Passive Crown Fire Research Articles

Changes in fire behavior caused by fire exclusion and fuel build-up vary with topography in California montane forests, USA

Wildfire sizes and proportions burned with high severity effects are increasing in seasonally dry forests, especially in the western USA. A critical need in efforts to restore or maintain these forest ecosystems is to determine where fuel build-up caused by fire exclusion reaches thresholds that compromise resilience to fire. Empirical studies identifying drivers of fire severity patterns in actual wildfires can be confounded by co-variation of vegetation and topography and the stochastic effects of weather and rarely consider long-term changes in fuel caused by fire exclusion.To overcome these limitations, we used a spatially explicit fire model (FlamMap) to compare potential fire behavior by topographic position in Lassen Volcanic National Park (LAVO), California, a large (43,000 ha), mountainous, unlogged landscape with extensive historical and contemporary fuels data. Fuel loads were uniformly distributed and incrementally increased across the landscape, meaning variation in fire behavior within each simulation was due to topography and among simulations, to fuels. We analyzed changes in fire line intensity (FLI) and crown fire potential as surface and canopy fuels increased from historical to contemporary levels and with percentile and actual wildfire weather conditions.Sensitivity to the influence of fuel build-up on fire behavior varied by topographic position. Steep slopes and ridges were most sensitive. At lower surface fuel loads, under pre-exclusion and contemporary canopy conditions, fire behavior was comparable and remained surface-type. As fuels increased, FLI and passive crown fire increased on steep slopes and ridgetops but remained largely unchanged on gentle slopes. Topographic variability in fire behavior was greatest with intermediate fuels. At higher surface fuel loads, under contemporary canopy fuels, passive crown fire dominated all topographic positions. With LAVO's current surface fuels, the area with potential for passive crown fire during actual fire weather increased from 6% pre-exclusion to 34% due to canopy fuel build-up. For topographically diverse landscapes, the results highlight where contemporary fire characteristics are most likely to deviate from historical patterns and may help managers prioritize locations for prescribed burning and managed wildfire to increase fire resilience in fuel rich landscapes.

Wildland Fire Tree Mortality Mapping from Hyperspatial Imagery Using Machine Learning

The use of imagery from small unmanned aircraft systems (sUAS) has enabled the production of more accurate data about the effects of wildland fire, enabling land managers to make more informed decisions. The ability to detect trees in hyperspatial imagery enables the calculation of canopy cover. A comparison of hyperspatial post-fire canopy cover and pre-fire canopy cover from sources such as the LANDFIRE project enables the calculation of tree mortality, which is a major indicator of burn severity. A mask region-based convolutional neural network was trained to classify trees as groups of pixels from a hyperspatial orthomosaic acquired with a small unmanned aircraft system. The tree classification is summarized at 30 m, resulting in a canopy cover raster. A post-fire canopy cover is then compared to LANDFIRE canopy cover preceding the fire, calculating how much the canopy was reduced due to the fire. Canopy reduction allows the mapping of burn severity while also identifying where surface, passive crown, and active crown fire occurred within the burn perimeter. Canopy cover mapped through this effort was lower than the LANDFIRE Canopy Cover product, which literature indicated is typically over reported. Assessment of canopy reduction mapping on a wildland fire reflects observations made both from ground truthing efforts as well as observations made of the associated hyperspatial sUAS orthomosaic.

Needle Senescence Affects Fire Behavior in Aleppo Pine (Pinus halepensis Mill.) Stands: A Simulation Study

Research Highlights: Pre-programmed cell death in old Aleppo pine needles leads to low moisture contents in the forest canopy in July, the time when fire activity nears its peak in the Western Mediterranean Basin. Here, we show, for the first time, that such needle senescence may increase fire behavior and thus is a potential mechanism explaining why the bulk of the annual burned area in the region occurs in early summer. Background and Objectives: The brunt of the fire season in the Western Mediterranean Basin occurs at the beginning of July, when live fuel moisture content is near its maximum. Here, we test whether a potential explanation to this conundrum lies in Aleppo pine needle senescence, a result of pre-programmed cell death in 3-years-old needles, which typically occurs in the weeks preceding the peak in the burned area. Our objective was to simulate the effects of needle senescence on fire behavior. Materials and Methods: We simulated the effects of needle senescence on canopy moisture and structure. Fire behavior was simulated across different phenological scenarios and for two highly contrasting Aleppo pine stand structures, a forest, and a shrubland. Wildfire behavior simulations were done with BehavePlus6 across a wide range of wind speeds and of dead fine surface fuel moistures. Results: The transition from surface to passive crown fire occurred at lower wind speeds under simulated needle senescence in the forest and in the shrubland. Transitions to active crown fire only occurred in the shrubland under needle senescence. Maximum fire intensity and severity were always recorded in the needle senescence scenario. Conclusions: Aleppo pine needle senescence may enhance the probability of crown fire development at the onset of the fire season, and it could partly explain the concentration of fire activity in early July in the Western Mediterranean Basin.

Mid-term effects of a thin-only treatment on fuel complex, potential fire behaviour and severity and post-fire soil erosion protection in fast-growing pine plantations

Fuel hazard reduction is an essential component of pine plantation management. In NW Spain, plantation managers assume that thin-only reduces the potential fire behavior and effects by decreasing the quantity and continuity of canopy fuels. Nevertheless, thin-only can alter additional variables than control fire behavior and effects such as surface fuel availability and microclimate conditions. Moreover, the duration of thinning effects could vary and be species-specific. We present an approach linking field-measured fuel variables to well-established models for assessing the mid-term effects (six years) of thin-only on potential fire behaviour and severity and ability of burned stands to protect soil against erosion. Field variables were obtained from 41 thinning trials installed in stands of P. pinaster (22 locations) and P. radiata (19 locations). Canopy fuel load and canopy bulk density were still significantly lower in treated sample plots for both species six years after treatments, whereas total and fine understory fuel loads were slightly but significantly larger in thinned plots in P. pinaster. In a simulation process, different fire danger scenarios were considered through two fire-related weather variables: the 10-m open wind speed and the fine dead fuel moisture content. Results showed that thin-only could significantly reduce the likelihood of active crown fire and its rate of spread for both species, particularly in P. pinaster, while passive crown fire probability increased. The potential fire severity, in terms of crown scorch height, scorch volume and tree mortality, hardly worsened by thinning. For fireline intensities lower than 4000 kW m−1, dead fuel moisture content effect on fire severity surpassed the wind speed influence. Moreover, protection of soil against erosion improved only slightly when thinning was previously carried out. The results of the study reveal that, in the mid-term, it is unlikely that thin-only, without intervention in the surface fuels, may have a marked influence on the reduction of the severity of a subsequent fire. The results also highlight the need of a comprehensive assessment of the effects of thin-only on both the whole fuel complex and microclimatic variables for obtaining realistic results.

Potential of Sentinel-2A Data to Model Surface and Canopy Fuel Characteristics in Relation to Crown Fire Hazard

Background: Crown fires are often intense and fast spreading and hence can have serious impacts on soil, vegetation, and wildlife habitats. Fire managers try to prevent the initiation and spread of crown fires in forested landscapes through fuel management. The minimum fuel conditions necessary to initiate and propagate crown fires are known to be strongly influenced by four stand structural variables: surface fuel load (SFL), fuel strata gap (FSG), canopy base height (CBH), and canopy bulk density (CBD). However, there is often a lack of quantitative data about these variables, especially at the landscape scale. Methods: In this study, data from 123 sample plots established in pure, even-aged, Pinus radiata and Pinus pinaster stands in northwest Spain were analyzed. In each plot, an intensive field inventory was used to characterize surface and canopy fuels load and structure, and to estimate SFL, FSG, CBH, and CBD. Equations relating these variables to Sentinel-2A (S-2A) bands and vegetation indices were obtained using two non-parametric techniques: Random Forest (RF) and Multivariate Adaptive Regression Splines (MARS). Results: According to the goodness-of-fit statistics, RF models provided the most accurate estimates, explaining more than 12%, 37%, 47%, and 31% of the observed variability in SFL, FSG, CBH, and CBD, respectively. To evaluate the performance of the four equations considered, the observed and estimated values of the four fuel variables were used separately to predict the potential type of wildfire (surface fire, passive crown fire, or active crown fire) for each plot, considering three different burning conditions (low, moderate, and extreme). The results of the confusion matrix indicated that 79.8% of the surface fires and 93.1% of the active crown fires were correctly classified; meanwhile, the highest rate of misclassification was observed for passive crown fire, with 75.6% of the samples correctly classified. Conclusions: The results highlight that the combination of medium resolution imagery and machine learning techniques may add valuable information about surface and canopy fuel variables at large scales, whereby crown fire potential and the potential type of wildfire can be classified.

Estimating canopy fuel characteristics for predicting crown fire potential in common forest types of the Atlantic Coastal Plain, USA

We computed four stand-level canopy stratum variables important for crown fire modelling – canopy cover, stand height, canopy base height and canopy bulk density – from forest inventory data. We modelled the relationship between the canopy variables and a set of common inventory parameters – site index, stem density, basal area, stand age or stand height – and number of prescribed burns. We used a logistic model to estimate canopy cover, a linear model to estimate the other canopy variables, and the information theoretic approach for model selection. Coefficients of determination across five forest groups were 0.72–0.91 for stand height, 0.36–0.83 for canopy base height, 0.39–0.80 for canopy cover, and 0.63–0.78 for canopy bulk density. We assessed crown fire potential (1) for several sets of environmental conditions in all seasons, and (2) with increasing age, density and number of prescribed burns using our modelled canopy bulk density and canopy base height variables and local weather data to populate the Crown Fire Initiation and Spread model. Results indicated that passive crown fire is possible in any season in Atlantic coastal plain pine stands with heavy surface fuel loads and active crown fire is most probable in infrequently burned, dense stands at low fuel moistures.

Surface fuels in recent Phytophthora ramorum created gaps and adjacent intact Quercus agrifolia forests, East Bay Regional Parks, California, USA

Phytophthora ramorum, cause of “sudden oak death” or SOD, has had significant impacts on composition and structure in coastal forests of central and northern coastal California and southwestern Oregon. Despite the proximity of susceptible coast live oak (Quercus agrifolia) forests to densely populated urban areas, the impacts of SOD on their fuels have not been studied. We sampled surface fuels and vegetation structure in 16 plots in both SOD-caused gaps and intact stands (32 plots total) across two parks in the East Bay Regional Park District, east of San Francisco Bay. Plots were selected from a set of randomly placed pre-existing locations used in determining the disease distribution and intensity across the park system. Among the vegetation characteristics examined, only coast live oak basal area and live and dead tree density, canopy cover and maximum forb height differed between SOD created gap plots and adjacent intact forest plots. However, surface fuels such as vegetation cover, litter cover, wood cover, duff depth, fuels height, ladder fuels abundance, 1h, 10h, 100h, and 1000h fuels were greater in gap plots than intact forest plots. Although no fire behavior models were run, surface fuels suggest SOD created gaps may facilitate passive crown fire due to increased ladder and other fuels. This study represents a spatially explicit (gap focused) point-in-time estimate of surface fuels that will continue to change through time as disease progresses through these stands causing vegetation changes as fuels accumulate and decompose.

Fuel Loads and Simulated Fire Behavior in “Old-Stage” Beetle-Infested Ponderosa Pine of the Colorado Plateau

Recent bark beetle outbreaks in western North America have led to concerns regarding changes in fuel profiles and associated changes in fire behavior. Data are lacking for a range of infestation severities and time since outbreak, especially for relatively arid cover types. We surveyed fuel loads and simulated fire behavior for ponderosa pine stands of the Colorado Plateau 15‐20 years after bark beetle infestation (i.e., “old-stage”). Increasing infestation severity resulted in reduced canopy bulk density, canopy base height, canopy cover, and litter loads whereas woody fuel loads were increased, especially among larger size classes. Using the Fire and Fuels Extension of the Forest Vegetation Simulator, torching index was predicted to decrease with infestation severity whereas crowning index was predicted to increase. Under modeled severe weather conditions, increasing infestation severity was predicted to shift the predominant fire type from surface fire to passive crown fire, whereas the probability of active crown fire was not significantly influenced by old-stage bark beetle-caused tree mortality. We also estimated snagfall rates of infested trees and found that the median time from infestation to snagfall was 9‐12 years, with larger trees taking longer to fall.

Predicted Crown Fire Risk Adds Incentive to Restore Open-Canopy Pine Barrens at the Wildland-Urban Interface

Thinning forest to restore fire-dependent, open-canopy pine barrens is important for promoting shrubland and young forest biodiversity and wildlife habitat and to mitigate chances for extreme fire behavior. Crown fire potential at the wildland-urban interface is a concern in northeastern (USA) pine barrens which contain extremely volatile fuels adjacent to densely populated areas. We used the Crown Fire Initiation and Spread simulator to model pitch pine (Pinus rigida) crown fire potential under simulated stand density reductions to help develop strategies for long-term management and conservation of pine barrens communities. Empirical data for model inputs were collected from pitch pine stands at the Albany Pine Bush (New York State, USA). Canopy structure, surface fuel moisture, and wind speed were used to predict crown fire occurrence, type (active vs. passive), and rate-of-spread. At winds > 20 km hr−1 and ≤ 9% fine fuel moisture, passive crown fire probabilities exceed 60%, and one stand near sensitive human infrastructure appears vulnerable to active crowning. Simulations suggest thinning to < 50 trees ha−1, 10–30% mean canopy cover, or about 5–10 m2 ha−1 basal area to minimize crown fire threat and restore ecologically high-quality pine barrens.

Mixed-severity fire in lodgepole pine dominated forests: are historical regimes sustainable on Oregon’s Pumice Plateau, USA?

In parts of central Oregon, coarse-textured pumice substrates limit forest composition to low-density lodgepole pine (Pinus contorta Douglas ex Loudon var. latifolia Engelm. ex S. Watson) with scattered ponderosa pine (Pinus ponderosa Lawson &amp; C. Lawson) and a shrub understory dominated by antelope bitterbrush (Purshia tridentata (Pursh) DC.). We reconstructed the historical fire regime from tree rings and simulated fire behavior over 783 ha of this forest type. For centuries (1650–1900), extensive mixed-severity fires occurred every 26 to 82 years, creating a multi-aged forest and shrub mosaic. Simulation modeling suggests that the historical mix of surface and passive crown fire were primarily driven by shrub biomass and wind speed. However, a century of fire exclusion has reduced the potential for the high-severity patches of fire that were common historically, likely by reducing bitterbrush cover, the primary ladder fuel. This reduced shrub cover is likely to persist until fire or insects create new canopy gaps. Crown fire potential may increase even with current fuel loadings if the climate predicted for midcentury lowers fuel moistures, but only under rare extreme winds. This study expands our emerging understanding of complexity in the disturbance dynamics of lodgepole pine across its broad North American range.

Changes in forest structure, fuels and potential fire behaviour since 1873 in theLakeTahoeBasin,USA

AbstractQuestionsWhat were the characteristics of pre‐Anglo‐American (reference) forests before logging, grazing and fire exclusion, and how have they changed? What were the structural characteristics of canopy and surface fuels and potential fire behaviour in reference forests, and how do they compare to contemporary forests? How might information from reference conditions be used to inform current restoration and management practices?LocationLakeTahoeBasin in theSierraNevada,California andNevada,USA.MethodsTree species composition, size structure, basal area, density, surface and canopy fuels, and potential fire behaviour were quantified for reference and contemporary conditions in 32 stands. This was accomplished by integrating field measurements and dendroecological techniques with vegetation and fire behaviour simulation models.ResultsContemporaryJeffrey pine and mixed conifer forests had more trees, more basal area, smaller trees and a different size structure than the reference forest. Contemporary red fir and lodgepole pine forests also had more and smaller trees, but basal areas were similar to the reference. Red fir forests also shifted in composition towards lodgepole pine. Vegetation and fire models indicate that contemporary Jeffrey pine and mixed conifer forests have higher flame length, rates of spread, lower crowning and torching indices, and more passive crown fire than the reference forests. In contrast, contemporary red fir and lodgepole pine forests only had lower crowning and torching indices, and flame length and rate of spread were only higher with extreme weather and high surface fuel load.ConclusionsContemporary Jeffrey pine and mixed conifer forests deviate the most from the reference, and restoration objectives for these forests should emphasize density and basal area reduction of smaller diameter stems. Restoration objectives for red fir should shift species composition and reduce basal area by thinning smaller diameter lodgepole pine. For lodgepole pine forests, restoration objectives should include reduction of density and basal area of smaller diameter stems. Fire or other surface fuel treatments will be needed in all the forests to maintain lower fuel loads, albeit at different time intervals.

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

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 80,000ha 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 developed 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 1.4m. Rate of spread varied the greatest with a range of 2.4–5.7mmin−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.

Effect of Fuel Treatments on Fuels and Potential Fire Behavior in California, USA, National Forests

In many parts of California, past timber harvesting, livestock grazing practices, and fire exclusion have changed the fire regime from low to mixed severity to a high severity regime with an increase in active crown fire. Land managers responded by implementing hazardous fuel treatment projects to reduce the risk of such uncharacteristic stand-replacing crown fires. Various fuel treatments have been implemented using either mechanical methods or prescribed fire in forested ecosystems across 14 national forests in California, USA. Mechanical treatments significantly altered forest structure (tree density, 75th percentile quadratic mean diameter, canopy cover, canopy base height, and canopy bulk density) and generally increased surface fuel loads as compared to pre-treatment conditions. Prescribed fire significantly reduced ground and surface fuel loads and increased canopy base height, but did not appreciably alter other forest structure metrics. The changes in forest and fuel structures from prescribed fire reduced predicted fire behavior metrics (fire type, flame length, fireline intensity, and rate of spread); mechanical methods showed mixed effects on resulting fire behavior metrics. Modeled fire type, in addition to predicted flame length, fireline intensity, and rate of spread, is an essential metric for managers when choosing where to implement fuel treatments and for assessing the effectiveness of completed treatments. Under 90th percentile windspeed, out of the five forest treatment combinations, three exhibited some passive crown fire before treatment and only one exhibited passive crown fire after treatment. Using gusting windspeed, four of the five combinations maintain the potential for crown fire (passive or conditional) after treatment. If reducing the potential for uncharacteristic crown fire is the main priority for fuel treatments, it might be beneficial to prioritize areas with elevated risk and to combine both mechanical methods and prescribed fire in order to achieve desired fire behavior under more extreme conditions.

Fire treatment effects on vegetation structure, fuels, and potential fire severity in western U.S. forests

Forest structure and species composition in many western U.S. coniferous forests have been altered through fire exclusion, past and ongoing harvesting practices, and livestock grazing over the 20th century. The effects of these activities have been most pronounced in seasonally dry, low and mid-elevation coniferous forests that once experienced frequent, low to moderate intensity, fire regimes. In this paper, we report the effects of Fire and Fire Surrogate (FFS) forest stand treatments on fuel load profiles, potential fire behavior, and fire severity under three weather scenarios from six western U.S. FFS sites. This replicated, multisite experiment provides a framework for drawing broad generalizations about the effectiveness of prescribed fire and mechanical treatments on surface fuel loads, forest structure, and potential fire severity. Mechanical treatments without fire resulted in combined 1-, 10-, and 100-hour surface fuel loads that were significantly greater than controls at three of five FFS sites. Canopy cover was significantly lower than controls at three of five FFS sites with mechanical-only treatments and at all five FFS sites with the mechanical plus burning treatment; fire-only treatments reduced canopy cover at only one site. For the combined treatment of mechanical plus fire, all five FFS sites with this treatment had a substantially lower likelihood of passive crown fire as indicated by the very high torching indices. FFS sites that experienced significant increases in 1-, 10-, and 100-hour combined surface fuel loads utilized harvest systems that left all activity fuels within experimental units. When mechanical treatments were followed by prescribed burning or pile burning, they were the most effective treatment for reducing crown fire potential and predicted tree mortality because of low surface fuel loads and increased vertical and horizontal canopy separation. Results indicate that mechanical plus fire, fire-only, and mechanical-only treatments using whole-tree harvest systems were all effective at reducing potential fire severity under severe fire weather conditions. Retaining the largest trees within stands also increased fire resistance.

FIRE AND FOREST HISTORY AT MOUNT RUSHMORE

Mount Rushmore National Memorial in the Black Hills of South Dakota is known worldwide for its massive sculpture of four of the United States' most respected presidents. The Memorial landscape also is covered by extensive ponderosa pine (Pinus ponderosa) forest that has not burned in over a century. We compiled dendroecological and forest structural data from 29 plots across the 517-ha Memorial and used fire behavior modeling to reconstruct the historical fire regime and forest structure and compare them to current conditions. The historical fire regime is best characterized as one of low-severity surface fires with occasional (> 100 years) patches (< 100 ha) of passive crown fire. We estimate that only approximately 3.3% of the landscape burned as crown fire during 22 landscape fire years (recorded at > or = 25% of plots) between 1529 and 1893. The last landscape fire was in 1893. Mean fire intervals before 1893 varied depending on spatial scale, from 34 years based on scar-to-scar intervals on individual trees to 16 years between landscape fire years. Modal fire intervals were 11-15 years and did not vary with scale. Fire rotation (the time to burn an area the size of the study area) was estimated to be 30 years for surface fire and 800+ years for crown fire. The current forest is denser and contains more small trees, fewer large trees, lower canopy base heights, and greater canopy bulk density than a reconstructed historical (1870) forest. Fire behavior modeling using the NEXUS program suggests that surface fires would have dominated fire behavior in the 1870 forest during both moderate and severe weather conditions, while crown fire would dominate in the current forest especially under severe weather. Changes in the fire regime and forest structure at Mount Rushmore parallel those seen in ponderosa pine forests from the southwestern United States. Shifts from historical to current forest structure and the increased likelihood of crown fire justify the need for forest restoration before a catastrophic wildfire occurs and adversely impacts the ecological and aesthetic setting of the Mount Rushmore sculpture.

Development and testing of models for predicting crown fire rate of spread in conifer forest stands

The rate of spread of crown fires advancing over level to gently undulating terrain was modeled through nonlinear regression analysis based on an experimental data set pertaining primarily to boreal forest fuel types. The data set covered a significant spectrum of fuel complex and fire behavior characteristics. Crown fire rate of spread was modeled separately for fires spreading in active and passive crown fire regimes. The active crown fire rate of spread model encompassing the effects of 10-m open wind speed, estimated fine fuel moisture content, and canopy bulk density explained 61% of the variability in the data set. Passive crown fire spread was modeled through a correction factor based on a criterion for active crowning related to canopy bulk density. The models were evaluated against independent data sets originating from experimental fires. The active crown fire rate of spread model predicted 42% of the independent experimental crown fire data with an error lower then 25% and a mean absolute percent error of 26%. While the models have some shortcomings and areas in need of improvement, they can be readily utilized in support of fire management decision making and other fire research studies.

Measuring Forest Restoration Effectiveness in Reducing Hazardous Fuels

Abstract Forest restoration treatments of thinning young trees followed by prescribed burning in north-western Arizona led to significantly lower stand density, lower crown fuel load, and higher crown base height than untreated stands. Simulated fire under extreme weather conditions caused 48 percent more canopy burning and higher flame lengths, heat/area, and rate of spread in untreated stands. Wind speeds required for passive crown fire (torching) were twice as high in treated stands. Treated stands were highly heterogeneous, but restoration treatments clearly enhanced crown-fire resistance.