Search Results (490)

The risk of explosive spalling in high-strength cement-based materials during fire exposure poses a significant threat to structural integrity. To help mitigate this issue, this study explores the use of expanded polystyrene (EPS) beads as both a lightweight filler and a potential spalling-reduction agent in lightweight geopolymer and conventional cementitious mortars. Two EPS-containing mortars were developed: a lightweight alkali-activated slag (LWAS) mortar and a conventional lightweight Portland cement (LWPC) mortar, both incorporating EPS beads as a 50% volumetric replacement for sand. Specimens from both mortars were subjected to elevated temperatures of 200 °C, 400 °C, and 600 °C at a heating rate of 10 °C/min to simulate a rapid-fire scenario. Following thermal exposure, two cooling regimes were employed: gradual cooling within the furnace and rapid cooling by water immersion. Mechanical performance was evaluated through compressive, splitting tensile, and impact tests at room and elevated temperatures. Microstructural analysis was also conducted to examine internal changes and heat-induced damage. The results indicated that LWAS showed remarkable resistance to spalling, remaining intact up to 600 °C due to its nanoporous geopolymer structure, which allowed controlled steam release, while LWPC failed explosively at 550 °C despite EPS pores. At 400 °C, EPS beads enhanced thermal insulation in LWAS, lowering internal temperature by over 100 °C, but increased porosity led to faster strength loss. Both mortars gained strength at 200 °C from continued curing, yet LWAS retained strength better at high temperatures than LWPC. Microscopy revealed that EPS created beneficial fine cracks in the slag matrix but harmful voids in cement. Overall, LWAS composites offer excellent spalling resistance for fire-prone environments, though reinforcement is recommended to mitigate strength loss. Full article

State-of-the-art historical global burned area (BA) products largely rely on MODIS data, offering long temporal coverage but limited spatial resolution. As a result, small fires and complex landscapes remain underrepresented in global fire history reconstructions. By contrast, Landsat provides the only continuous satellite record extending back to the 1980s, with substantially finer resolution. However, its use at a global scale has long been hindered by infrequent revisit times, cloud contamination, massive data volumes, and processing demands. We compared MODIS FireCCI51 with the only existing Landsat-based global product, GABAM, in a mountainous region characterized by frequent, small-scale fires. GABAM detected a higher number of burn scars, including small events, with higher Producer’s Accuracy (0.68 vs. 0.08) and similar User’s Accuracy (0.85 vs. 0.83). These results emphasize the value of Landsat for reconstructing past fire regimes in complex landscapes. Crucially, recent advances in cloud computing, data cubes, and processing pipelines now remove many of the former barriers to exploiting the Landsat archive globally. A more systematic integration of Landsat data into MODIS-based routines may help produce more complete and accurate databases of historical fire activity, ultimately enabling improved understanding of long-term global fire dynamics. Full article

The Neotropical Savanna (Cerrado) is a fire-prone biome characterized by seasonal climate, nutrient-poor soils, and variable fire regimes. While fire-induced germination responses are well documented in Cerrado plants, the role of seed size in mediating thermal tolerance remains poorly understood. Here, we investigate how seed size and fire-related heat treatments influence germination in Hymenaea stigonocarpa, a keystone Cerrado tree species. Specifically, we test the predictions that (i) low to moderate fire temperatures (<270 °C) do not impair seed germination and (ii) larger seeds exhibit greater heat tolerance than smaller seeds. We exposed 360 seeds from 30 individual trees to five heat-shock treatments (27, 100, 150, 200, and 270 °C) simulating fire intensities typically experienced in the Cerrado. Our results show that H. stigonocarpa produces relatively large seeds with an average germination rate of approximately 42%. The average time required for germination was 12.18 ± 0.43 (average ± standard error) days. The time required for seed germination varied significantly as a function of heat-shock treatment and seed mass, with seeds exposed to the highest temperature (270 °C) taking longer to germinate. Moreover, seed mass had a positive effect on the time required for seed germination. The germination percentage remains stable across heat treatments and seed sizes, indicating that H. stigonocarpa seeds exhibit characteristics typical of heat-tolerant species rather than those of heat-stimulated species. Our study showed that H. stigonocarpa trees produce large seeds that germinate quickly and are tolerant to moderate temperatures. These seed traits play a crucial role in the reproductive success of individual plants in fire-prone, nutrient-poor, and water-limited ecosystems. Furthermore, our results offer important guidance by emphasizing the role of seed size in effective restoration initiatives. Full article

To prevent or mitigate the negative impact of fires, spatial prediction maps of wildfires are created to identify susceptible locations and key factors that influence the occurrence of fires. This study uses artificial intelligence models, specifically machine learning (XGBoost) and deep learning (Kolmogorov-Arnold networks—KANs, and deep neural network—DNN), with data obtained from multi-sensor satellite imagery (MODIS, VIIRS, Sentinel-2, Landsat 8/9) for spatial modeling wildfires in Serbia (88,361 km²). Based on geographic information systems (GIS) and 199,598 wildfire samples, 16 quantitative variables (geomorphological, climatological, hydrological, vegetational, and anthropogenic) are presented, together with 3 synthesis maps and an integrated susceptibility map of the 3 applied models. The results show a varying percentage of Serbia’s very high vulnerability to wildfires (XGBoost = 11.5%; KAN = 14.8%; DNN = 15.2%; Ensemble = 12.7%). Among the applied models, the DNN achieved the highest predictive performance (Accuracy = 83.4%, ROC-AUC = 92.3%), followed by XGBoost and KANs, both of which also demonstrated strong predictive accuracy (ROC-AUC > 90%). These results confirm the robustness of deep and machine learning approaches for wildfire susceptibility mapping in Serbia. SHAP analysis determined that the most influential factors are elevation, air temperature, and humidity regime (precipitation, aridity, and series of consecutive dry/wet days). Full article

Fire and invasive plant species interactions are critical drivers of biodiversity loss and ecological change in grassland ecosystems worldwide. However, research efforts on this topic are often fragmented, regionally based, and lack synthesis across disciplines. This study aims to map the intellectual structure, collaboration networks, thematic focus, and knowledge gaps in research on fire-invasive species interactions in grassland restoration. A systematic bibliometric analysis was conducted using the Web of Science Core Collection, focusing on peer-reviewed English-language articles published between 1990 and 2024. The search strategy targeted studies addressing fire regimes and invasive plant species in grassland ecosystems, using co-authorship, co-occurrence and thematic clustering analyses to reveal collaboration patterns and research trends. The results highlight a concentration of publications in key ecological journals, with a dominant contribution from institutions in the Global North, through growing representation from the Global South, particularly South Africa, is evident. Thematic clusters are centred on biological invasions, fire regimes, species traits and ecosystem resilience, while long-term post-fire recovery and studies from underrepresented regions remain critical knowledge gaps. This synthesis emphasises the need for interdisciplinary, regionally inclusive and policy-aligned research to inform effective grassland restoration strategies in the context of fire and invasive species challenges. Full article

Forest fire regimes are undergoing systematic reorganization under climate change, particularly in monsoon–human coupled ecosystems such as Southeastern China, where risk dynamics remain poorly quantified. This study proposes a meteorology-driven machine learning model designed to assess long-term forest fire risk. Using kernel density estimation and standard deviational ellipse analysis, we assessed the spatiotemporal patterns of fire risk during the observational period and their future shifts across the SSP1-2.6 and SSP5-8.5 scenarios. The results indicate a significant overall decline in fire frequency from 2008 to 2024 (−467.3 fires/year, representing an annual average reduction of 10.8%, p < 0.001), which is attributed primarily to enhanced regional fire prevention and control measures, yet with a notable reversal after 2016 in Guangdong and Fujian. Fires are highly seasonal, with 74% occurring in the dry season (December–March). The meteorologically driven random forest model exhibited excellent performance (R² = 0.889), validating meteorological conditions as key drivers of regional fire dynamics. It is projected that intensified warming (+5.5 °C under SSP5-8.5) and increased precipitation variability (+23%) are likely to drive pronounced northward and inland migration in high-risk zones. Our projections indicate that by the end of the century, high-risk area coverage could expand to 19.2%, with a shift from diffuse to clustered patterns, particularly in Jiangsu and Zhejiang. These findings underscore the critical role of hydrothermal reconfiguration in reshaping fire risk geography and highlight the need for dynamic, region-specific fire management strategies in response to compound climate risks. Full article

Neuromorphic circuits emulate the brain’s massively parallel, energy-efficient, and robust information processing by reproducing the behavior of neurons and synapses in dense networks. Memristive technologies have emerged as key enablers of such systems, offering compact and low-power implementations. In particular, locally active memristors (LAMs), with their ability to amplify small perturbations within a locally active domain to generate action potential-like responses, provide powerful building blocks for neuromorphic circuits and offer new perspectives on the mechanisms underlying neuronal firing dynamics. This paper introduces a novel second-order locally active memristor (LAM) governed by two coupled state variables, enabling richer nonlinear dynamics compared to conventional first-order devices. Even when the capacitances controlling the states are equal, the device retains two independent memory states, which broaden the design space for hysteresis tuning and allow flexible modulation of the current–voltage response. The second-order LAM is then integrated into a FitzHugh–Nagumo neuron circuit. The proposed circuit exhibits oscillatory firing behavior under specific parameter regimes and is further investigated under both DC and AC external stimulation. A comprehensive analysis of its equilibrium points is provided, followed by bifurcation diagrams and Lyapunov exponent spectra for key system parameters, revealing distinct regions of periodic, chaotic, and quasi-periodic dynamics. Representative time-domain patterns corresponding to these regimes are also presented, highlighting the circuit’s ability to reproduce a rich variety of neuronal firing behaviors. Finally, two unknown system parameters are estimated using the Aquila Optimization algorithm, with a cost function based on the system’s return map. Simulation results confirm the algorithm’s efficiency in parameter estimation. Full article

Climate change is intensifying fire regimes, thereby challenging forest ecosystems and making it more difficult to predict the fate of burned trees. The significant ecological impacts of latent tree mortality remain poorly understood. In this study, we reviewed the scientific literature on latent tree mortality in conifer forests following wildfires or prescribed fires. A total of 2294 papers published between 2000 and 2024 were identified from Scopus and Web of Science databases. Using the PICO selection method, we included 16 relevant studies in the final analysis. These studies are based on field assessment, excluding remote sensing and controlled laboratory conditions. Our research revealed that latent mortality results from multiple forms of damage and environmental stressors that disrupt hydraulic function and carbon allocation, increasing tree vulnerability to secondary biotic and abiotic stressors. The discussion is structured around four thematic areas: physiology, ecophysiology, dendrochronology, and silviculture. This approach contributes to a deeper, interdisciplinary understanding of latent tree mortality. However, predicting it remains difficult, reflecting persistent knowledge gaps. Despite the limited literature on this specific field, our review highlights the need for integrated physiological indicators, such as sap flow, transpiration, nonstructural carbohydrates and glucose concentration, as well as long-term monitoring along many growing seasons to better assess tree survival after fire. Full article

The increasing share of renewable energy sources in power grids demands greater load flexibility from thermal power plants. Circulating Fluidized Bed (CFB) combustion systems, while offering fuel flexibility and high thermal inertia, face challenges in maintaining hydrodynamic and thermal stability during load transitions. This study investigates partial flue gas recirculation (FGR) as a strategy to enhance short-term load flexibility in a 1 MW_th CFB pilot plant fired exclusively with solid recovered fuel. Two experimental test series were conducted. Under conventional operation, where fuel and fluidization air are reduced proportionally, load reductions to 86% and 80% led to operating regime shift. Particle entrainment from the riser to the freeboard and loop seal decreased, circulation weakened, and the temperature difference between bed and freeboard zone increased by 71 K. Grace diagram analysis confirmed that the system approached the boundary of the circulating regime. In contrast, the partial FGR strategy maintained total fluidization rates by replacing part of the combustion air with recirculated flue gas. This stabilized pressure conditions, sustained particle circulation, and limited the increase in the temperature difference to just 7 K. Heat extraction in the freeboard remained constant or improved, despite slightly lower flue gas temperatures. While partial FGR introduces a minor efficiency loss due to the reheating of recirculated gases, it significantly enhances combustion stability and enables low-load operation without compromising fluidization quality. These findings demonstrate the potential of partial FGR as a control strategy for flexible, waste-fueled CFB systems and supports its application in future low-carbon energy systems. Full article

The Gadouras Reservoir, Rhodes Island’s primary water source, experiences recurrent whiting events—milky turbidity from calcium carbonate precipitation—that challenge treatment operations, with impacts compounded by a major 2023 wildfire in this fire-prone Mediterranean setting. To elucidate these dynamics, a pragmatic, multi-source monitoring framework integrates archived Sentinel-2 and Landsat imagery with treatment-plant records (2017–mid-2025). Unitless spectral indices (e.g., AreaBGR) for whiting detection and chlorophyll-a proxies are combined with laboratory measurements of turbidity, pH, total organic carbon, manganese, and hydrological metrics, analyzed via spatiotemporal Hovmöller diagrams, Pearson correlations, and interrupted time-series models. Two seasonal whiting regimes are identified: a biogenic summer mode (southern origin; elevated chlorophyll-a; water temperature > 15 °C; pH > 8.5) and a non-biogenic winter mode (northern inflows). Following the wildfire, the system exhibits characteristics that could be related to possible hypolimnetic anoxia, prolonged whiting, a ~50% rise in organic carbon, and a manganese excursion to ~0.4 mg L⁻¹ at the deeper intake. Crucially, the post-fire period shows a decoupling of AreaBGR from turbidity (r ≈ 0.233 versus ≈ 0.859 pre-fire)—a key diagnostic finding that confirms a fundamental shift in the composition and optical properties of suspended particulates. The manganese spike is best explained by the confluence of a wildfire-induced biogeochemical predisposition (anoxia and Mn mobilization) and a consequential operational decision (relocation to a deeper, Mn-rich intake). This framework establishes diagnostic baselines and thresholds for managing fire-impacted reservoirs, supports the use of remote sensing in data-scarce systems, and informs adaptive operations under increasing climate pressures. Full article

Fire has had a profound impact on Australia’s landscapes and biodiversity since the late Tertiary. Indigenous (Aboriginal) people have lived in Australia for at least 65,000 years and fire is an integral part of their culture and cosmology. In 2015, an Indigenous cultural burn was undertaken by Banbai rangers at Wattleridge Indigenous Protected Area, New England Tablelands, NSW. We compared the impact of this burn on the composition, cover, abundance, and species richness of dry sclerophyll vegetation and fuel hazard, with a hazard reduction burn at nearby Warra National Park, using a Before-After-Control-Impact experimental design. Our study found that the low-severity cultural burn and moderate-severity hazard reduction burn reduced fuel loads but did not have a significant impact on the composition of the vegetation overall or the herb layer. The hazard reduction burn had a significant impact on shrub and juvenile tree (woody species) cover, while the abundance of woody species was significantly affected by both fires, with a mass germination of ‘seeder’ species, particularly after the cultural burn. The long unburnt fire regime at Wattleridge may have made the vegetation more responsive to fire than the more frequently burnt vegetation at Warra, through accumulation of seed in the seed bank, so that the patchy cultural burn had a greater impact on woody species abundance. In terms of ecological and bushfire management outcomes, this study provides evidence to support claims that Indigenous cultural burning decreases fuel loads, stimulates regeneration of shrubs and trees, and manages at a local, place-based scale. We recommend cultural burning as a key management tool across Indigenous Protected Areas and other land tenures, with its implementation monitored and adaptively managed through two-way science, to foster fire regimes that are both culturally and ecologically beneficial. This is a vital element of our resilience in the Pyrocene and a significant step toward decolonizing science and land management. Full article

This paper presents findings based on eighty (80) lightning-caused wildfires that occurred on Mount Mainalo, in central Peloponnese, Greece, from May 1998 to November 2022. The frequency of lightning-caused wildfires was found to increase in July and August, consistent with the occurrence of dry summer thunderstorms. Most wildfires ignited in the southern part of the mountain, at elevations between 1200 and 1800 m, and were primarily detected in the afternoon hours. We present spatial data, statistics and frequency distribution histograms of subsets of the database. The likelihood of at least one fire per season is approximately 96%, while the average number of wildfires per fire season is 3.2. These findings on the number of lightning-caused wildfires per year, the holdover time (the time interval between the ignition and fire detection), the wildfire detection time, the elevation of lightning-caused wildfire occurrence, the total annual burned area and the burned area per fire can support improving wildfire management in the region since they provide a thorough description of the regime of lightning-caused wildfire on Mount Mainalo. This research addresses a critical knowledge gap in the study of lightning-caused wildfires in the Mediterranean, which remain underexplored despite their growing relevance under climate change. Full article

Wildfire regimes in Mediterranean landscapes are becoming increasingly unpredictable, driven by the combined effects of climate change, land-use transitions, and socio-economic pressures. Traditional metrics such as burned area or ignition points often fail to capture the complexity of the temporal and spatial recurrence of fire events. To address this gap, we apply, for the first time, a trajectory analysis framework to wildfire occurrence data across mainland Portugal (1975–2024), using pixel-level binary time series at 100 m resolution. Originally developed for land cover change detection, this method classifies each pixel into sequences representing distinct temporal patterns (e.g., stability, gains, losses, or alternations) over defined periods. Results reveal a predominance of stable absence and alternation-type trajectories, particularly “All alternation gain first”, which points to recurrent yet irregular fire activity. Regional differences further highlight the influence of divergent socio-ecological contexts. The findings suggest that fire regimes in Portugal are not only recurrent but structurally dynamic, and that trajectory-based classification offers a novel and valuable tool for long-term monitoring and regionally adapted fire management. Applying this method to wildfire data required specific adjustments to account for the unique temporal and thematic characteristics of fire regimes, ensuring a meaningful interpretation of the results. Full article

Pinus nigra Arnold, which is naturally widespread in mountainous and Mediterranean ecosystems, is a key species for reforestation due to its ecological and economic value. As climate change and changing fire regimes increase the wildfire risk, understanding its fire resilience has become critical. In this study, the morpho-physiological traits (thickness, roughness, moisture content) and flammability characteristics (ignition, heat release, mass loss, as determined in laboratory flammability tests) of the bark of P. nigra were investigated. The trees were selected based on their age (young vs. old) and fire exposure (burned vs. unburned). The bark thickness was significantly greater in older trees, while the bark moisture content was significantly lower in previously burned trees (p ≤ 0.05). The bark thickness correlated strongly with the ignition time, heat release, and mass loss. These results indicate that the age of the tree primarily affects the bark thickness and time to cambium death, while fire exposure primarily affects the bark moisture content, regardless of age. Understanding that the bark thickness and flammability play a key role in tree survival may aid in the selection of individuals or stand structures better suited to survive in fire-prone conditions and in the strategic planning of burns to reduce fuel loads without exceeding the mortality risk of younger or thinner-barked individuals. Full article

Forest disturbance is a major driver shaping the structure and function of plantation ecosystems. Current research predominantly focuses on single forest types or landscape scales. However, species-level fine-scale assessments of disturbance dynamics are still scarce. In this study, we investigated Chinese fir (Cunninghamia lanceolata), Armand pine (Pinus armandii), and Yunnan pine (Pinus yunnanensis) plantations in the mountainous eastern Yunnan Plateau. We developed a Spatial Coupling Framework of Disturbance Legacy (SC-DL) to systematically elucidate the spatial associations between contemporary species distribution patterns and historical disturbance regimes. Using the Google Earth Engine (GEE) platform, we reconstructed pixel-level disturbance trajectories by integrating long-term Landsat time series (1993–2024) and applying the LandTrendr algorithm. By fusing multi-source remote sensing features (Sentinel-1/2) with terrain factors, employing RFE, and performing a multi-model comparison, we generated 10 m-resolution species distribution maps for 2024. Spatial overlay analysis quantified the cumulative proportion of the historically disturbed area and the spatial aggregation patterns of historical disturbances within current species ranges. Key results include the following: (1) The model predicting disturbance year achieved high accuracy (R² = 0.95, RMSE = 2.02 years, MAE = 1.15 years). The total disturbed area from 1993 to 2024 was 872.7 km², exhibiting three distinct phases. (2) The random forest (RF) model outperformed other classifiers, achieving an overall accuracy (OA) of 95.17% and a Kappa coefficient (K) of 0.93. Elevation was identified as the most discriminative feature. (3) Significant spatial differentiation in disturbance types emerged: anthropogenic disturbances (e.g., logging and reforestation/afforestation) dominated (63.1% of total disturbed area), primarily concentrated within Chinese fir zones (constituting 70.2% of disturbances within this species’ range). Natural disturbances accounted for 36.9% of the total, with fire dominating within the Yunnan pine range (79.3% of natural disturbances in this zone) and drought prevailing in the Armand pine range (71.3% of natural disturbances in this zone). (4) Cumulative disturbance characteristics differed markedly among species zones: Chinese fir zones exhibited the highest cumulative proportion of disturbed area (42.6%), with strong spatial aggregation. Yunnan pine zones followed (36.5%), exhibiting disturbances linearly distributed along dry–hot valleys. Armand pine zones showed the lowest proportion (20.9%), characterized by sparse disturbances within fragmented, high-altitude habitats. These spatial patterns reflect the combined controls of topographic adaptation, management intensity, and environmental stress. Our findings establish a scientific basis for identifying disturbance-prone areas and inform the development of differentiated precision management strategies for plantations. Full article