Search Results (154)

We analyzed wildfire hazard profiles across the Hyrcanian temperate forests of northern Iran (Guilan Province) by simulating a large set of wildfires with FlamMap MTT. We first derived geospatial data on terrain, fuel models, weather conditions, and historical wildfire occurrence (1992–2022) for the study area. We stratified fire weather conditions and fuel moisture based on the bioclimatic classification of the study area, considering observed extreme fire weather, as well as observed and random fire ignition locations for the simulations. The wildfire simulations were used to estimate burn probability (BP), conditional flame length (CFL), fire size (FS), and crown fire probability (CFP). BP ranged from 0 to 5.0 × 10⁻², with mean values of 1.3 × 10⁻³ and 1.1 × 10⁻³ for observed and random scenarios, respectively. The mean value of CFL from random ignition simulations (0.78 m) was substantially higher than that obtained in the observed ignition simulations (0.54 m), ranging from 0 to 6.75 m. We evidenced significant differences between observed and random ignition simulations for all wildfire hazard metrics. The highest wildfire hazard profiles were observed in the Cold-Mountainous bioclimatic zone under the random ignition simulations. On average, the annual number of anthropic structures threatened by wildfires ranged from 97 (observed scenario) to 123 (random scenario). This research provides detailed and spatially explicit fire hazard and exposure maps to inform fire modeling, land management, and policy actions. Full article

The object of the study is a single heated carbonaceous particle of relatively small size, 0.003 to 0.01 m. Main hypothesis: The formation of soot particles and black carbon particles is caused by the thermochemical destruction of dry organic matter of forest fuel and the mechanical fragmentation of coke residue. The aim of the study is to conduct numerical simulations of heat and mass transfer in a single heated carbonaceous particle, taking into account the soot formation process and assessing its fragmentation with regard to heat exchange with the external environment in a 2D setting. As part of this study, a new model of heat and mass transfer in a pyrolyzed carbonaceous particle was developed, taking into account its step-by-step fragmentation (fragmentation tree model with four secondary particle formations from the initial particle). The calculations resulted in the distributions of temperature and volume fractions of phases in the carbonaceous particle across various scenarios. Scenarios of surface fires (initial temperatures of 900 K and 1000 K), crown fires (1100 K), and a firestorm (1200 K) for typical vegetation (pine, spruce, birch) are considered. Cubic carbonaceous particles are considered in the approximation of a 2D mathematical model. To describe heat and mass transfer in the structure of the carbonaceous particle, a differential equation of thermal conductivity with corresponding initial and boundary conditions of the third type is used, taking into account the gross reaction in the kinetic scheme of pyrolysis and soot formation. Differential analogues of partial differential equations are solved using the finite difference method of second-order approximation. Options for using the developed mathematical model and probabilistic fragmentation criterion for assessing aerosol emissions are proposed. Recommendations: The suggested mathematical model must be incorporated with mathematical models of forest fire plume and aerosol transport in the upper layers of the atmosphere. Moreover, probabilistic criteria for health assessment must be developed for the practical use of the suggested mathematical model. Full article

Wildland fires, including surface and crown fires, present significant challenges for ecosystems and forest management. Accurate fire modelling is crucial for risk assessment and mitigation strategies. The Fire Dynamics Simulator (FDS) v6.8.0, developed by the National Institute of Standards and Technology (NIST), is a physics-based model that simulates fire behaviour by incorporating advanced physics and chemistry. However, its reliability requires thorough validation. This study validates FDS 6.8.0’s performance in modelling both surface fires and single tree burning. Two separate simulation sets were conducted. For surface fires, pine needle fuel beds were used at a laboratory scale to examine fire behaviour on slopes of 0°, 10°, and 20°. The results were validated against experimental data. A burning Douglas fir tree was simulated, and the results were compared with experimental measurements. The surface fire simulations at 0° and 10° slopes showed strong agreement with experimental data. In single-tree burning, both experimental and simulated results exhibited similar trends, with a rapid increase to a peak mass-loss rate (MLR) followed by a gradual decline. Validating FDS 6.8.0 forms an essential first step toward supporting the investigation of complex wildland fire behaviour, such as surface-to-crown fire transition, canyon fire, and dynamic escalation, using the same FDS version. Full article

Eaton Canyon in California serves as the focal point for a comprehensive post-wildfire ecological impact assessment. This study employs an approach integrating satellite imagery from the European Space Agency’s Sentinel constellation to study an area of 271.49 km². The data encompasses both radar and multispectral data, offering a multi-dimensional view of the affected landscape. The analysis leverages the power of the random forest algorithm. Firstly, three widely used indices—the difference normalized burn ratio (dNBR), relative burn ratio (RBR), and relative difference normalized burn ratio (RdNBR)—were calculated and compared based on their accuracy and Kappa index. Secondly, we developed a fusion approach by using all the fire indices to obtain a precise severity map by classifying the affected area into distinct severity classes. Thirdly, a separate fusion approach was developed utilizing the normalized difference vegetation index (NDVI), radar vegetation index (RVI), and modified normalized difference vegetation index (MNDVI) to analyze the distribution of vegetation before and after the wildfire. The merger proposals were developed using a combination of index values to obtain better information on the fire severity map and post-fire vegetation distribution. The results indicated an accuracy of 78% when employing the dNBR index. A higher accuracy of 81% was observed with the RBR index, while the RdNBR demonstrated an accuracy of 95%. Our approach, which combines all fire indicators, offers optimal accuracy of 99%. A percentage of 56.76% did not burn due to the topography of the canyon creating natural firebreaks. Areas classified as low severity (7.83%) showed minimal damage with minimal tree mortality. Moderate- to low-severity areas (5.83%) represented regions with partial crown burns and some tree mortality. Moderate- to high-severity areas (7.22%) showed significant tree mortality. Finally, high-severity areas (22.36%), characterized by complete tree mortality and significant loss of vegetation cover, were largely concentrated in specific sections of the canyon, likely influenced by factors such as slope and fuel type. These findings provide valuable information for post-fire ecological recovery efforts and future land management strategies in Eaton Canyon and similar fire-prone landscapes. Full article

Burned area, fire severity, and suppression expenditures have increased in British Columbia in recent decades with climate change. Approximately 80% of suppression expenditures are attributable to wildfires near the Wildland–Urban Interface (WUI). Evaluating the potential for fuel management to reduce suppression expenditures is essential to mitigating demands on fire response resources and reducing impacts on communities. One management approach is to increase the proportion of deciduous tree species, which have a lower propensity for crown fire. Using fire suppression expenditure data from 1981 to 2014, we applied the machine learning method causal forests (CFs) to estimate the effect of the proportion of conifer forest cover on suppression expenditures for WUI fires and how these effects varied with other influential factors (i.e., heterogenous treatment effects). Across all fires, the effect of conifer cover on suppression expenditures was stronger on private land compared to public land, under high fire danger measured by daily severity ratings (DSRs), which reflect wind speed and fuel moisture, and for fires igniting earlier in the calendar year, based on Julian day. These findings provide insights into prioritizing wildland fuel treatment when budgets are limited. The CFs approach demonstrates potential for broader applications in fire risk mitigation and analysis beyond the scope of the current data. CFs may also be valuable in other areas of forest research where heterogenous treatment effects are common. Full article

The increasing frequency and intensity of wildfires pose severe risks to ecosystems, infrastructure, and human safety. In wildland–urban interface (WUI) areas, nearby vegetation strongly influences building ignition risk through flame contact and radiant heat exposure. However, limited research has leveraged Unmanned Aerial Systems (UAS) remote sensing (RS) to capture species-specific vegetation geometry and predict thermal responses during ignition events This study proposes a two-stage framework integrating UAS-based multispectral (MS) imagery, LiDAR data, and Fire Dynamics Simulator (FDS) modeling to estimate the maximum temperature (T) and heat flux (HF) of outdoor vegetation, focusing on Syzygium smithii (Lilly Pilly). The study data was collected at a plant nursery at Queensland, Australia. A total of 72 commercially available outdoor vegetation samples were classified into 11 classes based on pixel counts. In the first stage, ensemble learning and watershed segmentation were employed to segment target vegetation patches. Vegetation UAS-LiDAR point cloud delineation was performed using Raycloudtools, then projected onto a 2D raster to generate instance ID maps. The delineated point clouds associated with the target vegetation were filtered using georeferenced vegetation patches. In the second stage, cone-shaped synthetic models of Lilly Pilly were simulated in FDS, and the resulting data from the sensor grid placed near the vegetation in the simulation environment were used to train an XGBoost model to predict T and HF based on vegetation height (H) and crown diameter (D). The point cloud delineation successfully extracted all Lilly Pilly vegetation within the test region. The thermal response prediction model demonstrated high accuracy, achieving an RMSE of 0.0547 °C and R² of 0.9971 for T, and an RMSE of 0.1372 kW/m² with an R² of 0.9933 for HF. This study demonstrates the framework’s feasibility using a single vegetation species under controlled ignition simulation conditions and establishes a scalable foundation for extending its applicability to diverse vegetation types and environmental conditions. Full article

Wildfires are a major ecological disturbance in Mediterranean forests, whose frequency and intensity are increasingly driven by climate change and land-use dynamics. This study investigated post-fire natural regeneration and soil properties in Aleppo pine stands seven years after a high-severity crown fire in southern Italy. Two stand types—pure pine and mixed pine—were compared, differing in fire severity and structural composition. We evaluated seedling density and dendrometric parameters (height and collar diameter), as well as soil parameters (pH, organic matter, and bulk density) to assess their role in post-fire recovery. Regeneration was abundant and composed exclusively of Aleppo pine, with significantly higher seedling density in the pure pine stand, where fire severity was greatest. In mixed pine stand, moderate fire severity combined with interspecific competition limited regeneration density. Deadwood presence enhanced microclimatic conditions favorable to seedling establishment, supporting a post-fire recovery dynamic consistent with self-succession, whereby pre-fire dominant species are favored. Soil analyses revealed higher organic matter content and lower bulk density in the pure stand, which likely facilitated regeneration. Overall, these findings underscore the ecological value of deadwood retention and passive management strategies in fostering spontaneous forest recovery. A better understanding of post-fire regeneration patterns and soil conditions can inform adaptive management approaches to strengthen forest resilience in Mediterranean forests under increasing climate pressure. Full article

Crown fires are a major disturbance in boreal and cold–temperate forests worldwide, threatening both ecosystems and human activities. The Da Xing’anling Mountains of Northeast China exemplify these dangers due to their complex vegetation and high crown fire potential. Crown fire occurrence depends on vertical fuel continuity, fuel load, heating value, surface fire spread rate, and critical fireline intensity. However, many assessments rely on single-factor metrics or low-adaptability simulations. This study developed a Potential Canopy Fire Danger Index (PCDI) that integrates five parameters—fuel vertical distribution continuity index, fuel loading, heating value, surface fire rate of spread, and critical fireline intensity—based on field surveys and combustion tests. Pinus pumila (Regel, 1861), with its dense shrub layer, showed the highest PCDI values (0.502, 0.583 and 0.527), whereas other forest types generally fell in the low to low–moderate range (0.350–0.450), with ≈75% of plots within these classes. Surface fire spread rate correlated most strongly with PCDI, followed by vertical fuel continuity, heating value, and fuel load; critical fireline intensity had minimal influence. The elevated hazard in P. pumila reflects its structural and fuel characteristics, while other forest types present comparatively lower dangers. Model checks indicated high stability and agreement with BehavePlus 6.0 scenarios, with the PCDI showing the lowest sample SD. The PCDI provides a quantitative framework for assessing crown fire danger in cold–temperate forests and supports targeted mitigation—prioritizing P. pumila while employing cost-effective maintenance in low-danger forest types. Full article

In many hardwood forests, resprouting is a common response to disturbance and basal resprouts may represent a substantial component of the forest understory, especially post-wildfire. Despite this, resprouts are often overlooked in biomass assessments and drivers of resprouting responses in certain species are still unknown. These knowledge gaps are problematic as the contribution of resprouts to understory fuel loads are needed for wildfire risk modeling and effective forest stewardship. Here, we validated the handheld mobile laser scanning (HMLS) of basal resprout volume and field measurements of stem count and clump height as methods to estimate the mass of California Bay Laurel (Umbellularia californica) basal resprouts at Pepperwood and Saddle Mountain Preserves, Sonoma County, California. In addition, we examined the role of tree size and wildfire severity in predicting post-wildfire resprouting response. Both field measurements (clump height and stem count) and remote sensing (HMLS-derived volume) effectively estimated dry mass (total, leaf and wood) of U. californica resprouts, but underestimated dry mass for a large resprout. Tree size was a significant factor determining post-wildfire resprouting response at Pepperwood Preserve, while wildfire severity significantly predicted post-wildfire resprout size at Saddle Mountain. These site differences in post-wildfire basal resprouting predictors may be related to the interactions between fire severity, tree size, tree crown topkill, and carbohydrate mobilization and point to the need for additional demographic and physiological research. Monitoring post-wildfire changes in U. californica will deepen our understanding of resprouting dynamics and help provide insights for effective forest stewardship and wildfire risk assessment in fire-prone northern California forests. Full article

Background: To evaluate the fracture resistance of 3D-printed 3-unit fixed dental prostheses (FDPs) made from tetragonal zirconia polycrystal (3Y-TZP). Methods: Based on a maxillary typodont model with a missing first molar and neighboring teeth with full crown preparations, FDPs differing in wall thickness (d = 0.6 mm / d = 0.8 mm / d = 1.0 mm) were designed. For all test groups, 12 samples were fabricated from 3Y-TZP by either 3D-printing or milling. For 3D-printing, pontic designs were modified by basal slots to enable regular firing times. After luting on CoCr dies, samples underwent artificial aging. Loads tilted by 30° were applied on the mesio-buccal cusp of the pontic, and fracture resistance F_u was assessed. Welch ANOVA and Dunnett-T3 tests were used for statistical evaluation. Results: Significant differences in F_u were identified (Welch ANOVA, p < 0.001). For milled FDPs, fracture originated from connector areas, and F_u increased with increasing wall thickness (d = 0.6 mm: 1536 ± 131 N, d = 0.8 mm: 2226 ± 145 N, d = 1.0 mm: 2686 ± 127 N, significant differences but for the comparison d = 0.8 mm vs. d = 1.0 mm). For 3D-printed FDPs, the loaded cusp fractured, and F_u did not change with FDP wall thicknesses (p > 0.779, F_u = 1110 ± 26 N for all PZ FDPs). Milled FDPs showed significantly higher F_u when compared to 3D-printed FDPs with identical wall thickness. Conclusions: Although 3D-printed zirconia FDPs still show lower fracture resistance values than their milled counterparts, all tested FDP configurations clearly exceed the clinical reference thresholds and can therefore be recommended for clinical use. Full article

Crown fire hazard assessment and behavior prediction in dwarf pine (Pinus pumila) forests are dictated by the amount of canopy fuel available, topography, and weather. In this study, we collected data on CFL (available canopy fuel load), CBD (canopy bulk density), and CBH (canopy base height) through the destructive sampling of dwarf pine trees in the Greater Khingan Mountains of Northeast China. Allometric equations were developed for estimating the canopy’s available biomass, CFL, and CBD to support the assessment of canopy fuel. Three burning scenarios were designed to investigate the impact of various environmental parameters on fire behavior. Our findings indicated that the average CFL of a dwarf pine was 0.36 kg·m⁻², while the average CBD was measured at 0.17 kg·m⁻³. The vertical variation trends of both CFL and CBD exhibited consistency, with values increasing progressively from the bottom to the top of the tree crown. Fire behavior simulations indicated that the low CBH of dwarf pine trees increased the likelihood of crown fires. Various factors, including wind speed, slope, and CBH, exerted considerable influence on fire behavior, with wind speed emerging as the most critical determinant. Silvicultural treatments, such as thinning and pruning, may effectively reduce fuel loads and elevate the canopy base height, thereby decreasing both the probability and intensity of crown fires. Full article

The almost complete eradication of fire from grasslands in North America has led to non-linear hysteretic transitions to shrub- and woodlands that the reintroduction of low-intensity fire is unable to reverse. We explore the ability of the extreme ends of variation in fire behavior to help overcome hysteretic threshold behaviors in huisache (Vachellia farnesiana) encroached grasslands. We contrasted experimental fire treatments with unburned control areas to assess the ability of extreme fires burned during drought to alter the density and structure of huisache. We found that extreme fires reduced the density of huisache by over 30% compared to control plots, both through driving huisache mortality and reducing the number of new recruits following treatments. For instance, extreme fire drove 48% huisache mortality compared to 4% in control treatments. For surviving plants, the number of stems increased but the crown area did not significantly change. Prescribed fire, conducted under the right conditions, can drive high mortality in one of the most notorious encroaching species in the southern U.S. Great Plains. With the fire conditions observed in this study likely to increase under future climate projections, utilizing extreme fire as a management tool for huisache will help scale up management to meet the growing extent of woody encroachment into grasslands. Full article

Wildfire is a critical driver of ecological processes in western U.S. forests, but recent shifts in climate, land use, and fire suppression have altered forest structure and disturbance regimes. Understanding post-fire recovery is essential for land management, particularly across complex montane landscapes like the southern Rocky Mountains. We assessed forest recovery in montane conifer forests, ranging from ponderosa pine to spruce-fir, following a large mixed-severity fire using field-based forest stand data and remotely sensed Leaf Area Index (LAI) measurements. Our objectives were to determine whether LAI is a meaningful proxy for post-fire vegetative recovery and how recovery patterns vary by forest type, burn severity, and abiotic factors. Stand characteristics predicted crown burn severity inconsistently and did not predict soil burn severity. LAI correlated strongly with live overstory tree density and shrub cover (R² = 0.70). Recovery trajectories varied by forest type, with lower-severity burns generally recovering four years post-fire, while high-severity burns showed delayed recovery. Regeneration patterns were strongly influenced by climate, with higher seedling densities occurring at wetter sites. Our findings highlight the utility of LAI as a proxy for vegetative recovery and underscore the importance of forest type, fire severity, and climatic factors when assessing post-fire resilience. Full article

Wildfires impact forest ecosystems, affecting tree survival and physiological responses. This study explored the effects of surface fires on Pinus densiflora and Quercus variabilis, assessing mortality, internal injuries, and canopy health. By 2024, P. densiflora had an 18.0% mortality rate, whereas Q. variabilis exhibited no crown dieback. Morphological traits, including tree height, the bark scorch index (BSI), and bark thickness, influenced fire resistance. Despite superior stand characteristics, P. densiflora showed higher mortality due to thin bark, whereas Q. variabilis maintained xylem integrity. While sonic tomography (SoT) showed no significant differences, electrical resistance tomography (ERT) detected physiological stress, with higher ERT_R and ERT_Y area ratios correlating with mortality risk. Notably, F-W-W classified trees showed elevated resistance a year before mortality, suggesting ERT as a predictive tool. ERT_R values exceeding 15.0% were associated with a 37.5% mortality rate, whereas ERT_B values below 55.0% corresponded to 42.9% mortality. Despite fire exposure, canopy responses, including chlorophyll fluorescence and photosynthetic efficiency, remained stable, indicating that the surviving trees maintained functional integrity. This study underscores ERT’s efficacy in diagnosing fire-induced stress and predicting mortality risk. The findings highlight species-specific diagnostic criteria and inform post-fire management, supporting forest resilience through the early detection of high-risk trees and improved restoration strategies. Full article

Forest fine fuels are a crucial component of surface fuels and play a key role in igniting forest fires. However, despite nearly 20 years of long-term prescribed burning management on Zhaobi Mountain in Xinping County, Yunnan Province, China, there remains a lack of specific quantification regarding the effectiveness of fine fuel management in Pinus yunnanensis forests. In this study, 10 m × 10 m sample plots were established on Zhaobi Mountain following one year of growth after prescribed burning. The plots were placed in a prescribed burning (PB) area and an unburned control (UB) area. We utilized indicators such as forest stand characteristics, fine fuel physicochemical properties, and potential fire behavior parameters for evaluation. The results indicate that prescribed burning at one-year intervals significantly affects stand characteristics, particularly in metrics such as crown base height, diameter breast height, and fuel load (p < 0.05). However, the physical and chemical properties of fine fuels did not show significant differences. Notably, the mean range of spread (RS) of PB fuels downhill was 43.3% lower than that of UB fuels, and the mean flaming height (FH) was 35.2% lower. The fire line intensity was <750 kW/m, categorizing it as a low-intensity fire. These findings provide data on the composition of fine fuels and the variables of fire behavior affected by prescribed burning, demonstrating that low-intensity prescribed burns can regulate fine fuels in the understory and maintain a stable regional fire risk level. Full article