Wildfire Exposure Analysis on the National Forests in the Pacific Northwest,USA

We analyzed wildfire exposure for key social and ecological features on the national forests in Oregon and Washington. The forests contain numerous urban interfaces, old growth forests, recreational sites, and habitat for rare and endangered species. Many of these resources are threatened by wildfire, especially in the east Cascade Mountains fire‐prone forests. The study illustrates the application of wildfire simulation for risk assessment where the major threat is from large and rare naturally ignited fires, versus many previous studies that have focused on risk driven by frequent and small fires from anthropogenic ignitions. Wildfire simulation modeling was used to characterize potential wildfire behavior in terms of annual burn probability and flame length. Spatial data on selected social and ecological features were obtained from Forest Service GIS databases and elsewhere. The potential wildfire behavior was then summarized for each spatial location of each resource. The analysis suggested strong spatial variation in both burn probability and conditional flame length for many of the features examined, including biodiversity, urban interfaces, and infrastructure. We propose that the spatial patterns in modeled wildfire behavior could be used to improve existing prioritization of fuel management and wildfire preparedness activities within the Pacific Northwest region.     

Wildfire Policy in Mediterranean France: How Far is it Efficient and Sustainable?

A new fire policy reinforcing aggressive fire suppression was established in Mediterranean France in response to the devastating wildfires of the 1990s, but to what extent this has changed fire activity yet remains poorly understood. For this purpose, we compared the number and location of ignitions and of burned areas between two 20‐year periods (1975–1994 vs. 1995–2014), in parallel to the changes in fuel covering, human activity promoting ignitions, and fire weather. The number of fires decreased almost continuously since 1975, but sharply after 1994, suggesting an effect of better fire prevention due to the new policy. But the major change in fire activity is a considerable reduction in fire size and burned areas after 1994, especially during summer and in the most fire‐prone places, in response to massive efforts put into fire suppression. These reductions have occurred while the covering by fuel biomass, the human pressure on ignition, and the fire weather index increased, thus making the study area more hazardous. Our results suggest that a strategy of aggressive fire suppression has great potential for counterbalancing the effects of climate changes and human activities and for controlling fire activity in the short term. However, we discuss whether such a suppression‐oriented approach is sustainable in the context of global changes, which cast new fire challenges as demonstrated by the devastative fires of 2003 and 2016. We advocate for a more comprehensive fire policy to come.     

Wildfire Risk Transmission in the Colorado Front Range,USA

Wildfires are a global phenomenon that in some circumstances can result in human casualties, economic loss, and ecosystem service degradation. In this article we spatially identify wildfire risk transmission pathways and locate the areas of highest exposure of human populations to wildland fires under severe, but not uncommon, weather events. We quantify varying levels of exposure in terms of population potentially affected and tie the exposure back to the spatial source of the risk for the Front Range of Colorado, USA. We use probabilistic fire simulation modeling to address where fire ignitions are most likely to cause the highest impact to human communities, and to explore the role that various landowners play in that transmission of risk. Our results indicated that, given an ignition and the right fire weather conditions, large areas along the Front Range in Colorado could be exposed to wildfires with high potential to impact human populations, and that overall private ignitions have the potential to impact more people than federal ignitions. These results can be used to identify high‐priority areas for wildfire risk mitigation using various mitigation tools.     

Assessing Transboundary Wildfire Exposure in the Southwestern United States

We assessed transboundary wildfire exposure among federal, state, and private lands and 447 communities in the state of Arizona, southwestern United States. The study quantified the relative magnitude of transboundary (incoming, outgoing) versus nontransboundary (i.e., self‐burning) wildfire exposure based on land tenure or community of the simulated ignition and the resulting fire perimeter. We developed and described several new metrics to quantify and map transboundary exposure. We found that incoming transboundary fire accounted for 37% of the total area burned on large parcels of federal and state lands, whereas 63% of the area burned was burned by ignitions within the parcel. However, substantial parcel to parcel variation was observed for all land tenures for all metrics. We found that incoming transboundary fire accounted for 66% of the total area burned within communities versus 34% of the area burned by self‐burning ignitions. Of the total area burned within communities, private lands contributed the largest proportion (36.7%), followed by national forests (19.5%), and state lands (15.4%). On average seven land tenures contributed wildfire to individual communities. Annual wildfire exposure to structures was highest for wildfires ignited on state and national forest land, followed by tribal, private, and BLM. We mapped community firesheds, that is, the area where ignitions can spawn fires that can burn into communities, and estimated that they covered 7.7 million ha, or 26% of the state of Arizona. Our methods address gaps in existing wildfire risk assessments, and their implementation can help reduce fragmentation in governance systems and inefficiencies in risk planning.     

Risk Preferences in Strategic Wildfire Decision Making: A Choice Experiment with U.S. Wildfire Managers

Federal policy has embraced risa management as an appropriate paradigm for wildfire management. Economic theory suggests that over repeated wildfire events, potential economic costs and risas of ecological damage are optimally balanced when management decisions are free from biases, risa aversion, and risa seeking. Of primary concern in this article is how managers respond to wildfire risa, including the potential effect of wildfires (on ecological values, structures, and safety) and the likelihood of different fire outcomes. We use responses to a choice experiment questionnaire of U.S. federal wildfire managers to measure attitudes toward several components of wildfire risa and to test whether observed risa attitudes are consistent with the efficient allocation of wildfire suppression resources. Our results indicate that fire managers’ decisions are consistent with nonexpected utility theories of decisions under risa. Managers may overallocate firefighting resources when the likelihood or potential magnitude of damage from fires is low, and sensitivity to changes in the probability of fire outcomes depends on whether probabilities are close to one or zero and the magnitude of the potential harm.     

Coupling the Biophysical and Social Dimensions of Wildfire Risk to Improve Wildfire Mitigation Planning

We describe recent advances in biophysical and social aspects of risk and their potential combined contribution to improve mitigation planning on fire‐prone landscapes. The methods and tools provide an improved method for defining the spatial extent of wildfire risk to communities compared to current planning processes. They also propose an expanded role for social science to improve understanding of community‐wide risk perceptions and to predict property owners’ capacities and willingness to mitigate risk by treating hazardous fuels and reducing the susceptibility of dwellings. In particular, we identify spatial scale mismatches in wildfire mitigation planning and their potential adverse impact on risk mitigation goals. Studies in other fire‐prone regions suggest that these scale mismatches are widespread and contribute to continued wildfire dwelling losses. We discuss how risk perceptions and behavior contribute to scale mismatches and how they can be minimized through integrated analyses of landscape wildfire transmission and social factors that describe the potential for collaboration among landowners and land management agencies. These concepts are then used to outline an integrated socioecological planning framework to identify optimal strategies for local community risk mitigation and improve landscape‐scale prioritization of fuel management investments by government entities.     

Evaluating Lightning-Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain

It is widely accepted that the relationship between lightning wildfire occurrence and its influencing factors vary depending on the spatial scale of analysis, making the development of models at the regional scale advisable. In this study, we analyze the effects of different biophysical variables and lightning characteristics on lightning-caused forest wildfires in Castilla y León region (Central Spain). The presence/absence of at least one lightning-caused fire in any 4 × 4-km grid cell was used as a dependent variable and vegetation type and structure, terrain, climate, and lightning characteristics were used as possible covariates. Five prediction methods were compared: a generalized linear model (GLM), a random forest model (RFM), a generalized additive model (GAM), a GAM that includes a spatial trend function (GAMs) and a spatial autoregressive model (AUREG). A GAMs with just one covariate, apart from longitude and latitude for each observation included as a combined effect, was considered the most appropriate model in terms of both predictive ability and simplicity. According to our results, the probability of a forest being affected by a lightning-caused fire is positively and nonlinearly associated with the percentage of coniferous woodlands in the landscape, suggesting that occurrence is more closely associated with vegetation type than with topography, climate, or lightning characteristics. The selected GAMs is intended to inform the Regional Government of Castilla y León (the fire and fuel agency in the region) regarding identification of areas at greatest risk so it can design long-term forest fuel and fire management strategies.     

Cross-country risk quantification of extreme wildfires in Mediterranean Europe

We estimate the country-level risk of extreme wildfires defined by burned area (BA) for Mediterranean Europe and carry out a cross-country comparison. To this end, we avail of the European Forest Fire Information System (EFFIS) geospatial data from 2006 to 2019 to perform an extreme value analysis. More specifically, we apply a point process characterization of wildfire extremes using maximum likelihood estimation. By modeling covariates, we also evaluate potential trends and correlations with commonly known factors that drive or affect wildfire occurrence, such as the Fire Weather Index as a proxy for meteorological conditions, population density, land cover type, and seasonality. We find that the highest risk of extreme wildfires is in Portugal (PT), followed by Greece (GR), Spain (ES), and Italy (IT) with a 10-year BA return level of 50'338 ha, 33'242 ha, 25'165 ha, and 8'966 ha, respectively. Coupling our results with existing estimates of the monetary impact of large wildfires suggests expected losses of 162–439 million € (PT), 81–219 million € (ES), 41–290 million € (GR), and 18–78 million € (IT) for such 10-year return period events.

SUMMARY

We model the risk of extreme wildfires for Italy, Greece, Portugal, and Spain in form of burned area return levels, compare them, and estimate expected losses.     

Should I Stay or Should I Go Now? Or Should I Wait and See? Influences on Wildfire Evacuation Decisions

As climate change has contributed to longer fire seasons and populations living in fire‐prone ecosystems increase, wildfires have begun to affect a growing number of people. As a result, interest in understanding the wildfire evacuation decision process has increased. Of particular interest is understanding why some people leave early, some choose to stay and defend their homes, and others wait to assess conditions before making a final decision. Individuals who tend to wait and see are of particular concern given the dangers of late evacuation. To understand what factors might influence different decisions, we surveyed homeowners in three areas in the United States that recently experienced a wildfire. The Protective Action Decision Model was used to identify a suite of factors previously identified as potentially relevant to evacuation decisions. Our results indicate that different beliefs about the efficacy of a particular response or action (evacuating or staying to defend), differences in risk attitudes, and emphasis on different cues to act (e.g., official warnings, environmental cues) are key factors underlying different responses. Further, latent class analysis indicates there are two general classes of individuals: those inclined to evacuate and those inclined to stay, and that a substantial portion of each class falls into the wait and see category.     

Projections of Future Extreme Weather Losses Under Changes in Climate and Exposure

Many attempts are made to assess future changes in extreme weather events due to anthropogenic climate change, but few studies have estimated the potential change in economic losses from such events. Projecting losses is more complex as it requires insight into the change in the weather hazard but also into exposure and vulnerability of assets. This article discusses the issues involved as well as a framework for projecting future losses, and provides an overview of some state‐of‐the‐art projections. Estimates of changes in losses from cyclones and floods are given, and particular attention is paid to the different approaches and assumptions. All projections show increases in extreme weather losses due to climate change. Flood losses are generally projected to increase more rapidly than losses from tropical and extra‐tropical cyclones. However, for the period until the year 2040, the contribution from increasing exposure and value of capital at risk to future losses is likely to be equal or larger than the contribution from anthropogenic climate change. Given the fact that the occurrence of loss events also varies over time due to natural climate variability, the signal from anthropogenic climate change is likely to be lost among the other causes for changes in risk, at least during the period until 2040. More efforts are needed to arrive at a comprehensive approach that includes quantification of changes in hazard, exposure, and vulnerability, as well as adaptation effects.     

Social Amplification of Wildfire Risk: The Role of Social Interactions and Information Sources

Wildfire is a persistent and growing threat across much of the western United States. Understanding how people living in fire‐prone areas perceive this threat is essential to the design of effective risk management policies. Drawing on the social amplification of risk framework, we develop a conceptual model of wildfire risk perceptions that incorporates the social processes that likely shape how individuals in fire‐prone areas come to understand this risk, highlighting the role of information sources and social interactions. We classify information sources as expert or nonexpert, and group social interactions according to two dimensions: formal versus informal, and generic versus fire‐specific. Using survey data from two Colorado counties, we empirically examine how information sources and social interactions relate to the perceived probability and perceived consequences of a wildfire. Our results suggest that social amplification processes play a role in shaping how individuals in this area perceive wildfire risk. A key finding is that both “vertical” (i.e., expert information sources and formal social interactions) and “horizontal” (i.e., nonexpert information and informal interactions) interactions are associated with perceived risk of experiencing a wildfire. We also find evidence of perceived “risk interdependency”—that is, homeowners’ perceptions of risk are higher when vegetation on neighboring properties is perceived to be dense. Incorporating social amplification processes into community‐based wildfire education programs and evaluating these programs’ effectiveness constitutes an area for future inquiry.     

Risk Preferences,Probability Weighting,and Strategy Tradeoffs in Wildfire Management

Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey‐based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery‐choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation‐related fatalities. Respondents choose one of two strategies, each of which includes “good” (low cost/low damage) and “bad” (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting.     

Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region

Despite escalating expenditures in firefighting, extreme fire events continue to pose a major threat to ecosystem services and human communities in Mediterranean areas. Developing a safe and effective fire response is paramount to efficiently restrict fire spread, reduce negative effects to natural values, prevent residential housing losses, and avoid causalties. Though current fire policies in most countries demand full suppression, few studies have attempted to identify the strategic locations where firefighting efforts would likely contain catastrophic fire events. The success in containing those fires that escape initial attack is determined by diverse structural factors such as ground accessibility, airborne support, barriers to surface fire spread, and vegetation impedance. In this study, we predicted the success in fire containment across Catalonia (northeastern Spain) using a model generated with random forest from detailed geospatial data and a set of 73 fire perimeters for the period 2008–2016. The model attained a high predictive performance (AUC = 0.88), and the results were provided at fine resolution (25 m) for the entire study area (32,108 km²). The highest success rates were found in agricultural plains along the nonburnable barriers such as major road corridors and largest rivers. Low levels of containment likelihood were predicted for dense forest lands and steep-relief mountainous areas. The results can assist in suppression resource pre-positioning and extended attack decision making, but also in strategic fuels management oriented at creating defensive locations and fragmenting the landscape in operational firefighting areas. Our modeling workflow and methods may serve as a baseline to generate locally adapted models in fire-prone areas elsewhere.     

Provision of a Wildfire Risk Map: Informing Residents in the Wildland Urban Interface

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.     

Expecting the Unexpected: Predicting Physiological and Psychological Wildfire Preparedness from Perceived Risk,Responsibility, and Obstacles

People who live in wildfire‐prone communities tend to form their own hazard‐related expectations, which may influence their willingness to prepare for a fire. Past research has already identified two important expectancy‐based factors associated with people's intentions to prepare for a natural hazard: Perceived risk (i.e., perceived threat likelihood and severity) and perceived protection responsibility. We expanded this research by differentiating the influence of these factors on different types of wildfire preparedness (e.g., preparations for evacuation vs. for defending the house) and measured actual rather than intended preparedness. In addition, we tested the relation between preparedness and two additional threat‐related expectations: the expectation that one can rely on an official warning and the expectation of encountering obstacles (e.g., the loss of utilities) during a fire. A survey completed by 1,003 residents of wildfire‐prone areas in Perth, Australia, revealed that perceived risk (especially risk severity) and perceived protection responsibility were both positively associated with all types of preparedness, but the latter did not significantly predict preparedness after controlling for other predictors and demographics. Also, the two new expectancy‐based factors were significantly associated with all types of preparedness, and remained significant predictors of some types of preparedness after controlling for other predictors and demographics: the expectation of being able to rely on an official fire warning and expecting to lose electricity both still predicted less preparedness around house resilience, and expecting to lose water still predicted increased planning preparedness. We discuss public policy implications that follow from this research.     

A General Model for Exposure and Uptake from Consumer Products

To assess exposure to and uptake of chemical compounds from consumer products, a general model framework is proposed. The model framework separates exposure into the components contact, potential exposure, and potential uptake rate, and establishes the relation between the three. It adds a contact function and a spatial component to other exposure modeling concepts. Before the model framework can be used, its components need to be specified. A simple diffusional model is built as an example of specifying functions for exposure and uptake. A case study of 1,1,1 trichloroethane in some shoe impregnating product, partly based on the diffusional uptake model, illustrates the inclusion of the contact component. In the latter example, the exposure is calculated for the user and then, by only modifying the contact component, for a nonuser randomly walking in the house.     

Assessment of Health Risk from Exposure to Contaminated Soil

The risk to human health posed by contaminated soil in a residential area depends on the potential extent of exposure to soil and on the toxic properties of the contaminants. A detailed soil exposure analysis is presented for young children, older children, and adults living in a house surrounded by contaminated soil. From this analysis, a lifetime exposure model is derived and used to assess chronic health risks.     

Modeling Rabbit Responses to Single and Multiple Aerosol Exposures of Bacillus anthracis Spores

Survival models are developed to predict response and time‐to‐response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple‐dose data set to predict the probability of death through specifying functions of dose response and the time between exposure and the time‐to‐death (TTD). Among the models developed, the best‐fitting survival model (baseline model) is an exponential dose–response model with a Weibull TTD distribution. Alternative models assessed use different underlying dose–response functions and use the assumption that, in a multiple‐dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this article. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high‐dose rabbit data sets. More accurate survival models depend upon future development of dose–response data sets specifically designed to assess potential multiple‐dose effects on response and time‐to‐response. The process used in this article to develop the best‐fitting survival model for exposure of rabbits to multiple aerosol doses of B. anthracis spores should have broad applicability to other host–pathogen systems and dosing schedules because the empirical modeling approach is based upon pathogen‐specific empirically‐derived parameters.     

Are We Adapting to Floods? Evidence from Global Flooding Fatalities

There has been a growing interest in understanding whether and how people adapt to extreme weather events in a changing climate. This article presents one of the first empirical analyses of adaptation to flooding on a global scale. Using a sample of 97 countries between 1985 and 2010, we investigate the extent and pattern of flood adaptation by estimating the effects of a country's climatological risk, recent flood experiences, and socioeconomic characteristics on its flood‐related fatalities. Our results provide mixed evidence on adaptation: countries facing greater long‐term climatological flooding risks do not necessarily adapt better and suffer fewer fatalities; however, after controlling for the cross‐country heterogeneity, we find that more recent flooding shocks have a significant and negative effect on fatalities from subsequent floods. These findings may suggest the short‐term learning dynamics of adaptation and potential inefficacy of earlier flood control measures, particularly those that promote increased exposure in floodplains. Our findings provide important implications for climate adaptation policy making and climate modeling.     

Validation of a Novel Air Toxic Risk Model with Air Monitoring

Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state‐wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis‐St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model‐estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity.