Forest Fuels Research Articles

Dispersal Limitation Dominates the Spatial Distribution of Forest Fuel Loads in Chongqing, China

The forest fuel load influences the spreading rate and fire intensity during a forest fire. However, the mechanism of environmental filtering and dispersal limitation that affects the spatial distribution of the forest fuel load remains unclear. In this study, live (tree, herbaceous, and shrub) and dead fuel loads (litter and humus) were estimated based on the plot investigation results of 4 typical stands ( Pinus massoniana , Platycladus orientalis , Ficus microcarpa , and Cinnamomum camphora ) in Chongqing, China. The results demonstrated that the tree, shrub, herbaceous, litter, and humus fuel loads of the 4 typical stands were 66.92 to 118.54 Mg/ha, 2.93 to 4.04 Mg/ha, 0.77 to 1.01 Mg/ha, 0.90 to 1.39 Mg/ha, and 1.49 to 1.98 Mg/ha, respectively. The forest fuel load varied significantly among the different stands. The Mantel test revealed that the forest fuel load had significantly positive correlations with the geospatial distance and stand environment but no significant correlation with the topographic factor. Additionally, the redundancy analysis demonstrated that the stand factors, canopy density and average canopy height, and the topographic factor, altitude, had significant impacts on the forest fuel load. The variance partitioning analysis revealed that the spatial heterogeneity of the forest fuel load was mainly attributed to the covariation of environmental and spatial factors (29.55%). Moreover, the geospatial distance was a dominant independent factor for the fuel distribution (14.66%), followed by the stand environment (9.51%) and topographic factor (0.35%). In summary, the spatial distribution of the forest fuel load was dependent on niche-based and random processes, and dispersal limitation was the dominant factor.

Simulation of variations in the speed of fire propagation, during a prescribed burn

Fire behavior simulations are generally based on standardized models of forest fuels, which can hardly represent allpossible variations in forest ecosystems, which can result in biased estimates of fire behavior. Due to this, in the presentwork a comparative analysis of simulations of fire behavior (propagation rate [m/min]) is made, during the course of aprescribed burning in favor of the slope, in a pine-oak forest stand from the state of Chihuahua. These simulations varied inrelation to: a) fuel models; b) fuel loads; and c) wind speed. The models tested were: 1) the one that resulted from amultiple regression (considering temperature, relative humidity and slope); 2) the fuel model M-8 and its variant M-8R(includes the values of fuel charges obtained in the field); and 3) the fuel model M-9 and its variant M-9R (includes thevalues of fuel charges obtained in the field). The equations of the trends defined by the correlation between the relativehumidity (%) and the speed of fire propagation (m/min) were generated. Although neither model was found to bestatistically significant, the best fit was defined with the regression equation:, which can be used in apractical way for a rough estimation of the rate of fire spread (RP). It is concluded that, in general, the selected modelswere not appropriate for simulating fire behavior during prescribed burning. This highlights the need to generate specificfuel models for the analyzed vegetation and its variations in density, structure and composition

Comparative analysis of fuel loads in the area affected by fire and without fire in Malinaltepec, Guerrero

Forest fires are one of the factors that contribute to climate change, among the components that form the fire triangle, fuel is theonly factor that can be manipulated. The objective of this work was to estimate the load of forest fuels in Mg ha-¹ in an area burnedin 2015 and another area without fire. For the evaluation of forest fuel, three sampling sites were established in each of the areas,the woody material was counted by delay time (1, 10, 100 and 1000 h) according to the technique of planar intersections; at the endof each line, litter (h) and mulch (m) were collected in 0.09 m². Tests were carried out to contrast the general fuel load and by typebetween ecosystems; Tukey's means comparison test was used to contrast the fuels in a given area, finally the woody material (ml),mulch (m) and litter (h) were correlated with the total load (ct), litter depth (ph) and mulch depth (ph) using Pearson correlationtests. The total fuel load was 53.10 Mg ha-¹ in the burned area, while the area without fire showed a load of 27.26 Mg ha-¹ withoutsignificant differences (p = 0.114). On the comparison of loads by delay time, the fuel of 1, 10 and 100 h showed a higher load inthe burned area, although it was not significant (p > 0.05); the analysis by component showed a higher litter load in the non-burnedarea with 12.90 Mg ha-¹ (p = 0.015) and the woody material was statistically higher in the burned area with 35.95 Mg ha-¹ (p =0.024). The correlation of variables showed an r = 0.95 between the woody material and the total load; followed by leaf litter andmulch (r = 0.80); on the contrary, the total load in the non-burned area showed a correlation with the mulch and leaf litter (r = 0.89and 0.83). The forest fire contributed to the reduction of litter and mulch but maximized the load of woody fuel.

A Semi-Empirical Retrieval Method of Above-Ground Live Forest Fuel Loads by Combining SAR and Optical Data

Forest fuel load is the key factor for fire risk assessment, firefighting, and carbon emissions estimation. Remote sensing technology has distinct advantages in fuel load estimation due to its sensitivity to biomass and adequate spatiotemporal observations for large scales. Many related works applied empirical methods with individual satellite observation data to estimate fuel load, which is highly conditioned on local data and limited by saturation problems. Here, we combined optical data (i.e., Landsat 7 ETM+) and spaceborne Synthetic Aperture Radar (SAR) data (i.e., ALOS PALSAR) in a proposed semi-empirical retrieval model to estimate above-ground live forest fuel loads (FLAGL). Specifically, optical data was introduced into water cloud model (WCM) to compensate for vegetation coverage information. For comparison, we also evaluated the performance of single spaceborne L-band SAR data (i.e., ALOS PALSAR) in fuel load estimation with common WCM. The above two comparison experiments were both validated by field measurements (i.e., BioSAR-2008) and leave-one-out cross-validation (LOOCV) method. WCM with single SAR data could achieve reasonable performance (R2 = 0.64 or higher and RMSEr = 35.3% or lower) but occurred an underestimation problem especially in dense forests. The proposed method performed better with R2 increased by 0.05–0.13 and RMSEr decreased by 5.8–12.9%. We also found that the underestimation problem (i.e., saturation problem) was alleviated even when vegetation coverage reached 65% or the total FLAGL reached about 183 Tons/ha. We demonstrated our FLAGL estimation method by validation in an open-access dataset in Sweden.

The Consequential Role of Aesthetics in Forest Fuels Reduction Propensities: Diverse Landowners’ Attitudes and Responses to Project Types, Risks, Costs, and Habitat Benefits

Private landowners in the southern Willamette Valley of Oregon, USA were surveyed. The survey queried probabilities of implementing specific fuels reduction projects in extensive areas of specific forest types on their property. The projects were described in relation to the beginning and target forest types, the actions required, costs, and long-term maintenance. Forest types were first rated for scenic beauty and informed levels of wildfire risk reduction, scarce habitat production, and associated property rights risks. Propensities to perform each fuels reduction project were then obtained. These were adversely affected by disbelief in heightened wildfire risks or climate change, higher project costs, feelings of hopeless vulnerability to wildfire, and low aesthetic affections for target forests. Propensities were enhanced by aesthetic affection for target forests, belief in the efficaciousness of fuels reduction, previous experience with wildfire evacuation, and higher incomes. All landowners favored thinning of young conifer forests, but some were averse to thinning of mature conifer forests. Anthropocentric landowners, mainly farmers, foresters, and some small holders, tended to favor conventional thinnings toward commercially valuable conifer forests and avoided long-term habitat maintenance. Nature-centric landowners, mainly some rural residents and wealthy estate owners, leaned more toward long term habitat goals and oak forests.

Mapping Homogeneous Response Areas for Forest Fuel Management Using Geospatial Data, K-Means, and Random Forest Classification

Accurate description of forest fuels is necessary for developing appropriate fire management strategies aimed at reducing fire risk. Although field surveys provide accurate measurements of forest fuel load estimations, they are time consuming, expensive, and may fail to capture the inherent spatial heterogeneity of forest fuels. Previous efforts were carried out to solve this issue by estimating homogeneous response areas (HRAs), representing a promising alternative. However, previous methods suffer from a high degree of subjectivity and are difficult to validate. This paper presents a method, which allows eliminating subjectivity in estimating HRAs spatial distribution, using artificial intelligence machine learning techniques. The proposed method was developed in the natural protected area of “Sierra de Quila,” Jalisco, and was replicated in “Sierra de Álvarez,” San Luis Potosí and “Selva El Ocote,” Chiapas, Mexico, to prove its robustness. Input data encompassed a set of environmental variables including altitude, average annual precipitation, enhanced vegetation index, and forest canopy height. Four, three, and five HRAs with overall accuracy of 97.78%, 98.06%, and 98.92% were identified at “Sierra de Quila,” “Sierra de Álvarez,” and “Selva El Ocote,” respectively. Altitude and average annual precipitation were identified as the most explanatory variables in all locations, achieving a mean decrease in impurity values greater than 52.51% for altitude and up to 36.02% for average annual precipitation. HRAs showed statistically significant differences in all study sites according to the Kruskal–Wallis test (p-value < 0.05). Differences among groups were also significant based on the Wilcoxon–Mann–Whitney (p-value < 0.05) for all variables but EVI in “Selva El Ocote.” These results show the potential of our approach to objectively identify distinct homogeneous areas in terms of their fuel properties. This allows the adequate management of fire and forest fuels in decision-making processes.

Diffusion of indigenous fire management and carbon-credit programs: Opportunities and challenges for “scaling-up” to temperate ecosystems

Savanna burning programs across northern Australia generate millions of dollars per year for Indigenous communities through carbon and other greenhouse gas (GHG) markets. In catalyzing Indigenous knowledge and workforce to mitigate destructive wildfires, these programs are considered a success story on a range of social, ecological and economic measures. Scaling-up to temperate ecosystems requires a focus on applying the architecture and governance of these programs, and accounting for fundamental differences in context. We examine the opportunities and challenges in applying the architecture of savanna burning to an Indigenous Fire Management (IFM) program in central British Columbia, Canada (the Chilcotin). The Chilcotin project involves Yunesit’in and Xeni Gwet’in First Nations, and we draw from eight key elements of the Australian savanna burning model to identify a project area that includes Aboriginal title and reserve lands. The area encompasses Interior Douglas Fir (IDF) and Sub-Boreal Pine—Spruce (SBPS) biogeoclimatic zones, or dry forest and grassland ecosystems where low intensity fires are applied by community members to remove forest fuels, with the goal of mitigating wildfires and associated GHG emissions. The multi-decadal intervals between contemporary fires in the Chilcotin region make it challenging to accurately document historical fire location, scale and intensity, and thus to establish an emissions baseline. If this issue can be resolved, the British Columbia Forest Carbon Offset Protocol version 2 (FCOPv2) offers promise for developing verified carbon credits for three reasons: first, carbon (CO2), nitrous oxide (N2O), and methane (CH4), the three main GHG emissions from Indigenous fire management, are included in the protocol; second, credits under FCOPv2 are eligible for either compliance or voluntary markets, offering diversification; and third, a range of activities are eligible under the standard, including fire management and timber harvesting, which offers flexibility in terms of management practices. The Chilcotin project is likely to generate substantial co-benefits related to cultural, health and wellbeing, and livelihood values among First Nations participants. The Australian experience suggests that getting governance right, and building community ownership through “bottom-up” governance, is critical to the success of these programs. From the Australian model, community-based planning, like the Healthy Country Planning approach, can be a positive step to take, engaging community in goal setting for the program to guide and take ownership of its direction.

Classification of forest fuels in selected fire-prone ecosystems of Alberta, Canada—implications for crown fire behaviour prediction and fuel management

Key messageWe used clustering to construct fuel classes from fuel inventory data based on three stand attributes relevant to crown fire behaviour: surface fuel load (SFL), canopy base height (CBH) and canopy bulk density (CBD). Resulting fuel classes explained more of the stand-to-stand variability in predicted crown fire behaviour than fuel types of the Canadian Forest Fire Behaviour Prediction (FBP) System.ContextWildfire behaviour is partly determined by stand structure and composition. Fuel characterization is essential for predicting fire behaviour and managing vegetation. Currently, categorical fuel types based on associations with major forested or open vegetated landcovers are used nationally in Canada for fire research and management applications.AimTo provide an alternative description of selected forest fuels in Alberta, Canada, using direct classification in which fuel categories are constructed from data using analytical methods.MethodsFuel inventory data for 476 stands were used to construct fuel classes with clustering. Potential crown fire behaviour was modelled for resulting fuel class clusters (FCCs) and FCCs were compared with assigned FBP System fuel types. Tree-based modelling was used to identify stand characteristics most influential on FCC membership. Fuel treatment effects on FCC and modelled crown fire behaviour were explored for the FCC most susceptible to crown fire.ResultsFour FCCs were identified: Red (low SFL, low CBH, low CBD); Green (high SFL, low-moderate CBH, low CBD); Blue (low SFL, high CBH, low-moderate CBD); and Black (low SFL, moderate CBH, high CBD). Stand density of live conifers and FBP System fuel type were the most important variables influencing FCC membership; however, FCCs did not align directly with assigned FBP System fuel types. Fuel reduction treatments in the Black FCC were effective at shifting the stand to a less flammable FCC.ConclusionFCCs explained more of the stand-to-stand variability in predicted crown fire behaviour than assigned FBP System fuel types, which suggests FCCs could be used to improve fire behaviour predictions and aid fire managers in prioritizing areas for fuel treatments. Future technological and remote sensing advances could enable mapping FCCs across large regions.

Measurements from inside a Thunderstorm Driven by Wildfire: The 2019 FIREX-AQ Field Experiment

Abstract The 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field experiment obtained a diverse set of in situ and remotely sensed measurements before and during a pyrocumulonimbus (pyroCb) event over the Williams Flats fire in Washington State. This unique dataset confirms that pyroCb activity is an efficient vertical smoke transport pathway into the upper troposphere and lower stratosphere (UTLS). The magnitude of smoke plumes observed in the UTLS has increased significantly in recent years, following unprecedented wildfire and pyroCb activity observed worldwide. The FIREX-AQ pyroCb dataset is therefore extremely relevant to a broad community, providing the first measurements of fresh smoke exhaust in the upper troposphere, including from within active pyroCb cloud tops. High-resolution remote sensing reveals that three plume cores linked to localized fire fronts, burning primarily in dense forest fuels, contributed to four total pyroCb “pulses.” Rapid changes in fire geometry and spatial extent dramatically influenced the magnitude, behavior, and duration of pyroCb activity. Cloud probe measurements and weather radar identify the presence of large ice particles within the pyroCb and hydrometers below cloud base, indicating precipitation development. The resulting feedbacks suggest that vertical smoke transport efficiency was reduced slightly when compared with intense pyroCb events reaching the lower stratosphere. Physical and optical aerosol property measurements in pyroCb exhaust are compared with previous assumptions. A large suite of aerosol and gas-phase chemistry measurements sets a foundation for future studies aimed at understanding the composition of smoke plumes lifted by pyroconvection into the UTLS and their role in the climate system.

Emissions Released by Forest Fuel in the Daxing’an Mountains, China

The large amounts of emissions released by forest fires have a significant impact on the atmospheric environment, ecosystems, and human health. Revealing the main components of emissions released by forest fuel under different combustion states is of great importance to evaluate the impact of forest fires on the ecological environment. Here, a self-designed biomass combustion system was used to simulate the combustion of different parts (i.e., branch, trunk, and bark) of five tree species and branches, and three layers of surface dead fuel (i.e., litter layer, semi-humus layer, and humus layer) of three shrub species, in the Daxing’an Mountains, Inner Mongolia. The emission characteristics of the main gas pollutants (i.e., CO, CO2, HC, and NOx) and PM2.5 released under the two combustion states of smoldering and flaming, along with the correlation ratio among emission factors, were measured. The results show that the average amounts of emissions released by different trees and the three layers of surface dead fuel from a smoldering state are higher than those from the flaming state, while shrub combustion shows the opposite. The emissions released by trees, shrubs, and surface dead fuel from the flaming state are ordered from high to low as follows: CO2 > CO > HC > NOx > PM2.5; and from the smoldering state as CO2 > CO > HC > PM2.5 > NOx, indicating that the primary emissions under both conditions are mainly due to CO2, CO, and HC, while the emissions of NOx and PM2.5 are dependent on the combustion state—flaming promotes the emission of NOx, while smoldering promotes the emission of PM2.5. The average emissions of PM2.5 from the branches, bark, and trunks of Quercus mongolica are significantly higher than those of the other four tree species in the smoldering state, and the emissions of PM2.5 from the five tree species are ordered as follows: bark > branch > trunk. This study will help to further understand the impact of forest fires on the atmospheric environment and ecosystems in Northern China.

The dynamics of forest ground fires in the Saratov region

Forest fires are inevitable, as they have pyrological properties, which in turn are associated with weather conditions. Forest fire has a dynamics, i.e. the rate of its spreading under weather conditions and will continue until all available forest fuels are burn out or will extinguished. An important component of forecasting forest fire situations is the assessment of the dynamics of a forest fire, which makes it possible to assess the risk of its spread across the territory. The rate of spread of a forest fire is calculated from the ratio of the increment of area to time. Nevertheless, to obtain an accurate estimate, it is necessary to know the time of its occurrence, which is impossible in practical terms, since in case of careless handling of fire, they are usually not fixed for a while, and in case of deliberate arson, it is difficult to find and interrogate the arsonists. For solving this task, a mathematical model was created that makes it possible to calculate the average rate of development of a forest fire based on the rate of development of a fire (increase in the length of the edge of a forest fire over time) during its extinguishing, as well as the rate of extinguishing a fire. An assumption was made about the additive nature of the rate of increase in the length of the edge and the rate of quenching. Average rate of ground wild fire spread and the estimated time of its occurrence were calculated. The rate of spread of ground wild fire are compared with the data on the wind speed in the study area and the value of the complex indicator of fire danger. It was shown that forest fires spread only when the 3rd class of wild fire conditions is established according to weather, and the wind rate affects the dynamics of a ground wild fire only up to a 10 m s-1.

Airborne Emission Rate Measurements Validate Remote Sensing Observations and Emission Inventories of Western U.S. Wildfires.

Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r2 = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ-1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

Kinetic parameters and heat of reaction for forest fuels based on genetic algorithm optimization

Environmental issues and climate change are playing a central role in our society. Forest and peatland fires can prejudice the environment and population health. Therefore, it is vital to study this phenomenon. The main goal of this work is to determine the kinetic parameters and heat of reaction for different forest fuels. Pine needles and sphagnum peat are typical fuels from the Northern Hemisphere, while Amazonian leaves and high-density peat are from the Southern Hemisphere. The DTG curves for pine needles and Amazonian leaves clearly show two peaks of mass loss, while for sphagnum peat a third mass-loss peak occurs for higher temperatures. For high-density peat degradation, there is only one significant peak of mass loss, which happens at a higher temperature. Also, the DSC curves for pine needles, Amazonian leaves, and high-density peat show two exothermic peaks along with the mass-loss peaks. However, the overall pattern is not the same. The maximum heat released for pine needles and high-density peat occurs at the second degradation stage. There are two exothermic peaks of almost the same magnitude for Amazonian leaves. Finally, three exothermic peaks match the peaks of mass loss for sphagnum peat. DTG and DSC curves patterns for all forest fuels are independent of the heating rate and atmospheric composition. In this work, the proposed pseudo reaction mechanism for pyrolysis and oxidation of the forest fuels contains five (for Amazonian leaves, high-density peat, and sphagnum peat) and seven (for pine needle) steps. The genetic algorithm optimization process compares the instantaneous recorded data of TGA, DTG, and DSC with the calculated ones. The optimized kinetic reactions parameters for the forest fuels are the activation energy, the pre-exponential factor, the global order of reaction, the stoichiometric coefficients, and the heat of reaction. The overall performance of the proposed mechanism is evaluated taking the error or the experimental data into account. This set of reaction kinetics parameters allows for a suitable numerical model for forest fires. To the authors' knowledge, a comprehensive assessment of the above parameters, including the heat of reaction, for forest fuels is lacking.

Relationship between Forest Fuel Moisture Contents and Weather Factors During the Forest Fires Danger Season in Chuncheon, Gangwon

The amount of moisture contained in fallen leaves in the forest is closely related to the possibility of the ignition and spread of a forest fire. This moisture content is an important fundamental component of the forest fire danger rating system, as well as an essential parameter in forest fire management. This study examined the relationship between the moisture content of fuel in the forests and weather information obtained from HOBO data loggers installed in forests during the forest fire seasons of 2018 and 2020. The moisture content of the forest fuel was divided into two slopes (south and north), and the fallen leaves used were broad-leaved (Prunus serrulate and Quercus dentata) and coniferous (Pinus densiflora and Pinus koraiensis). The temperature (mean, minimum, and maximum) and relative humidity (mean and minimum) data obtained from the weather measuring devices installed in the forests were used to correlate weather factors with fuel moisture content. During the spring forest fire period, the temperature (mean, minimum, and maximum) and relative humidity (mean and minimum) of each slope and tree species were significant, while the average temperature and relative humidity were significant during the autumn. According to the correlations between the fuel moisture content and weather, factors with high significance were selected, and multiple regression analyses of the slope and species were found to be significant at 1 percent. The results of this study are expected to be used as primary data for calculating the fuel index of the forest fire forecasting system by accounting for the effects of weather factors on the moisture content of the fuel.

Sieving and Covering of Wood Chips Improves Storability

Minimising dry matter losses during storage of comminuted forest fuels is desirable from both an economic and a sustainability perspective. This study examined fuel quality and amount of recovered energy during the storage of forest wood chips stored at full industrial scale at three locations, and the effect of sieving and covering piles with a water-resistant, vapour-permeable fabric. Sieving wood chips before storage, that is, reducing the number of fines smaller than 8 mm, reduced the cumulative dry matter losses to <2%, while cumulative dry matter losses after storage for 4–6 months using current practices, that is, unsieved and uncovered, reached 10.6%. The combined effect of storage management led to a value loss of 11.5%, while both covering and sieving led to lower losses, with the combination of sieving and covering giving a 1.3% value increase, and thus, increased storability.

Determination of the fire hazard of forest plantations depending on surface fuels under laboratory combustion conditions using thermophysical parameters

The work aims to investigate experimentally the assessment of the combustion parameters of forest vegetation based on received ignition and combustion characteristics according to the presence of surface forest fuels (FF). The research was carried out using the laboratory test facility, which allowed simulating various types of combustion. Using the thermocouple method, as well as the heat flow sensor, made it possible to control the thermal characteristics. The maximum heat fluxes that are characteristic of FF fractions, such as oak bark, Salix acutifolia branches, and oak wood reached 49±3.5 kW/m2. Among grass species, the highest heat fluxes were recorded during the combustion of narrow-leaved bluegrass (47.4±3.21 kW/m2). The amount of stored energy directly depends on the material structure, density, and initial moisture content. It should be taken into account that the fire hazard of a forest area depends on pyrological properties, and especially on the moisture content of the dominant type of fuel bed.

Mathematical Simulation of Forest Fuel Pyrolysis and Crown Forest Fire Impact for Forest Fire Danger and Risk Assessment

In order to predict and assess the danger from crown forest fires, it is necessary to study the thermal degradation of different forest fuels in a high-temperature environment. In this paper, the main characteristics of pyrolysis accompanied by moisture evaporation in a foliage sample of angiosperms (birch) were investigated within conditions typical for a crown forest fire. The heat and mass transfer in the forest fuel element is described by the system of non-stationary non-linear heat conduction equations with corresponding initial and boundary conditions. The considered problem is solved within the framework of the three-dimensional statement by the finite difference method. The locally one-dimensional method was used to solve three-dimensional equations for heat conduction. The simple iteration method was applied to solve nonlinear effects caused by the forest fuel pyrolysis and moisture evaporation. The fourth kind of boundary conditions are applicable at the interface between the sub-areas. Software implementation of the mathematical model is performed in the high-level programming language Delphi in the RAD Studio software. The characteristic changes in the sample temperature field and the phase composition under high-temperature exposure from a forest fire are presented. The induction period of the thermal decomposition of dry organic matter in the sample was determined. Recommendations are made about key features of accounting for the pyrolysis and evaporation processes when predicting forest fire danger. The research results can be used in the development and improvement of systems for predicting forest fire danger and environmental consequences of the forest fires.

Innovative Action for Forest Fire Prevention in Kythira Island, Greece, through Mobilization and Cooperation of the Population: Methodology and Challenges

The island of Kythira in Greece suffered a major forest fire in 2017 that burned 8.91% of its total area and revealed many challenges regarding fire management. Following that, the Hellenic Society for the Protection of Nature joined forces with the Institute of Mediterranean and Forest Ecosystems in a project aiming to improve fire prevention there through mobilization and cooperation of the population. This paper describes the methodology and the results. The latter include an in-depth analysis of fire statistics for the island, development of a forest fuels map, and prevention planning for selected settlements based on fire modeling and on an assessment of the vulnerability of 610 structures, carried out with the contribution of groups of volunteers. Emphasis was placed on informing locals, including students, through talks and workshops, on how to prevent forest fires and prepare their homes and themselves for such an event, and on mobilizing them to carry out fuel management and forest rehabilitation work. In the final section of the paper, the challenges that the two partners faced and the project achievements and shortcomings are presented and discussed, leading to conclusions that can be useful for similar efforts in other places in Greece and elsewhere.

Scandinavian Forest Fire Activity Correlates with Proxies of the Baffin Bay Ice Cover

Understanding factors driving fire activity helps reveal the degree and geographical variability in the resilience of boreal vegetation to large scale climate forces. We studied the association between sea ice cover in the Baffin Bay and the Labrador Sea and observational records of forest fires in two Nordic countries (Norway and Sweden) over 1913–2017. We found a positive correlation between ice proxies and regional fire activity records suggesting that the Arctic climate and the associated changes in North Atlantic circulation exercise an important control on the levels of fire activity in Scandinavia. Changes in the sea cover are likely correlated with the dynamic of the North Atlantic Current. These dynamics may favor the development of the drought conditions in Scandinavia through promoting persistent high-pressure systems over the Scandinavian boreal zone during the spring and summer. These periods are, in turn, associated with an increased water deficit in forest fuels, leading to a regionally increased fire hazard. The Arctic climate will likely be an important future control of the boreal fire activity in the Nordic region.

Forest Fuel Drying, Pyrolysis and Ignition Processes during Forest Fire: A Review

Forest ecosystems perform several functions that are necessary for maintaining the integrity of the planet’s ecosystem. Forest fires are thus a significant danger to all living things. Forest fire fighting is a foreground task for modern society. Forest fire prediction is one of the most effective ways to solve this urgent issue. Modern prediction systems need to be developed in order to increase the quality of prediction; therefore, it is necessary to generalize knowledge about the processes occurring during a fire. This article discusses the key features of the processes prior to forest fuel ignition (drying and pyrolysis) and the ignition itself, as well as approaches to their experimental and mathematical modeling.