Wildfire risk in the wildland–urban interface: A simulation study in northwestern Wisconsin

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions.     

Forest fuel mapping and evaluation of LANDFIRE fuel maps in Boulder County,Colorado, USA

A key challenge in modern wildfire mitigation and forest management is accurate mapping of forest fuels in order to determine spatial fire hazard, plan mitigation efforts, and manage active fires. This study quantified forest fuels of the montane zone of Boulder County, CO, USA in an effort to aid wildfire mitigation planning and provide a metric by which LANDFIRE national fuel maps may be compared. Using data from 196 randomly stratified field plots, pre-existing vegetation maps, and derived variables, predictive classification and regression tree models were created for four fuel parameters necessary for spatial fire simulation with FARSITE (surface fuel model, canopy bulk density, canopy base height, and stand height). These predictive models accounted for 56–62% of the variability in forest fuels and produced fuel maps that predicted 91.4% and 88.2% of the burned area of two historic fires simulated in the FARSITE model. Simulations of areas burned based on LANDFIRE national fuel maps were less accurate, burning 77.7% and 40.3% of the historic fire areas. Our results indicate that fuel mapping efforts that utilize local area information and biotic as well as abiotic predictors will more accurately simulate fire spread rates and reflect the inherent variability of forested environments than do current LANDFIRE data products.     

Prehistoric fire area and emissions from California's forests,woodlands, shrublands,and grasslands

In the majority of US political settings wildland fire is still discussed as a negative force. Lacking from current wildfire discussions are estimates of the spatial extent of fire and their resultant emissions before the influences of Euro-American settlement and this is the focus of this work. We summarize the literature on fire history (fire rotation and fire return intervals) and past Native American burning practices to estimate past fire occurrence by vegetation type. Once past fire intervals were established they were divided into the area of each corresponding vegetation type to arrive at estimates of area burned annually. Finally, the First Order Fire Effects Model was used to estimate emissions. Approximately 1.8 million ha burned annually in California prehistorically (pre 1800). Our estimate of prehistoric annual area burned in California is 88% of the total annual wildfire area in the entire US during a decade (1994–2004) characterized as “extreme” regarding wildfires. The idea that US wildfire area of approximately two million ha annually is extreme is certainly a 20th or 21st century perspective. Skies were likely smoky much of the summer and fall in California during the prehistoric period. Increasing the spatial extent of fire in California is an important management objective. The best methods to significantly increase the area burned is to increase the use of wildland fire use (WFU) and appropriate management response (AMR) suppression fire in remote areas. Political support for increased use of WFU and AMR needs to occur at local, state, and federal levels because increasing the spatial scale of fire will increase smoke and inevitability, a few WFU or AMR fires will escape their predefined boundaries.     

基于随机森林模型的交界域火灾风险分析

【目的】城镇森林交界域火灾频繁发生,使民生经济遭受严重危害。使用随机森林模型对省域内的城镇森林交界域火灾风险与影响因子的关系进行空间建模,探究随机森林模型在拟合、解释交界域火灾风险方面的优势,并与森林火灾风险的影响因子对比,为进一步评估城镇森林交界域火险提供依据。【方法】研究基于安徽省2002—2011年火灾历史数据,采用气候、地理环境、人类活动、社会经济等方面的9个因子作为自变量,月均火灾密度作为因变量。使用特征选择方法得到模型内不同自变量的贡献度、统计特征以及内部模型的平均表现,选择出进入最后模型中的自变量;使用随机森林模型对城镇森林交界域火灾风险进行解释,分析影响城镇森林交界域火灾风险和森林火灾风险的重要因子。【结果】关键自变量对城镇森林交界域火灾风险的影响程度大小排序依次为:道路线密度、铁路线密度、月均最高温度、归一化植被指数、人口密度以及海拔;对森林火灾风险则为:月均最高温度、归一化植被指数、道路线密度、铁路线密度、人口密度以及海拔;经过训练与计算发现随机森林模型在5个子模型的训练集与测试集的表现基本一致,拟合值与实际值的简单相关系数均达0.90以上,可见随机森林模型对交界域火灾风险和森林火灾风险表现出显著的解释能力;此外,随机森林模型在总体数据集上进行了拟合,得到城镇森林交界域火灾风险的拟合值与实际值的相关性为0.997,森林火灾风险的拟合值与实际值的相关性为0.996,表明了随机森林模型具备极强的火灾风险拟合性能。【结论】影响城镇森林交界域火灾发生的最重要自变量是道路和铁路线密度,而对森林火灾则是月均最高温度与归一化植被指数,可见城镇森林交界域火灾发生人类活动因素密切相关。随机森林算法对城镇森林交界域火灾风险和森林火灾风险都能表现出稳健的和非常准确的拟合能力,是一个非常有用的工具。     

Analysis of the seasonal characteristics of forest fires in South Korea using the multivariate analysis approach

For efficient forest fire management, special precautions are required in dry and strong-wind seasons vulnerable to severe forest fires. To extract the seasonal characteristics of forest fires in South Korea, the statistics over the past 16 years, 1991 through 2005, were investigated. The daily records of the number of fire occurrences, the total area burned and the average burned area per occurrence were examined to identify the seasonal patterns of forest fires using cluster analysis and principal component analysis; the risk of daily fires was also assessed using the ordered logit model. As a result, the fire patterns were classified into five clusters and a general danger index for forest fires was derived from the first principal component, showing relatively large-scaled fire regimes in spring, and frequent small-scaled fire regimes in autumn and winter. In connection with the ordered logit model, the probability for the five ranks of forest fire risk was calculated and the threshold for high-risk fires was detected. As an implementation of the results above, the proper forest fire precautionary period in South Korea was estimated, and consequently October 21 through May 17 was recognized as a dry season at a high risk of forest fires. This period began 10 days earlier in autumn and extended into midwinter (late December and January) as opposed to the existing precautionary period, indicating the need of more cautious forest fire management earlier in autumn and continuing through midwinter.     

Prescribed fires as ecological surrogates for wildfires: A stream and riparian perspective

Forest managers use prescribed fire to reduce wildfire risk and to provide resource benefits, yet little information is available on whether prescribed fires can function as ecological surrogates for wildfire in fire-prone landscapes. Information on impacts and benefits of this management tool on stream and riparian ecosystems is particularly lacking. We used a beyond-BACI (Before, After, Control, Impact) design to investigate the effects of a prescribed fire on a stream ecosystem and compared these findings to similar data collected after wildfire. For 3 years after prescribed fire treatment, we found no detectable changes in periphyton, macroinvertebrates, amphibians, fish, and riparian and stream habitats compared to data collected over the same time period in four unburned reference streams. Based on changes in fuels, plant and litter cover, and tree scorching, this prescribed fire was typical of those being implemented in ponderosa pine forests throughout the western U.S. However, we found that the extent and severity of riparian vegetation burned was substantially lower after prescribed fire compared to nearby wildfires. The early-season prescribed fire did not mimic the riparian or in-stream ecological effects observed following a nearby wildfire, even in catchments with burn extents similar to the prescribed fire. Little information exists on the effects of long-term fire exclusion from riparian forests, but a “prescribed fire regime” of repeatedly burning upland forests while excluding fire in adjacent riparian forests may eliminate an important natural disturbance from riparian and stream habitats.     

Fuel types and crown fire potential in <Emphasis Type="Italic">Pinus halepensis</Emphasis> forests

There is a lack of knowledge to identify and classify forest structures according to the risk of crown fires, especially in Mediterranean regions. In this study, for the first time, we use real information, obtained after a wildfire that burnt under extreme meteorological conditions, to classify forest structures of Pinus halepensis into fuel types as a function of crown fire potential. We identified fourteen forest structures which characterize many forest types in Western Mediterranean areas depending on canopy closure, number of tree layers, percent of each tree layer and overall tree density. By using the pattern of fire types that burnt the most numerous forest structures, we have identified four fire hazard groups of forest structures which are considered different fuel types. The first two had the lowest risk of active crown fires and they differed in the proportion of surface fires and passive crown fires. The third fuel type was the threshold between structures with low and high extreme fire behavior; while the fourth had a high risk of active crown fires. Firefighters and forest managers who are demanding this kind of schema, will test and upgrade this classification of fuel types in function of crown fire potential during future wildfires.     

2003—2018年中国森林火灾时空分布格局研究

基于2003—2018年的中国森林火灾统计数据,全面分析了森林火灾发生的时空分布格局,定量分析了其统计学规律,旨在为森林火灾预测、管理和风险决策提供基础支撑.分析结果表明,森林火灾的发生具有极强的随机性和离散性,通过森林火灾总次数、火场面积和受害森林面积的平均数来反映森林火灾发生风险将会导致评估结果偏高.森林火灾发生次...     

Assessing fire risk using Monte Carlo simulations of fire spread

Understanding the spatial pattern of fire is essential for Mediterranean vegetation management. Fire-risk maps are typically constructed at coarse resolutions using vegetation maps with limited capacity for prescribing prevention activities. This paper describes and evaluates a novel approach for fire risk assessment that may produce a decision support system for actual fire management at fine scales. FARSITE, a two-dimensional fire growth and behavior model was activated, using ArcView VBA code, to generate Monte Carlo simulations of fire spread. The study area was 300 km² of Mt. Carmel, Israel. FARSITE fuel models were adjusted for Mediterranean conditions. The simulation session consisted of 500 runs. For each simulation run, a calendar date, fire length, ignition location, climatic data and other parameters were selected randomly from known distributions of these parameters. Distance from road served as a proxy for the probability of ignition. The resulting 500 maps of fire distribution (the entire area burnt in a specific fire) were overlaid to produce a map of ‘hotspots’ and ‘cold spots’ of fire frequency. The results revealed a clear pattern of fires, with high frequency areas concentrated in the northwestern part. The spatial pattern of the fire frequency map bears partial resemblance to the fuel map, but seems to be affected by several other factors as well, including the location of urban areas, microclimate, topography and the distribution of ignition locations (which is affected by road pattern). These results demonstrate the complexities of fire behavior, showing a very clear pattern of risk level even at fine scales, where neighboring areas have different risk levels due to combinations of vegetation cover, topography, microclimate and other factors.     

黑龙江省1980—2005年森林火灾时空特征

森林火灾是林火失去人为控制,在森林内自然蔓延和扩展,对生态系统和人类带来一定危害和损失的森林起火。森林火灾属世界性、跨国性的重大自然灾害,进入20世纪80—90年代以来,全球气候变暖导致森林火灾有上升的趋势,虽然各国的森林防火费用不断增加,但森林火灾发生的面积并未相     

Litter flammability in oak woodlands and shrublands of southeastern France

Characterizing the flammability of litter fuels is of major importance for assessing wildland fire ignition hazard. Here we compared the flammability of litter within a mosaic of Quercus suber (cork oak) woodlands and shrublands in a Mediterranean fire-prone area (Maures massif, southeastern France) to test whether the characteristics and the flammability of litter vary with the vegetation types. We tested experimentally the ignitability, the sustainability, the combustibility and the consumability of undisturbed (=non-reconstructed) litter samples with a point-source mode of ignition. Although the frequency of ignition was similar between all the vegetation types, we distinguished four groups having litter of specific composition and flammability: low and sparse shrublands dominated by Cistus species, medium shrublands with cork oak, high Erica shrublands with sparse cork oak woodlands, and mixed mature oak woodlands with Q. suber, Q. ilex and Q. pubescens. As these vegetation types corresponded to a specific range of past fire recurrence, we also tested the effect of the number of fires and the time since the last fire on litter flammability. Litters of plots recurrently burned had low ability to propagate flames and low flame sustainability. We discuss how the recent fire history can modify vegetation and litter flammability, and thus the fire ignition hazard.     

Modeling prescribed burns to serve as regional firebreaks to allow wildfire activity in protected areas

Management around wilderness parks ideally requires thorough fire suppression in proximate settled and commercially exploited lands and natural fire within protected areas. To satisfy these requirements, we explored a potential regional firebreak (firewall) based on a series of prescribed burns in Quetico Provincial Park in northwestern Ontario, Canada. Fire managers were recruited each to independently devise a regional firebreak using simulated prescribed burns. The experts’ five designs consisted of between 9 and 25 prescribed burns, set over periods ranging from 3 to 8 years, and covering from 7900 to 26,100 ha. Each wildlife ignition was run after the entire firebreak was created and the vegetation was reclassified to account for post-fire vegetation re-growth. The potential efficacy of each design was tested using worst-case historical weather and 100 random ignitions in the Prometheus fire growth simulation model. Without a firewall, 100 ignitions resulted in 69 fires escaping the park and consuming 483,900 ha of forest beyond the park boundary. The firewall designs were all effective, reducing the area burned outside the park to between 15,400 and 35,400 ha. There was a 77–90% reduction in the number of fires escaping the firewall areas and an average reduction of fire area beyond the park of 92%. Moreover, one can map the geographic weak points in each design, which encourages iterative firebreak design improvements. For instance, firewalls set nearer the park boundary allowed fewer fires to start between the firewall and the boundary, so increasing firebreak effectiveness. The cost of the above systems can be regarded as taking preventative measures against the risk of future economic loss, and the modeling approach reduces the uncertainties in associated decision making.     

Characterization of forest fires in Catalonia (north-east Spain)

The present study analyses the temporal variation in the distribution of the number of fires, area burned and fire sizes in Catalonia using fire data from 1942 to 2002. The study shows variations in the distribution of fire size over recent decades, with a significant increase in the number of very large fires. The study also analyses relationships between characteristics of the forest (altitude, slope, aspect, living fuels and species composition) and the probability of the fire occurrence. The analysis is based on the overlay of forest cover data and perimeters of forest fires during the period (1986–2002). Of the analysed variables, altitude affects most the probability of fire occurrence, with higher proportions of burned forest area at lower altitudes. Stand’s vertical structure is also relevant, with lower proportions of burned area in stands with mature tree cover without understory. The study helps to analyse the strengths and weaknesses of forest and fire management policies, especially those related to forest and fuel management at the landscape level.     

Modeling fire susceptibility in west central Alberta, Canada

Strategic modification of forest vegetation has become increasingly popular as one of the few preemptive activities that land managers can undertake to reduce the likelihood that an area will be burned by a wildfire. Directed use of prescribed fire or harvest planning can lead to changes in the type and arrangement of forest vegetation across the landscape that, in turn, may reduce fire susceptibility across large areas. While among the few variables that fire managers can influence, fuel conditions are only one of many factors that determine fire susceptibility. Variations in weather and topography, in combination with fuels, determine which areas are more likely to burn under a given fire regime. An understanding of these combined factors is necessary to identify high fire susceptibility areas for prioritizing and evaluating strategic fuel management activities, as well as informing other fire management activities, such as community protection planning and strategic level allocation of fire suppression resources across a management area. We used repeated fire growth simulations, automated in the Burn-P3 landscape-fire simulation model, to assess spatial variations in fire susceptibility across a 2.4 million ha study area in the province of Alberta, Canada. The results were used to develop a Fire Susceptibility Index (FSI). Multivariate statistical analyses were used to identify the key factors that determine variation in FSI across the study area and to describe the spatial scale at which these variables influence fire susceptibility at a given location. A fuel management scenario was used to assess the impact of prescribed fire treatments on FSI. Results indicated that modeled fire susceptibility was strongly influenced by fuel composition, fuel arrangement, and topography. The likelihood of high or extreme FSI values at a given location was strongly associated with the percent of conifer forest within a 2-km radius, and with elevation and ignition patterns within a 5-km radius. Results indicated that prescribed fire treatments can be effective at reducing forest fire susceptibility in community protection zones and that simulation modeling is an effective means of evaluating spatial variation in landscape fire susceptibility.     

Analyzing the effectiveness of alternative fuel reductions of a forested landscape in Northeastern China

Successful management of forest fire risk in the Northeastern China boreal forest ecosystem often involves trade-offs between fire dynamics, fire hazard reduction, and fiscal input. We used the LANDIS model to study the effects of alternative fuel reduction strategies on fire dynamics and analyzed cost effectiveness for each fuel reduction strategy based on cost–benefit theory. Five levels of fuel treatment area (2, 4, 6, 8, and 10% for each decade) and two fuel treatment types (prescribed burning [PB] and mechanical treatments in combination with prescribed fire [PR]) under current fire suppression simulated by LANDIS were compared in a 5 × 2 factorial design over a 300-year period. The results showed that PR scenarios are more effective at reducing the occurrence and burn area of catastrophic fires than PB scenarios. In addition, area burned by high intensity fire can be tremendously reduced by increasing low intensity fires with a higher level of treatment area under the various PR scenarios. The cost effectiveness of alternative fuel reduction strategies is strongly dependent on treatment area. In general, PB scenarios will be more cost effective in larger treatment areas and PR scenarios in smaller. We recommend mechanical treatments in combination with prescribed fire, with 4% of landscape treated in each decade (PR04) to be the optimal fuel reduction strategy in the study area based on risk control and cost efficiency analysis. However, the most challenging work in China is to make local forest policy makers and land managers accept the ecological function of fire on forest ecosystems.     

Factors influencing the formation of unburned forest islands within the perimeter of a large forest fire

Large forest fires have recently increased in frequency and severity in many ecosystems. Due to the heterogeneity in fuels, weather and topography, these large fires tend to form unburned islands of vegetation. This study focuses on a large forest fire that occurred in north-eastern Spain in 1998, which left large areas of unburned vegetation within its perimeter. Based on a satellite post-fire severity map we searched for the relative influence of biotic and abiotic factors leading to unburned island formation. We divided the area of the fire into individual units we called “slopes” which were meant to separate the differential microclimatic effects of contrasted aspects. The number of unburned islands and their areas were related to 12 variables that influence their formation (i.e. land cover composition, aspect, steepness, forest structure, two landscape indices and weather variables). We hypothesized that unburned vegetation islands would concentrate on northern aspects, in less flammable forests (i.e. broadleaf species) and higher fragmentation to interrupt the advance of fire. While north and western aspects did have a higher presence of unburned vegetation islands, our study suggests greater presence of islands in slopes that are larger (i.e. more continuous areas with relatively homogeneous aspect), with greater proportions of forest cover, with higher wood volumes and with lower proportions of broadleaf species. Climate also played a role, with relative humidity and wind speed positively and negatively correlated to island formation, respectively. Unburned vegetation was more frequent on slopes with lower diversity of land covers and higher dominance of one land cover in the slope. Since slopes with only one land cover (i.e. forests) had more islands than slopes with multiple cover types, we infer that under severe meteorological conditions, fragmented forests can be more affected by wind and by water stress, thus burning more readily than forests that are protected from this edge phenomenon. These results would reinforce forest management strategies that avoid linear features (fire-lines and fire-breaks), to enhance fuel treatments that focus on areas and minimize fragmentation.     

Comparing the role of fuel breaks across southern California national forests

Fuel treatment of wildland vegetation is the primary approach advocated for mitigating fire risk at the wildland-urban interface (WUI), but little systematic research has been conducted to understand what role fuel treatments play in controlling large fires, which factors influence this role, or how the role of fuel treatments may vary over space and time. We assembled a spatial database of fuel breaks and fires from the last 30 years in four southern California national forests to better understand which factors are consistently important for fuel breaks in the control of large fires. We also explored which landscape features influence where fires and fuel breaks are most likely to intersect. The relative importance of significant factors explaining fuel break outcome and number of fire and fuel break intersections varied among the forests, which reflects high levels of regional landscape diversity. Nevertheless, several factors were consistently important across all the forests. In general, fuel breaks played an important role in controlling large fires only when they facilitated fire management, primarily by providing access for firefighting activities. Fire weather and fuel break maintenance were also consistently important. Models and maps predicting where fuel breaks and fires are most likely to intersect performed well in the regions where the models were developed, but these models did not extend well to other regions, reflecting how the environmental controls of fire regimes vary even within a single ecoregion. Nevertheless, similar mapping methods could be adopted in different landscapes to help with strategic location of fuel breaks. Strategic location of fuel breaks should also account for access points near communities, where fire protection is most important.     

Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China

A forest fire can be a real ecological disaster regardless of whether it is caused by natural forces or human activities, it is possible to map forest fire risk zones to minimize the frequency of fires, avert damage, etc. A method integrating remote sensing and GIS was developed and applied to forest fire risk zone mapping for Baihe forestry bureau in this paper. Satellite images were interpreted and classified to generate vegetation type layer and land use layers （roads, settlements and farmlands）. Topographic layers （slope, aspect and altitude） were derived from DEM. The thematic and topographic information was analyzed by using ARC/INFO GIS software. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the layers （vegetation type, slope, aspect, altitude and distance from r3ads, farmlands and settlements） according to their sensitivity to fire or their fire-inducing capability. Five categories of forest fire risk ranging from very high to very low were derived automatically. The mapping result of the study area was found to be in strong agreement with actual fire-affected sites.     

A computer-system that classifies the prefectures of Greece in forest fire risk zones using fuzzy sets

All of the Mediterranean countries face a serious forest fire problem. The main factors that affect the problem of forest fires in Greece are vegetation, climate conditions and most of all, arson (Proceedings of Forest Fires in Greece, Thessaloniki, 1990, p. 97). In Greece, after 1974, the number of forest fires and the total burned areas have risen dramatically. The design of an effective fight and prevention policy is a very important matter, as it can minimize the destruction. This paper describes an expert system that classifies the prefectures of Greece into forest fire risk zones, using a completely new methodology. The concept of fuzzy expected intervals (F.E.I.) was defined by Kandel and Byatt (Proc. IEEE, 66, 1978, 1619) and offered a very good approach towards forest fire risk classification. Fuzzy expected intervals are narrow intervals of values that best describe the forest fire problem in the country or a part of the country for a certain time period. Fuzzy logic was applied to produce a F.E.I. for each prefecture of the country. A successful classification of the prefectures of Greece (in forest fire risk zones) was performed by the expert system by comparing the produced fuzzy expected intervals to each other and by using a supervised machine learning algorithm that assigns a certain weight of forest fire risk to each prefecture (Machine Learning, John Wiley and Sons, 1995).     

Modeling wildfire risk to northern spotted owl (Strix occidentalis caurina) habitat in Central Oregon,USA

Natural disturbances including wildfire, insects and disease are a growing threat to the remaining late successional forests in the Pacific Northwest, USA. These forests are a cornerstone of the region's ecological diversity and provide essential habitat to a number of rare terrestrial and aquatic species including the endangered northern spotted owl (Strix occidentalis caurina). Wildfires in particular have reduced the amount of late successional forests over the past decade, prompting land managers to expand investments in forest management in an attempt to slow losses and mitigate wildfire risk. Much of the emphasis is focused specifically on late successional reserves established under the Northwest Forest Plan to provide habitat for spotted owls. In this paper, we demonstrate a probabilistic risk analysis system for quantifying wildfire threats to spotted owl habitat and comparing the efficacy of fuel treatment scenarios. We used wildfire simulation methods to calculate spatially explicit probabilities of habitat loss for fuel treatment scenarios on a 70,245 ha study area in Central Oregon, USA. We simulated 1000 wildfires with randomly located ignitions and weather conditions that replicated a recent large fire within the study area. A flame length threshold for each spotted owl habitat stand was determined using the forest vegetation simulator and used to predict the proportion of fires that resulted in habitat loss. Wildfire modeling revealed a strong spatial pattern in burn probability created by natural fuel breaks (lakes and lava flows). We observed a non-linear decrease in the probability of habitat loss with increasing treatment area. Fuels treatments on a relatively minor percentage of the forested landscape (20%) resulted in a 44% decrease in the probability of spotted owl habitat loss averaged over all habitat stands. The modeling system advances the application of quantitative and probabilistic risk assessment for habitat and species conservation planning.