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Composition of pyrolysis gases for wildland fuels is often determined using ground samples heated in non-oxidising environments. Results are applied to wildland fires where fuels change spatially and temporally, resulting in variable fire behaviour with variable heating. Though historically used, applicability of traditional pyrolysis results to the wildland fire setting is unknown. Pyrolytic and flaming combustion gases measured in wind tunnel fires and prescribed burns were compared using compositional data techniques. CO2 was dominant in both. Other dominant gases included CO, H2 and CH4. Relative amounts of CO, CO2 and CH4 were similar between fire phases (pyrolysis, flaming combustion); relatively more H2 was observed in pyrolysis samples. All gas log-ratios with CO2 in pyrolysis samples were larger than in flaming combustion samples. Presence of live plants significantly affected gas composition. A logistic regression model correctly classified 76% of the wind tunnel samples as pyrolysis or flaming combustion based on gas composition. The model predicted 60% of the field samples originated from pyrolysis. Fire location (wind tunnel, field) and fire phase affected gas composition. The compositional approach enabled analysis and modelling of gas compositions, producing results consistent with the basic characteristics of the data.

Methods to accurately estimate spatially explicit fuel consumption are needed because consumption relates directly to fire behavior, effects, and smoke emissions. Our objective was to quantify sparkleberry (Vaccinium arboretum Marshall) shrub fuels before and after six experimental prescribed fires at Fort Jackson in South Carolina. We used a novel approach to characterize shrubs non-destructively from three-dimensional (3D) point cloud data collected with a terrestrial laser scanner. The point cloud data were reduced to 0.001 m–3 voxels that were either occupied to indicate fuel presence or empty to indicate fuel absence. The density of occupied voxels was related significantly by a logarithmic function to 3D fuel bulk density samples that were destructively harvested (adjusted R2 = .32, P < .0001). Based on our findings, a survey-grade Global Navigation Satellite System may be necessary to accurately associate 3D point cloud data to 3D fuel bulk density measurements destructively collected in small (submeter) shrub plots. A recommendation for future research is to accurately geolocate and quantify the occupied volume of entire shrubs as 3D objects that can be used to train models to map shrub fuel bulk density from point cloud data binned to occupied 3D voxels.

Wildland fuels, defined as the combustible biomass of live and dead vegetation, are foundational to fire behavior, ecological effects, and smoke modeling. Along with weather and topography, the composition, structure and condition of wildland fuels drive fire spread, consumption, heat release, plume production and smoke dispersion. To refine inputs to existing and next-generation smoke modeling tools, improved characterization of the spatial and temporal dynamics of wildland fuels is necessary. Computational fluid dynamics (CFD) models that resolve fire–atmosphere interactions offer a promising new approach to smoke prediction. CFD models rely on three-dimensional (3D) characterization of wildland fuelbeds (trees, shrubs, herbs, downed wood and forest floor fuels). Advances in remote sensing technologies are leading to novel ways to measure wildland fuels and map them at sub-meter to multi-kilometer scales as inputs to next-generation fire and smoke models. In this chapter, we review traditional methods to characterize fuel, describe recent advances in the fields of fuel and consumption science to inform smoke science, and discuss emerging issues and challenges.

Emissions from a stand replacement prescribed burn were sampled using an unmanned aircraft system (UAS, or “drone”) in Fishlake National Forest, Utah, U.S.A. Sixteen flights over three days in June 2019 provided emission factors for a broad range of compounds including carbon monoxide (CO), carbon dioxide (CO(2)), nitric oxide (NO), nitrogen oxide (NO(2)), particulate matter < 2.5 microns in diameter (PM(2.5)), volatile organic compounds (VOCs) including carbonyls, black carbon, and elemental/organic carbon. To our knowledge, this is the first UAS-based emission sampling for a fire of this magnitude, including both slash pile and crown fires resulting in wildfire-like conditions. The burns consisted of drip torch ignitions as well as ground-mobile and aerial helicopter ignitions of large stands comprising over 1,000 ha, allowing for comparison of same-species emission factors burned under different conditions. The use of a UAS for emission sampling minimizes risk to personnel and equipment, allowing flexibility in sampling location and ensuring capture of representative, fresh smoke constituents. PM(2.5) emission factors varied 5-fold and, like most pollutants, varied inversely with combustion efficiency resulting in lower emission factors from the slash piles than the crown fires.

In this study we capture and identify pyrolysis gases from prescribed burns conducted in pine forests with a shrub understory using a manual extraction device. The device selectively sampled emissions ahead of the flame front, minimizing collection of oxidized gases, with the captured gases analyzed in the laboratory using infrared absorption spectroscopy. Results show that emission ratios (ER) relative to CO for ethene, and acetylene were significantly greater than previous fire studies, suggesting that the sample device was able to collect gases prior to ignition. Further evidence that ignition had not begun was corroborated by novel infrared detections of several species, in particular naphthalene. With regards to oxygenated species, several aldehydes (acrolein, furaldehyde, acetaldehyde, formaldehyde) and the carboxylic acids (formic, acetic) were all observed; results show that ERs for acetaldehyde were noticeably greater while ERs for formaldehyde and acetic acid were lower compared to other studies. The acetylene-to-furan ratio also suggests that high temperature pyrolysis was the dominant process generating the collected gases. This hypothesis is further supported by the presence of HCN and the absence of NH3.

Reactive nitrogen (Nr) within smoke plumes plays important roles in the production of ozone, the formation of secondary aerosols, and deposition of fixed N to ecosystems. The Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN) field campaign sampled smoke from 23 wildfires throughout the western U.S. during summer 2018 using the NSF/NCAR C-130 research aircraft. We empirically estimate Nr normalized excess mixing ratios and emission factors from fires sampled within 80 min of estimated emission and explore variability in the dominant forms of Nr between these fires. We find that reduced N compounds comprise a majority (39%-80%; median = 66%) of total measured reactive nitrogen (ΣNr) emissions. The smoke plumes sampled during WE-CAN feature rapid chemical transformations after emission. As a result, within minutes after emission total measured oxidized nitrogen (ΣNOy) and measured total ΣNHx (NH3 + pNH4) are more robustly correlated with modified combustion efficiency (MCE) than NOx and NH3 by themselves. The ratio of ΣNHx/ΣNOy displays a negative relationship with MCE, consistent with previous studies. A positive relationship with total measured ΣNr suggests that both burn conditions and fuel N content/volatilization differences contribute to the observed variability in the distribution of reduced and oxidized Nr. Additionally, we compare our in situ field estimates of Nr EFs to previous lab and field studies. For similar fuel types, we find ΣNHx EFs are of the same magnitude or larger than lab-based NH3 EF estimates, and ΣNOy EFs are smaller than lab NOx EFs.

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.

Reliable estimates of pre-burn biomass and fuel consumption are important to estimate wildland fire emissions and assist in prescribed burn planning. We present empirical models for predicting fuel consumption in natural fuels from 60 prescribed fires in ponderosa pine-dominated forests in the western US and 60 prescribed fires in long-needle pine forests in the southeastern US. There was high variability across sites, but total surface fuel biomass was generally much lower on southern sites (23.0 ± 11.6 Mg ha −1 ) than western sites (61.5 ± 35.8 Mg ha −1 ). Differences in surface fuel composition, pre-burn loading and fuel consumption between the southern and western pine consumption datasets justify the development of regional models for predicting fuel consumption. Southern pine models of herb, shrub and 1-h consumption have close model fit with narrow prediction intervals across the range of sampled values. Relationships between 10-h and 100-h pre-burn loading and consumption produced models with reasonable fit but with no significant correlation with fuel moisture. Model fit of litter and duff consumption models was relatively poor compared to the other southern fuel categories. Western models were developed for 1-h, 10-h and 100-h fine wood, sound coarse wood, rotten coarse wood, litter and duff. All western models had high coefficients of variability, and model residuals indicate higher uncertainty with increasing pre-burn biomass. Although empirical models are widely used, they have limitations in that they are constrained by burning conditions and ranges of predictor variables.

The FireFlux II experiment was conducted in a tall grass prairie located in south-east Texas on 30 January 2013 under a regional burn ban and high fire danger conditions. The goal of the experiment was to better understand micrometeorological aspects of fire spread. The experimental design was guided by the use of a coupled fire–atmosphere model that predicted the fire spread in advance. Preliminary results show that after ignition, a surface pressure perturbation formed and strengthened as the fire front and plume developed, causing an increase in wind velocity at the fire front. The fire-induced winds advected hot combustion gases forward and downwind of the fire front that resulted in acceleration of air through the flame front. Overall, the experiment collected a large set of micrometeorological, air chemistry and fire behaviour data that may provide a comprehensive dataset for evaluating and testing coupled fire–atmosphere model systems.

There is limited research on the exposure of wildland firefighters to smoke because of the operational obstacles when monitoring air pollutants in the field. In this work, a grid of portable sensors was used to measure PM2.5 and CO concentrations in the near-source region during the burn of two shrubland research blocks in Central Portugal. Strong spatial variability of smoke levels was observed in the analysis of the ratios between mean concentrations of neighbouring sensors, with values as high as 4.4 for PM2.5 and 7.4 for CO. These large gradients were registered at a distance of only 5 m suggesting that considerable differences on individual exposure can occur depending on the location of that individual in relation to the smoke plume trajectory. Also, peak events of 2–3 times the mean were observed in periods exceeding 6 min. In the two experiments, the average concentrations of both PM2.5 and CO were higher during smouldering, which represents a risk of acute exposure due to the closer proximity of firefighters to the emission source during mop-up, stressing the importance of wearing portable gas detectors for managing critical exposure. The collected data constitutes a step forward in the effort to understand the mechanisms controlling the exposure during firefighting operations, by providing a source of information on near-ground concentration fluctuations within a biomass-burning smoke plume at a fine spatial-temporal resolution.

Laboratory and field experiments focused on pyrolysis and ignition coupled with sufficient description of fuel characteristics and physics-based modeling are being used to improve our understanding of combustion processes in mixed (heterogeneous) fuel beds managed with prescribed fire in the southern United States. Previous pyrolysis work has typically used ground-up samples, thus eliminating any effects caused by moisture content, fuel particle shape, or heating mode. We are measuring pyrolysis at bench, laboratory and field-scale using intact fuels from living plants. Pyrolysis products being measured include light gases and tars using off-line and real-time spectroscopic instruments. 3-D fuel description, heat transfer to the fuels, and air flow around the fuels are being determined using a variety of intrusive and nonintrusive methods. The ability of high fidelity physics-based FDS, WFDS, and GPYRO3D to reproduce experimental results and to study conditions outside the range of the experimental data is being examined. This presentation will present an overview of the project and the questions being addressed. Preliminary results from initial attempts to measure pyrolysis at field-scale and results from early modeling of pyrolysis of live leaves using coupled GPYRO3D and FDS models are presented.

Wildland firefighters are exposed to wood smoke, which contains hazardous air pollutants, by suppressing thousands of wildfires across the U. S. each year. We estimated the relative risk of lung cancer and cardiovascular disease mortality from existing PM2.5 exposure-response relationships using measured PM4 concentrations from smoke and breathing rates from wildland firefighter field studies across different exposure scenarios. To estimate the relative risk of lung cancer (LC) and cardiovascular disease (CVD) mortality from exposure to PM2.5 from smoke, we used an existing exposure-response (ER) relationship. We estimated the daily dose of wildfire smoke PM2.5 from measured concentrations of PM4, estimated wildland firefighter breathing rates, daily shift duration (hours per day) and frequency of exposure (fire days per year and career duration). Firefighters who worked 49 days per year were exposed to a daily dose of PM4 that ranged from 0.15 mg to 0.74 mg for a 5- and 25-year career, respectively. The daily dose for firefighters working 98 days per year of PM4 ranged from 0.30 mg to 1.49 mg. Across all exposure scenarios (49 and 98 fire days per year) and career durations (5–25 years), we estimated that wildland firefighters were at an increased risk of LC (8 percent to 43 percent) and CVD (16 percent to 30 percent) mortality. This unique approach assessed long term health risks for wildland firefighters and demonstrated that wildland firefighters have an increased risk of lung cancer and cardiovascular disease mortality.

As carbon modeling tools become more comprehensive, spatial data are needed to improve quantitative maps of carbon emissions from fire. The Wildland Fire Emissions Information System (WFEIS) provides mapped estimates of carbon emissions from historical forest fires in the United States through a web browser. WFEIS improves access to data and provides a consistent approach to estimating emissions at landscape, regional, and continental scales. The system taps into data and tools developed by the U.S. Forest Service to describe fuels, fuel loadings, and fuel consumption and merges information from the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration on fire location and timing. Currently, WFEIS provides web access to Moderate Resolution Imaging Spectroradiometer (MODIS) burned area for North America and U.S. fire-perimeter maps from the Monitoring Trends in Burn Severity products from the USGS, overlays them on 1-km fuel maps for the United States, and calculates fuel consumption and emissions with an open-source version of the Consume model. Mapped fuel moisture is derived from daily meteorological data from remote automated weather stations. In addition to tabular output results, WFEIS produces multiple vector and raster formats. This paper provides an overview of the WFEIS system, including the web-based system functionality and datasets used for emissions estimates. WFEIS operates on the web and is built using open-source software components that work with open international standards such as keyhole markup language (KML). Examples of emissions outputs from WFEIS are presented showing that the system provides results that vary widely across the many ecosystems of North America and are consistent with previous emissions modeling estimates and products.

Reliable predictions of fuel consumption are critical in the eastern United States (US), where prescribed burning is frequently applied to forests and air quality is of increasing concern. CONSUME and the First Order Fire Effects Model (FOFEM), predictive models developed to estimate fuel consumption and emissions from wildland fires, have not been systematically evaluated for application in the eastern US using the same validation data set. In this study, we compiled a fuel consumption data set from 54 operational prescribed fires (43 pine and 11 mixed hardwood sites) to assess each model’s uncertainties and application limits. Regions of indifference between measured and predicted values by fuel category and forest type represent the potential error that modelers could incur in estimating fuel consumption by category. Overall, FOFEM predictions have narrower regions of indifference than CONSUME and suggest better correspondence between measured and predicted consumption. However, both models offer reliable predictions of live fuel (shrubs and herbaceous vegetation) and 1 h fine fuels. Results suggest that CONSUME and FOFEM can be improved in their predictive capability for woody fuel, litter, and duff consumption for eastern US forests. Because of their high biomass and potential smoke management problems, refining estimates of litter and duff consumption is of particular importance.

Fuel consumption specifies the amount of vegetative biomass consumed during wildland fire. It is a two-stage process of pyrolysis and combustion that occurs simultaneously and at different rates depending on the characteristics and condition of the fuel, weather, topography, and in the case of prescribed fire, ignition rate and pattern. Fuel consumption is the basic process that leads to heat absorbing emissions called greenhouse gas and other aerosol emissions that can impact atmospheric and ecosystem processes, carbon stocks, and land surface reflectance. It is a critical requirement for greenhouse gas emission inventories. There are several fuel consumption models widely used by scientists and land managers including the First Order Fire Effects Model, Consume, and CanFIRE. However, these models have not been thoroughly evaluated with an independent, quality assured, fuel consumption data set. Furthermore, anecdotal evidence indicates the models have limited ability to predict consumption of specific fuel bed categories such as tree crowns, deep organic layers, and rotten logs that can contribute significantly to greenhouse gases. If we are to move forward in our ability to assess the contribution of wildland fire to greenhouse gas to the atmosphere, our current fuel consumption models must be evaluated and modified to improve their predictive capabilities. Finally, information is lacking on how much black and brown carbon from wildland fire is generated during the combustion process and how much remains on site becoming sequestered in soils, partially offsetting greenhouse gas emissions. This synthesis focuses on the process and modeling of fuel consumption and knowledge gaps that will improve our ability to predict fuel consumption and the resulting greenhouse gas emissions.

Mastication is an increasingly common fuels treatment that redistributes ‘‘ladder’’ fuels to the forest floor to reduce vertical fuel continuity, crown fire potential, and fireline intensity, but fuel models do not exist for predicting fire behavior in these fuel types. Recent fires burning in masticated fuels have behaved in unexpected and contradictory ways, likely because the shredded, compact fuel created when trees and shrubs are masticated contains irregularly shaped pieces in mixtures quite different from other woody fuels. We review fuels characteristics and fire behavior in masticated fuels across the United States. With insights from the few laboratory and field burning experiments conducted, we highlight the variation likely to occur across different ecosystems in which these treatments are being widely implemented. Masticated debris has a propensity to flame and smolder for long durations. Fuel variability and vegetation response will likely influence whether or not treatments reduce long-term fire hazard. We identify key science needs that will better elucidate fire behavior and effects in these treatments. With mastication widely applied in an expanding wildland–urban interface it is crucial to understand how such fuels burn. What we learn about combustion in these fuels will inform effective fuels management in these and other mixed fuels.

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

Fuel Loading Models (FLMs) and Fuel Characteristic Classification System (FCCSs) fuelbeds are used throughout wildland fire science and management to simplify fuel inputs into fire behavior and effects models, but they have yet to be thoroughly evaluated with field data. In this study, we used a large dataset of Forest Inventory and Analysis (FIA) surface fuel estimates (n = 13,138) to create a new fuel classification called Fuel Type Groups (FTGs) from FIA forest type groups, and then keyed an FLM, FCCS, and FTG class to each FIA plot based on fuel loadings and stand conditions. We then compared FIA sampled loadings to the keyed class loading values for four surface fuel components (duff, litter, fine woody debris, coarse woody debris) and to mapped FLM, FCCS, and FTG class loading values from spatial fuel products. We found poor performances (R2 < 0.30) for most fuel component loadings in all three classifications that, in turn, contributed to poor mapping accuracies. The main reason for the poor performances is the high variability of the four fuel component loadings within classification categories and the inherent scale of this variability does not seem to match the FIA measurement scale or LANDFIRE mapping scale.

[1] Biomass burning is a significant contributor to atmospheric carbon emissions but may also provide an avenue in which fire-affected ecosystems can accumulate carbon over time, through the generation of highly resistant fire-altered carbon. Identifying how fuel moisture, and subsequent changes in the fire behavior, relates to the production of fire-altered carbon is important in determining how persistent charred residues are following a fire within specific fuel types. Additionally, understanding how mastication (mechanical forest thinning) and fire convert biomass to black carbon is essential for understanding how this management technique, employed in many fire-prone forest types, may influence stand-level black carbon in soils. In this experimental study, 15 masticated fuel beds, conditioned to three fuel moisture ranges, were burned, and production rates of pyrogenic carbon and soot-based black carbon were evaluated. Pyrogenic carbon was determined through elemental analysis of the post-fire residues, and soot-based black carbon was quantified with thermochemical methods. Pyrogenic carbon production rates ranged from 7.23% to 8.67% relative to pre-fire organic carbon content. Black carbon production rates averaged 0.02% in the 4–8% fuel moisture group and 0.05% in the 13–18% moisture group. A comparison of the ratio of black carbon to pyrogenic carbon indicates that burning with fuels ranging from 13% to 15% moisture content resulted in a higher proportion of black carbon produced, suggesting that the precursors to black carbon were indiscriminately consumed at lower fuel moistures. This research highlights the importance of fuel moisture and its role in dictating both the quantity and quality of the carbon produced in masticated fuel beds.

Mechanical (e.g., shearblading) and manual (e.g., thinning) fuel treatments have become the preferred strategy of many fire managers and agencies for reducing fire hazard in boreal forests. This study attempts to characterize the effectiveness of four fuel treatments through direct measurement of fire intensity and forest floor consumption during a single prescribed burn. The treatments included (1) thinning trees and removing debris (THIN-REMOVE-1 and -2), (2) thinning trees and burning the debris onsite, (3) shearblading and leaving the debris in place (SHEAR), and (4) shearblading and piling the debris in windrows (SHEAR-ROW). Fire burned through treatments 1, 3, and 4 and one control unit. The highest fire intensities (maximum temperature of 1150 °C, maximum heat flux of 227 kW·m–2, and fire cumulative energy release of 4277 J·m–2) were measured in the control. Treatment 1 exhibited a peak temperature of 267 °C, peak heating of 16 kW·m–2, and cumulative energy release of 2600 J·m–2. Treatments 3 and 4 exhibited peak temperatures of 170 and 66 °C, peak heating of 51 and 3 kW·m–2, and cumulative energy release of 2500 and 1800 J·m–2, respectively. The thinned treatment showed the most significant impact in the context of reduced heat release.

Background/objective A study was undertaken at the United States Department of Energy's Savannah River Site (SRS), Aiken, South Carolina to investigate radionuclide activity concentrations in litter and duff from select areas at SRS. Litter (i.e. vegetative debris) and duff (i.e. highly decomposed vegetative debris) can often be the major fuels consumed during prescribed burns and have potential to release radiological contaminants into the environment. Methods Repeated samples from 97 locations were collected systematically across SRS and analyzed for radionuclide activity. Radionuclide activity concentrations found in litter and duff were compared. As spatial trends were of interest, spatial distributions of radionuclide activity concentrations found in litter and duff and spatial dependency amongst the data were explored. Results 7 Be, 40 K, and 137 Cs showed statistically significant proportional differences between litter and duff samples. Duff sample concentrations for 137 Cs ( p 40 K ( p = 0.0015) were statistically higher compared to litter samples. 7 Be activity concentrations were statistically higher in litter as compared to duff ( p 40 K litter and duff samples, spatial correlation tests were not significant at p = 0.05 and the maps did not indicate any apparent high concentrations centered near possible radionuclide sources (i.e. SRS facilities). For 7 Be litter samples, significant spatial correlation was calculated ( p = 0.0085). No spatial correlation was evident in the 7 Be duff samples ( p = 1.0000) probably due to small sample size ( n = 7). 137 Cs litter and duff samples showed significant spatial correlations ( p p Conclusions To date, few studies characterize radionuclide activity concentrations in litter and duff, and to our knowledge none present spatial analysis. Key findings show that across SRS, 137 Cs is the primary radionuclide of concern, with the highest number of samples reported above MDC in litter (51.4%) and duff samples (83.2%). However, 137 Cs litter and duff spatial trends in the maps generated from the kriging parameters do not appear to directly link the areas with higher activity concentrations with SRS facilities. The results found herein provide valuable baseline monitoring data for future studies of forest surface fuels and can be used to evaluate changes in radioactivity in surface fuels in the southeast region of the U.S.

Each year, the general public and wildland firefighters in the US are exposed to smoke from wildland fires. As part of an effort to characterize health risks of breathing this smoke, a review of the literature was conducted using five major databases, including PubMed and MEDLINE Web of Knowledge, to identify smoke components that present the highest hazard potential, the mechanisms of toxicity, review epidemiological studies for health effects and identify the current gap in knowledge on the health impacts of wildland fire smoke exposure. Respiratory events measured in time series studies as incidences of disease-caused mortality, hospital admissions, emergency room visits and symptoms in asthma and chronic obstructive pulmonary disease patients are the health effects that are most commonly associated with community level exposure to wildland fire smoke. A few recent studies have also determined associations between acute wildland fire smoke exposure and cardiovascular health end-points. These cardiopulmonary effects were mostly observed in association with ambient air concentrations of fine particulate matter (PM2.5). However, research on the health effects of this mixture is currently limited. The health effects of acute exposures beyond susceptible populations and the effects of chronic exposures experienced by the wildland firefighter are largely unknown. Longitudinal studies of wildland firefighters during and/or after the firefighting career could help elucidate some of the unknown health impacts of cumulative exposure to wildland fire smoke, establish occupational exposure limits and help determine the types of exposure controls that may be applicable to the occupation.

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.

Communicating emissions impacts to the public can sometimes be difficult because quantitatively conveying smoke concentrations is complicated. Regulators and land managers often refer to particulate-matter concentrations in micrograms per cubic meter, but this may not be intuitive or meaningful to everyone. The primary purpose of this guide is to serve as a tool for communicating potential particulate matter (PM2.5) levels during wildfire events using visual representation. Examples of visibility impairment under various levels of smoke concentration and humidity have been modeled using the WinHaze program.

Fuel treatment effectiveness in Southern forests has been demonstrated using fire behavior modeling and observations of reduced wildfire area and tree damage. However, assessments of treatment effectiveness may be improved with a more rigorous accounting of the fuel characteristics. We present two case studies to introduce a relatively new approach to characterizing fuels and predicting potential fire behavior, fuel consumption, and emissions in Southern forests using the Fuel Characteristic Classification System (FCCS) and Consume. The first case study provides fine-scale ( Results from the fine-scale assessment indicate that fuel treatments reduce reaction intensity, rate of spread, and flamelength by up to 58%, 57%, and 63%, respectively. Fuel loading of strata that control surface fire behavior (i.e., shrubs, grasses, fine woody fuels, and litter) range from 32.0 Mg ha−1 in the thinned, untreated unit to 8.5 Mg ha−1 in the unthinned unit treated with herbicides and prescribed fire. Based on model predictions, up to 80% less fuel would be consumed with concomitant reduction in emissions during a wildfire occurring in the treated units compared to the untreated unit. Assessments of potential fire behavior across the study area indicate that overall hazard is low to moderate for this forested landscape. However, localized areas of high surface fire and crown fire potential were identified. Plot- and stand-based modeling both suggest that the potential for high to extreme fire behavior exists for this landscape. Combined, the two case studies highlight the ability of the FCCS to represent measured fuel characteristics and predict differences in potential fire behavior resulting from fuel treatments. Even small differences in fuel characteristics resulting from fuel treatments or site variation could be detected, allowing the effects of both ecological processes and management actions to be quantified.

Fire hazard mitigation planning requires an accurate accounting of fuel complexes to predict potential fire behavior and effects of treatment alternatives. In the southeastern United States, rapid vegetation growth coupled with complex land use history and forest management options requires a dynamic approach to fuel characterization. In this study we assessed potential surface fire behavior with the Fuel Characteristic Classification System (FCCS), a tool which uses inventoried fuelbed inputs to predict fire behavior. Using inventory data from 629 plots established in the upper Atlantic Coastal Plain, South Carolina, we constructed FCCS fuelbeds representing median fuel characteristics by major forest type and age class. With a dry fuel moisture scenario and 6.4 km h −1 midflame wind speed, the FCCS predicted moderate to high potential fire hazard for the majority of the fuelbeds under study. To explore fire hazard under potential future fuel conditions, we developed fuelbeds representing the range of quantitative inventory data for fuelbed components that drive surface fire behavior algorithms and adjusted shrub species composition to represent 30% and 60% relative cover of highly flammable shrub species. Results indicate that the primary drivers of surface fire behavior vary by forest type, age and surface fire behavior rating. Litter tends to be a primary or secondary driver in most forest types. In comparison to other surface fire contributors, reducing shrub loading results in reduced flame lengths most consistently across forest types. FCCS fuelbeds and the results from this project can be used for fire hazard mitigation planning throughout the southern Atlantic Coastal Plain where similar forest types occur. The approach of building simulated fuelbeds across the range of available surface fuel data produces sets of incrementally different fuel characteristics that can be applied to any dynamic forest types in which surface fuel conditions change rapidly.

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation System. The fundamental fire intensity algorithms in these systems require surface fire behavior fuel models and canopy cover to model surface fire behavior. Canopy base height, stand height, and canopy bulk density are required in addition to surface fire behavior fuel models and canopy cover to model crown fire activity. Several surface fuel and canopy classification efforts have used various remote sensing and ecological relationships as core methods to develop the spatial layers. All of these methods depend upon consistent and temporally constant interpretations of crown attributes and their ecological conditions to estimate surface fuel conditions. This study evaluates modeled fire behavior for an 80,000 ha tract of land in the Atlantic Coastal Plain of the southeastern US using three different data sources. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developedmore » surface fire behavior fuel models and canopy attributes for the US using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern US using satellite imagery. Differences in modeled fire behavior, data development, and data utility are summarized to assist in determining which data source may be most applicable for various land management activities and required analyses. Characterizing fire behavior under different fuel relationships provides insights for natural ecological processes, management strategies for fire mitigation, and positive and negative features of different modeling systems. A comparison of flame length, rate of spread, crown fire activity, and burn probabilities modeled with FlamMap shows some similar patterns across the landscape from all three data sources, but there are potentially important differences. All data sources showed an expected range of fire behavior. Average flame lengths ranged between 1 and 1.4 m. Rate of spread varied the greatest with a range of 2.4-5.7 m min{sup -1}. Passive crown fire was predicted for 5% of the study area using FCCS and LANDFIRE while passive crown fire was not predicted using SWRA data. No active crown fire was predicted regardless of the data source. Burn probability patterns across the landscape were similar but probability was highest using SWRA and lowest using FCCS.« less

Climate change has increased the area affected by forest fires in boreal North America. An analysis of the depth of burning in forests and peatlands in Alaska indicates that ground-layer combustion has accelerated regional carbon losses.

In many fire-prone forests in the United States, changes occurring in the last century have resulted in overstory structures, conifer densities, down woody structure and fuel loads that deviate from those described historically. With these changes, forests are presumed to be unsustainable. Broad-scale treatments are proposed to reduce fuels and promote stand development on trajectories toward more sustainable structures. Yet little research to date has identified the effects of these treatments, especially in low elevation dry ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) forests. We report initial fuelbed conditions and changes immediately and 4–6 years after fuel reduction treatments in an operational-scale, replicated (N = 4), completely randomized experiment in northeastern Oregon. Treatments included a single entry thin from below conducted in 1998, a late season burn conducted in 2000, a thin followed by burning (thin + burn), and a no action treatment which served as a control. Between 1998 and 2004, litter mass declined about 4.4 Mg ha−1 in thin units, about 4.1 Mg ha−1 in thin + burn units, and about 1.5 Mg ha−1 in burn units. Duff mass did not change with treatment. Mass of woody fuels in the 1 and 10 h timelag classes increased in thin units immediately after treatment, but fell to nearly pre-treatment levels by 2004. Mass of woody fuels in the 100 h timelag class increased about 1.6 Mg ha−1 in thin units, and decreased about 0.7 Mg ha−1 in burn units and about 0.1 Mg ha−1 in thin + burn units. There was no difference in the change in total woody fuel mass among all treatments. About 62% of the residual trees in the burn and the thin + burn units were charred; charring extended up the bole about 1.1 m. About 50% of the residual trees in the burn and thin + burn units had scorched lower crowns. Mean scorch height was 4.3 m. Log density was greater in control units compared to actively treated units and greater in the thin units compared to burn or thin + burn units. We used the Fuel Characteristic Classification System (FCCS) to construct a representative fuelbed for each unit from inventoried data and to calculate three indices of fire potential as measures of the change in fire hazard resulting from our treatments: surface fire behavior, crown fire behavior, and fuels available for consumption. Projected flame length, rate of spread, and reaction intensity are derived as metrics of future surface fire behavior. These results are discussed in the context of management options for restoration of ecosystem health in similar low elevation dry ponderosa pine and Douglas-fir forests.

Wildland fuel characteristics are used in many applications of operational fire predictions and to understand fire effects and behaviour. Even so, there is a shortage of information on basic fuel properties and the physical characteristics of wildland fuels. The Fuel Characteristic Classification System (FCCS) builds and catalogues fuelbed descriptions based on realistic physical properties derived from direct or indirect observation, inventories, expert knowledge, inference, or simulated fuel characteristics. The FCCS summarizes and calculates wildland fuel characteristics, including fuel depth, loading, and surface area. Users may modify fuelbeds and thereby capture changing fuel conditions over time and (or) under different management prescriptions. Fuel loadings from four sample fuelbed pairs (i.e., pre- and post-prescribed fire) were calculated and compared by using FCCS to demonstrate the versatility of the system and how individual fuel components, such as shrubs, nonwoody fuels, woody fuels, and litter, can be calculated and summarized. The ability of FCCS to catalogue and summarize complex fuelbeds and reflect dynamic fuel conditions allows calculated results to be used in a variety of applications including surface and crown fire predictions, carbon assessments, and wildlife habitat management.

We present an overview of the Fuel Characteristic Classification System (FCCS), a tool that enables land managers, regulators, and scientists to create and catalogue fuelbeds and to classify those fuelbeds for their capacity to support fire and consume fuels. The fuelbed characteristics and fire classification from this tool will provide inputs for current and future sophisticated models for the quantification of fire behavior, fire effects, and carbon accounting and enable assessment of fuel treatment effectiveness. The system was designed from requirements provided by land managers, scientists, and policy makers gathered through six regional workshops. The FCCS contains a set of fuelbeds representing the United States, which were compiled from scientific literature, fuels photo series, fuels data sets, and expert opinion. The system enables modification and enhancement of these fuelbeds to represent a particular scale of interest. The FCCS then reports assigned and calculated fuel characteristics for each existing fuelbed stratum including the canopy, shrubs, nonwoody, woody, litter–lichen–moss, and duff. Finally, the system classifies each fuelbed by calculating fire potentials that provide an index of the intrinsic capacity of each fuelbed to support surface fire behavior, support crown fire, and provide fuels for flaming, smoldering, and residual consumption. The FCCS outputs are being used in a national wildland fire emissions inventory and in the development of fuelbed, fire hazard, and treatment effectiveness maps on several national forests. Although the FCCS was built for the United States, the conceptual framework is applicable worldwide.

Wildland fuelbed characteristics are temporally and spatially complex and can vary widely across regions. To capture this variability, we designed the Fuel Characteristic Classification System (FCCS), a national system to create fuelbeds and classify those fuelbeds for their capacity to support fire and consume fuels. This paper describes the structure of the fuelbeds internal to FCCS. Fuelbeds are considered relatively homogeneous units on the landscape, representing distinct combustion environments that determine potential fire behaviour and effects. The FCCS fuelbeds are organized into six strata: canopy, shrubs, nonwoody fuels, woody fuels, litter–lichen–moss, and ground fuels. Fuelbeds are described by several qualitative and quantitative physical and biological variables with emphasis on characteristics useful for fuels management and fire behaviour planning. The FCCS includes 216 fuelbeds that represent the major vegetation types of the United States. The FCCS fuelbeds can be used as presented or modified to create customized fuelbeds with general or site-specific data to address fire science management or research questions. This system allows resource managers to evaluate wildland fuels operations and management activities, fire hazard, and ecological and air quality impacts at small and large spatial scales. The FCCS fuelbeds represent the United States, although the system has the potential for building fuelbeds for international application.

In forests historically maintained by frequent fire, reintroducing fire after decades of exclusion often causes widespread overstory mortality. To better understand this phenomenon, we subjected 16 fire-excluded (ca. 40 years since fire) 10 ha longleaf pine ( Pinus palustris Mill.) stands to one of four replicated burning treatments based on volumetric duff moisture content (VDMC): wet (115% VDMC); moist (85% VDMC); dry (55% VDMC); and a no-burn control. During the first 2 years postfire, overstory pines in the dry burns suffered the greatest mortality (mean 20.5%); pine mortality in the wet and moist treatments did not differ from the control treatment. Duff reduction was greatest in the dry burns (mean 46.5%), with minimal reduction in the moist and wet burns (14.5% and 5%, respectively). Nested logistic regression using trees from all treatments revealed that the best predictors of individual pine mortality were duff consumption and crown scorch (P < 0.001; R2 = 0.34). Crown scorch was significant only in dry burns, whereas duff consumption was significant across all treatments. Duff consumption was related to moisture content in lower duff (Oa; R2 = 0.78, P < 0.001). Restoring fire to long-unburned forests will require development of burn prescriptions that include the effects of duff consumption, an often overlooked fire effect.

A screening health risk assessment was performed to assess the upper-bound risks of cancer and noncancer adverse health effects among wildland firefighters performing wildfire suppression and prescribed burn management. Of the hundreds of chemicals in wildland fire smoke, we identified 15 substances of potential concern from the standpoints of concentration and toxicology; these included aldehydes, polycyclic aromatic hydrocarbons, carbon monoxide, benzene, and respirable particulate matter. Data defining daily exposures to smoke at prescribed burns and wildfires, potential days of exposure in a year, and career lengths were used to estimate average and reasonable maximum career inhalation exposures to these substances. Of the 15 substances in smoke that were evaluated, only benzene and formaldehyde posed a cancer risk greater than 1 per million, while only acrolein and respirable particulate matter exposures resulted in hazard indices greater than 1.0. The estimated upper-bound cancer risks ranged from 1.4 to 220 excess cancers per million, and noncancer hazard indices ranged from 9 to 360, depending on the exposure group. These values only indicate the likelihood of adverse health effects, not whether they will or will not occur. The risk assessment process narrows the field of substances that deserve further assessment, and the hazards identified by risk assessment generally agree with those identified as a concern in occupational exposure assessments.

Fuel reduction by mechanical thinning and removal was studied in mixed-conifer stands in northeastern Oregon between 1995 and 1997. A single-grip harvester was coupled with either a forwarder or a skyline yarding system, and operational economics, fuel reduction, stand damage, soil disturbance, effects on soil biota and down-woody material were measured in three replicates of paired stands. After logging with the harvester, the two log-extraction systems achieved nearly equivalent fuel reduction with 45.7 and 46.8% mass reduction by the forwarder and skyline system, respectively. Fine-woody fuel increased slightly in all units, but mass of heavy fuels decreased. Most mass reduction in the forest floor occurred in the duff layer with 56 and 49% reduction in forwarder and skyline units, respectively. Reduction in stem density and basal area were similar for the two extraction systems; in forwarder units stem density was reduced by 61.6% and basal area by 55.4%, while in skyline units stem density was reduced by 66.5% and basal area by 51.1%. Of seedlings and trees examined, 32% had noticeable damage after harvest. Damage included bole wounding (38.9% of damaged stems), bark scraping (35.0%), wrenched stems (28.9%), broken branches (26.5%), broken terminal leaders (15.4%), and crushed foliage (4.1%). More damage occurred to residual large trees than to seedlings. Both log-extraction systems met the silvicultural prescription of reducing fuel and protecting residual large-diameter western larch, Engelmann spruce, Douglas-fir, and lodgepole pine. While fuel, stem, and basal area reduction lowered fire risk from a model 10 to a model 8 in all stands, large-woody material for wildlife also changed. Mean log length was lower in harvested units relative to unharvested controls, but this did not decrease occupation of logs by ants or the activities of woodpeckers feeding on them. Of 37 logged hectares, 1.4% (0.5 ha) of the soil area was compacted, mostly in forwarder units, within landings, and within trails close to landings. The percent area with displaced soil varied from 5 to 43% among units and was located within trails or in intertrail areas between the trails. Light displacement of soil resulted in a short-term increase in the abundance of soil microarthropods. The effects of compaction on litter microarthropods was more persistent, with lower numbers in compacted litter a year after harvest. While revenue was similar for forwarder and skyline units ($68 vs. $70/metric ton, respectively), total operational costs were $81/metric ton in the skyline units, compared to $46/metric ton in the forwarder units. These results are discussed in the context of options available to managers for balancing fuel reduction needs with both environmental and economic constraints. West. J. Appl. For. 18(4):238–249.

The inherent spatial and temporal heterogeneity of fuelbeds in forests of the southeastern United States may require fine scale fuel measurements for providing reliable fire hazard and fuel treatment effectiveness estimates. In a series of five papers, an intensive, fine scale fuel inventory from the Savanna River Site in the southeastern United States is used for building fuelbeds and mapping fire behavior potential, evaluating fuel treatment options for effectiveness, and providing a comparative analysis of landscape modeled fire behavior using three different data sources including the Fuel Characteristic Classification System, LANDFIRE, and the Southern Wildfire Risk Assessment. The research demonstrates that fine scale fuel measurements associated with fuel inventories repeated over time can be used to assess broad scale wildland fire potential and hazard mitigation treatment effectiveness in the southeastern USA and similar fire prone regions. Additional investigations will be needed to modify and improve these processes and capture the true potential of these fine scale data sets for fire and fuel management planning.

In order to better understand the dynamics of fire-atmosphere interactions and the role of micrometeorology on fire behaviour the FireFlux campaign was conducted in 2006 on a coastal tall-grass prairie in southeast Texas, USA. The FireFlux campaign dataset has become the international standard for evaluating coupled fire-atmosphere model systems. While FireFlux is one of the most comprehensive field campaigns to date, the dataset does have some major limitations especially the lack of sufficient measurements of fire spread and fire behaviour properties. In order to overcome this, a new, more comprehensive field experiment, called FireFlux II, was conducted on 30 January 2013. This paper will address the experimental design and preliminary results. The experiment was designed to allow an intense head fire to burn directly through an extensive instrumentation array including fixed 42-m and three 10-m micrometeorological towers (Figure 2). The fuels consist of a mixture of native grasses.Each tower was equipped with a variety of sensors, including 3D sonic anemometers, pressure sensors, heat flux radiometers, and an array of fine-wire thermocouples to measure plume temperatures. The experiment was carried out under red flag warning conditions with strong winds of 8 m s-1 and relative humidity of approximately 24%. Instrumentation also included a scanning Doppler wind lidar, microwave temperature profiler, radiosonde balloons for upper-air soundings, a full suite of air quality instrumentation located downwind, and multiple ground and tower mounted infrared and visible video cameras. In addition, the fire spread was monitored from the air using helicopter mounted infrared and visible video cameras. Because the experiment was designed to be conducted under a north wind, the timing of the experimental period only allowed for a northwest wind. This required the instrumentation array to be moved in order to document the fire spread and was a limitation to the experiment. Preliminary results showed that the fire spread rate was ~1.5-2.5 m s-1 for the head fire while the flanks spread at 0.7 m s-1. The surface pressure field indicated that a low-pressure region formed downwind of the advancing fire front. The observations from the 42-m tower show that the strongest fire-induced winds occur a the surface in the cross-wind direction.

Agricultural and silvicultural biomass burning is practiced in many undeveloped portions of the Amazon basin. In Rond nia, Brazil, such burning is restricted to a brief period in the dry season of August and September to minimize the duration of air quality impacts and to attempt to control escaped fires. During this period, much of the region and the communities within it experience significant exposure to smoke from agricultural and forest fires. In cooperation with Brazilian scientists of the University of Brasilia, the Brazilian Organization for Agricultural Research (EMBRAPA), and the Alternative to Slash and Burn Program coordinated by the International Center for Research in Agroforestry (ICRAF), ambient air quality was measured in Theobroma, a small town in Rond nia, during one week of the open burning period of 1995 to supplement available air quality data and to foster public awareness of the impacts of widespread fires. Personal sampling equipment was used to measure ambient levels of formaldehyde (HCHO), acrolein, CO, benzene, and respirable PM in outdoor air. The data obtained were compared with established Brazilian and U.S. ambient air quality guidelines. Ambient levels of respirable PM averaged 191 microg/m3, HCHO averaged 12.8 ppb, CO averaged 4.2 ppm, and benzene averaged 3.2 ppb. Almost all acrolein samples were less than the detection limit of 1 ppb. The results showed that the public can be exposed to relatively high levels of pollutants under the prescribed burning smoke management strategy of a two- to three-week prescription burning period, although this is an improvement over past years when burning was unregulated and continued through most of the dry season. The results also demonstrate the feasibility of using personal exposure monitoring equipment for low-cost surveys of ambient air quality in polluted regions.

We characterized recent historical and current vegetation composition and structure of a representative sample of subwatersheds on all ownerships within the interior Columbia River basin and portions of the Klamath and Great Basins. For each selected subwatershed, we constructed historical and current vegetation maps from 1932 to 1966 and 1981 to 1993 aerial photos, respectively. Using the raw vegetation attributes, we classified and attributed cover types, structural classes, and potential vegetation types to individual patches within subwatersheds. We characterized change in vegetation spatial patterns using a suite of class and landscape metrics, and a spatial pattern analysis program. We then translated change in vegetation patterns to change in patterns of vulnerability to wildfires, smoke production, and 21 major forest pathogen and insect disturbances. Results of change analyses were reported for province-scale ecological reporting units (ERUs). Here, we highlight significant findings and discuss management implications. Twentieth century management activities significantly altered spatial patterns of physiognomies, cover types and structural conditions, and vulnerabilities to fire, insect, and pathogen disturbances. Forest land cover expanded in several ERUs, and woodland area expanded in most. Of all physiognomic conditions, shrubland area declined most due to cropland expansion, conversion to semi- and non-native herblands, and expansion of forests and woodlands. Shifts from early to late seral conifer species were evident in forests of most ERUs; patch sizes of forest cover types are now smaller, and current land cover is more fragmented. Landscape area in old multistory, old single story, and stand initiation forest structures declined with compensating increases in area and connectivity of dense, multilayered, intermediate forest structures. Patches with medium and large trees, regardless of their structural affiliation are currently less abundant on the landscape. Finally, basin forests are now dominated by shade-tolerant conifers, and exhibit elevated fuel loads and severe fire behavior attributes indicating expanded future roles of certain defoliators, bark beetles, root diseases, and stand replacement fires. Although well intentioned, 20th-century management practices did not account for landscape-scale patterns of living and dead vegetation that enable forest ecosystems to maintain their structure and organization through time, or for the disturbances that create and maintain them. Improved understanding of change in vegetation spatial patterns, causative factors, and links with disturbance processes will assist managers and policymakers in making informed decisions about how to address important ecosystem health issues.

Timber harvesting residues have typically been burned within coniferous forest areas of the eastern Cascade Mountains of Washington State. Concerns about air pollution and quantities of coarse woody debris have generated interest in alternative residue treatments that will clear areas for planting and still reduce fire hazard. A total of six residue treatments were compared (three slash treatments where residues were burned (spring broadcast burning, fall broadcast burning, piling and burning) and three treatments where residues were not burned (clearing, chopping, pulling unmerchantable material)), along with no slash treatment to determine the effects of alternative approaches on soils and seedlings. Slash-treatment effects on soil bulk density and temperature, air temperature, and seedling growth and survival were examined at four different sites in the eastern Cascade Mountains. Results show that seedling performance was best with spring broadcast burning across all sites over five years of growth. Average height growth of Douglas-fir (Pseudotsuga menziesii) and lodgepole pine (Pinus contorta) over five years was 90 cm in the spring broadcast burn, with 75, 72, 71, 71, 66, and 61 cm for no slash treatment, piling and burning, pulling unmerchantable material, chopping, fall broadcast burn, and clearing, respectively. Seedling height growth may be related to soil temperatures that are closer to optimal for root and shoot growth when large quantities of slash were not insulating the soil. Soil bulk density did not appear to affect seedling growth (bulk density ranged from 0.7 to 1.15 g cm−3). None of the slash treatments that avoid burning increased growth relative to no slash treatment, and some may adversely affect survival. If slash burning can not be used to reduce quantities of timber harvesting residues, then leaving slash untreated appears to be the best alternative for seedling growth.

Summary This paper describes the procedures and data used to develop a database of 28 fire, fuels, and smoke attributes for the broad-scale scientific assessment of the Interior Columbia River Basin. These attributes relate to three general areas: (1) fire weather, fuel moisture, and fire characteristics; (2) fuel loading and fuel consumption; and (3) PM10 smoke emissions. The process flow and development protocols for creation of the database are fully described and illustrated, with examples provided where appropriate. This database was developed for application to a certain geographic area with parameters specific to both the biophysical environment and the management issues of that area. However, the methods and protocols used to develop this comprehensive suite of fire-related data are applicable to any ecosystem for which predictions are needed for wildfire hazard, fire potential, biomass consumption, and smoke emissions.

The Fuel Characteristic Classification System (FCCS) is a software module that records wildland fuel characteristics and calculates potential fire behavior and hazard potentials based on input environmental variables. The FCCS 3.0 is housed within the Integrated Fuels Treatment Decision Support System (Joint Fire Science Program 2012). It can also be run from command line as a stand-alone calculator. The flexible design of FCCS allows users to represent the structural complexity and diversity of fuels created through natural processes (e.g., forest succession and disturbance) and management activities (e.g., forest harvesting and fuels reduction). Each fuelbed is organized into six strata, including canopy, shrubs, herbaceous vegetation, woody fuels, litter-lichen-moss, and ground fuels. Strata are further divided into categories and subcategories. Fuelbeds representing common fuel types throughout much of North America are available in the FCCS reference library. Users may select an FCCS fuelbed to represent their specific project or customize a fuelbed to reflect actual site conditions. The FCCS reports the following results: (1) fuel characteristics by fuelbed, stratum, category, and subcategory; (2) surface fire behavior (i.e., reaction intensity, rate of spread, and flame length); and (3) FCCS fire potential ratings of surface fire behavior, crown fire behavior, and available fuels. With its large fuels data set and ability to represent a wide variety of fuel conditions, the FCCS has numerous applications, from small-scale fuel reduction projects to large-scale emissions and carbon assessments. This report provides technical documentation of the required inputs and computations in the FCCS.

Prescribed burning of slash following tree harvest is a standard practice to reduce fire hazard and prepare seed beds for planting conifers. This study examined the co-occurrence and intensity of hydrophobic and allelopathic layers created in sand pits under burned slash piles and broadcast slash. Following slash burning, 24 sand cores were taken from the sand pits and analyzed for water repellency and allelopathic effects on germination, emergence, and height growth of a bioassay species, blue wildrye (Elymus glaucus Buckley). Water drop penetration that was instantaneous in untreated sand cores was delayed in sand cores from burn treatments for 5 to 90 s in seven cores and for >270 s in five cores. Seedling emergence and height of the bioassay species declined in both the created hydrophobic sand layer and in an allelopathic zone of wettable sand immediately below the hydrophobic layer. Lack of allelopathic response when free water was present suggests that allelopathic effects are exhibited only under unsaturated soil conditions. Results indicate that nonwettable soils and allelopathy effects will act in unison to reduce water penetration and slow plant establishment following wildfires or prescribed burns.