Evaluation of the Fire Simulation Processes of the National Fire Management System's Initial Attack Analysis Processor

The fire simulation processes of the National Fire Management System's (NFMAS) Initial Attack Analysis (IAA) processor were evaluated by conducting two types of sensitivity analysis: one based on a hypothetical set of data to assess IAA's outputs under a wide range of fire input values, and the other using an actual Stanislaus National Forest database to test IAA's validity with a real set of data. The results revealed that IAA's outputs (projected annual number of fires and area burned) were most sensitive, in descending order, to the input values of the fire spread rate, the productivity rates of the suppression forces, and the initial attack time, for all fuel models tested. In contrast, IAA's outputs were extremely insensitive to variations in the fire size at discovery. Changes are necessary in the ways IAA incorporates the fire size at discovery to facilitate the comparison among various fire detection options. The program's “escaped fire situation” analysis was found inadequate, because the projected annual frequencies and final sizes of the simulated escaped fire events produced unacceptable results with the Stanislaus National Forest database. Assigning final sizes to simulated escaped fires according to the fire intensity level in which they are historically expected to occur provides a consistent way of calculation of the projected annual area burned and the consequent cost plus net value change (C + NVC).     

Predicting Sustained Fire Spread in Tasmanian Native Grasslands

Fire is widely used in conservation management of native grasslands. Burning is often carried out under conditions that are marginal for sustained fire spread, and therefore it would be useful to be able to predict fire sustainability. There is currently no model allowing such prediction in temperate grasslands. This study aims to identify the environmental variables that determine whether fires will sustain in native grasslands in Tasmania, Australia, and develop a model for predicting fire sustainability in this vegetation. Fuel characteristics and weather conditions were recorded for 111 test fires. Logistic regression modeling identified dead fuel moisture content, fuel load, and percentage dead fuel as predictors of fire sustainability. Classification tree modeling identified dead fuel moisture and fuel load threshold values for sustaining fires. There was also evidence indicating a percentage dead fuel threshold. The logistic regression model and a model combining the results of the classification tree and the percentage dead fuel threshold accurately predicted the outcomes of a small set of experimental fires. These models are likely to have utility in predicting fire sustainability in Tasmanian grasslands and are also likely to be applicable to similar grasslands elsewhere.     

Remotely-Sensed Active Fire Data for Protected Area Management: Eight-Year Patterns in the Manas National Park, India

The Terai-Duar savanna and grasslands, which once extended along most of the Himalayan foothills, now only remain in a number of protected areas. Within these localities, grassland burning is a major issue, but data on frequency and distribution of fires are limited. Here, we analysed the incidence of active fires, which only occur during the dry season (Nov.–Mar.), within a significant area of Terai grasslands: the Manas National Park (MNP), India. We obtained locations of 781 fires during the 2000–2008 dry seasons, from the Fire Information for Resource Management System (FIRMS) that delivers global MODIS hotspot/fire locations using remote sensing and GIS technologies. Annual number of fires rose significantly from around 20 at the start of the study period to over 90 after 2002, with most (85%) detected between December and January. Over half of the fires occurred in tall grasslands, but fire density was highest in wetland and riverine vegetation, dry at the time. Most burning took place near rivers, roads and the park boundary, suggesting anthropogenic origins. A kernel density map of all recorded fires indicated three heavily burnt areas in the MNP, all within the tall grasslands. Our study demonstrates, despite some technical caveats linked to fire detection technology, which is improving, that remote fire data can be a practical tool in understanding fire concentration and burning temporal patterns in highly vulnerable habitats, useful in guiding management.     

A Review of the Main Driving Factors of Forest Fire Ignition Over Europe

Knowledge of the causes of forest fires, and of the main driving factors of ignition, is an indispensable step towards effective fire prevention policies. This study analyses the factors driving forest fire ignition in the Mediterranean region including the most common human and environmental factors used for modelling in the European context. Fire ignition factors are compared to spatial and temporal variations of fire occurrence in the region, then are compared to results obtained in other areas of the world, with a special focus on North America (US and Canada) where a significant number of studies has been carried out on this topic. The causes of forest fires are varied and their distribution differs among countries, but may also differ spatially and temporally within the same country. In Europe, and especially in the Mediterranean basin, fires are mostly human-caused mainly due arson. The distance to transport networks and the distance to urban or recreation areas are among the most frequently used human factors in modelling exercises and the Wildland-Urban Interface is increasingly taken into account in the modelling of fire occurrence. Depending on the socio-economic context of the region concerned, factors such as the unemployment rate or variables linked to agricultural activity can explain the ignition of intentional and unintentional fires. Regarding environmental factors, those related to weather, fuel and topography are the most significant drivers of ignition of forest fires, especially in Mediterranean-type regions. For both human and lightning-caused fires, there is a geographical gradient of fire ignition, mainly due to variations in climate and fuel composition but also to population density for instance. The timing of fires depends on their causes. In populated areas, the timing of human-caused fires is closely linked to human activities and peaks in the afternoon whereas, in remote areas, the timing of lightning-caused fires is more linked to weather conditions and the season, with most such fires occurring in summer.     

Mapping probability of fire occurrence in San Jacinto Mountains,California, USA

An ecological data base for the San Jacinto Mountains, California, USA, was used to construct a probability model of wildland fire occurrence. The model incorporates both environmental and human factors, including vegetation, temperature, precipitation, human structures, and transportation. Spatial autocorrelation was examined for both fire activity and vegetation to determine the specification of neighborhood effects in the model. Parameters were estimated using stepwise logistic regressions. Among the explanatory variables, the variable that represents the neighborhood effects of spatial processes is shown to be of great importance in the distribution of wildland fires. An important implication of this result is that the management of wildland fires must take into consideration neighborhood effects in addition to environmental and human factors. The distribution of fire occurrence probability is more accurately mapped when the model incorporates the spatial term of neighborhood effects. The map of fire occurrence probability is useful for designing large-scale management strategies of wildfire prevention.     

Lightning Fires in a Brazilian Savanna National Park: Rethinking Management Strategies

Fire occurrences and their sources were monitored in Emas National Park, Brazil (17°49′–18°28′S; 52°39′–53°10′W) from June 1995 to May 1999. The extent of burned area and weather conditions were registered. Forty-five fires were recorded and mapped on a GIS during this study. Four fires occurred in the dry winter season (June–August; 7,942 ha burned), all caused by humans; 10 fires occurred in the seasonally transitional months (May and September) (33,386 ha burned); 31 fires occurred in the wet season, of which 30 were caused by lightning inside the park (29,326 ha burned), and one started outside the park (866 ha burned). Wet season lightning fires started in the open vegetation (wet field or grassy savanna) at a flat plateau, an area that showed significantly higher fire incidence. On average, winter fires burned larger areas and spread more quickly, compared to lightning fires, and fire suppression was necessary to extinguish them. Most lightning fires were patchy and extinguished primarily by rain. Lightning fires in the wet season, previously considered unimportant episodes, were shown to be very frequent and probably represent the natural fire pattern in the region. Lightning fires should be regarded as ecologically beneficial, as they create natural barriers to the spread of winter fires. The present fire management in the park is based on the burning of preventive firebreaks in the dry season and exclusion of any other fire. This policy does not take advantage of the beneficial effects of the natural fire regime and may in fact reduce biodiversity. The results presented here stress the need for reevaluating present policies and management procedures concerning fire in cerrado conservation areas.     

Spatio-temporal analysis of fire events in India: implications for environmental conservation

Information on fires in different geographic regions of India is relatively scarce. This study quantifies spatial and temporal patterns in fire occurrences covering different states and districts in India. Two important scientific questions are answered in this study: (1) how are the fire events distributed across different geographical regions? (2) are there any specific districts where fire events clustered across space and time? To address these questions, Along Track Scanning Radiometer (ATSR) derived satellite fire counts from 1997–2006 were used and the datasets were analysed using spatial scan statistic. Spatial scan statistic provides a test statistic for most likely ‘hotspot’ spatial clusters, based on the likelihood ratio test and Monte Carlo simulation. Results from geographical analysis based on state boundaries suggested Maharastra state had the highest number of fires followed by Madhya Pradesh, Chattisgarh, Orissa, etc., during the 10-year period. Among the several districts, the spatial scan statistic identified the most likely cluster of fire events in Dausa, Karauli, Sawai Madhopur, Bharatpur and Alwar in addition to several other secondary clusters, with high statistical significance. These results are based on a large sample of cases, and they provide convincing evidence of spatial clustering of fire events in the Indian region. Results relating to hotspot areas of fire risk can guide policy makers towards the best management strategies for avoiding damages to forests, human life and personal property in the ‘hotspot’ districts.     

Wildland–Urban Interface Fires and Socioeconomic Conditions: A Case Study of a Northwestern Patagonia City

In many regions of the world, fires are primarily of anthropogenic origin. In northwestern Patagonia, the number of fires is not correlated with meteorological variables, but is concentrated in urban areas. This study was conducted in the wildland–urban interface (WUI) area of San Carlos de Bariloche (Patagonia, Argentina), within the Nahuel Huapi National Park. WUI fires are particularly problematic because, besides people and goods, they represent a danger to protected areas. We studied the relationship between fire records and socioeconomic indicators within the WUI of San Carlos de Bariloche. We conducted a Multiple Correspondence Factorial Analysis and an Ascendant Hierarchical Classification of the city neighborhoods. The results show that the neighborhoods in Bariloche can be divided into three classes: High Socioeconomic Fire Risk neighborhoods, including neighborhoods with the highest fire rates, where people have low instruction level, high levels of unsatisfied basic needs and high unemployment levels; Low Socioeconomic Fire Risk neighborhoods, that groups neighborhoods which present the opposite characterization, and Moderate Socioeconomic Fire Risk neighborhoods, which are more heterogeneous. Once neighborhoods were classified, a Socioeconomic Fire Risk map was generated, supplementing the existing WUI Fire Danger map. Our results emphasize the relevance of socioeconomic variables to fire policies.     

Biophysical and anthropogenic controls of forest fires in the Deccan Plateau, India

Forest fires constitute one of the most serious environmental problems in several forested regions of India. In the Indian sub-continent, relatively few studies have focused on the assessment of biophysical and anthropogenic controls of forest fires at a landscape scale and the spatial aspects of these relationships. In this study, we used fire count data sets from satellite remote sensing data covering 78 districts over four different states of the Deccan Plateau, India, for assessing the underlying causes of fires. Spatial data for explanatory variables of fires pertaining to topography, vegetation, climate, anthropogenic and accessibility factors have been gathered corresponding with fire presence/absence. A logistic regression model was used to estimate the probability of the presence of fires as a function of the explanatory variables. Results for fire area estimates suggested that, of the total fires covering 47,043km(2) that occurred during the year 2000 for the entire Indian region, 29.0% occurred in the Deccan Plateau, with Andhra Pradesh having 13.5%, Karnataka 14.7%, Kerala 0.1%, and Tamilnadu 1.15%. Results from the logistic regression suggest that the strongest influences on the fire occurrences were the amount of forest area, biomass densities, rural population density (PD), average precipitation of the warmest quarter, elevation (ELE) and mean annual temperature (MAT). Among these variables, biomass density (BD) and average precipitation of the warmest quarter had the highest significance, followed by others. These results on the best predictors of forest fires can be used both as a strategic planning tool to address broad scale fire risk concerns, and also as a tactical guide to help forest managers to design fire mitigation measures at the district level.     

Development of Customized Fire Behavior Fuel Models for Boreal Forests of Northeastern China

Knowledge of forest fuels and their potential fire behavior across a landscape is essential in fire management. Four customized fire behavior fuel models that differed significantly in fuels characteristics and environmental conditions were identified using hierarchical cluster analysis based on fuels data collected across a boreal forest landscape in northeastern China. Fuel model I represented the dense and heavily branched Pinus pumila shrubland which has significant fine live woody fuels. These forests occur mainly at higher mountain elevations. Fuel model II is applicable to forests dominated by Betula platyphylla and Populus davidiana occurring in native forests on hill slopes or at low mountain elevations. This fuel model was differentiated from other fuel models by higher herbaceous cover and lower fine live woody loading. The primary coniferous forests dominated by Larix gmelini and Pinus sylvestris L. var. mongolica were classified as fuel model III and fuel model IV. Those fuel models differed from one another in average cover and height of understory shrub and herbaceous layers as well as in aspect. The potential fire behavior for each fuel model was simulated with the BehavePlus5.0 fire behavior prediction system. The simulation results indicated that the Pinus pumila shrubland fuels had the most severe fire behavior for the 97th percentile weather condition, and had the least severe fire behavior under 90th percentile weather condition. Fuel model II presented the least severe fire potential across weather conditions. Fuel model IV resulted in greater fire severity than Fuel model III across the two weather scenarios that were examined.     

Forest Fires in Mediterranean Countries: CO2 Emissions and Mitigation Possibilities Through Prescribed Burning

Forest fires are an integral part of the ecology of the Mediterranean Basin; however, fire incidence has increased dramatically during the past decades and fire is expected to become more prevalent in the future due to climate change. Fuel modification by prescribed burning reduces the spread and intensity potential of subsequent wildfires. We used the most recently published data to calculate the average annual wildfire CO(2) emissions in France, Greece, Italy, Portugal and Spain following the IPCC guidelines. The effect of prescribed burning on emissions was calculated for four scenarios of prescribed burning effectiveness based on data from Portugal. Results show that prescribed burning could have a considerable effect on the carbon balance of the land use, land-use change and forestry (LULUCF) sector in Mediterranean countries. However, uncertainty in emission estimates remains large, and more accurate data is needed, especially regarding fuel load and fuel consumption in different vegetation types and fuel layers and the total area protected from wildfire per unit area treated by prescribed burning, i.e. the leverage of prescribed burning.     

Determining Relative Contributions of Vegetation and Topography to Burn Severity from LANDSAT Imagery

Fire is a dominant process in boreal forest landscapes and creates a spatial patch mosaic with different burn severities and age classes. Quantifying effects of vegetation and topography on burn severity provides a scientific basis on which forest fire management plans are developed to reduce catastrophic fires. However, the relative contribution of vegetation and topography to burn severity is highly debated especially under extreme weather conditions. In this study, we hypothesized that relationships of vegetation and topography to burn severity vary with fire size. We examined this hypothesis in a boreal forest landscape of northeastern China by computing the burn severity of 24 fire patches as the difference between the pre- and post-fire Normalized Difference Vegetation Index obtained from two Landsat TM images. The vegetation and topography to burn severity relationships were evaluated at three fire-size levels of small (<100 ha, n = 12), moderate (100–1,000 ha, n = 9), and large (>1,000 ha, n = 3). Our results showed that vegetation and topography to burn severity relationships were fire-size-dependent. The burn severity of small fires was primary controlled by vegetation conditions (e.g., understory cover), and the burn severity of large fires was strongly influenced by topographic conditions (e.g., elevation). For moderate fires, the relationships were complex and indistinguishable. Our results also indicated that the pattern trends of relative importance for both vegetation and topography factors were not dependent on fire size. Our study can help managers to design fire management plans according to vegetation characteristics that are found important in controlling burn severity and prioritize management locations based on the relative importance of vegetation and topography.     

Human-caused wildfire risk rating for prevention planning in Spain

This paper identifies human factors associated with high forest fire risk in Spain and analyses the spatial distribution of fire occurrence in the country. The spatial units were 6,066 municipalities of the Spanish peninsular territory and Balearic Islands. The study covered a 13-year series of fire occurrence data. One hundred and eight variables were generated and input to a dedicated Geographic Information System (GIS) to model different factors related to fire ignition. After exploratory analysis, 29 were selected to build a predictive model of human fire ignition using logistic regression analysis. The binary model estimated the probability of high or low occurrence of forest fires, as defined by an ignition danger index that is currently used by the Spanish forest service (number of fires divided by forest area in each municipality). Thirteen explanatory variables were identified by the model. They were related to agricultural landscape fragmentation, agricultural abandonment and development processes. The prediction agreement found between the model binary outputs and the historical fire data was 85.3% for the model building dataset (60% of municipalities). A slightly lower predictive power (76.2%) was found for the validation data (the remaining 40%). The probabilistic output of the logistic was significantly related to the raw ignition index (Spearman correlation of 0.710) used by the Spanish Forest Service. Therefore, the model can be considered a good predictor of human-caused fire risk, aiding spatial decisions related to prevention planning in Spanish municipalities.     

Locating Spatial Variation in the Association Between Wildland Fire Risk and Social Vulnerability Across Six Southern States

Wildland fire in the South commands considerable attention, given the expanding wildland urban interface (WUI) across the region. Much of this growth is propelled by higher income retirees and others desiring natural amenity residential settings. However, population growth in the WUI increases the likelihood of wildfire fire ignition caused by people, as humans account for 93% of all wildfires fires in the South. Coexisting with newly arrived, affluent WUI populations are working class, poor or otherwise socially vulnerable populations. The latter groups typically experience greater losses from environmental disasters such as wildfire because lower income residents are less likely to have established mitigation programs in place to help absorb loss. We use geographically weighted regression to examine spatial variation in the association between social vulnerability (SOVUL) and wildfire risk. In doing so, we identify “hot spots” or geographical clusters where SOVUL varies positively with wildfire risk across six Southern states—Alabama, Arkansas, Florida, Georgia, Mississippi, and South Carolina. These clusters may or may not be located in the WUI. These hot spots are most prevalent in South Carolina and Florida. Identification of these population clusters can aid wildfire managers in deciding which communities to prioritize for mitigation programming.     

Slash fire hazard analysis on the Siskiyou National Forest

Potential increase in fire hazard as a result of timber harvesting is a concern of forest managers throughout the United States. Treating fuels can help reduce unacceptable fire hazards. To evaluate alternative fuel treatments, managers need to know their effects on fire hazard. A decision analysis approach to estimating fire hazard in terms of expected burned area was applied to a watershed in the Siskiyou National Forest (Oregon). Three treatment alternatives (do nothing and two levels of yarding unmerchantable material) were evaluated, and the effects of the treatments were projected over a 90-yr period. Initially, the effects of applying a treatment are small. After 50 years of treatment, the most intense alternative can be expected to show almost a 50% reduction in burned area compared to no treatment. The procedure also estimates burned are by fire size and fire intensity classes. Managers may find this useful for estimating expected fire effects associated with a particular fuel treatment regime.     

Effects of anthropogenic fire history on savanna vegetation in northeastern Namibia

Anthropogenic fires in Africa are an ancient form of environmental disturbance, which probably have shaped the savanna vegetation more than any other human induced disturbance. Despite anthropogenic fires having played a significant role in savanna management by herders, previous ecological research did not incorporate the traditional knowledge of anthropogenic fire history. This paper integrates ecological data and anthropogenic fire history, as reconstructed by herders, to assess landscape and regional level vegetation change in northeastern Namibia. We investigated effects of fire frequency (i.e. <5, 5-10 and >10 years) to understand changes in vegetation cover, life form species richness and savanna conditions (defined as a ratio of shrub cover to herbaceous cover). Additionally, we analysed trends in the vegetation variables between different fire histories at the landscape and regional scales. Shrub cover was negatively correlated to herbaceous cover and herbaceous species richness. The findings showed that bush cover homogenisation at landscape and regional scales may suggest that the problem of bush encroachment was widespread. Frequent fires reduced shrub cover temporarily and promoted herbaceous cover. The effects on tree cover were less dramatic. The response to fire history was scale-independent for shrub, herbaceous and tree cover, but scale-dependent for the richness of grass and tree life forms. Fire history, and not grazing pressure, improved savanna conditions. The findings emphasise the need to assess effects of anthropogenic fires on vegetation change before introducing new fire management policies in savanna ecosystems of northeastern Namibia.     

Factors influencing fire behaviour in shrublands of different stand ages and the implications for using prescribed burning to reduce wildfire risk

Fire behaviour under experimental conditions is described in nine Mediterranean gorse shrublands ranging from 3-12 years of age with different fuel loads. Significant differences in the fire-line intensity, fuel load and rate of fire spread have been found to be related to the stage of development of the communities. Fire spread is correlated with fuel moisture using multiple regression techniques. Differences in fuel moisture between mature and young communities under moderate weather conditions have been found. The lower moisture content identified in the mature shrubland is due both to the decreasing moisture content of senescent shrubland in some species, mainly in live fractions of Ulex parviflorus Pour. fuel, and to a substantial increase in dead fuel fractions with low percentages of moisture content. The result is that the older the shrubland is, the greater will be the decrease in the total moisture content of the vegetation. In these moderate weather conditions, the fire intensity of the mature community was as high as the maximum intensity recommended for prescribed fires. This fact seems to indicate that, even under moderate conditions, prescribed burning as an alternative management tool in the mature shrubland must always take into account fuel control; on the other hand, this technique could be applied more easily when the shrubland is at an intermediate growth stage (4-5 years of age). Therefore, more frequent low-intensity prescribed fires are indicated to abate the risk of catastrophic fire.     

Integrating fire management into land-use planning: A multiple-use management research,development, and applications program

The traditional view of fire as a destructive agent requiring immediate suppression is giving way to the view that fire can and should be used to meet land management goals. Thus,fire control is being replaced by the more general concept offire management, which is based on the need to integrate fire policy with land management objectives. The social, economic, and ecologic effects of fire must be evaluated in the selection of land management alternatives.The activities of fire management organizations—fire prevention, control, and use of fire—must respond to needs of land management. Many agencies have developed fire organizations as separate entities that set their own objectives. The many land and resource managers who have recognized the need to incorporate fire considerations into land-use planning have so far lacked the techniques to do so.As a natural process, fire has an important function in forest and range ecosystems. Fire can greatly influence the quantity and quality of resource outputs; it is a two-edged sword that can either harm or benefit our goals, depending upon the complex effects of fire and the nature of our wants.The Fire in Multiple-Use Management Research, Development, and Applications (RD&A) Program was initiated by the U.S. Department of Agriculture, Forest Service, at the Northern Forest Fire Lab in Missoula to assist land managers. This profile explains what an RD&A program is; discusses its mission, goals, and approach to the problem; and tells why the approach involves federal laboratories, universities, and private research foundations.