Research highlights—Feedbacks between fire severity, vegetation structure and ecosystem flammability are understudied in highly fire-tolerant forests that are dominated by epicormic resprouters. We examined the relationships between the severity of two overlapping fires in a resprouting eucalypt forest and the subsequent effect of fire severity on fuel structure. We found that the likelihood of a canopy fire was the highest in areas that had previously been exposed to a high level of canopy scorch or consumption. Fuel structure was sensitive to the time since the previous canopy fire, but not the number of canopy fires. Background and Objectives—Feedbacks between fire and vegetation may constrain or amplify the effect of climate change on future wildfire behaviour. Such feedbacks have been poorly studied in forests dominated by highly fire-tolerant epicormic resprouters. Here, we conducted a case study based on two overlapping fires within a eucalypt forest that was dominated by epicormic resprouters to examine (1) whether past wildfire severity affects future wildfire severity, and (2) how combinations of understorey fire and canopy fire within reburnt areas affect fuel properties. Materials and Methods—The study focused on ≈77,000 ha of forest in south-eastern Australia that was burnt by a wildfire in 2007 and reburnt in 2013. The study system was dominated by eucalyptus trees that can resprout epicormically following fires that substantially scorch or consume foliage in the canopy layer. We used satellite-derived mapping to assess whether the severity of the 2013 fire was affected by the severity of the 2007 fire. Five levels of fire severity were considered (lowest to highest): unburnt, low canopy scorch, moderate canopy scorch, high canopy scorch and canopy consumption. Field surveys were then used to assess whether combinations of understorey fire (<80% canopy scorch) and canopy fire (>90% canopy consumption) recorded over the 2007 and 2013 fires caused differences in fuel structure. Results—Reburn severity was influenced by antecedent fire severity under severe fire weather, with the likelihood of canopy-consuming fire increasing with increasing antecedent fire severity up to those classes causing a high degree of canopy disturbance (i.e., high canopy scorch or canopy consumption). The increased occurrence of canopy-consuming fire largely came at the expense of the moderate and high canopy scorch classes, suggesting that there was a shift from crown scorch to crown consumption. Antecedent fire severity had little effect on the severity patterns of the 2013 fire under nonsevere fire weather. Areas affected by canopy fire in 2007 and/or 2013 had greater vertical connectivity of fuels than sites that were reburnt by understorey fires, though we found no evidence that repeated canopy fires were having compounding effects on fuel structure. Conclusions—Our case study suggests that exposure to canopy-defoliating fires has the potential to increase the severity of subsequent fires in resprouting eucalypt forests in the short term. We propose that the increased vertical connectivity of fuels caused by resprouting and seedling recruitment were responsible for the elevated fire severity. The effect of antecedent fire severity on reburn severity will likely be constrained by a range of factors, such as fire weather. Full article

Forest fire risk has increased globally during the previous decades. The Mediterranean region is traditionally the most at risk in Europe, but continental countries like Serbia have experienced significant economic and ecological losses due to forest fires. To prevent damage to forests and infrastructure, alongside other societal losses, it is necessary to create an effective protection system against fire, which minimizes the harmful effects. Forest fire probability mapping, as one of the basic tools in risk management, allows the allocation of resources for fire suppression, within a fire season, from zones with a lower risk to those under higher threat. Logistic regression (LR) has been used as a standard procedure in forest fire probability mapping, but in the last decade, machine learning methods such as fandom forest (RF) have become more frequent. The main goals in this study were to (i) determine the main explanatory variables for forest fire occurrence for both models, LR and RF, and (ii) map the probability of forest fire occurrence in Eastern Serbia based on LR and RF. The most important variable was drought code, followed by different anthropogenic features depending on the type of the model. The RF models demonstrated better overall predictive ability than LR models. The map produced may increase firefighting efficiency due to the early detection of forest fire and enable resources to be allocated in the eastern part of Serbia, which covers more than one-third of the country’s area. Full article

This work introduces a methodology for assessing near-future fire weather pattern changes based on the Canadian Fire Weather Index system components (Fire Weather Index (FWI), Initial Spread Index (ISI), Fire Severity Rating (FSR)), applied in touristic areas in Greece. Four series of daily raster-based datasets for the fire seasons (May–October), concerning a historic (2006 to 2015) and a future climatology period (2036–2045), were created for the areas under consideration, based on high-resolution climate modelling with the Representative Concentration Pathway (RCP), PCR 4.5 and RCP 8.5 scenarios. The climate model data were obtained from the European Coordinated Downscaling Experiment (EURO-CORDEX) climate database and consisted of atmospheric variables as required by the FWI system, at 12.5 km spatial resolution. The final datasets of the abovementioned variables used for the study were processed at 5 km spatial resolution for the domain of interest after applying regridding based on the nearest neighbour interpolating process. Geographic Information Systems (GIS) spatial operations, including spatial statistics and zonal analyses, were applied on the series of the derived daily raster maps in order to provide a number of output thematic layers. Moreover, historic FWI percentile values, which were estimated for Greece in the frame of a past research study of the Environmental Research Laboratory (EREL), were used as reference data for further evaluation of future fire weather changes. The straightforward methodology for the assessment of the evolution of spatial and temporal distribution of Fire weather Danger due to climate change presented herewith is an essential tool for enhancing the knowledge for the decision support process for forest fire prevention, planning and management policies in areas where the fire risk both in terms of fire hazard likelihood and expected impact is quite important due to human presence and cultural prestige, such as archaeological and tourist protected areas. Full article

Research Highlights: Pre-programmed cell death in old Aleppo pine needles leads to low moisture contents in the forest canopy in July, the time when fire activity nears its peak in the Western Mediterranean Basin. Here, we show, for the first time, that such needle senescence may increase fire behavior and thus is a potential mechanism explaining why the bulk of the annual burned area in the region occurs in early summer. Background and Objectives: The brunt of the fire season in the Western Mediterranean Basin occurs at the beginning of July, when live fuel moisture content is near its maximum. Here, we test whether a potential explanation to this conundrum lies in Aleppo pine needle senescence, a result of pre-programmed cell death in 3-years-old needles, which typically occurs in the weeks preceding the peak in the burned area. Our objective was to simulate the effects of needle senescence on fire behavior. Materials and Methods: We simulated the effects of needle senescence on canopy moisture and structure. Fire behavior was simulated across different phenological scenarios and for two highly contrasting Aleppo pine stand structures, a forest, and a shrubland. Wildfire behavior simulations were done with BehavePlus6 across a wide range of wind speeds and of dead fine surface fuel moistures. Results: The transition from surface to passive crown fire occurred at lower wind speeds under simulated needle senescence in the forest and in the shrubland. Transitions to active crown fire only occurred in the shrubland under needle senescence. Maximum fire intensity and severity were always recorded in the needle senescence scenario. Conclusions: Aleppo pine needle senescence may enhance the probability of crown fire development at the onset of the fire season, and it could partly explain the concentration of fire activity in early July in the Western Mediterranean Basin. Full article

This study analyzed fire weather and fire regimes in Central Asia from 2001–2015 and projected the impacts of climate change on fire weather in the 2030s (2021–2050) and 2080s (2071–2099), which would be helpful for improving wildfire management and adapting to future climate change in the region. The study area included five countries: Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan. The study area could be divided into four subregions based on vegetation type: shrub (R1), grassland (R2), mountain forest (R3), and rare vegetation area (R4). We used the modified Nesterov index (MNI) to indicate the fire weather of the region. The fire season for each vegetation zone was determined with the daily MNI and burned areas. We used the HadGEM2-ES global climate model with four scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) to project the future weather and fire weather of Central Asia. The results showed that the fire season for shrub areas (R1) was from 1 April to 30 November, for grassland (R2) was from 1 March to 30 November, and for mountain forest (R3) was from 1 April to 30 October. The daily burned areas of R1 and R2 mainly occurred in the period from June–August, while that of R3 mainly occurred in the April–June and August–October periods. Compared with the baseline (1971–2000), the mean daily maximum temperature and precipitation, in the fire seasons of study area, will increase by 14%–23% and 7%–15% in the 2030s, and 21%–37% and 11%–21% in the 2080s, respectively. The mean MNI will increase by 33%–68% in the 2030s and 63%–146% in the 2080s. The potential burned areas of will increase by 2%–8% in the 2030s and 3%–13% in the 2080s. Wildfire management needs to improve to adapt to increasing fire danger in the future. Full article

Research highlights: Moisture diffusion coefficients for stems and branches of degenerated Calluna vulgaris L. have been obtained and a mathematical model for the drying process has been developed and validated as an input to future fire danger modeling. Background and objectives: In Norway, several recent wildland–urban interface (WUI) fires have been attributed to climate changes and accumulation of elevated live and dead biomass in degenerated Calluna stands due to changes in agricultural activities, i.e., in particular abandonment of prescribed burning for sheep grazing. Prescribed burning is now being reintroduced in these currently fire prone landscapes. While available wildfire danger rating models fail to predict the rapidly changing fire hazard in such heathlands, there is an increasing need for an adapted fire danger model. The present study aims at determining water diffusion coefficients and develops a numerical model for the drying process, paving the road for future fire danger forecasts and prediction of safe and efficient conditions for prescribed burning. Materials and methods: Test specimens (3–6 mm diameter) of dead Calluna stems and branches were rain wetted 48 h and subsequently placed in a climate chamber at 20 °C and 50% relative humidity for mass loss recordings during natural convection drying. Based on the diameter and recorded mass versus time, diffusion coefficients were obtained. A numerical model was developed and verified against recoded mass loss. Results: Diffusion coefficients were obtained in the range 1.66–10.4 × 10⁻¹¹ m²/s. This is quite low and may be explained by the very hard Calluna “wood”. The large span may be explained by different growth conditions, insect attacks and a varying number of years of exposure to the elements after dying. The mathematical model described the drying process well for the specimens with known diffusion coefficient. Conclusions: The established range of diffusion coefficients and the developed model may likely be extended for forecasting moisture content of degenerated Calluna as a proxy for fire danger and/or conditions for efficient and safe prescribed burning. This may help mitigate the emerging fire risk associated with degenerated Calluna stands in a changing climate. Full article

To explore the possible relationship between diseased trees and wildfires, we assessed the flammability of canker-resistant and susceptible common cypress clones that were artificially infected with Seiridium cardinale compared to healthy trees. This study explored the effect of terpenoids produced by the host plant in response to infection and the presence of dead plant portions on flammability. Terpenoids were extracted and quantified in foliage and bark samples by gas chromatography–mass spectrometry (GC–MS). A Mass Loss Calorimeter was used to determine the main flammability descriptors. The concentration of terpenoids in bark and leaf samples and the flammability parameters were compared using a generalized linear mixed models (GLMM) model. A partial least square (PLS) model was generated to predict flammability based on the content of terpenoid, clone response to bark canker and the disease status of the plants. The total terpenoid content drastically increased in the bark of both cypress clones after infection, with a greater (7-fold) increase observed in the resistant clone. On the contrary, levels of terpenoids in leaves did not alter after infection. The GLMM model showed that after infection, plants of the susceptible clone appeared to be much more flammable in comparison to those of resistant clones, showing higher ignitability, combustibility, sustainability and consumability. This was mainly due to the presence of dried crown parts in the susceptible clone. The resistant clone showed a slightly higher ignitability after infection, while the other flammability parameters did not change. The PLS model (R²Y = 56%) supported these findings, indicating that dead crown parts and fuel moisture content accounted for most of the variation in flammability parameters and greatly prevailed on terpenoid accumulation after infection. The results of this study suggest that a disease can increase the flammability of trees. The deployment of canker-resistant cypress clones can reduce the flammability of cypress plantations in Mediterranean areas affected by bark canker. Epidemiological data of diseased tree distribution can be an important factor in the prediction of fire risk. Full article

Reasonable forest fire management measures can effectively reduce the losses caused by forest fires and forest fire driving factors and their impacts are important aspects that should be considered in forest fire management. We used the random forest model and MODIS Global Fire Atlas dataset (2010~2016) to analyse the impacts of climate, topographic, vegetation and socioeconomic variables on forest fire occurrence in six geographical regions in China. The results show clear regional differences in the forest fire driving factors and their impacts in China. Climate variables are the forest fire driving factors in all regions of China, vegetation variable is the forest fire driving factor in all other regions except the Northwest region and topographic variables and socioeconomic variables are only the driving factors of forest fires in a few regions (Northwest and Southwest regions). The model predictive capability is good: the AUC values are between 0.830 and 0.975, and the prediction accuracy is between 70.0% and 91.4%. High fire hazard areas are concentrated in the Northeast region, Southwest region and East China region. This research will aid in providing a national-scale understanding of forest fire driving factors and fire hazard distribution in China and help policymakers to design fire management strategies to reduce potential fire hazards. Full article

The occurrence and behavior of forest fires are mainly affected by litter moisture content, which is very important for fire risk forecasting. Errors in models of litter moisture content prediction mainly stem from the neglect of diurnal variation. Consequently, it is essential to determine the diurnal variation of litter moisture content and establish a high-precision prediction model. In this study, the moisture contents of litters of Mongolian oak (Quercus mongolica) and Korean pine (Pinus koraiensis) were monitored at 1 h time steps to obtain the diurnal variations of moisture content, and two direct estimation (Nelson and Simard) methods as well as one meteorological factor regression method were selected to establish prediction models at 1 h time steps. The moisture contents of the two litter types showed obvious diurnal variation, and the changes were significantly correlated with the air temperature and relative humidity. The wind speed had no significant effect on the change within 1 h. The mean absolute error (MAE) values of the three prediction models of Mongolian oak were 1.02%, 1.03%, and 1.46%, and those of Korean pine were 0.50%, 0.50%, and 1.95%, respectively. Similarly, the mean relative error (MRE) values of the three prediction models of oak litter were 4.76%, 4.73%, and 6.65%, and those of pine were 3.53%, 3.59%, and 13.26%, respectively. These results indicated that the accuracy of the Nelson and Simard methods was similar, and both met the requirements for the forecasting of forest fire risk. Therefore, the direct estimation method was selected to predict the moisture contents of two litter types in this area. Full article

Understanding of the characteristics of water-soluble inorganic ions (WSI) in fine particulate matter (PM_2.5) emitted during forest fires has paramount importance due to their potential effect on ecosystem acidification. Thus, we investigated the emission factors (EFs) of ten most common WSI from combustion of leaves and branches of ten dominant tree species in Chinese boreal and sub-tropical forests under smoldering and flaming combustion stages using a self-designed combustion unit. The results showed that EF of PM_2.5 was three times higher for the boreal (6.83 ± 0.67 g/kg) than the subtropical forest (1.97 ± 0.34 g/kg), and coniferous species emitted 1.5 times more PM_2.5 (5.35 ± 0.64 g/kg) than broadleaved species (3.45 ± 0.37 g/kg). EF of total WSI was 1.27 ± 0.08 g/kg for the boreal and 1.08 ± 0.07 g/kg for the subtropical forest and 1.28 ± 0.09 and 1.07 ± 0.06 g/kg for broadleaved and coniferous species, respectively. Individual ionic species also varied significantly between forest types and species within forest types, and K⁺ and Cl⁻ were the dominant ionic species in PM_2.5, accounting for 25% and 30% for the boreal forest and 23% and 27% for the subtropical forest, respectively. Emissions of NO₂⁻ and SO₄²⁻ were the lowest, accounting for 3% and 5% for the boreal forest and 4% for each of the subtropical forests, respectively. Combustion of leaves emitted significantly more ionic species (1.29 ± 0.05g/kg) than branches (1.05 ± 0.07 g/kg), and smoldering consistently emitted more ionic species (1.49 ± 0.09 g/kg) than flaming combustion (0.88 ± 0.03 g/kg). The cation to anion ratio was ≥1.0, suggesting that the particulate matter is neutral to alkalescent. As a whole, our findings demonstrate that forest fire in these regions may not contribute to ecosystem acidification despite the emission of a considerable amount of WSI during forest fires. Full article

Previous studies have shown that Live Fuel Moisture Content (LFMC) is a crucial driver affecting wildfire occurrence worldwide, but the effect of LFMC in driving wildfire occurrence still remains unexplored over the southwest China ecosystem, an area historically vulnerable to wildfires. To this end, we took 10-years of LFMC dynamics retrieved from Moderate Resolution Imaging Spectrometer (MODIS) reflectance product using the physical Radiative Transfer Model (RTM) and the wildfire events extracted from the MODIS Burned Area (BA) product to explore the relations between LFMC and forest/grassland fire occurrence across the subtropical highland zone (Cwa) and humid subtropical zone (Cwb) over southwest China. The statistical results of pre-fire LFMC and cumulative burned area show that distinct pre-fire LFMC critical thresholds were identified for Cwa (151.3%, 123.1%, and 51.4% for forest, and 138.1%, 72.8%, and 13.1% for grassland) and Cwb (115.0% and 54.4% for forest, and 137.5%, 69.0%, and 10.6% for grassland) zones. Below these thresholds, the fire occurrence and the burned area increased significantly. Additionally, a significant decreasing trend on LFMC dynamics was found during the days prior to two large fire events, Qiubei forest fire and Lantern Mountain grassland fire that broke during the 2009/2010 and 2015/2016 fire seasons, respectively. The minimum LFMC values reached prior to the fires (49.8% and 17.3%) were close to the lowest critical LFMC thresholds we reported for forest (51.4%) and grassland (13.1%). Further LFMC trend analysis revealed that the regional median LFMC dynamics for the 2009/2010 and 2015/2016 fire seasons were also significantly lower than the 10-year LFMC of the region. Hence, this study demonstrated that the LFMC dynamics explained wildfire occurrence in these fire-prone regions over southwest China, allowing the possibility to develop a new operational wildfire danger forecasting model over this area by considering the satellite-derived LFMC product. Full article

Forest fire management relies on fire danger rating to optimize its suite of activities. Limiting fire size is the fire management target whenever minimizing burned area is the primary goal, such as in the Mediterranean Basin. Within the region, wildfire incidence is especially acute in Portugal, a country where fire-influencing anthropogenic and landscape features vary markedly within a relatively small area. This study establishes daily fire weather thresholds associated to transitions to increasingly larger fires for individual Portuguese regions (2001–2011 period), using the national wildfire and Canadian fire weather index (FWI) databases and logistic regression. FWI thresholds variation in relation to population density, topography, land cover, and net primary production (NPP) metrics is examined through regression and cluster analysis. Larger fires occur under increasingly higher fire danger. Resistance to fire spread (the fire-size FWI thresholds) varies regionally following biophysical gradients, and decreases under more complex topography and when NPP and occupation by flammable forest or by shrubland increase. Three main clusters synthesize these relationships and roughly coincide with the western north-central, eastern north-central and southern parts of the country. Quantification of fire-weather relationships can be improved through additional variables and analysis at other spatial scales. Full article

Globally, fire regimes are being altered by changing climatic conditions. New fire regimes have the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Despite the co-occurrence of forest fires with drought, current approaches to modelling flammability largely overlook the large body of research into plant vulnerability to drought. Here, we outline the mechanisms through which plant responses to drought may affect forest flammability, specifically fuel moisture and the ratio of dead to live fuels. We present a framework for modelling live fuel moisture content (moisture content of foliage and twigs) from soil water content and plant traits, including rooting patterns and leaf traits such as the turgor loss point, osmotic potential, elasticity and leaf mass per area. We also present evidence that physiological drought stress may contribute to previously observed fuel moisture thresholds in south-eastern Australia. Of particular relevance is leaf cavitation and subsequent shedding, which transforms live fuels into dead fuels, which are drier, and thus easier to ignite. We suggest that capitalising on drought research to inform wildfire research presents a major opportunity to develop new insights into wildfires, and new predictive models of seasonal fuel dynamics. Full article