, pre-wildfire planning DSSs to support end-user understanding and use is provided. [ABSTRACT FROM AUTHOR]