Western Wildland Environmental Threat Assessment Center

Risk analysis evolved out of the need to make decisions concerning highly stochastic events, and is well suited to analyse the timing, location and potential effects of wildfires. Over the past 10 years, the application of risk analysis to wildland fire management has seen steady growth with new risk-based analytical tools that support a wide range of fire and fuels management planning scales from individual incidents to national, strategic interagency programs. After a brief review of the three components of fire risk – likelihood, intensity and effects – this paper reviews recent advances in quantifying and integrating these individual components of fire risk. We also review recent advances in addressing temporal dynamics of fire risk and spatial optimisation of fuels management activities. Risk analysis approaches have become increasingly quantitative and sophisticated but remain quite disparate. We suggest several necessary and fruitful directions for future research and development in wildfire risk analysis.

Abstract Tropospheric ozone (O 3 ) is an important stressor in natural ecosystems, with well‐documented impacts on soils, biota and ecological processes. The effects of O 3 on individual plants and processes scale up through the ecosystem through effects on carbon, nutrient and hydrologic dynamics. Ozone effects on individual species and their associated microflora and fauna cascade through the ecosystem to the landscape level. Systematic injury surveys demonstrate that foliar injury occurs on sensitive species throughout the globe. However, deleterious impacts on plant carbon, water and nutrient balance can also occur without visible injury. Because sensitivity to O 3 may follow coarse physiognomic plant classes (in general, herbaceous crops are more sensitive than deciduous woody plants, grasses and conifers), the task still remains to use stomatal O 3 uptake to assess class and species’ sensitivity. Investigations of the radial growth of mature trees, in combination with data from many controlled studies with seedlings, suggest that ambient O 3 reduces growth of mature trees in some locations. Models based on tree physiology and forest stand dynamics suggest that modest effects of O 3 on growth may accumulate over time, other stresses (prolonged drought, excess nitrogen deposition) may exacerbate the direct effects of O 3 on tree growth, and competitive interactions among species may be altered. Ozone exposure over decades may be altering the species composition of forests currently, and as fossil fuel combustion products generate more O 3 than deteriorates in the atmosphere, into the future as well.

Abstract The area burned annually by wildfires is expected to increase worldwide due to climate change. Burned areas increase soil erosion rates within watersheds, which can increase sedimentation in downstream rivers and reservoirs. However, which watersheds will be impacted by future wildfires is largely unknown. Using an ensemble of climate, fire, and erosion models, we show that postfire sedimentation is projected to increase for nearly nine tenths of watersheds by >10% and for more than one third of watersheds by >100% by the 2041 to 2050 decade in the western USA. The projected increases are statistically significant for more than eight tenths of the watersheds. In the western USA, many human communities rely on water from rivers and reservoirs that originates in watersheds where sedimentation is projected to increase. Increased sedimentation could negatively impact water supply and quality for some communities, in addition to affecting stream channel stability and aquatic ecosystems.

We used simulation modelling to analyse spatial variation in wildfire exposure relative to key social and economic features on the island of Sardinia, Italy. Sardinia contains a high density of urban interfaces, recreational values and highly valued agricultural areas that are increasingly being threatened by severe wildfires. Historical fire data and wildfire simulations were used to estimate burn probabilities, flame length and fire size. We examined how these risk factors varied among and within highly valued features located on the island. Estimates of burn probability excluding non-burnable fuels, ranged from 0–1.92 × 10–3, with a mean value of 6.48 × 10–5. Spatial patterns in modelled outputs were strongly related to fuel loadings, although topographic and other influences were apparent. Wide variation was observed among the land parcels for all the key values, providing a quantitative approach to inform wildfire risk management activities.

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.

Abstract Wildfires devastated communities in Oregon and Washington in September 2020, burning almost as much forest west of the Cascade Mountain crest (“the westside”) in 2 weeks (~340,000 ha) as in the previous five decades (~406,00 ha). Unlike dry forests of the interior western United States, temperate rain forests of the Pacific Northwest have experienced limited recent fire activity, and debates surrounding what drove the 2020 fires, and management strategies to adapt to similar future events, necessitate a scientific evaluation of the fires. We evaluate five questions regarding the 2020 Labor Day fires: (1) How do the 2020 fires compare with historical fires? (2) How did the roles of weather and antecedent climate differ geographically and from the recent past (1979–2019)? (3) How do fire size and severity compare to other recent fires (1985–2019), and how did forest management and prefire forest structure influence burn severity? (4) What impact will these fires have on westside landscapes? and (5) How can we adapt to similar fires in the future? Although 5 of the 2020 fires were much larger than any others in the recent past and burned ~10 times the area in high‐severity patches >10,000 ha, the 2020 fires were remarkably consistent with historical fires. Reports from the early 1900s, along with paleo‐ and dendro‐ecological records, indicate similar and potentially even larger wildfires over the past millennium, many of which shared similar seasonality (late August/early September), weather conditions, and even geographic locations. Consistent with the largest historical fires, strong east winds and anomalously dry conditions drove the rapid spread of high‐severity wildfire in 2020. We found minimal difference in burn severity among stand structural types related to previous management in the 2020 fires. Adaptation strategies for similar fires in the future could benefit by focusing on ignition prevention, fire suppression, and community preparedness, as opposed to fuel treatments that are unlikely to mitigate fire severity during extreme weather. While scientific uncertainties remain regarding the nature of infrequent, high‐severity fires in westside forests, particularly under climate change, adapting to their future occurrence will require different strategies than those in interior, dry forests.

Fuel breaks are increasingly being implemented at broad scales (100s to 10,000s of square kilometers) in fire‐prone landscapes globally, yet there is little scientific information available regarding their ecological effects (eg habitat fragmentation). Fuel breaks are designed to reduce flammable vegetation (ie fuels), increase the safety and effectiveness of fire‐suppression operations, and ultimately decrease the extent of wildfire spread. In sagebrush ( Artemisia spp) ecosystems of the western US , installation of extensive linear fuel breaks is also intended to protect habitat, especially for the greater sage‐grouse ( Centrocercus urophasianus ), a species that is sensitive to habitat fragmentation. We examine this apparent contradiction in the Great Basin region, where invasive annual grasses have increased wildfire activity and threaten sagebrush ecosystems. Given uncertain outcomes, we examine how implementation of fuel breaks might (1) directly alter ecosystems, (2) create edges and edge effects, (3) serve as vectors for wildlife movement and plant invasions, (4) fragment otherwise contiguous sagebrush landscapes, and (5) benefit from scientific investigation intended to disentangle their ecological costs and benefits.

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. Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon pools to account for stochastic wildfire occurrence. The study area was a 68 474 ha watershed located on the Fremont-Winema National Forest in southeastern Oregon, USA. Fuel reduction treatments were simulated on 10% of the watershed (19% of federal forestland). We simulated 30 000 wildfires with random ignition locations under both treated and untreated landscapes to estimate the change in burn probability by flame length class resulting from the treatments. Carbon loss functions were then calculated with the Forest Vegetation Simulator for each stand in the study area to quantify change in carbon as a function of flame length. We then calculated the expected change in carbon from a random ignition and wildfire as the sum of the product of the carbon loss and the burn probabilities by flame length class. The expected carbon difference between the non-treatment and treatment scenarios was then calculated to quantify the effect of fuel treatments. Overall, the results show that the carbon loss from implementing fuel reduction treatments exceeded the expected carbon benefit associated with lowered burn probabilities and reduced fire severity on the treated landscape. Thus, fuel management activities resulted in an expected net loss of carbon immediately after treatment. However, the findings represent a point in time estimate (wildfire immediately after treatments), and a temporal analysis with a probabilistic framework used here is needed to model carbon dynamics over the life cycle of the fuel treatments. Of particular importance is the long-term balance between emissions from the decay of dead trees killed by fire and carbon sequestration by forest regeneration following wildfire.

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

Abstract Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide plausible results for future climate in the region of interest. We demonstrate an approach to select a subset of GCMs that incorporates both concepts and provides insights into the range of climate impacts. To represent how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an ecosystem variable responds locally to projected regional temperature and precipitation changes. We illustrate our approach in the Pacific Northwest, focusing on (a) changes in streamflow magnitudes in critical seasons for water management and (b) changes in annual vegetation carbon.

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.

We investigated nonindustrial private forest (NIPF) owners' invasive plant risk perceptions and mitigation practices using statistical analysis of mail survey data and qualitative analysis of interview data collected in Oregon's ponderosa pine zone. We found that 52% of the survey sample was aware of invasive plant species considered problematic by local natural resource professionals; 70% was concerned about these species; and 46% had treated invasive plants on their parcels. Owners' perceptions of invasive plant risks fell along a spectrum ranging from a lack of awareness or concern, to the view that invasive plant infestations have discrete causes and controllable consequences, to the perception that incursions by invasive plants have diffuse causes and uncontrollable effects. Being aware or concerned about invasive plant species were predictors ( p ≤ 0.001) of whether owners treat their parcels to control invasive plants. Holding wildlife habitat and/or biodiversity as an important forest management goal was also a predictor ( p ≤ 0.08) of whether owners treated their parcels to control invasive plants. Some owners were sensitive to the risks of invasive plant infestations from nearby properties, and a surprisingly high percentage of respondents had cooperated with others in forest management activities previously. Our findings suggest three approaches to increasing the frequency of invasive plant mitigation by NIPF owners that hold promise: (1) raising awareness and concern about invasive plants and their impacts on forest management goals that owners care about, such as wildlife habitat and/or biodiversity; (2) providing assistance to help owners mitigate invasive plants they feel unable to control; and (3) engaging owners in coordinated efforts across ownership boundaries to address invasive plant risks.

Designing policies to harness the potential of heterogeneous target groups such as nonindustrial private forest owners to contribute to public policy goals can be challenging. The behaviors of such groups are shaped by their diverse motivations and circumstances. Segmenting heterogeneous target groups into more homogeneous subgroups may improve the chances of successfully identifying policy strategies to influence their behavior. Findings from a multimethod study of nonindustrial private forest owners in eastern Oregon suggest four unique subgroups of owners with different fuel management motivations and suitabilities for policy tools: commodity managers could benefit from market-based incentives; amenity managers could benefit from capacity building programs paired with symbolic campaigns; recreational managers could benefit from public incentives provided through consultants or contractors who can help plan the work; and passive managers may benefit from opportunities to respond to the policy strategies designed for the other groupings until more information can be gathered. Incorporating qualitative analysis of interview data with statistical analysis of survey data improved understanding of the groupings and appropriate policy strategies for them.

Extensive bark beetle outbreaks have recently occurred in western North American forests, resulting in overstory tree mortality across millions of hectares. Annual aerial surveys are currently used to operationally monitor bark beetle induced tree mortality, though this method is subjective and can exclude some forest areas. Daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data offer a potential alternative means to develop regional tree mortality maps. Accurate methods using such data could aid natural resource managers in surveys of forests with frequent overstory mortality, helping to prioritize forest treatment and restoration activities. This paper discusses a study to test the potential of using MODIS data to detect tree mortality. We developed and tested an approach to use 250-m resolution MODIS Normalized Difference Vegetation Index (NDVI) data products collected during a mountain pine beetle (MPB) outbreak and related tree mortality event in the northern Rocky Mountains of Colorado, USA. The 94 km2 study area is predominantly lodgepole pine forest with most of the MPB-caused mortality occurring between 2003 and 2008. We used a 2.4-m forest conditions map from 2008 aerial multispectral imagery to calculate percentage of mortality within 240-m pixels for use as reference data. Using either daily or 16-day products, MODIS NDVI change products were calculated for 2008 versus either 2000 or 2003 baselines. MODIS change products were used as predictors in linear regression analysis to assess correlation between MODIS data and the aerial percent forest mortality map. Depending on the MODIS product, linear regression analyses yielded r2 values ranging from 0.362 to 0.544 without outliers removed and from 0.406 to 0.570 with extreme outliers removed. Daily MODIS NDVI products from 2003 and 2008 were used with exponential regression to improve the r2 to 0.593. The project showed some MODIS NDVI data potential for mapping percent tree mortality in forests subjected to regional bark beetle outbreaks and severe drought.

Spatially explicit information on the probability of burning is necessary for virtually all strategic fire and fuels management planning activities, including conducting wildland fire risk assessments, optimizing fuel treatments, and prevention planning. Predictive models providing a reliable estimate of the annual likelihood of fire at each point on the landscape have enormous potential to support strategic fire and fuels management planning decisions, especially when combined with information on the values at risk and the expected fire impacts. To this end, a spatially-explicit modelling technique, termed 'burn probability' (BP) modelling, has been developed to simulate fires as a function of the physical factors that drive their spread -fuels, weather, and topographyusing the most sophisticated landscape-scale fire spread algorithms available. Despite several applications of the BP technique, much remains to be learned about their predictive ability. To achieve this goal, we are conducting experiments to not only unearth new discoveries about the complexities of fireenvironment relationships, but also to test and compare the relevance and accuracy of modelling approaches.

The physical and chemical environment of the Earth has changed rapidly over the last 100 years and is predicted to continue to change into the foreseeable future. One of the main concerns with potential alterations in climate is the propensity for increases in the magnitude and frequency of extremes to occur. Even though precipitation is predicted to increase in some locations, in others precipitation is expected to decrease and evapotranspiration increase with air temperature, resulting in exacerbated drought in the future. Chemical [ozone (O3 ) and other air contaminants] and subsequent physical alterations in the environment will have a profound effect on the 'disease triangle' (a favourable environment, a susceptible host and a virulent pathogen) and should be included in any analysis of biological response to climate change. The chemical and physical environment affects plant health and alters plant susceptibility to insect and pathogen attack through increased frequency, duration and severity of drought and reduction in host vigour. The potential effects of climate change and O3 on tree diseases with emphasis on the western United States are discussed. We describe a generalised modelling approach to incorporate the complexities of the 'disease triangle' into dynamic vegetation models.

Abstract Tamarisk species are shrubs or small trees considered by some to be among the most aggressively invasive and potentially detrimental exotic plants in the United States. Although extensively studied in the southern and interior west, northwestern (Oregon, Washington, and Idaho) distribution and habitat information for tamarisk is either limited or lacking. We obtained distribution data for the northwest, developed a habitat suitability map, and projected changes in habitat due to climate change in a smaller case study area using downscaled climate data. Results show extensive populations of tamarisk east of the Cascade Mountains. Despite the perceived novelty of tamarisk in the region, naturalized populations were present by the 1920s. Major population centers are limited to the warmest and driest environments in the central Snake River Plain, Columbia Plateau, and Northern Basin and Range. Habitat suitability model results indicate that 21% of the region supports suitable tamarisk habitat. Less than 1% of these areas are occupied by tamarisk; the remainder is highly vulnerable to invasion. Although considerable uncertainty exists regarding future climate change, we project a 2- to 10-fold increase in highly suitable tamarisk habitat by the end of the century. Our habitat suitability maps can be used in “what if” exercises as part of planning, detection, restoration, management, and eradication purposes.

In this review, we discuss current research on forest carbon risk from natural disturbance under climate change for the United States, with emphasis on advancements in analytical mapping and modeling tools that have potential to drive research for managing future long-term stability of forest carbon. As a natural mechanism for carbon storage, forests are a critical component of meeting climate mitigation strategies designed to combat anthropogenic emissions. Forests consist of long-lived organisms (trees) that can store carbon for centuries or more. However, trees have finite lifespans, and disturbances such as wildfire, insect and disease outbreaks, and drought can hasten tree mortality or reduce tree growth, thereby slowing carbon sequestration, driving carbon emissions, and reducing forest carbon storage in stable pools, particularly the live and standing dead portions that are counted in many carbon offset programs. Many forests have natural disturbance regimes, but climate change and human activities disrupt the frequency and severity of disturbances in ways that are likely to have consequences for the long-term stability of forest carbon. To minimize negative effects and maximize resilience of forest carbon, disturbance risks must be accounted for in carbon offset protocols, carbon management practices, and carbon mapping and modeling techniques. This requires detailed mapping and modeling of the quantities and distribution of forest carbon across the United States and hopefully one day globally; the frequency, severity, and timing of disturbances; the mechanisms by which disturbances affect carbon storage; and how climate change may alter each of these elements. Several tools (e.g. fire spread models, imputed forest inventory models, and forest growth simulators) exist to address one or more of the aforementioned items and can help inform management strategies that reduce forest carbon risk, maintain long-term stability of forest carbon, and further explore challenges, uncertainties, and opportunities for evaluating the continued potential of, and threats to, forests as viable mechanisms for forest carbon storage, including carbon offsets. A growing collective body of research and technological improvements have advanced the science, but we highlight and discuss key limitations, uncertainties, and gaps that remain.

Abstract Context Several plant traits are associated with resistance to fire, thus fire-resistant species may give rise to more fire-resistant landscapes. However, up-scaling from plant traits to landscape- and regional-scale fire effects remains a challenge. Objectives We test two hypotheses: (1) forests composed of fire-resistant species experience lower fire severity than forests composed of less fire-resistant species; and (2) wildfires affecting forests with greater fire resistance experience smaller patches of high-severity fire. Methods We used a predictive map of existing forest types (major tree species dominating forest composition) and a trait-based map of fire resistance. We examined large-scale spatial patterns of fire severity derived from Landsat imagery in 611 wildfires across the range of western larch in the Inland Northwest USA (1985–2014). We then applied structural equation modeling to study complex relationships between fire resistance and high-severity fire in each wildfire. Results Forest types dominated by fire-resister species (e.g., ponderosa pine) experienced lower fire severity than forest types dominated by non-resister species such as lodgepole pine (fire-embracer) and subalpine fir (fire-avoider). We found a strong negative correlation between the fire resistance index and average values of the relative differenced normalized burn ratio, as well as an indirect relationship between fire resistance and high-severity patch size. Conclusions The large-scale differences in fire severity among forest types generally reflect the degree of fire resistance that fire-related traits confer to individual trees species, providing evidence that incorporating plant traits has the potential to assist in assessing fire resistance at large spatial scales.