Showing papers in "International Journal of Wildland Fire in 2009"

Fire intensity, fire severity and burn severity: a brief review and suggested usage

Abstract: Several recent papers have suggested replacing the terminology of fire intensity and fire severity. Part of the problem with fire intensity is that it is sometimes used incorrectly to describe fire effects, when in fact it is justifiably restricted to measures of energy output. Increasingly, the term has created confusion because some authors have restricted its usage to a single measure of energy output referred to as fireline intensity. This metric is most useful in understanding fire behavior in forests, but is too narrow to fully capture the multitude of ways fire energy affects ecosystems. Fire intensity represents the energy released during various phases of a fire, and different metrics such as reaction intensity, fireline intensity, temperature, heating duration and radiant energy are useful for different purposes. Fire severity, and the related term burn severity, have created considerable confusion because of recent changes in their usage. Some authors have justified this by contending that fire severity is defined broadly as ecosystem impacts from fire and thus is open to individual interpretation. However, empirical studies have defined fire severity operationally as the loss of or change in organic matter aboveground and belowground, although the precise metric varies with management needs. Confusion arises because fire or burn severity is sometimes defined so that it also includes ecosystem responses. Ecosystem responses include soil erosion, vegetation regeneration, restoration of community structure, faunal recolonization, and a plethora of related response variables. Although some ecosystem responses are correlated with measures of fire or burn severity, many important ecosystem processes have either not been demonstrated to be predicted by severity indices or have been shown in some vegetation types to be unrelated to severity. This is a critical issue because fire or burn severity are readily measurable parameters, both on the ground and with remote sensing, yet ecosystem responses are of most interest to resource managers.

Implications of changing climate for global wildland fire

Abstract: Wildland fire is a global phenomenon, and a result of interactions between climate–weather, fuels and people. Our climate is changing rapidly primarily through the release of greenhouse gases that may have profound and possibly unexpected impacts on global fire activity. The present paper reviews the current understanding of what the future may bring with respect to wildland fire and discusses future options for research and management. To date, research suggests a general increase in area burned and fire occurrence but there is a lot of spatial variability, with some areas of no change or even decreases in area burned and occurrence. Fire seasons are lengthening for temperate and boreal regions and this trend should continue in a warmer world. Future trends of fire severity and intensity are difficult to determine owing to the complex and non-linear interactions between weather, vegetation and people. Improved fire data are required along with continued global studies that dynamically include weather, vegetation, people, and other disturbances. Lastly, we need more research on the role of policy, practices and human behaviour because most of the global fire activity is directly attributable to people.

LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment

Abstract: LANDFIRE is a 5-year, multipartner project producing consistent and comprehensive maps and data describing vegetation, wildland fuel, fire regimes and ecological departure from historical conditions across the United States. It is a shared project between the wildland fire management and research and development programs of the US Department of Agriculture Forest Service and US Department of the Interior. LANDFIRE meets agency and partner needs for comprehensive, integrated data to support landscape-level fire management planning and prioritization, community and firefighter protection, effective resource allocation, and collaboration between agencies and the public. The LANDFIRE data production framework is interdisciplinary, science-based and fully repeatable, and integrates many geospatial technologies including biophysical gradient analyses, remote sensing, vegetation modelling, ecological simulation, and landscape disturbance and successional modelling. LANDFIRE data products are created as 30-m raster grids and are available over the internet at www.landfire.gov, accessed 22 April 2009. The data products are produced at scales that may be useful for prioritizing and planning individual hazardous fuel reduction and ecosystem restoration projects; however, the applicability of data products varies by location and specific use, and products may need to be adjusted by local users.

Wildland surface fire spread modelling, 1990-2007. 1: Physical and quasi-physical models

Abstract: In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across the landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007, providing a useful starting point for those readers interested in recent modelling activities. The current paper surveys models of a physical or quasi-physical nature. These models are based on the fundamental chemistry and physics, or physics alone, of combustion and fire spread. Other papers in the series review models of an empirical or quasi-empirical nature, and mathematical analogues and simulation models. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but in much less detail.

Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models

Abstract: In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007. The current paper surveys models of an empirical or quasi-empirical nature. These models are based on the statistical analysis of experimentally obtained data with or without some physical framework for the basis of the relations. Other papers in the series review models of a physical or quasi-physical nature, and mathematical analogues and simulation models. The main relations of empirical models are those of wind speed and fuel moisture content with rate of forward spread. The focus of the discussion is on the treatment of the wind speed and fuel moisture functions by the models.

Modeling and mapping wildfire ignition risk in Portugal

Abstract: Portugal has the highest density of wildfire ignitions among southern European countries. The ability to predict the spatial patterns of ignitions constitutes an important tool for managers, helping to improve the effectiveness of fire prevention, detection and firefighting resources allocation. In this study, we analyzed 127 490 ignitions that occurred in Portugal during a 5-year period. We used logistic regression models to predict the likelihood of ignition occurrence, using a set of potentially explanatory variables, and produced an ignition risk map for the Portuguese mainland. Results show that population density, human accessibility, land cover and elevation are important determinants of spatial distribution of fire ignitions. In this paper, we demonstrate that it is possible to predict the spatial patterns of ignitions at the national level with good accuracy and using a small number of easily obtainable variables, which can be useful in decision-making for wildfire management.

Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models

Abstract: In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007. The present paper surveys models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one-dimensional models to two dimensions and then simulate the propagation of a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical concept (rather than a physical representation of fire spread) that coincidentally represents the spread of fire. Other papers in the series survey models of a physical or quasi-physical nature, and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.

Synthesis of sediment yields after wildland fire in different rainfall regimes in the western United States

Abstract: Measurements of post-fire sediment erosion, transport, and deposition collected within 2 years of a wildfire were compiled from the published literature (1927–2007) for sites across the western United States. Annual post-fire sediment yields were computed and grouped into four measurement methods (hillslope point and plot measurements, channel measurements of suspended-sediment and sediment erosion or deposition volumes). Post-fire sediment yields for each method were then grouped into eight different rainfall regimes. Mean sediment yield from channels (240 t ha–1) was significantly greater than from hillslopes (82 t ha–1). This indicated that on the time scale of wildfire (10–100 years) channels were the primary sources of available sediment. A lack of correlation of sediment yield with topographic slope and soil erodibility further suggested that sediment availability may be more important than slope or soil erodibility in predicting post-fire sediment yields. The maximum post-fire sediment yields were comparable to long-term sediment yields from major rivers of the world. Based on 80 years of data from the literature, wildfires have been an important geomorphic agent of landscape change when linked with sufficient rainfall. These effects are limited in spatial scale to the immediate burned area and to downstream channel corridors.

Regional variations in wildfire susceptibility of land-cover types in Portugal: implications for landscape management to minimize fire hazard

Abstract: Patterns of wildfire occurrence at the landscape level were characterised during the period 1990–94 in Portugal. Based on land-cover information within 5591 burned patches (larger than 5 ha) and in the surrounding landscape, selection ratio functions were used to measure fire preference or avoidance for different land-cover types in 12 regions of the country. Shrublands were the most fire-prone land cover, whereas annual crops, permanent crops and agro-forestry systems were the most avoided by fire. In terms of forest types, conifer plantations were more susceptible to fire than eucalyptus, and broadleaved forests were the least fire-prone. There were regional variations in land-cover susceptibility to fire, which may be explained by differences in climate, management, ignition patterns, firefighting strategies, and regional availability. A cluster analysis of regional variations in selection ratios for all land covers allowed the identification of three main geographical areas with similar fire selection patterns. These results can be used for planning landscape-scale fuel management in order to create landscapes with a lower fire hazard.

The BlueSky smoke modeling framework

Abstract: Smoke from fire is a local, regional and often international issue that is growing in complexity as competition for airshed resources increases. BlueSky is a smoke modeling framework designed to help address this problem by enabling simulations of the cumulative smoke impacts from fires (prescribed, wildland, and agricultural) across a region. Versions of BlueSky have been implemented in prediction systems across the contiguous US, and land managers, air-quality regulators, incident command teams, and the general public can currently obtain BlueSky-based predictions of smoke impacts for their region. A highly modular framework, BlueSky links together a variety of state-of-the-art models of meteorology, fuels, consumption, emissions, and air quality, and offers multiple model choices at each modeling step. This modularity also allows direct comparison between similar component models. This paper presents the overall model framework Version 2.5 - the component models, how they are linked together, and the results from case studies of two wildfires. Predicted results are affected by the specific choice of modeling pathway. With the pathway chosen, the modeled output generally compares well with plume shape and extent as observed by satellites, but underpredicts surface concentrations as observed by ground monitors. Sensitivity studies show that knowledge of fire behavior can greatly improve the accuracy of these smoke impact calculations.

Improving estimates of savanna burning emissions for greenhouse accounting in northern Australia: limitations, challenges, applications

Abstract: Although biomass burning of savannas is recognised as a major global source of greenhouse gas emissions, quantification remains problematic with resulting regional emissions estimates often differing markedly. Here we undertake a critical assessment of Australia’s National Greenhouse Gas Inventory (NGGI) savanna burning emissions methodology. We describe the methodology developed for, and results and associated uncertainties derived from, a landscape-scale emissions abatement project in fire-prone western Arnhem Land, northern Australia. The methodology incorporates (i) detailed fire history and vegetation structure and fuels type mapping derived from satellite imagery; (ii) field-based assessments of fuel load accumulation, burning efficiencies (patchiness, combustion efficiency, ash retention) and N : C composition; and (iii) application of standard, regionally derived emission factors. Importantly, this refined methodology differs from the NGGI by incorporation of fire seasonality and severity components, and substantial improvements in baseline data. We consider how the application of a fire management program aimed at shifting the seasonality of burning (from one currently dominated by extensive late dry season wildfires to one where strategic fire management is undertaken earlier in the year) can provide significant project-based emissions abatement. The approach has wider application to fire-prone savanna systems dominated by anthropogenic sources of ignition.

The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests

Abstract: In ecosystems with frequent surface fire regimes, fire and fuel heterogeneity has been largely overlooked owing to the lack of unburned patches and the difficulty in measuring fire behavior at fine scales (0.1-10 m). The diverse vegetation in these ecosystems varies at these fine scales. This diversity could be driven by the influences of local interactions among patches of understorey vegetation and canopy-supplied fine fuels on fire behavior, yet no method we know of can capture fine-scale fuel and fire measurements such that these relationships could be rigorously tested. We present here an original method for inventorying of fine-scale fuels and in situ measures of fire intensity within longleaf pine forests of the south-eastern USA. Using ground-based LIDAR (Light Detection and Ranging) with traditional fuel inventory approaches, we characterized within-fuel bed variation into discrete patches, termed wildland fuel cells, which had distinct fuel composition, characteristics, and architecture that became spatially independent beyond 0.5 m 2 . Spatially explicit fire behavior was measured in situ through digital infrared thermography. We found that fire temperatures and residence times varied at similar scales to those observed for wildland fuel cells. The wildland fuels cell concept could seamlessly connect empirical studies with numerical models or cellular automata models of fire behavior, representing a promising means to better predict within-burn heterogeneity and fire effects.

Prediction of the probability of large fires in the Sydney region of south-eastern Australia using fire weather

Abstract: The probability of large-fire (≥1000 ha) ignition days, in the Sydney region, was examined using historical records Relative influences of the ambient and drought components of the Forest Fire Danger Index (FFDI) on large fire ignition probability were explored using Bayesian logistic regression The preferred models for two areas (Blue Mountains and Central Coast) were composed of the sum of FFDI (Drought Factor, DF = 1) (ambient component) and DF as predictors Both drought and ambient weather positively affected the chance of large fire ignitions, with large fires more probable on the Central Coast than in the Blue Mountains The preferred, additive combination of drought and ambient weather had a marked threshold effect on large-fire ignition and total area burned in both localities This may be due to a landscape-scale increase in the connectivity of available fuel at high values of the index Higher probability of large fires on the Central Coast may be due to more subdued terrain or higher population density and ignitions Climate scenarios for 2050 yielded predictions of a 20–84% increase in potential large-fire ignitions days, using the preferred model

Climate, lightning ignitions, and fire severity in Yosemite National Park, California, USA.

Abstract: Continental-scale studies of western North America have attributed recent increases in annual area burned and fire size to a warming climate, but these studies have focussed on large fires and have left the issues of fire severity and ignition frequency unaddressed. Lightning ignitions, any of which could burn a large area given appropriate conditions for fire spread, could be the first indication of more frequent fire. We examined the relationship between snowpack and the ignition and size of fires that occurred in Yosemite National Park, California (area 3027 km2), between 1984 and 2005. During this period, 1870 fires burned 77 718 ha. Decreased spring snowpack exponentially increased the number of lightning-ignited fires. Snowpack mediated lightning-ignited fires by decreasing the proportion of lightning strikes that caused lightning-ignited fires and through fewer lightning strikes in years with deep snowpack. We also quantified fire severity for the 103 fires >40 ha with satellite fire-severity indices using 23 years of Landsat Thematic Mapper data. The proportion of the landscape that burned at higher severities and the complexity of higher-severity burn patches increased with the log10 of annual area burned. Using one snowpack forecast, we project that the number of lightning-ignited fires will increase 19.1% by 2020 to 2049 and the annual area burned at high severity will increase 21.9%. Climate-induced decreases in snowpack and the concomitant increase in fire severity suggest that existing assumptions may be understated – fires may become more frequent and more severe.

Relative importance of fuel management, ignition management and weather for area burned: evidence from five landscape–fire–succession models

Abstract: The behaviour of five landscape fire models (CAFE, FIRESCAPE, LAMOS(HS), LANDSUM and SEM- LAND) was compared in a standardised modelling experiment. The importance of fuel management approach, fuel management effort, ignition management effort and weather in determining variation in area burned and number of edge pixels burned (a measure of potential impact on assets adjacent to fire-prone landscapes) was quantified for a standardised modelling landscape. Importance was measured as the proportion of variation in area or edge pixels burned explained by each factor and all interactions among them. Weather and ignition management were consistently more important for explaining variation in area burned than fuel management approach and effort, which were found to be statistically unimportant. For the number of edge pixels burned, weather and ignition management were generally more important than fuel management approach and effort. Increased ignition management effort resulted in decreased area burned in all models and decreased number of edge pixels burned in three models. The findings demonstrate that year-to-year variation in weather and the success of ignition management consistently prevail over the effects of fuel management on area burned in a range of modelled ecosystems.

Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics

Abstract: Ground-based LIDAR (also known as laser ranging) is a novel technique that may precisely quantify fuelbed characteristics important in determining fire behavior. We measured fuel properties within a south-eastern US longleaf pine woodland at the individual plant and fuelbed scale. Data were collected using a mobile terrestrial LIDAR unit at sub-cm scale for individual fuel types (shrubs) and heterogeneous fuelbed plots. Spatially explicit point-intercept fuel sampling also measured fuelbed heights and volume, while leaf area and biomass measurements of whole and sectioned shrubs were determined from destructive sampling. Volumes obtained by LIDAR and traditional methods showed significant discrepan- cies. We found that traditional means overestimated volume for shrub fuel types because of variation in leaf area distribution within shrub canopies. LIDAR volume estimates were correlated with biomass and leaf area for individual shrubs when factored by species, size, and plant section. Fuelbed heights were found to be highly variable among the fuel plots, and ground LIDAR was more sensitive to capturing the height variation than traditional point intercept sampling. Ground LIDAR is a promising technology capable of measuring complex surface fuels and fuel characteristics, such as fuel volume.

Effects of targeted cattle grazing on fire behavior of cheatgrass-dominated rangeland in the northern Great Basin, USA

Abstract: We evaluated the effectiveness of using targeted, or prescribed, cattle grazing to reduce the flame length and rate of spread of fires on cheatgrass (Bromus tectorum)-dominated rangeland in northern Nevada. Cattle removed 80–90% of B. tectorum biomass during the boot (phenological) stage in grazed plots in May 2005. Grazed and ungrazed plots were burned in October 2005 to assess fire behavior characteristics. Targeted grazing reduced B. tectorum biomass and cover, which resulted in reductions in flame length and rate of spread. When the grazing treatments were repeated on the same plots in May 2006, B. tectorum biomass and cover were reduced to the point that fires did not carry in the grazed plots in October 2006. Fuel characteristics of the 2005 burns were used to parameterize dry-climate grass models in BEHAVE Plus, and simulation modeling indicates that targeted grazing in spring (May) will reduce the potential for catastrophic fires during the peak fire season (July–August) in the northern Great Basin.

Prediction of fire occurrence from live fuel moisture content measurements in a Mediterranean ecosystem

Abstract: The present paper presents and discusses the relationships between live Fuel Moisture Content (FMC) measurements and fire occurrence (number of fires and burned area) in a Mediterranean area of central Spain. Grasslands and four shrub species (Cistus ladanifer L., Rosmarinus officinalis L., Erica australis L. and Phillyrea angustifolia L.) were sampled in the field from the spring to the summer season over a 9-year period. Higher seasonal FMC variability was found for the herbaceous species than for shrubs, as grasslands have very low values in summertime. Moisture variations of grasslands were found to be good predictors of number of fires and total burned surface, while moisture variation of two shrubs (C. ladanifer L. and R. officinalis L.) was more sensitive to both the total burned area and the occurrence of large fires. All these species showed significant differences between the FMC of high and low occurrence periods. Three different logistic regression models were built for the 202 periods of analysis: one to predict periods with more and less than seven fires, another to predict periods with and without large fires (>500 ha), and the third to predict periods with more and less than 200 ha burned. The results showed accuracy in predicting periods with a high number of fires (94%), and extensive burned area (85%), with less accuracy in estimating periods with large fires (58%). Finally, empirical functions based on logistic regression analysis were successfully related to fire ignition or potential burned area from FMC data. These models should be useful to integrate FMC measurements with other variables of fire danger (ignition causes, for instance), to provide a more comprehensive assessment of fire danger conditions.

Critical live fuel moisture in chaparral ecosystems: a threshold for fire activity and its relationship to antecedent precipitation

Abstract: Large wildfires in southern California typically occur during periods of reduced live fuel moisture (LFM) and high winds. Previous work has found evidence that a LFM threshold may determine when large fires can occur. Using a LFM time series and a fire history for Los Angeles County, California, we found strong evidence for a LFM threshold near 79%. Monthly and 3-month total precipitation data were used to show that the timing of this threshold during the fire season is strongly correlated with antecedent rainfall. Spring precipitation, particularly in the month of March, was found to be the primary driver of the timing of LFM decline, although regression tree analysis revealed that high winter precipitation may delay the timing of the threshold in some years. This work further establishes relationships between precipitation and fire potential that may prove important for anticipating shifts in fire regimes under climate-change scenarios.

Spot fires: fuel bed flammability and capability of firebrands to ignite fuel beds.

Abstract: A series of tests were conducted under laboratory conditions to assess, first, the capacity of several fuel beds to be ignited by firebrands and to sustain a fire and, second, the capability of different types of firebrands to ignite fuel beds Fuel beds and firebrands were selected among the most common in southern Europe Regarding fuel bed flammability, results show that grasses are more flammable than litter and, among litters, Pinus species are the most flammable The increase in bulk density and fuel moisture content involves an increase in the time to ignition, and a decrease in the other flammability parameters The capability of firebrands to ignite fuel beds is higher when the firebrands drop in the flaming phase and with no air flow than in glowing phase with air flow Logistic regression models to predict fuel bed ignition probability were developed As a whole, results show a relationship between ignition probability of fuel bed and type or weight of firebrands Pinus pinaster cone scale, P halepensis cone scale, and Eucalyptus globulus leaf and bark can have ignition probabilities at least twice higher than pine bark when falling while in flaming combustion

An overview of mountain meteorological effects relevant to fire behaviour and bushfire risk.

Abstract: Many of the processes that can occur in mountainous landscapes have the potential to significantly affect fire behaviour and bushfire risk in general These processes can lead to otherwise unexpected fire behaviour and escalation in fire size and severity that could endanger firefighting crews and compromise suppression activities Interaction of upper winds with rugged terrain can often result in highly variable and turbulent wind patterns and variations in temperature and humidity that can affect fire regimes in the long and short term More generally, the effect of rugged terrain on atmospheric flows can give rise to complex dynamics and emergent properties that are discontinuous in nature Hence, the ‘fire weather continuum’ that is often assumed in fire management practices is of reduced validity in mountainous or hilly landscapes This paper presents an overview of the main elements of mountain meteorology relevant to fire weather and discusses the potential roles they may play in bushfire behaviour, development and risk As such, the paper is intended to promote understanding, across the wide range of professions concerned with bushfire, of how mountain meteorological effects might contribute to fire potential and fire behaviour

The fire history of an arid grassland: the influence of antecedent rainfall and ENSO

Abstract: Implementing appropriate fire regimes has become an increasingly important objective for biodiversity conservation programs. Here, we used Landsat imagery from 1972 to 2003 to describe the recent fire history and current wildfire regime of the north-eastern Simpson Desert, Australia, within each of the region’s seven main vegetation classes. We then explored the relationship between antecedent rainfall and El Nino–Southern Oscillation with wildfire area. Wildfires were recorded in 11 years between 1972 and 2003, each differing in size. In 1975, the largest wildfire was recorded, burning 55% (4561 km2) of the study region. Smaller fires in the intervening years burnt areas that had mostly escaped the 1975 fire, until 2002, when 31% (2544 km2) of the study region burnt again. Wildfires burnt disproportionally more spinifex (Triodia basedowii) than any other vegetation class. A total of 49% of the study area has burnt once since 1972 and 20% has burnt twice. Less than 1% has burnt three times and 36% has remained unaffected by wildfire since 1972. The mean minimum fire return interval was 26 years. Two years of cumulative rainfall before a fire event, rainfall during the year of a fire event, and the mean Southern Oscillation Index from June to November in the year before a fire event could together be used to successfully predict wildfire area. We use these findings to describe the current fire regime.

The importance of fire–atmosphere coupling and boundary-layer turbulence to wildfire spread

Abstract: The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire’s environment. The changes in flow are dominated by two factors. The first is the interaction or ‘coupling’ between the fire and the fire-induced flow. The second is the interaction or ‘coupling’ between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire–atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire–atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts.

Empirical modelling of surface fire behaviour in maritime pine stands

Abstract: An experimental burning program took place in maritime pine (Pinus pinaster Ait.) stands in Portugal to increase the understanding of surface fire behaviour under mild weather. The spread rate and flame geometry of the forward and backward sections of a line-ignited fire front were measured in 94 plots 10–15 m wide. Measured head fire rate of spread, flame length and Byram’s fire intensity varied respectively in the intervals of 0.3–13.9 m min–1, 0.1–4.2 m and 30–3527 kW m–1. Fire behaviour was modelled through an empirical approach. Rate of forward fire spread was described as a function of surface wind speed, terrain slope, moisture content of fine dead surface fuel, and fuel height, while back fire spread rate was correlated with fuel moisture content and cover of understorey vegetation. Flame dimensions were related to Byram’s fire intensity but relationships with rate of spread and fine dead surface fuel load and moisture are preferred, particularly for the head fire. The equations are expected to be more reliable when wind speed and slope are less than 8 km h–1 and 15°, and when fuel moisture content is higher than 12%. The results offer a quantitative basis for prescribed fire management.

Traditional fire management: historical fire regimes and land use change in pastoral East Africa

Abstract: Although there is considerable research on the ecological effects of fire in sub-Saharan Africa, research on traditional fire practices is very limited and the consequences of substantial changes to historical fire regimes have not been adequately explored. The present paper examines historic and contemporary uses of fire as a land management tool among Maasai pastoralists in northern Tanzania and explores the potential impacts of changing fire management and fire suppression on savanna vegetation. Village members were interviewed about historical and current practices, reasons for burning, the history of land use, and their perceptions of fire. Eight recent burn sites were selected for examination of size, ignition source, and timing of the burn. The Maasai identified eight major reasons for using fire on a landscape scale in savannas and historically used a progression of small fires throughout the dry season as grasses cured to create a fragmented burn pattern and to prevent large, catastrophic late-season fires. Currently, there is little active vegetation management using fire largely owing to federal fire suppression policies, unpredictable rainfall patterns, increasing population pressures, and a subsequent increase in the number of catastrophic accidental fires. Substantial modifications to historical fire regimes could have cascading consequences for savanna health by increasing late-season fuel loads and the occurrence of large, catastrophic fires.

Novel fuelbed characteristics associated with mechanical mastication treatments in northern California and south-western Oregon, USA

Abstract: Mechanically masticated fuelbeds are distinct from natural or logging slash fuelbeds, with different particle size distributions, bulk density, and particle shapes, leading to challenges in predicting fire behavior and effects. Our study quantified some physical properties of fuel particles (e.g. squared quadratic mean diameter, proportion of non-cylindrical particles) and surface fuel loading with planar intercept and plot-based methods in 10 mechanically masticated sites in northern California and south-western Oregon. Total woody fuel load differed among masticated sites, ranging from 15.3 to 63.4 Mg ha −1 , with the majority of the load concentrated in the 10-h (53.7%) and 1-h (29.2%) time-lag classes. Masticated fuels were densely packed, with total depths ranging from 4.6 to 8.0 cm and fuelbed bulk densities ranging from 45.9 to 115.3 kg m −3 . To accurately quantify loading in masticated fuelbeds, we recommend using a hybrid methodology, where 1-h and 10-h fuel loadings are estimated using a plot-based method and 100-h and 1000-h fuel loadings are estimated using the standard planar intercept method. Most masticated fuelbeds differed in loading by fuel class and fuelbed depth, when compared with existing natural and slash-based fuelbeds, suggesting new fire behavior fuel models specific to masticated fuelbeds may be warranted.

Remote sensing for prediction of 1-year post-fire ecosystem condition

Abstract: Appropriate use of satellite data in predicting >1 year post-fire effects requires remote measurement of sur- face properties that can be mechanistically related to ground measures of post-fire condition. The present study of burned ponderosa pine (Pinus ponderosa) forests in the Black Hills of South Dakota evaluates whether immediate fractional cover estimates of char, green vegetation and brown (non-photosynthetic) vegetation within a pixel are improved predictors of 1-year post-fire field measures, when compared with single-date and differenced Normalized Burn Ratio (NBR and dNBR) indices. The modeled estimate of immediate char fraction either equaled or outperformed all other immediate metrics in predicting 1-year post-fire effects. Brown cover fraction was a poor predictor of all effects (r 2 < 0.30), and each remote measure produced only poor predictions of crown scorch (r 2 < 0.20). Application of dNBR (1 year post) provided a consid- erable increase in regression performance for predicting tree survival. Immediate post-fire NBR or dNBR produced only marginal differences in predictions of all the 1-year post-fire effects, perhaps limiting the need for prefire imagery.Although further research is clearly warranted to evaluate fire effects data available 2-20 years after fire, char and green vegetation fractions may be viable alternatives to dNBR and similar indices to predict longer-term post-fire ecological effects.

Factors influencing the pattern of fire severities in a large wildfire under extreme meteorological conditions in the Mediterranean basin

Abstract: In Mediterranean ecosystems, large fires frequently burn under extreme meteorological conditions, but they are usually characterized by a spatial heterogeneity of burn severities. The way in which such mixed-severity fires are a result of fuels, topography and weather remains poorly understood. We computed fire severity of a large wildfire that occurred in Catalonia, Spain, as the difference between the post- and pre-fire Normalized Difference Vegetation Index (NDVI) values obtained through Landsat images. Fuel and topographic variables were derived from remote sensing, and fire behavior variables were obtained from an exhaustive reconstruction of the fire. Results showed that fire severity had a negative relationship with percentage of canopy cover, i.e. green surviving plots were mainly those with more forested conditions. Of the topographic variables, only aspect had a significant effect on fire severity, with higher values in southern than in northern slopes. Fire severity was higher in head than in flank and back fires. The interaction of these two variables was significant, with differences between southern and northern aspects being small for head fires, but increasing in flank and back fires. The role of these variables in determining the pattern of fire severities is of primary importance for interpreting the current landscapes and for establishing effective fire prevention and extinction policies.

Validation of FIRETEC wind-flows over a canopy and a fuel-break

Abstract: The wildfire model FIRETEC simulates the large coherent eddies of the wind-flows induced by the canopy. It has been qualitatively validated in its ability to simulate fire behavior, but there is still a need to validate physical submodels separately. In the present study, the dynamics and turbulence of the flow simulated by FIRETEC are validated in a manner similar to other air-flow models without fire, through comparison with measurements associated with flows within continuous and discontinuous forests captured through in situ and wind-tunnel experiments with neutral thermal stratification. The model is shown to be able to reproduce accurately all essential features of turbulent flow over both forests. Moreover, a short sensitivity study shows that the model is not very sensitive to uncertain parameters such as vegetation drag coefficient. Finally, it is shown in the discontinuous forest case that wind gusts on fuel-breaks can be very strong and significantly higher than in surrounding canopies, even if their directions are more stable. These results and others briefly reviewed in the present paper allow better understanding of wind-flow perturbations induced by fuel-breaks. This new validation added to previous ones confirms the ability of FIRETEC for investigating effects of fuel-break design on fire propagation.

Spatial fuel data products of the LANDFIRE Project

Abstract: The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50 states. Here we describe development of the LANDFIRE wildland fuels data layers for the conterminous 48 states: surface fire behavior fuel models, canopy bulk density, canopy base height, canopy cover, and canopy height. Surface fire behavior fuel models are mapped by developing crosswalks to vegetation structure and composition created by LANDFIRE. Canopy fuels are mapped using regression trees relating field-referenced estimates of canopy base height and canopy bulk density to satellite imagery, biophysical gradients and vegetation structure and composition data. Here we focus on the methods and data used to create the fuel data products, discuss problems encountered with the data, provide an accuracy assessment, demonstrate recent use of the data during the 2007 fire season, and discuss ideas for updating, maintaining and improving LANDFIRE fuel data products.