Search Results (2,234)

Forest fires are recurrent in Spain and affect tree species in different ways. Fire incidence in the main Spanish forest species, both native and alien, is estimated in this study based on actual fire occurrences. Indices of presence, burned area, fire extent, frequency, and recurrence were calculated for each species, and with them, fire incidence indices were obtained. Significant fire incidence was detected in Pinus canariensis, P. pinaster, Eucalyptus globulus, Quercus robur, Betula spp., Castanea sativa, Pinus radiata, and Quercus pyrenaica. Most of the species with the highest fire incidence are not located in the areas with the highest climatic hazard. There is limited correlation between flammability and fire extension, and this is not significant when considering fire incidence. The relationship between fire incidence and conifers is valid in absolute terms, but only partially in relative terms. Similarly, there is no general relationship between relative fire incidence and species with a natural or reforested origin. Some native hardwood species have unexpectedly high incidence, probably due to collateral damage caused by fires in nearby pine and eucalyptus stands. The fire incidence index of forest species is useful for forest management and for protecting species that are suffering severely from fire effects. Full article

Entomopathogenic fungi (EPF) are one of the most environmentally friendly ways to control a plethora of chewing insects such as T. pityocampa, G. mellonella, and A. grisella. Bioassay of EPF on these highly damaging pests is considered important in the face of climate change in order to research alternative solutions that are capable of limiting chemical control, the overuse of which increases insects’ resistance to chemical compounds. In this study, the insecticidal virulence of Metarhizium robertsii isolates, retrieved from forest ecosystems, was tested on second-instar larvae of T. pityocampa, G. mellonella, and A. grisella. Bioassays were carried out in the laboratory, where experimental larvae were sprayed with 2 mL of a six-conidial suspension from each isolate. Mortality was recorded for 144 h after exposure. Mean mortality, lethal concentrations, sporulation percentage, and sporulation time were estimated for each isolate. Metarhizium isolates resulted in the highest mortality (89.2% for G. mellonella and 90.2% for A. grisella). Based on the LC₅₀ estimates determined by the concentration–mortality relationships for the tested fungal isolates, we demonstrated significant virulence on larvae of G. mellonella, A. grisella, and T. pityocampa. Our results indicate that entomopathogenic fungi have the potential to become a very useful tool in reducing chemical applications. Full article

The connection between sugar and ethanol prices is in line with concerns about the connection between oil and food prices. This paper studies the nexus between Colombia’s ethanol and sugar prices and the role that weather shocks play. Data on production and prices from the sugar mills and climate data on precipitation and temperature are used to estimate two ways to capture the relationship between prices and the role of weather shocks. First, a reduced-form estimation is made, where the study finds evidence of the pass-through of the international price to domestic prices and how high precipitation and temperature shocks increase prices. Then, the study addresses potential simultaneity problems between prices and estimates a VEC model with exogenous variables such as weather shocks. Results show that all domestic prices are affected by the international price, and the international price is affected by the white sugar domestic prices. Additionally, sugar prices react to shocks in ethanol prices, but ethanol prices do not react to shocks in sugar prices. Finally, weather shocks affect sugar prices, with daytime temperature shocks being the most damaging. Full article

Floods are considered one of the most devastating natural hazards, frequently resulting in substantial loss of lives and widespread damage to infrastructure. In the period of 4–7 September 2023, the region of Thessaly experienced unprecedented rainfall rates due to Storm Daniel, which caused significant flooding and many damages and fatalities. The southeastern areas of Trikala were among the many areas of Thessaly that suffered the effects of these rainfalls. In this research, a flood susceptibility assessment (FSA) of the broader area surrounding the settlement of Megala Kalyvia is carried out through the analytical hierarchy process (AHP) as a multicriteria analysis method, using Geographic Information Systems (GIS). The purpose of this study is to evaluate the prolonged flood susceptibility indicated within the area due to the past floods of 2018, 2020, and 2023. To determine the flood-prone areas, seven factors were used to determine the influence of flood susceptibility, namely distance from rivers and channels, drainage density, distance from confluences of rivers or channels, distance from intersections between channels and roads, land use–land cover, slope, and elevation. The flood susceptibility was classified as very high and high across most parts of the study area. Finally, a comparison was made between the modeled flood susceptibility and the maximum extent of past flood events, focusing on that of 2023. The results confirmed the effectiveness of the flood susceptibility assessment map and highlighted the need to adapt to the changing climate patterns observed in September 2023. Full article

Nano- and microplastic pollution, together with the ongoing rise in global temperatures driven by climate change, represent increasingly critical environmental challenges. Although these stressors often co-occur in the environment, their combined effects on plant systems remain largely unexplored. To test the hypothesis that their interaction may exacerbate the effects observed under each stressor individually, we investigated the response of seedlings of Triticum turgidum to treatments with fluorescent polystyrene nanoplastics under optimal (25 °C) and elevated (35 °C) temperature conditions. We evaluated seedling growth, photosynthetic pigment content, and oxidative stress markers using both biochemical and histochemical techniques. In addition, we assessed enzymatic and non-enzymatic antioxidant responses. The use of fluorescently labeled nanoplastics enabled the visualization of their uptake and translocation within plant tissues. Elevated temperatures negatively affect plant growth, increasing the production of proline, a key protective molecule, and weakly activating secondary defense mechanisms. Nanoplastics disturbed wheat seedling physiology, with these effects being amplified under high temperature conditions. Combined stress enhances nanoplastic uptake in roots, increases oxidative damage, and alters antioxidant responses, reducing defense capacity in leaves while triggering compensatory mechanisms in roots. These findings underscore a concerning interaction between plastic pollution and climate warming in crop plants. Full article

Wildfires have become increasingly frequent and destructive environmental hazards, especially in boreal ecosystems facing prolonged droughts and temperature extremes. This study presents an integrated spatio-temporal framework that combines Spatio-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN), Fire Radiative Power (FRP), and the differenced Normalized Burn Ratio (ΔNBR) to characterize the dynamics and ecological impacts of large-scale wildfires, using the extreme 2023 Quebec fire season as a case study. The analysis of 80,228 VIIRS fire detections resulted in 19 distinct clusters across four fire zones. Validation against the National Burned Area Composite (NBAC) showed high spatial agreement in densely burned areas, with Intersection over Union (IoU) scores reaching 62.6%. Gaussian Process Regression (GPR) revealed significant non-linear relationships between FRP and key fire behavior metrics. Higher mean FRP was associated with both longer durations and greater burn severity. While FRP was also linked to faster spread rates, this relationship varied by zone. Notably, Fire Zone 2 exhibited the most severe ecological impact, with 83.8% of the area classified as high-severity burn. These findings demonstrate the value of integrating spatial clustering, radiative intensity, and post-fire vegetation damage into a unified analytical framework. Unlike traditional methods, this approach enables scalable, hypothesis-driven assessment of fire behavior, supporting improved fire management, ecosystem recovery planning, and climate resilience efforts in fire-prone regions. Full article

The city of Acapulco was impacted by two near-consecutive hurricanes. On 25 October 2023, Hurricane Otis made landfall, reaching the highest Category 5 storm on the Saffir–Simpson scale, causing extensive coastal destruction due to extreme winds and waves. Nearly one year later (23 September 2024), Hurricane John—a Category 2 storm—caused severe flooding despite its lower intensity, primarily due to its unusual trajectory and prolonged rainfall. Digital shoreline analysis of PlanetScope images (captured one month before and after Hurricane Otis) revealed that the southern coast of Acapulco, specifically Zona Diamante—where the major seafront hotels are located—experienced substantial shoreline erosion (94 ha) and damage. In the northwestern section of the study area, the Coyuca Bar experienced the most dramatic geomorphological change in surface area. This was primarily due to the complete disappearance of the bar on October 26, which resulted in a shoreline retreat of 85 m immediately after the passage of Hurricane Otis. Sentinel-1 Synthetic Aperture Radar (SAR) showed that Hurricane John inundated 2385 ha, four times greater than Hurricane Otis’s flooding (567 ha). The retrofitted QGIS methodology demonstrated high reliability when compared to limited in situ local reports. Given the increased frequency of intense hurricanes, these methods and findings will be relevant in other coastal areas for monitoring and managing local communities affected by severe climate events. Full article

The pepper weevil Anthonomus eugenii is a devastating pest native to Central America that can cause severe damage to over 35 pepper varieties. Global trade in peppers has significantly increased the risk of its spread and expansion. Moreover, future climate change may add more uncertainty to its distribution, resulting in considerable ecological and economic damage globally. Therefore, we employed an ensemble model combining Random Forests and CLIMEX to predict the potential global distribution of A. eugenii in historical and future climate scenarios. The results indicated that the maximum temperature of the warmest month is an important variable affecting global A. eugenii distribution. Under the historical climate scenario, the potential global distribution of A. eugenii is concentrated in the Midwestern and Southern United States, Central America, the La Plata Plain, parts of the Brazilian Plateau, the Mediterranean and Black Sea coasts, sub-Saharan Africa, Northern and Southern China, Southern India, Indochina Peninsula, and coastal area in Eastern Australia. Under future climate scenarios, suitable areas in the Northern Hemisphere, including North America, Europe, and China, are projected to expand toward higher latitudes. In China, the number of highly suitable areas is expected to increase significantly, mainly in the south and north. Contrastingly, suitable areas in Central America, northern South America, the Brazilian Plateau, India, and the Indochina Peninsula will become less suitable. The total land area suitable for A. eugenii under historical and future low- and high-emission climate scenarios accounted for 73.12, 66.82, and 75.97% of the global land area (except for Antarctica), respectively. The high-suitability areas identified by both models decreased by 19.05 and 35.02% under low- and high-emission scenarios, respectively. Building on these findings, we inferred the future expansion trends of A. eugenii globally. Furthermore, we provide early warning of A. eugenii invasion and a scientific basis for its spread and outbreak, facilitating the development of effective quarantine and control measures. Full article

Climate change is generally having a negative impact on forest health by inducing drought stress and favouring the spread of pest species, such as bark beetles. The terrestrial monitoring of bark beetle infestation is very time-consuming, especially in the early stages, and therefore not feasible for extensive areas, emphasising the need for a comprehensive approach based on remote sensing. Although numerous studies have researched the use of optical data for this task, radar data remains comparatively underexplored. Therefore, this study uses the weekly and cloud-free acquisitions of Sentinel-1 in the Bavarian Forest National Park. Time series analysis within a Multi-SAR framework using Random Forest enables the monitoring of moisture content loss and, consequently, the assessment of tree vitality, which is crucial for the detection of stress conditions conducive to bark beetle outbreaks. High accuracies are achieved in predicting future bark beetle infestation (R² of 0.83–0.89). These results demonstrate that forest vitality trends ranging from healthy to bark beetle-affected states can be mapped, supporting early intervention strategies. The standard deviation of 0.44 to 0.76 years indicates that the model deviates on average by half a year, mainly due to the uncertainty in the reference data. This temporal uncertainty is acceptable, as half a year provides a sufficient window to identify stressed forest areas and implement targeted management actions before bark beetle damage occurs. The successful application of this technique to extensive test sites in the state of North Rhine-Westphalia proves its transferability. For the first time, the results clearly demonstrate the expected relationship between radar backscatter expressed in the Kennaugh elements K₀ and K₁ and bark beetle infestation, thereby providing an opportunity for the continuous and cost-effective monitoring of forest health from space. Full article

Trachypteris picta (Pallas, 1773) is a significant pest that can cause serious damage to poplars and willows. To assess the impact of climate change on the suitable habitats of T. picta, this study conducted a comparative analysis of its global suitable habitats using climatic factors, global land use type, and global vegetation from different periods, in combination with the maximum entropy (MaxEnt) model. The results indicate that the annual mean temperature (Bio01), mean temperature of the coldest quarter (Bio11), precipitation of the coldest quarter (Bio19), and isothermality (Bio03) are the four most important climate variables determining the distribution of T. picta. Under the current climate conditions, the highly suitable areas are primarily located in southern Europe, covering an area of 2.22 × 10⁶ km². Under future climate scenarios, the suitable habitat for T. picta is expected to expand and shift towards higher latitudes. In the 2050s, the SSP5-8.5 scenario has the largest suitable area compared to other scenarios, while the SSP2-4.5 scenario has the largest suitable area in the 2090s. In addition, the centroids of the total suitable areas are expected to shift toward higher latitudes under future climate conditions. The results of this study provide valuable data for the monitoring, control, and management of this pest. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

As China’s first systematic assessment of high-risk Amaranthaceae invaders, this study addresses a critical knowledge gap identified in the National Invasive Species Inventory, in which four invasive Amaranthaceae species (Dysphania ambrosioides, Celosia argentea, Amaranthus palmeri, and Amaranthus spinosus) are prioritized due to CNY 2.6 billion annual ecosystem damages in China. By coupling multi-species comparative analysis with a parameter-optimized Maximum Entropy (MaxEnt) model integrating climate, soil, and topographical variables in China under Shared Socioeconomic Pathways (SSP) 126/245/585 scenarios, we reveal divergent expansion mechanisms (e.g., 247 km faster northward shift in A. palmeri than D. ambrosioides) that redefine invasion corridors in the North China Plain. Under current conditions, the suitable habitats of these species span from 92° E to 129° E and 18° N to 49° N, with high-risk zones concentrated in central and southern China, including the Yunnan–Guizhou–Sichuan region and the North China Plain. Temperature variables (Bio: Bioclimatic Variables; Bio6, Bio11) were the primary contributors based on permutation importance (e.g., Bio11 explained 56.4% for C. argentea), while altitude (e.g., 27.3% for A. palmeri) and UV-B (e.g., 16.2% for A. palmeri) exerted lower influence. Model validation confirmed high accuracy (mean area under the curve (AUC) > 0.86 and true skill statistic (TSS) > 0.6). By the 2090s, all species showed net habitat expansion overall, although D. ambrosioides exhibited net total contractions during mid-century under the SSP126/245 scenarios, C. argentea experienced reduced total suitability during the 2050s–2070s despite high-suitability growth, and A. palmeri and A. spinosus expanded significantly in both total and highly suitable habitat. All species shifted their distribution centroids northward, aligning with warming trends. Overall, these findings highlight the critical role of temperature in driving range dynamics and underscore the need for latitude-specific monitoring strategies to mitigate invasion risks, providing a scientific basis for adaptive management under global climate change. Full article

To address the freezing damage to tunnel lining caused by frost heaving of the surrounding rock in water-rich tunnels in cold regions, a numerical thermo-mechanical coupling model for tunnel-surrounding rock that considers the anisotropy of frost heave deformation was established by examining overall frost heaves in a freeze–thaw cycle. Using a COMSOL Multiphysics 6.0 platform and the sequential coupling method, the temperature field evolution of tunnel-surrounding rock, freezing cycle development, and distribution characteristics of the frost heaving force of a tunnel lining under different minimum temperatures, numbers of negative temperature days, frost heave ratios, and anisotropy coefficients of frost heave deformation were systematically simulated. The results revealed that the response of the temperature field of tunnel-surrounding rock to the external temperature varies spatially with time lags, the shallow surface temperatures and the area around the lining fluctuate with the climate, and the temperature of the deep surrounding rock is dominated by the geothermal gradient. The extent of the freezing cycle and the frost heaving force increase significantly when lowering the minimum temperature. The maximum frost heaving force usually occurs in the region of the side wall and the spring line, and tensile stress is prone to be generated at the spring line; the influence of slight fluctuations in the minimum temperature or the short shift in the coldest day on the frost heaving force is limited. A substantial increase in frost heaving force is observed with higher frost heave ratios; for example, an increase from 0.25% to 2.0% results in a 116% rise at the sidewall. Although the increase in the anisotropy coefficient of frost heave deformation does not change the overall distribution pattern of frost heaving force, it can exacerbate the directional concentration of frost heave strain, which can increase the frost heaving force at the periphery of the top arch of the lining. This study revealed the distribution pattern and key influencing factors of the freezing cycle and frost heaving force for tunnels, providing a theoretical basis and data reference for the frost resistance design of tunnels in cold regions. Full article

Temperature fluctuations caused by climate change and global warming pose a threat to fish. The burbot (lota lota) population is particularly sensitive to increased water temperature, but the systematic impacts of high-temperature exposure on their liver and intestinal health remain unclear. In January of 2025, we collected wild adult burbot individuals from the Ussuri River (water temperature: about 2 °C), China. The burbot were exposed to 2 °C, 7 °C, 12 °C, 17 °C, and 22 °C environments for 96 h; then, the liver and intestinal contents were subsequently collected for histopathology observation, immunohistochemistry, biochemical index assessment, and transcriptome/16S rDNA sequencing analysis. There was obvious liver damage including hepatocyte necrosis, fat vacuoles, and cellular peripheral nuclei. Superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) activities were elevated and subsequently decreased. Additionally, the malondialdehyde (MDA) level significantly increased with increasing temperature. These results indicate that 7 °C (heat stress temperature), 12 °C (tipping point for normal physiological metabolism status), 17 °C (tipping point for individual deaths), and 22 °C (thermal limit) are critical temperatures in terms of the physiological response of burbot during their breeding period. In the hepatic transcriptome profiling, 6538 differentially expressed genes (DEGs) were identified, while KEGG enrichment analysis showed that high-temperature stress could affect normal liver function by regulating energy metabolism, immune, and apoptosis-related pathways. Microbiomics also revealed that acute heat stress could change the intestinal microbe community structure. Additionally, correlation analysis suggested potential regulatory relationships between intestinal microbe taxa and immune/apoptosis-related DEGs in the liver. This study revealed the potential impact of environmental water temperature changes in cold habitats in winter on the physiological adaptability of burbot during the breeding period and provides new insights for the ecological protection of burbot in the context of global climate change and habitat warming. Full article

The Mediterranean region, identified by scientists as a ‘climate hot spot’, is experiencing warmer and drier conditions, along with an increase in the intensity and frequency of extreme weather events. One such extreme phenomena is droughts. The recent wildfires in this region are a concerning consequence of this phenomenon, causing severe environmental damage and transforming natural landscapes. However, droughts involve a two-way interaction: On the one hand, climate change and various human activities, such as urbanization and deforestation, influence the development and severity of droughts. On the other hand, droughts have a significant impact on various sectors, including ecology, agriculture, and the local economy. This study investigates drought dynamics in four Mediterranean countries, Greece, France, Italy, and Spain, each of which has experienced severe wildfire events in recent years. Using satellite-based Earth observation data, we monitored drought conditions across these regions over a five-year period that includes the dates of major wildfires. To support this analysis, we derived and assessed key indices: the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI). High-resolution satellite imagery processed within the Google Earth Engine (GEE) platform enabled the spatial and temporal analysis of these indicators. Our findings reveal that, in all four study areas, peak drought conditions, as reflected in elevated NDDI values, were observed in the months leading up to wildfire outbreaks. This pattern underscores the potential of satellite-derived indices for identifying regional drought patterns and providing early signals of heightened fire risk. The application of GEE offered significant advantages, as it allows efficient handling of long-term and large-scale datasets and facilitates comprehensive spatial analysis. Our methodological framework contributes to a deeper understanding of regional drought variability and its links to extreme events; thus, it could be a valuable tool for supporting the development of adaptive management strategies. Ultimately, such approaches are vital for enhancing resilience, guiding water resource planning, and implementing early warning systems in fire-prone Mediterranean landscapes. Full article