Search Results (221)

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

Century-long land-use practices have a profound impact on soil physical and chemical properties, with direct implications for soil health and agricultural sustainability. This study aimed to assess the effects of four contrasting land uses—remnant vegetation, pasture, cultivated areas, and loafing areas—on the physical and chemical properties of Red Ferrosols in the Toowoomba region, Queensland, Australia. Soil samples were collected from upper and lower slope positions for each land use. Physical properties, including bulk density, porosity, water retention, and permeability, as well as chemical properties such as organic carbon, nitrogen, phosphorus, and potassium, were analysed. The results showed that remnant vegetation preserved the most favourable soil conditions, with lower bulk density, higher porosity, and greater water retention. Cultivated areas exhibited significant soil degradation, marked by compaction, reduced infiltration, and depleted organic matter. Loafing areas displayed localised nutrient enrichment but higher compaction due to livestock trampling. Pastures maintained intermediate conditions, retaining some beneficial soil characteristics. These findings emphasise the critical need for sustainable land management strategies to protect soil structure and function, supporting the long-term productivity and resilience of Red Ferrosols. Full article

Grass-covered levees commonly protect river and estuarine areas against flooding. Climate-induced water level changes may increasingly expose these levees to overflow events. This study investigates whether grass-covered levees can withstand such events, and under what conditions failure may occur. Between 2020 and 2022, full-scale overflow tests were conducted at the Living Lab Hedwige-Prosperpolder along the Dutch–Belgian Scheldt Estuary to assess erosion resistance under varying hydraulic conditions and vegetation states. A custom-built overflow generator was used, with instrumentation capturing flow velocity, water levels, and erosion progression. The results show that well-maintained levees with intact grass cover endured overflow durations up to 30 h despite high terminal flow velocities (4.9–7.7 m/s), without structural damage. In contrast, levee sections with pre-existing surface anomalies, such as animal burrows, slope irregularities, surface damage, or reed-covered soft soils, failed rapidly, often within one to two hours. Animal burrows facilitated subsurface flow and internal erosion, initiating fast, retrograde failure. These findings highlight the importance of preventive maintenance, particularly the timely detection and repair of anomalies. Once slope failure begins, the process unfolds rapidly, leaving no practical window for intervention. Full article

Climate change and declining economic revenues are driving the closure of many ski resorts in mountainous regions worldwide, particularly at lower elevations, where winter snow cover is becoming increasingly sporadic. This abandonment is impacting wide areas of the Alps, previously managed to reduce erosion and to control trees/shrubs encroachment. As result, natural rewilding processes may lead either to the environmental degradation or to the restoration of pre-disturbance conditions, each with different implications for sustainability. Our aim was to assess the rewilding state and the drivers of sustainability at an abandoned ski resort in the Italian Alps (Valcanale, Bergamo), where the ecosystem has been evolving under minimal human pressure since the ski facilities were decommissioned in 1993. The assessment focused on pedological/vegetational perspectives, with particular attention to soil-based ecosystem services (SBESs). The results show that the interventions made during ski run construction significantly influenced the recovery of SBESs (and thus their long-term sustainability). Areas with minimal disturbance (e.g., forest vegetation removal without soil movement) now support SBESs at levels comparable to nearby undisturbed areas. Conversely, ski runs that underwent slope reshaping/grading support poorly developed soils and significant sheet/gully erosion, rendering them hazardous for pedestrians. Nevertheless, plant biodiversity has benefited in some cases, as many rare/endemic protected species colonize stony/eroded ski runs soils, extending their distribution beyond their original habitat. Full article

In this study, we investigate the impact of soil moisture at varying depths on the stability of Chinese ecosystems, with ecosystem stability assessed using the Enhanced Vegetation Index (EVI) and Gross Primary Productivity (GPP). A multi-perspective analysis is conducted across different climatic zones and land cover types. Sen’s Slope Estimation and the Mann–Kendall trend test, combined with linear regression and correlation analyses, are employed to analyze the long-term trends of EVI and GPP in different climatic zones and land cover types and to assess the effects of soil moisture changes on ecosystem stability. The research reveals the following findings: (1) On a national scale, both EVI and GPP exhibit positive growth trends, with more significant increases in humid areas and relatively slower growth in arid areas. In addition, EVI and GPP of different land cover types exhibit positive inter-annual variation trends, reflecting a gradual enhancement in ecosystem productivity. (2) Cluster analysis shows that EVI has strong spatial correlation, with a distribution pattern of low–low (L-L) clusters in the north and high–high (H-H) clusters in the south. L-H clusters are concentrated in the Huaihai, Southwest Rivers, and Pearl River basins, while H-L clusters are scattered along the eastern coast. The spatial correlation of GPP is mainly concentrated in the south and the northeast, with a distribution pattern of L-L in the northeast, L-H in the Yangtze River basin, and H-H in the south. H-L clusters are dispersed in the downstream area of the Yangtze River. Both EVI and GPP show a tendency for high-value aggregation in space, with high-value areas of EVI located in the south and low-value areas in the central and western regions. High-value areas of GPP are in the south, while low-value areas are in the northeast, particularly in the Yangtze River Delta. (3) The correlation between EVI, GPP, and soil moisture varies significantly across different climatic regions. Arid and semi-humid regions show significant correlations between specific soil moisture depths and EVI and GPP, while such correlations are not significant in humid regions. The EVI and GPP values of croplands and grasslands are significantly and negatively correlated with soil moisture at depths of 150–200 cm (SM4). Conversely, wetland GPP values increase significantly with increasing soil moisture. Other vegetation types do not show significant correlations with soil moisture. The results of this study provide an important basis for understanding the impact of climate change on ecosystem stability and offer scientific guidance for ecological protection and water resource management. Full article

Natural restoration of vegetation and plantation are effective land use measures to promote soil organic carbon (SOC) sequestration. How soil physicochemical properties, microorganisms, Glomalin-related soil proteins (GRSPs), and aggregates interact to regulate SOC accumulation and sequestration remains unclear. This study examined five land uses in the karst region of Southwest China: corn field (CF), corn intercropped with cabbage fields (CICF), orchard (OR), plantation (PL), and natural restoration of vegetation (NRV). The results revealed that SOC, total nitrogen (TN), total phosphorus (TP), total GRSP (T-GRSP), and easily extractable GRSP (EE-GRSP) contents were significantly higher under NRV and PL than in the CF, CICF, and OR, with increases ranging from 10.69% to 266.72%. Land use significantly influenced bacterial α-diversity, though fungal α-diversity remained unaffected. The stability of soil aggregates among the five land uses followed the order: PL > NRV > CF > OR > CICF. Partial least-squares path modeling (PLS-PM) identified land use as the most critical factor influencing SOC. SOC accumulation and stability were enhanced through improved soil properties, increased microbial diversity, and greater community abundance, promoting GRSP secretion and strengthening soil aggregate stability. In particular, soil microorganisms adhere to the aggregates of soil particles through the entanglement of fine roots and microbial hyphae and their secretions (GRSPs, etc.) to maintain the stability of the aggregates, thus protecting SOC from decomposition. Natural restoration of vegetation and plantation proved more effective for soil carbon sequestration in the karst region of Southwest China compared to sloping cropland and orchards. Full article

Drought stress is a crucial factor limiting plant survival and growth, especially during the seedling establishment stage. A deep understanding of different plants’ responses to drought stress and their drought resistance is of great significance for vegetation restoration under drought conditions. This study selected one-year-old seedlings of Winter Jasmine (Jasminum nudiflorum), Oleander (Nerium oleander), Privet (Ligustrum lucidum), and Redleaf Photinia (Photinia × fraseri) as research objects. Through pot experiments, we investigated the physiological and biochemical responses of these shrubs under different levels of drought stress (control, mild, moderate, and severe drought stress, corresponding to 75%, 60%, 45%, and 30% of field maximum water holding capacity) to comprehensively assess their drought resistance capabilities. The research results indicated that as the level of drought stress increased, significant changes (p < 0.05) occurred in the physiological and biochemical indicators of all four plant species. The chlorophyll content (Chla+b) of Winter Jasmine and Redleaf Photinia gradually decreased with the intensification of stress, while the Chla+b of Oleander showed the most significant decline under moderate stress and Privet was most affected under mild stress. The proline (Pro) and soluble sugar (SS) contents of all four plants exhibited an upward trend, suggesting that the plants coped with drought stress by accumulating these osmoregulatory substances. Drought stress led to damage to plant cell membranes, manifested by an increase in malondialdehyde content (MDA), with Winter Jasmine showing the most pronounced increase. The activities of peroxidase (POD) and superoxide dismutase (SOD) in the four plant species responded differently to drought stress: the POD activity of Oleander and Redleaf Photinia increased with the deepening of stress, while that of Winter Jasmine and Privet decreased. A comprehensive evaluation of the drought tolerance of the four plant species was performed using principal component analysis and affiliation function value methods. The drought tolerance of the four shrubs, from strongest to weakest, was as follows: Redleaf Photinia > Oleander > Privet > Winter Jasmine. This finding provides valuable insights for plant selection in ecological slope protection projects, and Redleaf Photinia and Oleander can be promoted for use in vegetation restoration work under drought conditions. Full article

An urban heat island (UHI) refers to urban areas that experience higher temperatures due to heat absorption and retention by impervious surfaces compared to the surrounding rural areas. Urban wetlands are crucial in mitigating the UHI effect and improving climate resilience via their cooling effect. This study examines Colombo, Sri Lanka, the RAMSAR-accredited wetland city in South Asia, to assess the cooling effect of urban wetlands based on 2023 dry season data for effective sustainable management. We used Landsat 8 and 9 data to create Land Use/Cover (LUC), Land Surface Temperature (LST), and surface-reflectance-based maps using the Google Earth Engine (GEE). The Enhanced Vegetation Index (EVI), Modified Normalized Difference Water Index (mNDWI), topographic wetness, elevation, slope, and impervious surface percentage were identified as the influencing variables. The results show that urban wetlands in Colombo face tremendous pressure due to rapid urban expansion. The cooling intensity positively correlates with wetland size. The threshold value of efficiency (TVoE) of urban wetlands in Colombo was 1.42 ha. Larger and more connected wetlands showed higher cooling effects. Vegetation- and water-based wetlands play an important role in <10 km urban areas, while more complex shape configuration wetlands provide better cooling effects in urban and peri-urban areas due to edge effects. Urban planners should prioritize protecting wetland areas and ensuring hydrological connectivity and interconnected wetland clusters to maximize the cooling effect and sustain ecosystem services in rapidly urbanizing coastal cities. Full article

The China Baijiu Golden Triangle (BGT) serves as the core production hub of China’s Baijiu industry, where the ecological environment plays a pivotal role in ensuring the industry’s sustainable development. However, urbanization, industrial expansion, and climate change pose potential threats to the region’s vegetation dynamics. Utilizing Landsat remote sensing data from 2002 to 2022, this study integrates Theil–Sen trend analysis, the Mann–Kendall (MK) test, coefficient of variation (CV) analysis, and the Geodetector model (GD model) to investigate the spatiotemporal evolution of the Normalized Difference Vegetation Index (NDVI) and its underlying driving mechanisms within the BGT. The findings reveal an overall upward trend in vegetation NDVI, with the annual mean NDVI increasing from 0.45 to 0.67, corresponding to a growth rate of 0.49%. Spatially, areas of high vegetation cover are predominantly located in mountainous forest zones with favorable ecological conditions, whereas regions of low vegetation cover are concentrated in zones of urban expansion. Precipitation and topographic factors (elevation and slope) emerge as the primary natural drivers of vegetation change, while land use change and the night-time light index stand out as the most influential human-induced factors. Further analysis uncovers a nonlinear interactive enhancement effect between natural and anthropogenic factors, with the interaction between the night-time light index and precipitation being particularly pronounced. This suggests that urbanization not only directly impacts vegetation but may also exert indirect effects on the ecosystem by altering regional hydrological and climatic processes. The results indicate that ecological protection policies in the BGT have yielded some success; however, vegetation fragmentation and ecological pressures stemming from urban expansion remain significant challenges. Moving forward, optimizing land use policies and promoting eco-friendly development models will be essential to achieving ecosystem stability and sustaining industrial growth. Full article

As an important ecological security barrier on the Tibetan Plateau, southeastern Tibet is crucial to maintaining regional carbon balance under climate change. This study innovatively integrates multi-source remote sensing data (Landsat 8, Sentinel-1, and GEDI) on the Google Earth Engine (GEE) platform, and uses machine learning to model forest carbon storage dynamics from 2019 to 2023. The fusion of multi-source data improves forest vertical structure characterization and makes up for the shortage of single optical data. By comparing machine learning algorithms, the Gradient Boosting model performs excellently (validation set R² = 0.909, RMSE = 26.608 Mg/Ha), achieving high-resolution spatiotemporal mapping. The results show significant spatial heterogeneity; the increase in carbon storage in the central and southern regions is mainly in contrast to the scattered decreases in the eastern and western regions, reflecting vegetation restoration and topographic influence. High-altitude areas are subject to climate restrictions and small changes, while low-altitude areas show significant fluctuations due to human activities. Key drivers were elevation (importance score 22.06), slope (17.00), and temperature (22.04). Land use transformation (such as forest expansion) promotes net carbon accumulation and highlights the effectiveness of regional protection policies. This study provides a scientific basis for targeted ecological management of high-altitude ecosystems. Full article

Tall fescue (Festuca arundinacea Schreb.) is a herbaceous species that is commonly used for ecological slope restoration in China. However, water scarcity often constrains its growth due to the unique site conditions of steep slopes and climate-induced drought stress. This study aims to compare the ameliorative effects of silicon nanoparticles (Si NPs) and cellulose nanocrystals (CNCs) on drought stress in tall fescue and to elucidate their underlying mechanisms of action. The results indicated that drought stress impaired photosynthesis, restricted nutrient absorption, and increased oxidative stress, ultimately reducing biomass. However, Si NPs and CNCs enhanced drought tolerance and promoted biomass accumulation by improving photosynthesis, osmotic regulation, and antioxidant defense mechanisms. Specifically, Si NP treatment increased biomass by 48.71% compared to drought-stressed control plants, while CNCs resulted in a 33.41% increase. Transcriptome sequencing further revealed that both nanomaterials enhanced drought tolerance by upregulating genes associated with photosynthesis and antioxidant defense. Additionally, Si NPs improved drought tolerance by stimulating root growth, enhancing nutrient uptake, and improving leaf structure. In contrast, CNCs play a distinct role by regulating the expression of genes related to cell wall synthesis and metabolism. These findings highlight the crucial roles of these two nanomaterials in plant stress protection and offer a sustainable strategy for the maintenance and management of slope vegetation. Full article

This paper focuses on the stability issues of geological and engineering structures and conducts research from two perspectives: the mechanism of slope landslides under micro-seismic action and the cyclic failure behavior of concrete materials. In terms of slope stability, through the combination of model tests and theories, the cumulative effect of circulating micro-seismic waves on the internal damage of slopes was revealed. This research finds that the coupling of micro-vibration stress and static stress significantly intensifies the stress concentration on the slope, promotes the development of potential sliding surfaces and the extension of joints, and provides a scientific basis for the prediction of landslide disasters. This helps protect mountain ecosystems and reduce soil erosion and vegetation destruction. The number of cyclic loads has a power function attenuation relationship with the compressive strength of concrete. After 1200 cycles, the strength drops to 20.5 MPa (loss rate 48.8%), and the number of cracks increases from 2.7 per mm³ to 34.7 per mm³ (an increase of 11.8 times). Damage evolution is divided into three stages: linear growth, accelerated expansion, and critical failure. The influence of load amplitude on the number of cracks shows a threshold effect. A high amplitude (>0.5 g) significantly stimulates the propagation of intergranular cracks in the mortar matrix, and the proportion of intergranular cracks increases from 12% to 65%. Grey correlation analysis shows that the number of cycles dominates the strength attenuation (correlation degree 0.87), and the load amplitude regulates the crack initiation efficiency more significantly (correlation degree 0.91). These research results can optimize the design of concrete structures, enhance the durability of the project, and indirectly reduce the resource consumption and environmental burden caused by structural damage. Both studies are supported by numerical simulation and experimental verification, providing theoretical support for disaster prevention and control and sustainable engineering practices and contributing to ecological environment risk management and the development of green building materials. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

Safety zones protect firefighters from bodily injury and death caused by exposure to dangerous heat levels. These zones are defined by maintaining a safe distance from combustible fuels, a safe separation distance (SSD) derived from flame height. This study aimed to determine safety zones, integrating an existing automated identification-of-safety-zone model with vegetation height derived from a freely available high-resolution global canopy height dataset for Manavgat Forest Management Directorate (FMD) in Türkiye. Flame height, terrain slope, size of a safety zone, and distance to the closest road were also used as input in this model. The results indicated that vegetation height from high-resolution global canopy height offered promising results for determining potential safety zones (SZs) associated with SSD. Integrating the global canopy height dataset into the existing model could assist in determining the safety zone in the absence of lidar. Thus, this spatial model would provide a framework for decision-makers to develop fire prevention and suppression strategies for higher fire risk areas, especially before and during a fire. Full article

Severe soil erosion and land productivity degradation caused by inadequate vegetation cover pose significant challenges to regional ecological protection and sustainable development. To assess changes and variations in soil quality, three sample areas with different distinct texture characteristics were selected from the Pisha sandstone region located northeastern of the Loess Plateau. The total data set (TDS) was determined through sampling experiments, and the minimum data set (MDS) was established using principal component analysis. A Random Forest (RF) machine learning model was applied to predict soil quality distribution. The prediction indices were derived from soil analysis dimensions, mean weight diameter measured via wet sieving, and soil enrichment ratio obtained from slope erosion experiments conducted at the corresponding sampling points. During the RF modeling process, 80% of the total soil quality index (SQI), calculated using TDS and MDS evaluation methods, was allocated for model training. The results indicated that pH, ammonia nitrogen, bulk density, silt content, clay content, soil water content, hygroscopic water content, total phosphorus, soluble calcium, and actinomycetes were identified as the optimal predictors for SQI. Furthermore, the RF model demonstrated superior performance in predicting the regional distribution of SQI, with evaluation metrics including (R² = 0.76–0.78, RMSE = 0.03–0.06, MAE = 0.04–0.09). This study confirms the reliability of RF in simulating SQI within the study area and highlights that, in regions undergoing extensive vegetation restoration and with limited sampling conditions, experimental measurements of soil particles and sediment parameters provide an effective approach for evaluating SQI. Full article