Search Results (6,296)

The Tibetan Plateau (TP) is experiencing higher warming rates than elsewhere, which may affect regional vegetation growth. Particularly on the Eastern Tibetan Plateau (ETP), where the topography is diverse and rich in biodiversity, it is necessary to clarify the drivers of climate and topography on vegetation cover. In this research, we selected the Shaluli Mountains (SLLM) in the ETP as the study area, monitored the spatial and temporal dynamics of the regional vegetation cover using remote sensing methods, and quantified the drivers of vegetation change using Geodetector (GD). The results showed a decreasing trend in annual precipitation (PRE) (−2.4054 mm/year) and the Palmer Drought Severity Index (PDSI) (−0.1813/year) in the SLLM. Annual maximum temperature (TMX) on the spatial and temporal scales showed an overall increasing trend, and the regional climate tended to become warmer and drier. Since 2000, fractional vegetation cover (FVC) has shown a fluctuating upward trend, with an average value of 0.6710, and FVC has spatially shown a pattern of “low in the middle and high in the surroundings”. The areas with non-significant increases (p > 0.05) and significant increases (p < 0.05) in FVC accounted for 46.03% and 5.76% of the SLLM. Altitude (q = 0.3517) and TMX (q = 0.3158) were the main drivers of FVC changes. As altitude and TMX increased, FVC showed a trend of increasing and then decreasing. The results of this study help us to clarify the influence of climate and topography on the vegetation ecosystem of the ETP and provide a scientific basis for regional biodiversity conservation and sustainable development. Full article

As urbanization processes are no longer characterized by simple linear expansion but exhibit leaping, edge-sparse, and discontinuous features, spatiotemporally continuous impervious surface coverage data are needed to better characterize urbanization processes. This study utilized GAIA impervious surface binary data and employed spatiotemporal aggregation methods to convert thirty years of 30 m resolution data into 1 km resolution spatiotemporal impervious surface coverage data, constructing a long-term time series annual impervious surface coverage dataset for the Beijing–Tianjin–Hebei region. Based on this dataset, we analyzed urban expansion processes and landscape pattern indices in the Beijing–Tianjin–Hebei region, exploring the spatiotemporal response relationships of ecological environment changes. Results revealed that the impervious surface area increased dramatically from 7579.3 km² in 1985 to 37,484.0 km² in 2020, representing a year-on-year growth of 88.5%. Urban expansion rates showed two distinct peaks: 800 km²/year around 1990 and approximately 1700 km²/year during 2010–2015. In high-density urbanized areas with impervious surfaces, the average forest area significantly increased from approximately 2500 km² to 7000 km² during 1985–2005 before rapidly declining, grassland patch fragmentation intensified, while in low-density areas, grassland area showed fluctuating decline with poor ecosystem stability. Furthermore, by incorporating natural and social factors such as Fractional Vegetation Coverage (FVC), Habitat Quality Index (HQI), Land Surface Temperature (LST), slope, and population density, we assessed the vulnerability of urbanization development in the Beijing–Tianjin–Hebei region. Results showed that high vulnerability areas (EVI > 0.5) in the Beijing–Tianjin core region continue to expand, while the proportion of low vulnerability areas (EVI < 0.25) in the northern mountainous regions decreased by 4.2% in 2020 compared to 2005. This study provides scientific support for the sustainable development of the Beijing–Tianjin–Hebei urban agglomeration, suggesting location-specific and differentiated regulation of urbanization processes to reduce ecological risks. Full article

This study analyzes spatiotemporal aridity dynamics in Central Kazakhstan (1960–2022) using a monthly Aridity Index (AI = P/PET), where P is precipitation and PET is potential evapotranspiration, Mann–Kendall trend analysis, and climate zone classification. Results reveal a northeast–southwest aridity gradient, with Aridity Index ranging from 0.11 to 0.14 in southern deserts to 0.43 in the Kazakh Uplands. Between 1960–1990 and 1991–2022, southern regions experienced intensified aridity, with Aridity Index declining from 0.12–0.15 to 0.10–0.14, while northern mountainous areas became more humid, where Aridity Index increased from 0.40–0.44 to 0.41–0.46. Seasonal analysis reveals divergent patterns, with winter showing improved moisture conditions (52.4% reduction in arid lands), contrasting sharply with aridification in spring and summer. Summer emerges as the most extreme season, with hyper-arid zones (8%) along with expanding arid territories (69%), while autumn shows intermediate conditions with notable dry sub-humid areas (5%) in northwestern regions. Statistical analysis confirms these observations, with northern areas showing positive Aridity Index trends (+0.007/10 years) against southwestern declines (−0.003/10 years). Key drivers include rising temperatures (with recent degradation) and variable precipitation (long-term drying followed by winter and spring), and PET fluctuations linked to temperature. Since 1991, arid zones have expanded from 40% to 47% of the region, with semi-arid lands transitioning to arid, with a northward shift of the boundary. These changes are strongly seasonal, highlighting the vulnerability of Central Kazakhstan to climate-driven aridification. Full article

With the global economic restructuring and the consequent population mobility, urban shrinkage has become a common phenomenon. The Qinling–Daba Mountains, a zone with a key ecological function in China, have long experienced population decline and functional degradation. Clarifying the dynamics and influencing factors of urban shrinkage plays a vital role in supporting the sustainable development of the region. This study, using permanent resident population growth rates and nighttime light data, classified cities in the region into four spatial patterns: expansion–growth, intensive growth, expansion–shrinkage, and intensive shrinkage. It further examined the spatial characteristics of shrinkage across four periods (2005–2010, 2010–2015, 2015–2020, and 2020–2022). A Geographically and Temporally Weighted Regression (GTWR) model was applied to examine core influencing factors and their spatiotemporal heterogeneity. The results indicated the following: (1) The dominant pattern of urban shrinkage in the Qinling–Daba Mountains shifted from expansion–growth to expansion–shrinkage, highlighting the paradox of population decline alongside continued spatial expansion. (2) Three critical indicators significantly influenced urban shrinkage: the number of students enrolled in general secondary schools (X₅), the per capita disposable income of urban residents (X₇), and the number of commercial and residential service facilities (X₁₂), with their effects exhibiting significant spatiotemporal heterogeneity. Temporally, X₁₂ was the most influential factor in 2005 and 2010, while in 2015, 2020, and 2022, X₅ and X₇ became the dominant factors. Spatially, X₇ significantly affected both eastern and western areas; X₅’s influence was most pronounced in the west; and X₁₂ had the greatest impact in the east. This study explored the patterns and underlying drivers of urban shrinkage in underdeveloped areas, aiming to inform sustainable development practices in regions facing comparable challenges. Full article

For further investigation of the properties of the muon component in the core regions of extensive air showers (EASs), a new underground hodoscopic set-up with a total sensitive area of 22 m² was built at the Tien Shan High Mountain Cosmic Ray Station. The hodoscope is based on a set of large-sized scintillation charged particle detectors with an output signal of analog type. The installation ensures a (5–8) GeV energy threshold of muon registration and a ∼${10}^4$ dynamic range for the measurement of the density of muon flux. A program facility was designed that uses modern machine learning techniques for automated search for the typical scintillation pulse pattern in an oscillogram of a noisy analog signal at the output of the hodoscope detector. The program provides a ∼99% detection probability of useful signals, with a relative share of false positives below 1%, and has a sufficient operation speed for real-time analysis of incoming data. Complete verification of the hardware and software tools was performed under realistic operation conditions, and the results obtained demonstrate the correctness of the proposed method and its practical applicability to the investigation of the muon flux in EASs. In the course of the installation testing, a preliminary physical result was obtained concerning the rise of the multiplicity of muon particles around an EAS core in dependence on the primary EAS energy. Full article

This article presents a comprehensive assessment of mudflow risk in the Talgar River basin through the application of Multi-Criteria Decision Analysis (MCDA) methods and numerical modeling using the Rapid Mass Movement Simulation (RAMMS) environment. The first part of the study involves a spatial assessment of mudflow hazard and susceptibility using GIS technologies and MCDA. The key condition for evaluating mudflow hazard is the identification of factors influencing the formation of mudflows. The susceptibility assessment was based on viewing the area as an object of spatial and functional analysis, enabling determination of its susceptibility to mudflow impacts across geomorphological zones: initiation, transformation, and accumulation. Relevant criteria were selected for analysis, each assigned weights based on expert judgment and the Analytic Hierarchy Process (AHP). The results include maps of potential mudflow hazard and susceptibility, showing areas of hazard occurrence and risk impact zones within the Talgar River basin. According to the mudflow hazard map, more than 50% of the basin area is classified as having a moderate hazard level, while 28.4% is subject to high hazard, and only 1.8% falls under the very high hazard category. The remaining areas are categorized as very low (4.1%) and low (14.7%) hazard zones. In terms of susceptibility to mudflows, 40.1% of the territory is exposed to a high level of susceptibility, 35.6% to a moderate level, and 5.5% to a very high level. The remaining areas are classified as very low (1.8%) and low (15.6%) susceptibility zones. The predictive performance was evaluated through Receiver Operating Characteristic (ROC) curves, and the Area Under the Curve (AUC) value of the mudflow hazard assessment is 0.86, which indicates good adaptability and relatively high accuracy, while the AUC value for assessing the susceptibility of the territory is 0.71, which means that the accuracy of assessing the susceptibility of territories to mudflows is within the acceptable level of model accuracy. To refine the spatial risk assessment, mudflow modeling was conducted under three scenarios of glacial-moraine lake outburst using the RAMMS model. For each scenario, key flow parameters—height and velocity—were identified, forming the basis for classification of zones by impact intensity. The integration of MCDA and RAMMS results produced a final mudflow risk map reflecting both the likelihood of occurrence and the extent of potential damage. The presented approach demonstrates the effectiveness of combining GIS analysis, MCDA, and physically-based modeling for comprehensive natural hazard assessment and can be applied to other mountainous regions with high mudflow activity. Full article

The cessation of traditional mountain grazing has emerged as a principal driver of habitat degradation and the local extinction of Parnassius apollo (Linnaeus, 1758) in Serbia. While previous studies have cited multiple contributing factors, our research provides evidence that the abandonment of extensive livestock grazing has triggered vegetation succession, the disappearance of the larval host plant (Sedum album), and a reduction in microhabitat heterogeneity—conditions essential for the persistence of this stenophagous butterfly species. Through satellite-based analysis of vegetation dynamics (2015–2024), we identified clear structural differences between habitats that currently support populations and those where the species is no longer present. Occupied sites were characterized by low levels of exposed soil, moderate grass coverage, and consistently high shrub and tree density, whereas unoccupied sites exhibited dense encroachment of grasses and woody vegetation, leading to structural instability. Furthermore, MODIS-derived indices (2010–2024) revealed a consistent decline in vegetation productivity (GPP, FPAR, LAI) in succession-affected areas, alongside significant correlations between elevated land surface temperatures (LST), thermal stress (TCI), and reduced photosynthetic capacity. A wildfire event on Mount Stol in 2024 further exacerbated habitat degradation, as confirmed by remote sensing indices (BAI, NBR, NBR2), which documented extensive burn scars and post-fire vegetation loss. Collectively, these findings indicate that the decline of P. apollo is driven not only by ecological succession and climatic stressors, but also by the abandonment of land-use practices that historically maintained suitable habitat conditions. Our results underscore the necessity of restoring traditional grazing regimes and integrating ecological, climatic, and landscape management approaches to prevent further biodiversity loss in montane environments. Full article

The population dynamics of high-altitude mountainous areas are shaped by a complex interplay of socioeconomic and environmental drivers. Despite their significance, such regions have received limited scholarly attention. This research identifies and examines the principal determinants of population changes in the high-altitude mountainous zones of Sichuan Province, China. Utilizing a robust quantitative framework, we introduce the Sustainable Population Migration Index (SPMI) to systematically analyze the migration potential over two decades. The findings indicate healthcare accessibility as the most significant determinant influencing resident and rural population changes, while economic factors notably impact urban populations. The SPMI reveals a pronounced deterioration in migration attractiveness, decreasing by 0.27 units on average from 2010 to 2020. Furthermore, a fixed-effects panel regression confirmed the predictive capability of SPMI regarding population trends, emphasizing its value for demographic forecasting. We also develop a Digital Twin-based Simulation and Decision-support Platform (DTSDP) to visualize policy impacts effectively. Scenario simulations suggest that targeted enhancements in healthcare and infrastructure could significantly alleviate demographic pressures. This research contributes critical insights for sustainable regional development strategies and provides an effective tool for informed policymaking. Full article

To study the generation and dissipation process of agglomerate fog in mountainous expressways and deeply understand the hazard mechanisms of agglomerate fog sections in mountainous expressways, based on the analysis of the geographical location characteristics of mountainous expressways and the spatial and temporal distribution characteristics of agglomerate fog, the airspace constitutive model of agglomerate fog in mountainous expressways was constructed based on Newton constitutive theory. Firstly, the properties of the Newtonian fluid and cluster fog were compared and analyzed, and the influence mechanism of environmental factors such as the altitude difference, topography, water system, valley effect, and vegetation on the generation and dissipation of agglomerate fog in mountainous expressways was analyzed. Based on Newton’s constitutive theory, the constitutive model of temperature, humidity, wind speed, and agglomerate fog points in the foggy airspace of the mountainous expressway was established. Then, the time and spatial distribution of fog in Chongqing and Guizhou from 2021 to 2023 were analyzed. Finally, the model was verified by using the meteorological data and fog warning data of Liupanshui City, Guizhou Province in 2023. The results show that the foggy airspace of mountainous expressways can be defined as “the space occupied by the agglomerate fog that occurs above the mountain expressway”; The temporal and spatial distribution of foggy airspace on expressways in mountainous areas is closely related to the topography, water system, vegetation distribution, and local microclimate formed by thermal radiation. The horizontal and vertical movements of the atmosphere have little influence on the foggy airspace on expressways in mountainous areas. The specific manifestation of time distribution is that the occurrence of agglomerate fog is concentrated from November to April of the following year, and the daily occurrence time is mainly concentrated between 4:00–8:00 and 18:00–22:00. The calculation results of the foggy airspace constitutive model of the expressway in the mountainous area show that when there is low surface radiation or no surface radiation, the fogging value range is [90, 100], and the fogging value range is [50, 70] when there is high surface radiation (>200), and there is generally no fog in other intervals. The research results can provide a theoretical basis for traffic safety management and control of mountainous expressway fog sections. Full article

This paper investigates how governance frameworks shape sustainable tourism outcomes in protected areas by comparing Tara National Park (Serbia) and Triglav National Park (Slovenia). Both parks, established in 1981 and classified under IUCN Category II, exhibit rich biodiversity and mountainous terrain but differ markedly in governance structures, institutional integration, and local community engagement. Using a qualitative, indicator-based methodology, this research evaluates ecological, economic, and social dimensions of sustainability. The findings reveal that Triglav NP demonstrates higher levels of participatory governance, tourism integration, and educational outreach, while Tara NP maintains stricter ecological protection with less inclusive management. Triglav’s zoning model, community council, and economic alignment with regional development policies contribute to stronger sustainability outcomes. Conversely, Tara NP’s centralized governance and infrastructural gaps constrain its potential despite its significant conservation value. This study highlights the importance of adaptive, inclusive governance in achieving the Sustainable Development Goals (SDGs) within protected areas. It concludes that hybrid approaches, combining legal rigor with participatory flexibility, can foster resilience and sustainability in ecologically sensitive regions. Full article

Situated in the southern hilly-mountain belt of China’s “Three Zones and Four Belts Strategy”, Gannan region is a critical ecological shelter belt for the Ganjiang River. Decades of intensive mineral extraction and irrational agricultural development have rendered it into an ecologically fragile area. Consequently, multiple restoration initiatives have been implemented in the region over recent decades. However, it remains unclear how relationships among ecosystem services have evolved under these interventions and how future ecosystem management should be optimized based on these changes. Thus, in this study, we simulated and assessed the spatiotemporal dynamics of five key ESs in Gannan region from 1990 to 2020. Through integrated correlation, clustering, and redundancy analyses, we quantified ES interactions, tracked the evolution of ecosystem service bundles (ESBs), and identified their socio-ecological drivers. Despite a 31% decline in water yield, ecological restoration initiatives drove substantial improvements in key regulating services: carbon storage increased by 6.9 × 10¹² gC while soil conservation rose by 4.8 × 10⁸ t. Concurrently, regional habitat quality surged by 45% in mean scores, and food production increased by 2.1 × 10⁵ t. Critically, synergistic relationships between habitat quality, soil retention, and carbon storage were progressively strengthened, whereas trade-offs between food production and habitat quality intensified. Further analysis revealed that four distinct ESBs—the Agricultural Production Bundle (APB), Urban Development Bundle (UDB), Eco-Agriculture Transition Bundle (ETB), and Ecological Protection Bundle (EPB)—were shaped by slope, forest cover ratio, population density, and GDP. Notably, 38% of the ETB transformed into the EPB, with frequent spatial interactions observed between the APB and UDB. These findings underscore that future ecological restoration and conservation efforts should implement coordinated, multi-service management mechanisms. Full article

The Santurbán paramo is a sensitive high-mountain ecosystem exposed to pressures from extractive and agricultural activities, as well as increasing tourism. In response, this study presents a context-aware recommendation system designed to support sustainable tourism through the integration of deep neural networks and ontology-based semantic modeling. The proposed system delivers personalized recommendations—such as activities, accommodations, and ecological routes—by processing user preferences, geolocation data, and contextual features, including cost and popularity. The architecture combines a trained TensorFlow Lite model with a domain ontology enriched with GeoSPARQL for geospatial reasoning. All inference operations are conducted locally on Android devices, supported by SQLite for offline data storage, which ensures functionality in connectivity-restricted environments and preserves user privacy. Additionally, the system employs geofencing to trigger real-time environmental notifications when users approach ecologically sensitive zones, promoting responsible behavior and biodiversity awareness. By incorporating structured semantic knowledge with adaptive machine learning, the system enables low-latency, personalized, and conservation-oriented recommendations. This approach contributes to the sustainable management of natural reserves by aligning individual tourism experiences with ecological protection objectives, particularly in remote areas like the Santurbán paramo. Full article

In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects. Full article

Karst groundwater systems are critical to water supply and ecological sustainability in northern China, yet their heterogeneity poses challenges for flow characterization. The Yuquan Mountain (YM) Spring, historically a major karst spring in western Beijing, has experienced persistent drying, raising concerns about its recharge and flow mechanisms. This study integrates published isotope data, spatial distributions of Na⁺ and Cl⁻ as hydrochemical tracers, groundwater age estimates, and geophysical survey results to assess the recharge sources and flow pathways within the YM Spring catchment area. The analysis identifies two major recharge zones: the Tanzhesi area, primarily recharged by direct infiltration of precipitation through exposed carbonate rocks, and the Junzhuang area, which receives mixed recharge from rainfall and Yongding River seepage. Three potential flow pathways are proposed, including shallow flow along faults and strata, and a deeper, speculative route through the Jiulongshan-Xiangyu syncline. The synthesis of multiple lines of evidence leads to a refined conceptual model that illustrates how geological structures govern recharge, flow, and discharge processes in this karst system. These findings not only enhance the understanding of subsurface hydrodynamics in complex geological settings but also provide a scientific basis for future spring restoration planning and groundwater management strategies in the regions. Full article

During the period from 2020 to 2024, 900 springs were mapped on the southern slopes of Medvednica Mountain Nature Park. Physicochemical parameters (temperature, pH, and electrical conductivity) were measured at 701 of these springs using a portable multimeter, and results were analyzed in relation to local lithology and human activities. This research provides the first results of this kind in this study area, aiming to expand the knowledge on local springs and to support the future protection and management of spring ecosystems. Springs on the Medvednica mountain showed substantial variation in measured parameters. The temperature ranged from 3.4 to 18.9 °C, reflecting local hydrological conditions, aquifer characteristics, and seasonal variability. Electrical conductivity (EC) ranged between 41 μS/cm and 2062 μS/cm, determined by both hydrogeological settings and anthropogenic impacts such as winter road salting. The pH values showed moderate variability, remaining mostly within neutral levels. These results emphasize the importance of continued monitoring and further research of Medvednica springs, in order to highlight their importance and to preserve their ecological and hydrological roles. Full article