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.     

Analysis of the prescribed burning practice in the pine forest of northwestern Portugal

The ignition of low-intensity fires in the dormant season in the pine stands of north-western Portugal seeks to reduce the existing fuel hazard without compromising site quality. The purpose of this study is to characterise this practice and assess its effectiveness, based on information resulting from the normal monitoring process at the management level, and using operational guidelines, fire behaviour models and a newly developed method to classify prescribed fire severity. Although the region's humid climate strongly constrains the activity of prescribed fire, 87% of the fires analysed were undertaken under acceptable meteorological and fuel moisture conditions. In fact, most operations achieved satisfactory results. On average, prescribed fire reduces by 96% the potential intensity of a wildfire occurring under extreme weather conditions, but 36% of the treated sites would still require heavy fire fighting resources to suppress such fire, and 17% would still carry it in the tree canopy. Only 10% of the prescribed burns have an excessive impact on trees or the forest floor, while 89% (normal fire weather) or 59% (extreme fire weather) comply with both ecological integrity maintenance and wildfire protection needs. Improved planning and monitoring procedures are recommended in order to overcome the current deficiencies.     

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.     

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.     

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.     

A Multidisciplinary Decision Support System for Forest Fire Crisis Management

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The systems architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.     

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.     

A heuristic expert system for forest fire guidance in Greece

Forests and forestlands are common inheritance for all Greeks and a piece of the national wealth that must be handed over to the next generations in the best possible condition. After 1974, Greece faces a severe forest fire problem and forest fire forecasting is the process that will enable the Greek ministry of Agriculture to reduce the destruction. This paper describes the basic design principles of an Expert System that performs forest fire forecasting (for the following fire season) and classification of the prefectures of Greece into forest fire risk zones. The Expert system handles uncertainty and uses heuristics in order to produce scenarios based on the presence or absence of various qualitative factors. The initial research focused on the construction of a mathematical model which attempted to describe the annual number of forest fires and burnt area in Greece based on historical data. However this has proven to be impossible using regression analysis and time series. A closer analysis of the fire data revealed that two qualitative factors dramatically affect the number of forest fires and the hectares of burnt areas annually. The first is political stability and national elections and the other is drought cycles. Heuristics were constructed that use political stability and drought cycles, to provide forest fire guidance. Fuzzy logic was applied to produce a fuzzy expected interval for each prefecture of Greece. A fuzzy expected interval is a narrow interval of values that best describes the situation in the country or a part of the country for a certain time period. A successful classification of the prefectures of Greece in forest fire risk zones was done by the system, by comparing the fuzzy expected intervals to each other. The system was tested for the years 1994 and 1995. The testing has clearly shown that the system can predict accurately, the number of forest fires for each prefecture for the following year. The average accuracy was as high as 85.25% for 1995 and 80.89% for 1994. This makes the Expert System a very important tool for forest fire prevention planning.     

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.     

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.     

Constructing and justifying risk and accountability after extreme events: public administration and stakeholders’ responses to a wildfire disaster

ABSTRACT

The impacts of extreme weather events, causing severe storms and wildfires, cascade across administrative borders within a country, challenging the steering capacity of governance networks at different political scales. This paper examines how accountability and risk were constructed and negotiated in the aftermath of Sweden’s largest wildfire. It draws on results from an interview study with executives of organizations and landowners involved, and an analysis of government reports about the wildfire’s cause and consequences. Although the fire was human-caused, public administrative bodies paid considerable attention to the local emergency services and their poor handling of the wildfire, caused by lack of knowledge of forest fire behavior. The study confirms many of the challenges associated with governance networks. It finds that issues about who to hold accountable, in what forum and for what issue are not fully addressed, being overwhelmed by demands for better knowledge of forest fire prevention and improved coordination and collaboration. To conclude, the paper calls for a better-informed public administration, forest sector and interrelated networks that take responsibility for their actions or lack thereof.     

The Impact of Land Use/Land Cover Changes on Land Degradation Dynamics: A Mediterranean Case Study

In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.     

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.     

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.     

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.     

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.