Forest Fire Management Research Articles

Bromine enrichment in marsh sediments as a marker of environmental changes driven by Grand Solar Minima and anthropogenic activity (Caminha, NW of Portugal)

A sediment core collected in Caminha tidal marsh, NW Portugal, was used to assess bromine (Br) signal over the last ca. 1700years. The Br temporal variability reflects its close relationship with soil/sediment organic matter (OM) and also alterations in Br biogeochemical recycling in marsh environment. The highest Br enrichment in sediments was found during the Maunder Solar Minimum, a major solar event characterized by lower irradiance (TSI) and temperature, increased cloudiness and albedo. The obtained results suggest that those climate-induced changes weakened the natural mechanisms that promote Br biochemical transformations, driven by both living plants metabolism and plant litter degradation, with the ensuing generation of volatile methyl bromide (CH3Br). It seems that the prevailing climate conditions during the Maunder favoured the retention of more Br in marsh ecosystem, ultimately decreasing the biogenic Br emissions to the atmosphere. During the 20th century, the Br pattern in sediments appears to mirror likewise anthropogenic sources. The significant correlation (p<0.05) between Br/OM ratios and Pb contents in sediments after 1934 suggests a common source. This is most probably related with the rise, massive consumption and prohibition of leaded gasoline, where ethylene dibromide was added as lead scavenger to antiknock mixtures. More regionally, the concerted use of flame retardants on forest fire management, covering the 1980s through mid-1990s in the north of Portugal and Galicia, could be responsible for the observed increase of sediment Br (relatively to Pb) pool of this tidal marsh. Although man-made brominated compounds are being phased-out since the inception of the 1992 Montreal Protocol, the Caminha tidal marsh sedimentary record showed that Br levels only started to decline after 2002.

Dynamics of the multi-stakeholder forum and its effectiveness in promoting sustainable forest fire management practices in South Sumatra, Indonesia

To provide an effective institutional response to frequent forest fires, a multi-stakeholder approach was introduced in the province of South Sumatra, in Indonesia. This study examines in detail the structure, dynamics and effectiveness of a multi-stakeholder forum (MSF) at promoting sustainable forest fire management practices in Ogan Komering Ilir District of South Sumatra. Using factor analysis of multi-variate techniques, we examined those factors underlying the dynamics and effectiveness of the MSF. Four factors were found to contribute positively: (1) intra-forum coordination dynamics, (2) transparency in decision making, (3) collective learning quality, and (4) decentralization within the implementation process. The analysis in this study shows that an MSF can function effectively when these four factors are in place. The study recommends that in view of the persisting fire threat and its trans-boundary implications, the MSF, which was discontinued in 2007, should be reactivated in order to further utilize its already established and proven coordination capacity.

Professionals' perspectives: exploring the occupational and organizational psychology of community-agency interactions in forest fire management

Researchers exploring the challenges of public intolerance for forest fires in the US predominantly focus on nonmanagers. Forest fire managers have unique perspectives on public perceptions and attitudes towards forest firesbecausemanagersfrequentlyinteractdirectlywiththepublicandarethefaceoftheinstitutionsthatprescribe fire management practicestowhich the public reacts. Therefore, managers’ perspectives deserve more empirical attention. Additionally, a recent review of social science research on wildfire management suggested a need for better understanding of the organizational dimensions of forest fire management. For this study, interviews were used to explore how fire management professionals understand and explain public attitudes towards forest fires and smoke. Interviewees suggested that community‐forest dependence and community‐agency interactions shape public perceptions and attitudes. Interviewees elaborated on how professionals’ personality andperceivedorganizationalobstructionunderminecommunity‐agencyinteractions,provokeunfavourableattitudes towards the agency and fire management practices and ultimately, interfere with the accomplishment of fire management objectives. These findings suggest that, to better understand and more effectively manage public attitudes towards forest fires, we need to paydue attention to the occupational and organizational psychologyoffiremanagementprofessionalsandinstitutions.Organizationalambidexterity,theinwardlookingprocess necessary for organizational effectiveness, could enhance community‐agency relations, favourable attitudes towards forest fires and achievement of fire management objectives.

Operational perspective of remote sensing-based forest fire danger forecasting systems

Forest fire is a natural phenomenon in many ecosystems across the world. One of the most important components of forest fire management is the forecasting of fire danger conditions. Here, our aim was to critically analyse the following issues, (i) current operational forest fire danger forecasting systems and their limitations; (ii) remote sensing-based fire danger monitoring systems and usefulness in operational perspective; (iii) remote sensing-based fire danger forecasting systems and their functional implications; and (iv) synergy between operational forecasting systems and remote sensing-based methods. In general, the operational systems use point-based measurements of meteorological variables (e.g., temperature, wind speed and direction, relative humidity, precipitations, cloudiness, solar radiation, etc.) and generate danger maps upon employing interpolation techniques. Theoretically, it is possible to overcome the uncertainty associated with the interpolation techniques by using remote sensing data. During the last several decades, efforts were given to develop fire danger condition systems, which could be broadly classified into two major groups: fire danger monitoring and forecasting systems. Most of the monitoring systems focused on determining the danger during and/or after the period of image acquisition. A limited number of studies were conducted to forecast fire danger conditions, which could be adaptable. Synergy between the operational systems and remote sensing-based methods were investigated in the past but too much complex in nature. Thus, the elaborated understanding about these developments would be worthwhile to advance research in the area of fire danger in the context of making them operational.

Development of Standard Fuel Models in Boreal Forests of Northeast China through Calibration and Validation

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management.

English

Spatial information on the distribution of biomass is an important issue for monitoring and managing the environment. It is a prerequisite for successful forest fire management and for predicting fire intensity and fire behaviour, but estimates of biomass are time consuming and expensive and need to be done depending on size classes. We propose a method that takes into account the contemporary use of an allometric approach and remote sensed data from Very High Resolution (VHR) satellite images&nbsp; to obtain distribution maps of biomass subdivided into different components while keeping plant-destructive collection of data to a minimum. To test the feasibility of distributing biomass into classes, we subdivided biomass into two size classes according to the size of leaves (thickness) and branches (diameter). This is an approach that can be adapted to both fuel classes or to estimation of the ligneaous component. We haphazardly selected eight areas, within the Site of Community Importance &ldquo;Monteferrato e Monte Iavello&rdquo; (Italy), where easy-to-measure characteristics (height, diameter, cover) of vascular plants were collected. Regression equations between easy-to-measure vegetation characteristics and biomass values were derived to estimate the biomass of each area in the two size classes. Then, we evaluated the relationships between the normalized difference vegetation index (NDVI) and the estimated biomass values for each area using regression equations and size class. The equations that resulted from the regression analysis were used to create maps of biomass using NDVI map. Such a procedure allows the identification of features otherwise lost when the vegetation is represented only by vegetation class labels. This includes the orientation of vegetation lines which may favor the spread of fire in a given direction; information that may be useful for hazard management and prevention. &nbsp; Key words: Allometric equation, Pinus pinaster, Erica scoparia, biomass size class, Very High Resolution (VHR) satellite imagery.

黑龙江省温带森林火灾碳排放的计量估算研究

As global climate change continues to accelerate,the frequency and intensity of forest fires continue to grow.Forest fires,which play an important ecological role in forest ecosystems,have a very significant effect on carbon emissions and carbon sinks,and also play an important role in the carbon cycle. Although the impact of forest fires on carbon emissions has been analyzed in detail,studies that scientifically and accurately measure carbon and carbonaceous gas emissions from forest fires are lacking. Carbon dioxide( CO2) emissions from temperate forest fires are usually calculated based on Intergovernmental Panel on Climate Change guidelines( IPCC 1997) and only include direct effects of burning.Forest fires have been shown to release significant amounts of carbon into the atmosphere and play a significant role in theglobal carbon cycle and carbon balance. In this study,we estimated the level of emissions from forest fires for carbon and carbonaceous gases including CO2,carbon monoxide( CO),methane( CH4),and non-methane hydrocarbons( NMHC)from 1953 to 2012 in Heilongjiang Province,China. We used a geographic information system based modeling approach to simulate emissions using a two-step procedure. First,we calculated total carbon released from forest fires in Heilongjiang for selected years between 1953 and 2012 by merging and analyzing measurements of several parameters. Second,we calculated the amounts of four carbonaceous gases released during the burn,CO2,CO,CH4,and NMHC,using several different experimentally derived emission factors. The origin of each of the inputs used in our models was based on a combination of analysis of forest fire inventory,forest resources inventory,field research,and laboratory experiments.Direct total carbon emissions from forest fires in Heilongjiang during 1953—2012 were about 5. 88×107t,and mean annual carbon emissions were about 9. 80 ×105t per year,accounting for 8. 66% of the direct total carbon emissions from forest fires in China. Carbon emissions of four trace gases,CO2,CO,CH4and NMHC,from forest fires were 1. 89×108,1.06×107,6.33×105and 4. 43×105t,respectively; mean annual emissions of CO2,CO,CH4and NMHC were 3. 15×106,1.77×105,1.05×104and 7. 38×103t,respectively,accounting for 7. 74%,6. 52%,9. 42% and 6. 53% of the amounts of CO2,CO,CH4and NMHC released from forest fires in China,respectively,during that period. Our results indicate that combustion efficiency of coniferous broad-leaved mixed forest is lower than other forest types. The mean annual burned area for this type of forest accounts for 57. 54% of China's total burn area,while this area's fires account for only 38. 57% of carbon total emissions from forest fires. We propose the following forest fire management strategy. First,our studies show that the area's mean annual forest fire carbon emissions have an important impact on the regional carbon balance. So,we suggest strengthening the management of forest fuels( fine fuels,heavy fuels,etc.) as part of the regional forest fire management strategy. Fuels on the ground do not decompose easily in Heilongjiang's cold and dry temperate forests. Land managers should implement a reasonable prescribed burning plan designed to reduce the accumulation of combustible fuels.A policy for conducting periodic prescribed burning will reduce the incidence of forest fires. Prescribed burning should help land managers to control and limit the incidence and intensity of wildfires while allowing them to improve the condition of the ecosystem. Finally,we should give full consideration to the role of forest fires in maintaining the ecological balance of forest ecosystems.

Simulation analysis of the impact of ignitions, rekindles, and false alarms on forest fire suppression

Rekindles and false alarms are phenomena that have a significant presence in the Portuguese forest fire management system and an important impact on suppression resources in particular and fire management resources in general. In this paper, we propose a discrete-event simulation model of a forest fire suppression system designed to analyze the joint impact of ignitions, rekindles, and false alarms on the performance of the system. The model is applied to a case study of the district of Porto, Portugal, for the critical period of the forest fire season, between July and September 2010. We study the behavior of the system’s point of collapse, comparing the real base scenario with a benchmark scenario built with reference values for rekindles and false alarms, and also as a function of the number of fire incidents, considering historical variations. The results of the analysis are useful for operational decision-making and provide relevant information on the trade-off between prevention and suppression efforts.

Advances in remote sensing and GIS applications in support of forest fire management

Corresponding author. Email: jesus.san-miguel@jrc.ec.europa.euIntroductionIn recent years, the importance of wildfires as a natural or ahuman-inducedphenomenonhasgainedrecognitionnotonlyatlocal but also at regional and global levels. Improved remotesensing and computational capabilities enable the rapid pro-cessing of large image datasets in near-real time. As a result,remote sensing and geographic information systems arebecoming common tools for fire monitoring at local, regionaland global levels (San-Miguel-Ayanz

Directions on Forest Fire Prevention Policies through the Deduction of Priority Area for Forest Fire Management

Directions on Forest Fire Prevention Policies through the Deduction of Priority Area for Forest Fire Management

Visualization tools for assessing the Markov property: sojourn times in the forest Fire Weather Index in Ontario

AbstractIn Canada, the Fire Weather Index (FWI) provides forest fire managers with an overall measure of fire danger. Specifically, the FWI is a numerical rating of the potential intensity of a forest fire based on its potential spread rate and the amount of vegetation available for combustion. In our analyses, we consider daily FWI time series, recorded over 42 fire seasons from a sample of fire‐weather stations in Ontario, Canada. Graphical exploratory analyses of the data, including stalagmite plots (a new interactive, three‐dimensional visualization tool), show that the FWI switches between epochs of nil and non‐nil behaviour. This paper develops a framework for assessing sojourn times in these two phases. At some sites, the FWI process appears to begin each year as an approximate Markov process before gradually losing its Markovian character. However, a time‐homogeneous discrete time Markov chain model is insufficient overall, because those sojourn times are not found to be geometrically distributed. Instead, the duration of epochs in each of these phases can be more accurately modelled using beta‐geometric random variables which incorporate seasonality of phase‐specific run length behaviour using local likelihood methods. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Assessing possible shifts in wildfire regimes under a changing climate in mountainous landscapes

Climate change may affect the probability of extreme events such as wildfires. Although wildfires are some of the most important ecological processes in forest ecosystems, large-scale wildfires are often perceived as an environmental disaster. Since failure to include the dynamic nature of ecosystems in planning will inevitably lead to unexpected outcomes, we need to enhance our ability to cope with future extreme events coupled with climate change. This study presents several future scenarios in three different time periods for Canada’s Columbia Montane Cordillera Ecoprovince, which is prone to wildfires. These scenarios predict the probability of occurrence of widespread wildfires based on the hierarchical Bayesian model. The model was based on the relationships between wildfires and the Monthly Drought Code (MDC). The MDC is a generalized monthly version of the Daily Drought Code widely used across Canada by forest fire management agencies for monitoring of wildfire risk. To calculate future MDC values, we relied on different possible future conditions of climate, given by the Global Circulation Models. We found a regime shift in drought intensity with abrupt decreases in lightning-caused wildfire activity around 1940, suggesting that future wildfire risks can be inferred primarily from the summer drought code. For future periods, we found increasing trends in the probabilities of large-scale fires with time in most areas. It should be notable that, by the 2080s, there is a probability of some areas having more than 50% of large-scale wildfires under the “average” climatic conditions in the future, indicating that, even without “extreme” weather conditions, some ecosystems will have a fundamental probability of experiencing catastrophic fires under the condition of average summer. However, the rate of progression toward a fire-prone condition is quite different among the three climate change scenarios and among the region analyzed. Given such scenario-sensitive, spatially-heterogeneous patterns of wildfire probability in response to climate variability, management strategy should be flexible and more localized. By drawing on this knowledge, it may be possible to mitigate climate change impacts both before they arise and once they have occurred. These considerations are critical for maintaining the integrity of systems shaped by large-scale natural disturbances to increase their resilience to the changing climate while protecting human society and infrastructures. Working with alternative scenarios will facilitate our adaptation to climate change in managing fire-prone forest ecosystems.

Forest fire management to avoid unintended consequences: A case study of Portugal using system dynamics

Forest fires are a serious management challenge in many regions, complicating the appropriate allocation to suppression and prevention efforts. Using a System Dynamics (SD) model, this paper explores how interactions between physical and political systems in forest fire management impact the effectiveness of different allocations. A core issue is that apparently sound management can have unintended consequences. An instinctive management response to periods of worsening fire severity is to increase fire suppression capacity, an approach with immediate appeal as it directly treats the symptom of devastating fires and appeases the public. However, the SD analysis indicates that a policy emphasizing suppression can degrade the long-run effectiveness of forest fire management. By crowding out efforts to preventative fuel removal, it exacerbates fuel loads and leads to greater fires, which further balloon suppression budgets. The business management literature refers to this problem as the firefighting trap, wherein focus on fixing problems diverts attention from preventing them, and thus leads to inferior outcomes. The paper illustrates these phenomena through a case study of Portugal, showing that a balanced approach to suppression and prevention efforts can mitigate the self-reinforcing consequences of this trap, and better manage long-term fire damages. These insights can help policymakers and fire managers better appreciate the interconnected systems in which their authorities reside and the dynamics that may undermine seemingly rational management decisions.

Vulnerabilidade aos incêndios florestais: reflexões em torno de aspetos conceptuais e metodológicos

O paradigma físico tem sido dominante na gestão dos incêndios florestais, mas estes são um processo complexo resultante da interação entre as componentes ecológica e humana. Este artigo propõe uma reflexão sobre a polissemia com que os termos risco, perigo e vulnerabilidade têm sido utilizados na investigação sobre incêndios florestais e apresenta um modelo de avaliação da vulnerabilidade. É realçada a importância deste conceito para uma gestão mais eficaz do risco de incêndio florestal assim como são apresentados alguns desafios para a sua operacionalização.

산불감시카메라 가시권 분석 및 설치 적정대수 산정 (삼척시를 중심으로)

산불에 취약하고 피해를 많이 입었던 삼척시를 중심으로 행정구역별(읍 면 동) 기존 산불감시카메라에 대한 가시권과 효과성을 분석하였다. 그 결과 총 9개의 카메라 중 7번 카메라의 경우 카메라간의 거리가 가깝게 위치하고 있어 가시면적이 좁고, 카메라 간 중복성이 높은 것으로 나타났다. 따라서 본 연구를 통해 기존 설치된 산불감시카메라에 대한 가시권을 분석함으로써 효과성이 낮은 곳에 설치된 카메라는 잘 보이는 지역으로 이동 설치해야할 필요성을 제시하였다. 또한, 삼척시 산불감시카메라의 설치 적정대수를 산정한 바, 최소한 32대 이상은 되어야 가장 효율적인 산불감시체계가 가능할 것으로 분석되었다. This study suggested the proper number of the forest fire surveillance cameras. The visualities and effectiveness of surveillance cameras were analyzed according to basic administrative units in Samcheok City. First, we assessed the visual range and effectiveness of each surveillance camera. The results showed that visibility of the seventh surveillance camera was narrow and overlapped because of short distance from other camera. Consequently, The results of these analysis shows that the cameras which had a poor visual range located must be relocated in area where that had a high visual range. As new surveillance cameras are installed in this region, the location of these would have to be considered by these conditions; the overlapping of visibility with other cameras or other organizations, the adequacy of its location, etc. And over 32 surveillance camera would be need for the most effective monitoring in Samcheok City. These results would be utilized for improving an efficiency of surveillance camera and forest fire management techniques.

A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.

GENETIC ALGORITHM BASED SIMULATION–OPTIMIZATION FOR FIGHTING WILDFIRES

Wildfire is one of the most significant disturbances responsible for reshaping the terrain and changing the ecosystem of a particular region. Its detrimental effects on environment as well as human lives and properties, and growing trend in terms of frequency and intensity of wildfires over the last decade have necessitated the development of efficient forest fire management techniques. During the last three decades, Forest Fire Decision Support Systems (FFDSS) have been developed to help in the decision-making processes during forest fires by providing necessary information on fire detection, their status and behavior, and other aspects of forest fires. However, most of these decision support systems lack the capability of developing intelligent fire suppression strategies based upon current status and predicted behavior of forest fire. This paper presents an approach for development of efficient fireline building strategies via intelligent resource allocation. A Genetic Algorithm based approach has been proposed in this paper for resource allocation and optimum fireline building that minimizes the total damage due to wildland fires. The approach is based on a simulation–optimization technique in which the Genetic Algorithm uses advanced forest fire propagation models based upon Huygens principles for evaluation of cost index of its solutions. Both homogeneous and heterogeneous environmental conditions have been considered. Uncertainties in weather conditions as well as imperfect knowledge about exact vegetation and topographical conditions make exact prediction of wildfires very difficult. The paper incorporates Monte-Carlo simulations to develop robust strategies in uncertain conditions. Extensive simulations demonstrate the effectiveness of the proposed approach in efficient resource allocation for fighting complex wildfires in uncertain and dynamic conditions.

An integrated optimization model for fuel management and fire suppression preparedness planning

Fuel management and suppression preparedness planning are elements of forest fire management that are strongly interrelated with one another. Despite this interrelation, previous forest fire management optimization models have tended to consider these components in isolation from one another. Here we present an integer programming model that incorporates both fuel management and suppression preparedness decisions, thus providing an integrated planning framework. A series of hypothetical test landscapes are used to demonstrate the model’s functionality with easily interpretable results. A number of possible extensions to the model formulation are also discussed.

Modelling of Environment Vulnerability to Forests Fires and Assessment by GIS Application on the Forests of Djelfa (Algeria)

Risk management of forest fires starts from its assessment. This assessment has been subject of several research works and many models of fire risk have been developed. One of them has been developed by ourselves, for the Mediterranean areas. However environmental vulnerability to forest fires is an important part of risk; it represents, in fact, the exposed challenge to this scourge and therefore it worths particular attention by decision makers. Thus and due to the importance of socio-economic potential of forest and the negative influence of fire on this one, we propose in this work, a model for vulnerability assessment to forest fires based on the principle of the weighted sum. Application of the proposed model suggested to use of geomatics technologies to the spatialize level of vulnerability. Within this framework, a GIS was developed and applied to the forests of Djelfa in the Saharian Atlas, as originality, it will allow the understanding of the concept of vulnerability and risk associated the steppes area scale to reach a good space control.

Engineering of holonic multi agent intelligent forest fire monitoring system

In this paper we describe holonic multi agent architecture of iForestFire Intelligent Forest Fire Monitoring System through phases and activities of the holonic software engineering process. iForestFire is a web-based information system used in all aspects of forest fire management. Its central part is an artificial perception system, observer network, whose aim is early detection of forest fires. Although the agents that the system consists of are inseparably connected, they can be clustered in several independent systems that can be used separately. Independent holons are built from agents that are part of the observer network, as well as other agents with auxiliary functionalities.