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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.

The most unpredictable and uncontrollable wildfires are those that burn in the crowns of live vegetation. The fuels that feed these crown fires are mostly live, green foliage. Unfortunately, little is known about how live fuels combust. To understand how live fuels burn, piloted ignition experiments were performed with lodgepole pine and Douglas-fir. The thermal behavior (thick versus thin) of both live and dead needles was explored. Both live and dry needles were shown to behave as thermally intermediate solids in this apparatus. Additionally, samples were collected throughout the growing season to take advantage of the natural variation in moisture content and chemical composition. This data set was then compared to several correlations found in the literature to determine whether live fuel ignition can be predicted by moisture content alone and to test the applicability of these models to the wildland fire problem. Many of the correlations from the literature for ignition time with moisture content fail to capture the trends with live fuels. A linear regression of the ignition time with moisture content only predicts 74–80% of the variability suggesting that there is another mechanism controlling ignition time of live fuels. Based on the hypothesized difference in water storage between live and wet dead fuels, the chemical composition of the live needles was included in an empirical model for ignition time. Including chemical composition improved the prediction accuracy for Douglas-fir needles only. Because the thermal properties of live foliage are largely unknown, it is possible that the predictions from more physically-based models would show improvement with more accurate values of density, thermal conductivity, and specific heat.

We used simulation modeling to analyze wildfire exposure to social and ecological values on a 0.6 million ha national forest in central Oregon, USA. We simulated 50,000 wildfires that replicated recent fire events in the area and generated detailed maps of burn probability (BP) and fire intensity distributions. We also recorded the ignition locations and size of each simulated fire and used these outputs to construct a fire source–sink ratio as the ratio of fire size to burn probability. Fire behavior was summarized for federal land management designations, including biological conservation reserves, recreational sites, managed forest, and wildland urban interface. Burn probability from the simulations ranged from 0.00001 to 0.026 within the study area (mean = 0.0023), and exhibited substantial variation among and within land designations. Simulated fire behavior was broadly related to gradients in fire regimes, although the combined effects of fuel, topography, and simulated weather resulted in fine scale patterns not reflected in ecological and vegetation data. Average BP for the northern spotted owl (Strix occidentalis caurina) nesting sites ranged from 0.0002 to 0.04. Among the 130 different wildland urban interface areas, average BP varied from 0.0001 to 0.02. Spatial variation in the source–sink ratio was pronounced, and strongly affected by the continuity and arrangement of surface and canopy fuel. We discuss the management implications in terms of prioritizing fuel management activities and designing conservation strategies on fire prone landscapes within the 177 million ha national forest network.

In this paper we review progress towards the implementation of a risk management framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical methods to measure wildfire risk to human and ecological values and to inform fuel treatment investment strategies at national, regional, and local scales. Application of the risk management framework to support wildfire incidents has been dramatically advanced with the Wildland Fire Decision Support System and allowed policy modifications that encourage management of incidents for multiple objectives. The new wildfire risk management decision support systems we discuss provide Federal agencies in the US the ability to integrate risk-informed approaches to a wide range of wildfire management responsibilities and decisions. While much progress has been made, there remain several barriers that need to be addressed to fully integrate risk science into current wildfire management practices. We conclude by identifying five primary issues that if properly addressed could help public land management better realize the opportunities and potential payoffs from fully adopting a risk management paradigm.

This simulation research was conducted in order to develop a large-fire risk assessment system for the contiguous land area of the United States. The modeling system was applied to each of 134 Fire Planning Units (FPUs) to estimate burn probabilities and fire size distributions. To obtain stable estimates of these quantities, fire ignition and growth was simulated for 10,000 to 50,000 “years” of artificial weather. The fire growth simulations, when run repeatedly with different weather and ignition locations, produce burn probabilities and fire behavior distributions at each landscape location (e.g., number of times a “cell” burns at a given intensity divided by the total years). The artificial weather was generated for each land unit using (1) a fire danger rating index known as the Energy Release Component (ERC) which is a proxy for fuel moisture contents, (2) a time-series analysis of ERC to represent daily and seasonal variability, and (3) distributions of wind speed and direction from weather records. Large fire occurrence was stochastically modeled based on historical relationships to ERC. The simulations also required spatial data on fuel structure and topography which were acquired from the LANDFIRE project ( http://www.landfire.gov ). Fire suppression effects were represented by a statistical model that yields a probability of fire containment based on independent predictors of fire growth rates and fuel type. The simulated burn probabilities were comparable to observed patterns across the U.S. over the range of four orders of magnitude, generally falling within a factor of 3 or 4 of historical estimates. Close agreement between simulated and historical fire size distributions suggest that fire sizes are determined by the joint distributions of spatial opportunities for fire growth (dependent on fuels and ignition location) and the temporal opportunities produced by conducive weather sequences. The research demonstrates a practical approach to using fire simulations at very broad scales for purposes of operational planning and perhaps ecological research.

The spatial, temporal, and social dimensions of wildfire risk are challenging U.S. federal land management agencies to meet societal needs while maintaining the health of the lands they manage. In this paper we present a quantitative, geospatial wildfire risk assessment tool, developed in response to demands for improved risk-based decision frameworks. The methodology leverages off recent and significant advancements in wildfire simulation models and geospatial data acquisition and management. The tool is intended to facilitate monitoring trends in wildfire risk over time and to develop information useful in prioritizing fuels treatments and mitigation measures. Wildfire risk assessment requires analyzing the likelihood of wildfire by intensity level, and the magnitude of potential beneficial and negative effects to valued resources from fire at different intensity levels. This effort is designed to support strategic planning by systematically portraying how fire likelihood and intensity influence risk to social, economic, and ecological values at the national scale. We present results for the continental United States, analyze high risk areas by geographic region, and examine how risk evaluations changes under different assumptions with sensitivity analysis. We conclude by discussing further potential uses of the tool and research needs.

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.

We simulated fuel reduction treatments on a 16,000 ha study area in Oregon, US, to examine tradeoffs between placing fuel treatments near residential structures within an urban interface, versus treating stands in the adjacent wildlands to meet forest health and ecological restoration goals. The treatment strategies were evaluated by simulating 10,000 wildfires with random ignition locations and calculating burn probabilities by 0.5 m flame length categories for each 30 m � 30 m pixel in the study area. The burn conditions for the wildfires were chosen to replicate severe fire events based on 97th percentile historic weather conditions. The burn probabilities were used to calculate wildfire risk profiles for each of the 170 residential structures within the urban interface, and to estimate the expected (probabilistic) wildfire mortality of large trees (>53.3 cm) that are a key indicator of stand restoration objectives. Expected wildfire mortality for large trees was calculated by building flame length mortality functions using the Forest Vegetation Simulator, and subsequently applying these functions to the burn probability outputs. Results suggested that treatments on a relatively minor percentage of the landscape (10%) resulted in a roughly 70% reduction in the expected wildfire loss of large trees for the restoration scenario. Treating stands near residential structures resulted in a higher expected loss of large trees, but relatively lower burn probability and flame length within structure buffers. Substantial reduction in burn probability and flame length around structures was also observed in the restoration scenario where fuel treatments were located 5–10 km distant. These findings quantify off-site fuel treatment effects that are not analyzed in previous landscape fuel management studies. The study highlights tradeoffs between ecological management objectives on wildlands and the protection of residential structures in the urban interface. We also advance the application of quantitative risk analysis to the problem of wildfire threat assessment.

Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of environmental factors on BP patterns is not well understood. This study examined the relative effects of ignitions, fuels, and weather on mean BP and spatial patterns in BP (i.e., BP variability) using highly simplified artificial landscapes and wildfire simulation methods. Our results showed that a limited set of inputs yielded a wide range of responses in the mean and spatial patterning of BP. The input factors contributed unequally to mean BP and to BP variability: so-called top-down controls (weather) primarily influenced mean BP, whereas bottom-up influences (ignitions and fuels) were mainly responsible for the spatial patterns of BP. However, confounding effects and interactions among factors suggest that fully separating top-down and bottom-up controls may be impossible. Furthermore, interactions among input variables pro- duced unanticipated but explainable BP patterns, hinting at complex topological dependencies among the main determinants of fire spread and the resulting BP. The results will improve our understanding of the spatial ecology of fire regimes and help in the interpretation of patterns of fire likelihood on real landscapes as part of future wildfire risk assessments.

Methods for scheduling forest management activities in a spatial pattern (dispersed, clumped, random, and regular) are presented, with the intent to examine the effects of placement of activities on resulting simulated wildfire behavior. Both operational and fuel reduction management prescriptions are examined, and a heuristic was employed to schedule the activities. The main hypothesis is that simulated wildfire effects during a severe fire season may be mitigated by scheduling activities in a pattern across the landscape. Results suggest: (1) operational management prescriptions, designed to promote the development of forest structure within a desired range of stand density, were not appropriate for mitigating wildfire effects, and (2) increased harvest levels obscure spatial patterns of activity, making patterns less clear as harvests increase. Results also suggest that fuel reduction management prescriptions may marginally minimize wildfire severity during a severe fire season, when scheduled in a spatial pattern.

The National Wildfire Coordinating Group’s definition of extreme fire behavior indicates a level of fire behavior characteristics that ordinarily precludes methods of direct control action. One or more of the following is usually involved: high rate of spread, prolific crowning/ spotting, presence of fire whirls, and strong convection column. Predictability is difficult as such fires often influence their environment to some degree and behave erratically, sometimes dangerously. Alternate terms include “blow up” and “fire storm.” Fire managers examining fires over the last 100 years have come to understand many of the factors necessary for extreme fire behavior development. This effort produced guidelines included in current firefighter training, which presents the current methods of predicting extreme fire behavior by using the crown fire model, which is based on the environmental influences of weather, fuels, and topography. Current training does not include the full extent of scientific understanding nor does it include the most recent scientific knowledge. National Fire Plan funds and the Joint Fire Science Program have sponsored newer research related to wind profiles’ influence on fire behavior, plume growth, crown fires, fire dynamics in live fuels, and conditions associated with vortex development. Of significant concern is that characteristic features of extreme fire behavior depend on conditions undetectable on the ground, namely invisible properties such as wind shear or atmospheric stability. No one completely understands all the factors contributing to extreme fire behavior because of gaps in our knowledge. These gaps, as well as the limitations as to when various models or indices apply should be noted to avoid application where they are not appropriate or warranted. This synthesis summarizes existing extreme fire behavior knowledge. It consists of two volumes. Volume 1 is for fire managers, firefighters, and others in the fire community who are not experts or specialists in fire behavior but need to understand the basics of extreme fire behavior. Volume 2 is more technical and is intended for fire behaviorists and fire researchers. The objective of this project is to synthesize existing extreme fire behavior knowledge in a way that connects the weather, fuel, and topographic factors that contribute to development of extreme fire behavior. This synthesis focuses on the state of the science but also considers how that science is currently presented to the fire management community, including incident commanders, fire behavior analysts, incident meteorologists, National Weather Service office forecasters, and firefighters. The synthesis seeks to delineate the known, the unknown, and areas of research with the greatest potential impact on firefighter protection.

Effective decisionmaking in environmental management requires the consideration of multiple objectives that may conflict. Common optimization methods use weights on the multiple objectives to aggregate them into a single value, neglecting valuable insight into the relationships among the objectives in the management problem.

Large wildfires of increasing frequency and severity threaten local populations and natural resources and contribute carbon emissions into the earth-climate system. Although wildfires have been researched and modeled for decades, no verifiable physical theory of spread is available to form the basis for the precise predictions needed to manage fires more effectively and reduce their environmental, economic, ecological, and climate impacts. Here, we report new experiments conducted at multiple scales that appear to reveal how wildfire spread derives from the tight coupling between flame dynamics induced by buoyancy and fine-particle response to convection. Convective cooling of the fine-sized fuel particles in wildland vegetation is observed to efficiently offset heating by thermal radiation until convective heating by contact with flames and hot gasses occurs. The structure and intermittency of flames that ignite fuel particles were found to correlate with instabilities induced by the strong buoyancy of the flame zone itself. Discovery that ignition in wildfires is critically dependent on nonsteady flame convection governed by buoyant and inertial interaction advances both theory and the physical basis for practical modeling.

We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981-2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981-2010, 2011-2040, and 2041-2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041-2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.

Performance of fuel treatments in modifying behavior and effects of the largest wildfires has rarely been evaluated, because the necessary data on fire movement, treatment characteristics, and fire severity were not obtainable together. Here we analyzed satellite imagery and prescribed fire records from two Arizona wildfires that occurred in 2002, finding that prescribed fire treatments reduced wildfire severity and changed its progress. Prescribed burning in ponderosa pine forests 1-9 years before the Rodeo and Chediski fires reduced fire severity compared with untreated ar- eas, despite the unprecedented 1860-km 2 combined wildfire sizes and record drought. Fire severity increased with time since treatment but decreased with unit size and number of repeated prescribed burn treatments. Fire progression cap- tured by Landsat 7 enhanced thematic mapper plus (ETM+) clearly showed the fire circumventing treatment units and protecting areas on their lee side. This evidence is consistent with model predictions that suggest wildland fire size and severity can be mitigated by strategic placement of treatments. Resume : L'impact de la reduction des combustibles sur le comportement et les effets des incendies de foret de grande envergure a rarement ete evalue parce qu'il n'etait pas possible de rassembler les donnees necessaires sur le mouve- ment du feu, les caracteristiques du traitement et la severite du feu. Les auteurs ont analyse des images satellitaires et des donnees de brulages diriges associes a deux incendies de foret qui sont survenus en Arizona en 2002. Les resultats montrent que les brulages diriges ont reduit la severite des incendies de foret et modifie leur progression. Des brulages diriges dans les forets de pin ponderosa, un a neuf ans avant que surviennent les incendies de Rodeo et Chediski, ont reduit la severite du feu comparativement aux zones non traitees, malgre la dimension combinee sans precedent de ces incendies, soit 1860 km 2 , et une secheresse record. La severite du feu a augmente en fonction du temps ecoule depuis le traitement mais a diminue en fonction de la dimension et du nombre de fois que les brulages diriges avaient ete re- petes. La progression des incendies captee par Landsat 7 (appareil de cartographie thematique ameliore) a clairement demontre que le feu a contourne les aires traitees et que les zones situees du cote sous le vent des aires traitees ont ainsi ete protegees. Cette observation est consistante avec les predictions du modele qui indique que la dimension et la severite des incendies de foret peuvent etre attenuees en disposant les traitements de facon strategique. (Traduit par la Redaction) Finney et al. 1722

Quantitative fire risk analysis depends on characterizing and combining fire behavior probabilities and effects. Fire behavior probabilities are different from fire occurrence statistics (historic numbers or probabilities of discovered ignitions) because they depend on spatial and temporal factors controlling fire growth. That is, the likelihood of fire burning a specific area is dependent on ignitions occurring off-site and the fuels, topography, weather, and relative fire direction allowing each fire to reach that location. Research is required to compare computational short-cuts that have been proposed for approximating these fire behavior distributions. Fire effects in a risk analysis must also be evaluated on a common scale for the variety of values susceptible to wildland fire. This means that appraisals of fire impacts to human infrastructure and ecological values must be measured by the same currency so that the risk assessment yields a single expectation of fire effects. Ultimately, this will help guide planning and investment into management activities that can alter either the probabilities of damaging fire or the susceptibility to those fire behaviors.

Fire-growth modeling on complex landscapes can be approached as a search for the minimum time for fire to travel among nodes in a two-dimensional network. The paths producing minimum travel time between nodes are then interpolated to reveal the fire perimeter positions at an instant in time. These fire perimeters and their fire behavior characteristics (e.g., spread rate, fireline intensity) are essentially identical to the products of perimeter expansion techniques. Travel time methods offer potential advantages for some kinds of modeling applications, because they are more readily parallelized for computation than methods for expanding fire fronts and require no correction for crossed fronts or merging separate fires.

Logistic regression equations of prescribed fire mortality were developed for white fir (Abies concolor [Gord. and Glend.] Lindl.), sugar pine (Pinus lambertiana Dougl.), ponderosa pine (Pinus ponderosa Laws.), incense-cedar (Calocedrus decurrens [Torr.] Floren.), and giant sequoia (Sequoiadendron giganteum [Lindley] Buchholz) in the southern Sierra Nevada, California. A total of 1025 trees were analyzed in this study. Variables included in the mortality equations are diameter at breast height, percent crown volume scorched, crown scorch height, and local forest floor consumption. The likelihood ratio χ2 was highly significant (P

Wind-aided laboratory fires spreading through laser-cut cardboard fuel beds were instrumented and analyzed for physical processes associated with spread. Flames in the spanwise direction appeared as a regular series of peaks and troughs that scaled directly with flame length. Flame structure in the stream-wise direction fluctuated with the forward advection of coherent parcels that originated near the rear edge of the flame zone. Thermocouples arranged longitudinally in the fuel beds revealed the frequency of temperature fluctuations decreased with flame length but increased with wind speed. The downstream extent of these fluctuations from the leading flame edge scaled with Froude number and flame zone depth. The behaviors are remarkably similar to those of boundary layers, suggesting a dominant role for buoyancy in determining wildland fire spread.

In this second part of a two-part exploration into the dynamic behavior observed in wildland fires, time scales differentiating convective and radiative heat transfer are further explored. Scaling laws for the two different types of heat transfer were considered: radiation-driven fire spread and convection-driven fire spread, which can both occur during wildland fires. A new interpretation of the inertial forces introduced a downstream, time-dependent frequency ω, which captures the dynamic, vortex shedding behavior of flames due to the unstable nature of the turbulent flow created in the wake of the fire. Excelsior and paper strip experiments suggest many wildland fire scenarios fall into the convection-driven spread regime.

Shaded fuelbreaks and larger landscape fuel treatments, such as prescribed fire, are receiving renewed interest as forest protection strategies in the western United States. The effectiveness of fuelbreaks remains a subject of debate because of differing fuelbreak objectives, prescriptions for creation and maintenance, and their placement in landscapes with differing fire regimes. A well-designed fuelbreak will alter the behavior of wildland fire entering the fuel-altered zone. Both surface and crown fire behavior may be reduced. Shaded fuelbreaks must be created in the context of the landscape within which they are placed. No absolute standards for fuelbreak width or fuel reduction are possible, although recent proposals for forested fuelbreaks suggest 400 m wide bands where surface fuels are reduced and crown fuels are thinned. Landscape-level treatments such as prescribed fire can use shaded fuelbreaks as anchor points, and extend the zone of altered fire behavior to larger proportions of the landscape. Coupling fuelbreaks with area-wide fuel treatments can reduce the size, intensity, and effects of wildland fires. # 2000 Elsevier Science B.V. All rights reserved.

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.

We evaluated the spatiotemporal changes in wildfire regime and exposure in a fire-prone Mediterranean area (Sardinia, Italy) in relation to changes in ignition patterns, weather, suppression activities, and land uses. We also used wildfire simulations to identify fine-scale changes in wildfire exposure of important features on the island. Sardinia experienced a sharp reduction in fire number and area burned between the periods 1980–1994 and 1995–2009. Despite this decrease, losses and fatalities from wildfires continue. This suggests that localized areas and seasons of high wildfire risk persist on the island. Our analysis showed (1) a reduction in area burned (60,000–20,000 ha/year) and ignitions (3,700–2,600 fires/year), (2) an advance of 15 days for the fire season peak, (3) an increase in spring temperatures, and (4) an increase in fire exposure for WUI areas. Little change was noted for land use types and associated fuels. Most likely the reduction in fire activity may be due to a combination of social factors and suppression capabilities. On the other hand, simulation modeling suggested pockets of high wildfire exposure in specific places. The combined empirical analyses and simulation modeling provided a robust approach to understanding the spatiotemporal dynamics of wildfire risk on the island.

Res_eng:Laboratory fires spreading through laser-cut cardboard fuel beds were instrumented and analyzed for physical processes associated with spread. Flames in the span-wise direction appeared as a regular series of peaks-and-troughs that scaled directly with flame length. Flame structure in the stream-wise direction fluctuated with the forward advection of coherent parcels that originated near the rear edge of the flame zone. Thermocouples arranged longitudinally in the fuel beds revealed the frequency of temperature fluctuations decreased with flame length but increased with wind speed. The behaviors are remarkably similar to those of boundary layers, suggesting a dominant role for buoyancy in determining wildland fire spread.

Maps of the number, size, and species of trees in forests across the United States are desirable for a number of applications. For landscape-level fire and forest simulations that use the Forest Vegetation Simulator (FVS), a spatial tree-level dataset, or “tree list”, is a necessity. FVS is widely used at the stand level for simulating fire effects on tree mortality, carbon, and biomass, but uses at the landscape level are limited by lack of availability of forest inventory data for large contiguous areas. Detailed mapping of trees across large areas is not feasible with current technologies, but statistical methods for matching forest plot data with biophysical characteristics of the landscape offer a practical means to populate landscapes with a limited set of forest plot inventory data. We used a modified random forests approach, with Landfire vegetation and biophysical predictors at 30m grid resolution. In essence, the random forests method creates a “forest” of decision trees in order to choose the forest plot with the best statistical match for each grid cell in the landscape. Landfire data was used in this project because is publicly available, offers seamless coverage of variables needed for fire models, and is consistent with other datasets, including burn probabilities and flame length probabilities generated for the continental US by Fire Program Analysis (FPA). We used the imputed forest plot data to generate a map of forest cover and height as well as existing vegetation group for a study area in eastern Oregon, and examined correlations with Landfire data. The results showed good correspondence between the two data sets (84-97% within-class agreement, depending on the variable). In future research, the new imputed grid of inventory data will be used for landscape simulation studies to determine risk to terrestrial carbon resources from wildfire as well as to investigate the effect of fuel treatments on burn probability and fire sizes.

Substantial investments in fuel management activities on national forests in the western US are part of a national strategy to reduce human and ecological losses from catastrophic wildfire and create fire resilient landscapes. Prioritizing these investments within and among national forests remains a challenge, partly because a comprehensive assessment that establishes the current wildfire risk and exposure does not exist, making it difficult to identify national priorities and target specific areas for fuel management. To gain a broader understanding of wildfire exposure in the national forest system, we analyzed an array of simulated and empirical data on wildfire activity and fuel treatment investments on the 82 western US national forests. We first summarized recent fire data to examine variation among the Forests in ignition frequency and burned area in relation to investments in fuel reduction treatments. We then used simulation modeling to analyze fine-scale spatial variation in burn probability and intensity. We also estimated the probability of a mega-fire event on each of the Forests, and the transmission of fires ignited on national forests to the surrounding urban interface. The analysis showed a good correspondence between recent area burned and predictions from the simulation models. The modeling also illustrated the magnitude of the variation in both burn probability and intensity among and within Forests. Simulated burn probabilities in most instances were lower than historical, reflecting fire exclusion on many national forests. Simulated wildfire transmission from national forests to the urban interface was highly variable among the Forests. We discuss how the results of the study can be used to prioritize investments in hazardous fuel reduction within a comprehensive multi-scale risk management framework.

Experiments were conducted to examine the potential for rifle bullets to ignite organic matter after impacting a hard surface. The tests were performed using a variety of common cartridges (7.62x51, 7.62x39, 7.62x54R, and 5.56x45) and bullet materials (steel core, lead core, solid copper, steel jacket, and copper jacket). Bullets were fired at a steel plate that deflected fragments downward into a collection box containing oven-dried peat moss. We found that bullets could reliably cause ignitions, specifically those containing steel components (core or jacket) and those made of solid copper. Lead core-copper jacketed bullets caused one ignition in these tests. Ignitions of peat also occurred with a small set of tests using solid copper bullets and a granite target. Thermal infra-red video and temperature sensitive paints suggested that the temperature of bullet fragments could exceed 800°C. Bullet fragments collected from a water tank were larger for solid copper and steel core/jacketed bullets than for lead core bullets, which also facilitate ignition. Physical processes are reviewed with the conclusion that kinetic energy of bullets is transformed to thermal energy by plastic deformation and fracturing of bullets because of the high-strain rates during impact. Fragments cool rapidly but can ignite organic matter, particularly fine material, if very dry and close to the impact site.

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 management within the United States continues to increase in complexity, as the converging drivers of (1) increased development into fire-prone areas, (2) accumulated fuels from historic management practices, and (3) climate change potentially magnify threats to social and ecological values (Bruins et al., 2010; Gude et al., 2008; Littell et al., 2009). The need for wildfire risk assessment tools continues to grow, as land management agencies attempt to map wildfire risk and develop strategies for mitigation. Developing and employing wildfire risk assessment models can aid management decision-making, and can facilitate prioritization of investments in mitigating losses and restoring fire on fire prone landscapes. Further, assessment models can be used for monitoring trends in wildfire risk over space and across time.

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 nonburnable fuels, ranged from 0–1.92x10^3, with a mean value of 6.48x10^5. Spatial patterns in modelled outputs werebr /> 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 managementbr /> activities./p>

The FLAME Act of 2009 requires the U.S. Department of Agriculture Forest Service and the U.S. Department of Interior to submit to Congress a Cohesive Wildfire Management Strategy. In this report, we explore the general science available for a risk-based approach to fire and fuels management and suggest analyses that may be applied at multiple scales to inform decisionmaking and tradeoff analysis. We discuss scientific strengths and limitations of wildfire risk assessment frameworks, including the benefit of broad scalability as demonstrated by four recent case studies. We further highlight the role of comparative risk assessment, which extends the analysis to include the decision space available to managers and stakeholders to allow them to explore the tradeoffs between alternative courses of action. We identify scientific limitations of the analytical protocol and discuss questions of how to better address climate change, smoke modeling issues, and socioeconomic vulnerability, and how to better quantify treatment effectiveness. Key challenges are: achieving a balance between retaining analytical flexibility at regional and sub-regional planning scales while simultaneously retaining data and methodological consistency at the national scale, and identifying and aligning regional and national priorities to inform multi-objective strategy development. As implementation proceeds, the analytical protocol will no doubt be modified, but the contents of this report comprise a rigorous and transparent framework for comparative risk assessment built from the best available science.

The National Wildfire Coordinating Group definition of extreme fire behavior (EFB) indicates a level of fire behavior characteristics that ordinarily precludes methods of direct control action. One or more of the following is usually involved: high rate of spread, prolific crowning/spotting, presence of fire whirls, and strong convection column. Predictability is difficult because such fires often exercise some degree of influence on their environment and behave erratically, sometimes dangerously. Alternate terms include “blow up” and “fire storm.” Fire managers examining fires over the last 100 years have come to understand many of the factors necessary for EFB development. This work produced guidelines included in current firefighter training, which presents the current methods of predicting EFB by using the crown fire model, which is based on the environmental influences of weather, fuels, and topography. Current training does not include the full extent of scientific understanding. Material in current training programs is also not the most recent scientific knowledge. National Fire Plan funds have sponsored newer research related to wind profiles’ influence on fire behavior, plume growth, crown fires, fire dynamics in live fuels, and conditions associated with vortex development. Of significant concern is that characteristic features of EFB depend on conditions undetectable on the ground, relying fundamentally on invisible properties such as wind shear or atmospheric stability.Obviously no one completely understands all the factors contributing to EFB because of gaps in our knowledge. These gaps, as well as the limitations as to when various models or indices apply should be noted to avoid application where they are not appropriate or warranted. This synthesis will serve as a summary of existing extreme fire behavior knowledge for use by fire managers, firefighters, and fire researchers.The objective of this project is to synthesize existing EFB knowledge in a way that connects the weather, fuel, and topographic factors that contribute to development of EFB. This synthesis will focus on the state of the science, but will also consider how that science is currently presented to the fire management community, including incident commanders, fire behavior analysts, incident meteorologists, National Weather Service office forecasters, and firefighters. It will seek to clearly delineate the known, the unknown, and areas of research with the greatest potential impact on firefighter protection.

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.

The study was designed to produce data for modeling effects of prescribed fire treatments on top killing and basal sprouting of coast redwood trees (Sequoiasempervirens (D. Don) Endl.) at the plot and individual-tree level. Prescribed fire treatments included two levels of fireline intensity and surface fuel consumption crossed in randomized blocks. Burning was conducted on 32 plots each containing approximately 150 to 250 redwoods. Binary responses of individual trees were modeled using logistic regression analysis. Percent response of trees on each plot by 5-cm diameter classes was modeled using logistic and nonlinear regression analysis. Tree diameter, surface fuel consumption, flame length, and crown scorch were significant predictors in all models of top killing and basal sprouting. Models relating heights of crown scorch and bark charring to fire and tree characteristics were also developed. The ability of coast redwood to sprout along branches following foliar damage from fire is unusual among conifers and contributes to a low incidence of top killing.

This paper explores crisis coverage in local, small-market newspapers. Comparing relevant theory with the practice of journalism in Alamosa, CO’s Valley Courier, this content analysis suggests close relationships between media, government and business in small communities, contributing to coverage that veers away from journalism’s best practices. The result is coverage that overlooks potentially important information about the crisis’ causes and eschews journalism’s watchdog and investigative responsibilities, while offering local elite sources significant degrees of power over the shape of the coverage. As national news coverage contracts, situations like this rise in prominence.

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 topography - using 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.

Forests in the vicinity of Desolation Peak, Washington, are of special ecological interest because of their transitional nature between coastal and interior forest types. The area is west of the Cascade Mountain crest but in the rainshadow of mountains farther to the west. Fire return intervals were hypothesized to be shorter than typical for coastal forest types, such as those dominated by western hemlock and Pacific silver fir, and longer than typical for interior forest types, such as ponderosa pine, owing to the close juxtaposition of these types at Desolation Peak. Seven forest community types were defined, and a 400-year fire history was developed for this 3500-ha area. The average natural fire rotation was 100 years; this varied by a factor of two by century and by topographic aspect. Forest types typical of coastal regions, such as Douglas-fir, – western hemlock and mountain hemlock – Pacific silver fir, had mean fire return intervals (108–137 years) much lower than in other western Washington areas. The most interior forest type, ponderosa pine – Douglas-fir, had a higher mean fire return interval (52 years) than reported for similar forest types east of the Cascades. Historically, fire has created structural and landscape diversity on Desolation Peak and may be an important process in the maintenance of such diversity into the future.

Acomprehensive, mechanistic simulation of wildland fire and ecosystem dynamics across a landscape may not be possible because of computer limitations, inadequate research, inconsistent data, and extensive parameterization. Therefore empirical and stochastic approaches must be substituted for many mechanistic modules until research and technology improve. Unfortunately, nonmechanistic approaches limit the scope and applicability of spatial ecosystem process models. Ecosystem dynamics models need to be refined so that appropriate compartments that model fire spread and effects are explicitly represented in their structure. Landscape disturbance models need to simulate fire growth unconstrained by vegetation polygon delineations. Most important, these models must be designed in the context of the simulation objective to ensure that appropriate simulation modules are included.