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.     

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 wildland-urban interfaces at large scales integrating housing density and vegetation aggregation for fire prevention in the South of France

Every year, more than 50,000 wildland fires affect about 500,000 ha of vegetation in southern European countries, particularly in wildland-urban interfaces (WUI). This paper presents a method to characterize and map WUIs at large scales and over large areas for wildland fire prevention in the South of France. Based on the combination of four types of building configuration and three classes of vegetation structure, 12 interface types were classified. Through spatial analysis, fire ignition density and burned area ratio were linked with the different types of WUI. Among WUI types, isolated WUIs with the lowest housing density represent the highest level of fire risk.     

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.     

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.     

Public Acceptance of Wildland Fire and Fuel Management: Panel Responses in Seven Locations

Wildland fire affects both public and private resources throughout the United States. A century of fire suppression has contributed to changing ecological conditions and accumulated fuel loads. Managers have used a variety of approaches to address these conditions and reduce the likelihood of wildland fires that may result in adverse ecological impacts and threaten communities. Public acceptance is a critical component of developing and implementing successful management programs. This study examines the factors that influence citizen support for agency fuel reduction treatments over time—particularly prescribed fire and mechanical vegetation removal. This paper presents findings from a longitudinal study examining resident beliefs and attitudes regarding fire management and fuels treatments in seven states: Arizona, Colorado, Oregon, Utah, Michigan, Minnesota, and Wisconsin. The study was implemented in two phases over a 6-year period using mail surveys to residents of communities adjacent to federal lands in each location. Questions replicated measures from the original project as well as some new items to allow a more in-depth analysis of key concepts. The study design enables comparisons over time as well as between locations. We also assess the factors that influence acceptance of both prescribed fire and mechanical vegetation removal. Findings demonstrate a relative stability of attitudes toward fuels management approaches over time and suggest that this acceptance is strongly influenced by confidence in resource managers and beliefs that the treatments would result in positive outcomes.     

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.     

Cluster analysis of structural stage classes to map wildland fuels in a Madrean ecosystem

Geospatial information technology is changing the nature of fire mapping science and management. Geographic information systems (GIS) and global positioning system technology coupled with remotely sensed data provide powerful tools for mapping, assessing, and understanding the complex spatial phenomena of wildland fuels and fire hazard. The effectiveness of these technologies for fire management still depends on good baseline fuels data since techniques have yet to be developed to directly interrogate understory fuels with remotely sensed data. We couple field data collections with GIS, remote sensing, and hierarchical clustering to characterize and map the variability of wildland fuels within and across vegetation types. One hundred fifty six fuel plots were sampled in eight vegetation types ranging in elevation from 1150 to 2600 m surrounding a Madrean 'sky island' mountain range in the southwestern US. Fuel plots within individual vegetation types were divided into classes representing various stages of structural development with unique fuel load characteristics using a hierarchical clustering method. Two Landsat satellite images were then classified into vegetation/fuel classes using a hybrid unsupervised/supervised approach. A back-classification accuracy assessment, which uses the same pixels to test as used to train the classifier, produced an overall Kappa of 50% for the vegetation/fuels map. The map with fuel classes within vegetation type collapsed into single classes was verified with an independent dataset, yielding an overall Kappa of 80%.     

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.     

Modeling the Landscape Drivers of Fire Recurrence in Sardinia (Italy)

Although recurrent fire events with very short return periods have the most dangerous effects on landscape degradation, only a few papers have explored the landscape ecological factors that drive the probability of fire recurrence. In this paper we apply a habitat suitability model for analyzing the spatial relationship between a selected set of landscape factors (mainly land use types) and fire recurrence in Sardinia (Italy) in the years 2005–2010. Our results point out that fire occurrence in already burned areas is lower than expected in natural and semi-natural land cover types, like forest and shrublands. To the contrary, like in all regions where human activity is the main source of fire ignitions, the probability of fire recurrence is higher at low altitudes and close to roads and to urban and agricultural land cover types, thus showing marked preference for those landscape factors denoting higher anthropogenic ignition risk.     

Creating Defensible Space in the Wildland–Urban Interface: The Influence of Values on Perceptions and Behavior

We examined the effect that value orientation to forests and wildland fire management has on an individual’s decision to create defensible space around his or her residence in the wildland–urban interface. Using data from a mail-back questionnaire, respondents in north central Minnesota were clustered by basic value–laden beliefs toward forest and wildland fire management and compared across a number of perceptions and behaviors related to creating defensible space around residences. Value orientation groups differed in attitudes, subjective norms, and perceived behavior control toward creating defensible space. In addition, relative effects of these perceptions on intention to create defensible space differed across groups. Implications lie in (a) understanding differences in motivations and reasons for support of strategies for managing fires near the wildland–urban interface, (b) developing information designed to address the perspectives of different groups related to creating defensible space, and (c) contributing to an improved integration of land management and public concerns and interests.     

Neighborhood effects in bird distributions,Navarre, Spain

This study examines the role of neighborhood effects in the spatial distributions of selected bird species in Navarre, Spain. We employed a geographic information system (GIS) to organize the data on bird distributions and relevant environmental variables and to analyze their spatial patterns. Three bird species were selected for analysis: the European honey-buzzard (Pernis apivorus), the Eurasian hobby (Falco subbuteo), and the European pied flycatcher (Ficedula hypoleuca). Selected environmental variables of the study area were digitized to create a comprehensive data base and logistic regression models were used to evaluate the significance of each variable in the spatial distribution. The spatial patterns of bird distributions were used to extract topological relationships and to identify neighborhood effects. Although all the selected species illustrate a pattern of positive spatial autocorrelation in their distributions, the significance of neighborhood effects varies from species to species. Among the selected species, neighborhood effects are most evident in the distribution of the European pied flycatcher and are significant for the Eurasian hobby. The distribution of the European honey-buzzard is not much affected by neighborhood effects. The results suggest that examination of neighborhood effects is a prerequisite for modeling bird distributions.     

100-years of Australian bushfire property losses: Is the risk significant and is it increasing?

This study examines the bushfire (wildland fire) risk to the built environment in Australia. The most salient result is that the annual probability of building destruction has remained almost constant over the last century despite large demographic and social changes as well as improvements in fire fighting technique and resources. Most historical losses have taken place in a few extreme fires which if repeated are likely to overwhelm even the most professional of fire services. We also calculate the average annual probability of a random home on the urban–bushland interface being destroyed by a bushfire to be of the order of 1 in 6500, a factor 6.5 times lower than the ignition probability of a structural house fire. Thus on average and if this risk was perceived rationally, the incentive for individual homeowners to mitigate and reduce the bushfire danger even further is low. This being the case and despite predictions of an increasing likelihood of conditions favouring bushfires under global climate change, we suspect that building losses due to bushfires are unlikely to alter materially in the near future.     

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.     

Soil carbon and nitrogen storage in response to fire in a temperate mixed-grass savanna

Vegetation fires may alter the quantity and quality of organic matter inputs to soil, rates of organic matter decay, and environmental factors that influence those processes. However, few studies have evaluated the impacts of this land management technique on soil organic carbon (SOC) and total N in grasslands and savannas. We evaluated the impact of repeated fires and their season of occurrence on SOC and total N storage in a temperate mixed-grass-mesquite savanna where fire is used to control woody plant encroachment. Four fire treatments varying in season of occurrence were examined: summer only (SF), winter only (WF), alternate summer and winter fires (SWF), and unburned controls. In each treatment, soils were sampled to 1 m under three vegetation types: C3 grasses, C4 grasses, and mesquite trees. The SOC storage at 0 to 20 cm was significantly greater in SF (2693 g C m(-2)) and SWF (2708 g C m(-2)) compared to WF (2446 g C m(-2)) and controls (2445 g C m(-2)). The SWF treatment also increased soil total N (271 g N m(-2)) relative to all other treatments (228-244 g N m(-2)) at 0 to 20 cm. Fire had no effect on SOC or total N at depths of > 20 cm. Vegetation type had no significant influence on SOC or total N stocks. The delta13C value of SOC was not affected by fire, but increased from -21 per thousand at 0 to 10 cm to -15 per thousand at depths of > 20 cm indicating that all treatments were once dominated by C4 grasses before woody plant encroachment during the past century. These results have implications for scientists, land managers, and policymakers who are now evaluating the potential for land uses to alter ecosystem C storage and influence atmospheric CO2 concentrations and global climate.     

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.     

Investing in rangeland restoration in the Arid West,USA: Countering the effects of an invasive weed on the long-term fire cycle

In large areas of the arid western United States, much of which are federally managed, fire frequencies and associated management costs are escalating as flammable, invasive cheatgrass (Bromus tectorum) increases its stronghold. Cheatgrass invasion and the subsequent increase in fire frequency result in the loss of native vegetation, less predictable forage availability for livestock and wildlife, and increased costs and risk associated with firefighting. Revegetation following fire on land that is partially invaded by cheatgrass can reduce both the dominance of cheatgrass and its associated high fire rate. Thus restoration can be viewed as an investment in fire-prevention and, if native seed is used, an investment in maintaining native vegetation on the landscape. Here we develop and employ a Markov model of vegetation dynamics for the sagebrush steppe ecosystem to predict vegetation change and management costs under different intensities and types of post-fire revegetation. We use the results to estimate the minimum total cost curves for maintaining native vegetation on the landscape and for preventing cheatgrass dominance. Our results show that across a variety of model parameter possibilities, increased investment in post-fire revegetation reduces long-term fire management costs by more than enough to offset the costs of revegetation. These results support that a policy of intensive post-fire revegetation will reduce long-term management costs for this ecosystem, in addition to providing environmental benefits. This information may help justify costs associated with revegetation and raise the priority of restoration in federal land budgets.     

Modelling the Ecological Vulnerability to Forest Fires in Mediterranean Ecosystems Using Geographic Information Technologies

Forest fires represent a major driver of change at the ecosystem and landscape levels in the Mediterranean region. Environmental features and vegetation are key factors to estimate the ecological vulnerability to fire; defined as the degree to which an ecosystem is susceptible to, and unable to cope with, adverse effects of fire (provided a fire occurs). Given the predicted climatic changes for the region, it is urgent to validate spatially explicit tools for assessing this vulnerability in order to support the design of new fire prevention and restoration strategies. This work presents an innovative GIS-based modelling approach to evaluate the ecological vulnerability to fire of an ecosystem, considering its main components (soil and vegetation) and different time scales. The evaluation was structured in three stages: short-term (focussed on soil degradation risk), medium-term (focussed on changes in vegetation), and coupling of the short- and medium-term vulnerabilities. The model was implemented in two regions: Aragón (inland North-eastern Spain) and Valencia (eastern Spain). Maps of the ecological vulnerability to fire were produced at a regional scale. We partially validated the model in a study site combining two complementary approaches that focused on testing the adequacy of model’s predictions in three ecosystems, all very common in fire-prone landscapes of eastern Spain: two shrublands and a pine forest. Both approaches were based on the comparison of model’s predictions with values of NDVI (Normalized Difference Vegetation Index), which is considered a good proxy for green biomass. Both methods showed that the model’s performance is satisfactory when applied to the three selected vegetation types.     

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.