Search Results (781)

Forest structural complexity underpins habitat quality, microclimate buffering, and resilience, yet it remains poorly characterized across the Hindu Kush Himalaya (HKH) where field inventories and airborne LiDAR are difficult to scale across rugged terrain. Conservation planning and protected-area evaluation in the HKH therefore often rely on canopy height or cover proxies that do not directly represent vertical structural organization. Here we develop a repeatable, uncertainty-aware indicator of forest structural complexity from GEDI waveform LiDAR using the Waveform Structural Complexity Index (WSCI) and its prediction intervals. We first define a conservative analysis footprint (“trustable pixels”) by combining a woody-vegetation screen with minimum GEDI sampling support and canopy-stature plausibility, and by excluding the highest-uncertainty tail using a relative prediction-interval criterion. To separate complexity from canopy height, we model the HKH-wide expected WSCI–RH98 relationship and map height-normalized excess complexity (observed minus expected), identifying structural complexity hotspots and coldspots as the upper and lower tails of the excess distribution. Anomaly patterns are strongly organized along elevation and treeline-relevant belts and show coherent departures among ecoregions that persist after stratified adjustment for elevation and mean annual precipitation, indicating additional controls beyond broad environmental gradients. Protected areas exhibit systematically lower hotspot prevalence than surrounding landscapes, and within-elevation comparisons suggest this association is not explained by elevation alone, highlighting the need to interpret protected-area signals in the context of placement and land-use pressure. Overall, the anomaly atlas provides an operational indicator framework to stratify monitoring, prioritize field validation, and support the landscape-scale assessment of structural conditions beyond canopy height across one of the world’s most critical mountain forest systems. Full article

Earthquake-induced landslides in active orogens such as the Nepal Himalaya pose severe threats to lives, infrastructure, and post-disaster recovery. While machine learning (ML) and deep learning (DL) approaches to coseismic landslide susceptibility mapping have advanced considerably, spaceborne interferometric synthetic aperture radar (InSAR) products, particularly line-of-sight (LOS) displacement and coherence-based damage proxy maps (DPMs), remain underutilized in event-based frameworks. This study develops and evaluates a multi-factor coseismic landslide probability model that integrates InSAR-derived deformation metrics with geomorphic and hydrologic predictors to support rapid post-earthquake hazard assessment. Using the 25 April 2015 Mw 7.8 Gorkha earthquake as a case study, LOS displacement was derived from ALOS-2 PALSAR-2 ScanSAR interferometry, and the normalized channel steepness index (K_sn) was computed from a digital elevation model. Fourteen conditioning factors were used to train five architectures: Random Forest (RF), XGBoost, CNN, U-Net, and DeepLabV3. Spatial autocorrelation was mitigated using a leave-one-basin-out three-fold spatial cross-validation strategy, with models evaluated on a patch-based domain comprising 655,360 pixels at a positive-class prevalence of 6.35%, establishing a no-skill AUC-PR baseline of 0.0635. InSAR integration consistently improved model performance under high class imbalance, increasing AUC-PR across all models by 7.8% to 17.3%. Random Forest achieved the highest AUC-PR (0.7940, nearly 12.5 times the baseline) and CSI (0.3027), providing the best balance between landslide recall (88.09%) and non-landslide specificity (88.68%) with the lowest false alarm rate (11.32%). XGBoost attained the highest AUC-ROC (0.9501) but exhibited lower recall (83.73%) and poorer calibration (Brier = 0.1397). Among DL models, DeepLabV3 produced the best-calibrated probabilities (Brier = 0.0693) and the highest CSI (0.2307), while U-Net offered the most balanced DL performance and CNN achieved the highest recall (92.40%) at the expense of elevated false alarms. Permutation feature importance identified K_sn as the dominant predictor, highlighting the strong tectono-geomorphic control on coseismic landslide occurrence. These results demonstrate that integrating InSAR-derived products substantially enhances landslide hazard assessment and supports more reliable rapid response in the Nepal Himalaya. Full article

India, home to 4 biodiversity hotspots, hosts 675 wild species used for nutritional and therapeutic purposes. Wild edible fruits are highly valuable for their rich content of health-beneficial compounds, such as polyphenols, carotenoids, and vitamins. The shift in modern lifestyles has increasingly impacted human health. Several factors contribute to heightened oxidative stress, which underpins the development of non-communicable diseases (NCDs). Endometriosis, one of these conditions influenced by oxidative stress, currently lacks a definitive cure, leaving patients reliant on hormonal and surgical treatments. According to the WHO, 10% of girls and women worldwide are affected by endometriosis, often experiencing severe symptoms. This review explores the role of oxidative stress in the progression of endometriosis, its pathophysiology, and the effects of polyphenols found in wild Himalayan fruits, including various phenolic acids, flavonoids, stilbenes, and lignans. It also examines their synergistic effects with other non-polyphenolic compounds in reducing these biomarkers, such as inflammatory enzymes, pro-inflammatory cytokines, and estrogen receptors, and in modulating pathways like NF-κB, PI3K/AKT, among others, based on preclinical and clinical studies. Additionally, the review highlights key wild fruit species native to the Indian Himalayas, details their nutritional and phytochemical profiles, and assesses their potential, individually and synergistically, as functional foods or nutraceuticals for non-invasive treatment options for endometriosis. Full article

Winter precipitation plays an important role in the Himalayan region. However, its reliable assessment is difficult due to sparse ground precipitation measurements, limited ability to capture heterogeneity, and snowfall undercatch. Recent advances in satellite-based winter precipitation products (SPPs) enable comprehensive, consistent spatial data in this region; however, despite rapid improvements and the increased availability of SPPs, their accuracy is still uncertain. This calls for rigorous evaluation across several regions. This study presents a new SPP evaluation method that extends existing frameworks by adding two additional indicators—spatial correlation and the water balance consistency ratio (WBCR) to create a unified multi-criteria matrix for selecting spatially and hydrologically consistent products from among 11 latest and earlier SPPs from the global satellite mapping of precipitation (GSMaP) and The integrated multi-satellite retrievals for the global precipitation measurement Mission (IMERG) in the Kabul, Dudhkoshi, and Chamkharchu River basins. The results show that the latest non-calibrated product performed significantly better than earlier releases, demonstrating improved ability to capture precipitation events, spatial heterogeneity, and WBCR across all three basins. However, the performance of those SPPs varies substantially across regions. GSMaP gauge-calibrated product performance was more consistent across conventional multi-criteria assessment and WBCR, but their inability to capture spatial heterogeneity limits their applicability for sub-catchment water resource management. On the other hand, IMERG Final V07 (gauge-calibrated) performed exceptionally well across all regions, although its 3.5 month latency limits near-real-time applications. Therefore, GSMaP NRT V08 is suitable for real-time applications, given its short ~4 h latency and relatively good performance across all three basins. Future studies using the selected products will provide reliable information for policymakers and will support water hazard risk reduction. Full article

Sikkim, located in the northeastern Himalaya, is highly vulnerable to natural hazards and increasing depletion of surface and subsurface water resources, particularly springs and lakes. In South Sikkim, several lakes exhibit rapid drainage behavior, among which Nagi Lake shows near-complete water loss shortly after rainfall, indicating the presence of subsurface leakage pathways. This study investigates shallow subsurface moisture dynamics and identifies potential seepage-prone zones beneath the Nagi Lake basin using geoelectrical methods. Electrical resistivity profiling was conducted along seven survey lines during the non-rainy season (October–November 2025) to minimize the influence of transient rainfall-induced moisture variations. Profiling was carried out using the Wenner method, achieving investigation depths of approximately 6.5–9 m. Additionally, Vertical Electrical Sounding (VES) using the Schlumberger configuration was performed at selected locations to examine deeper subsurface conditions. Resistivity results indicate that profiles L1, L2, L3, L4, and L7 contain relatively higher moisture restricted to the upper ~5 m, whereas profiles L5 and L6 exhibit persistently low resistivity values from the surface to depths of ~9 m, suggesting sustained subsurface moisture accumulation. The downward extension of low-resistivity zones along L5 and L6 indicates possible preferential seepage pathways or localized subsurface water storage. VES results further reveal a higher density of subsurface anomalies below ~14 m in these areas. These low-resistivity anomalies are interpreted as potential subsurface flow pathways. Although confirmation of active seepage requires additional hydrological or time-lapse investigations, the findings provide important baseline geophysical insights for lake rejuvenation. Full article

Background: HIMALAYA demonstrated that STRIDE (Single Tremelimumab Regular Interval Durvalumab) significantly improved overall survival (OS) compared with sorafenib in participants with unresectable hepatocellular carcinoma (HCC). This retrospective, real-world cohort study evaluated outcomes with STRIDE in veterans with HCC. Methods: Patients diagnosed with HCC between 1 January 2008 and 28 February 2024 who received ≥1 dose of STRIDE for unresectable disease were included. Data were collected from the Veteran Affairs Corporate Data Warehouse. Safety and efficacy were evaluated overall and for subgroups of patients with Child–Pugh A versus Child–Pugh B cirrhosis, viral versus non-viral HCC, and those with versus without prior non-systemic therapies. Results: Overall, 107 patients (100.0% male) were included. Median (interquartile range) age was 72.2 (68.0–76.1) years. There were 22 Grade 3–4 adverse events reported (three in patients with Child–Pugh B cirrhosis). Median OS (95% CI) was 12.4 (9.1–22.1) months and 5.2 (1.5–9.3) months in patients with Child–Pugh A (n = 81; 75.7%) and Child–Pugh B cirrhosis (n = 26; 24.3%), respectively. In patients with viral (n = 64; 59.8%) versus non-viral etiology (n = 43; 40.2%), median OS (95% CI) was 10.5 (7.0–25.6) months versus 9.0 (4.6–16.0) months, respectively. In patients without (n = 30; 28.0%) versus with prior non-systemic therapies (n = 77; 72.0%), median OS (95% CI) was 7.7 (2.8–17.3) months versus 11.1 (7.6–17.6) months, respectively. Conclusions: These results suggest that STRIDE is well tolerated and may offer a survival benefit to a broad range of patients with unresectable HCC, representing populations that are more reflective of real-world clinical practice. Full article

Micronutrient deficiencies in human diets, often exacerbated by soil degradation, pose a significant global health challenge. Glacial flour, fine sediments produced by glacial erosion, may offer a sustainable, low-cost solution to improve soil fertility and enhance micronutrient availability in crops. This study evaluates the potential of glacial flour soil amendments from glaciers with two contrasting lithologies—basaltic Sólheimajökull (Iceland) and metasedimentary Chhota Shigri (Himalaya)—to enrich soybeans (Glycine max var. Black Jet) with essential nutrients while assessing the risk associated with potentially toxic elements. In a controlled glasshouse experiment, soybeans were grown in artificial soils amended with five doses of glacial flour (0.5–20 T ha⁻¹) and analysed for 18 elements. Results demonstrated enhanced uptake of key nutrients such as Zn, Fe, Mo, and Se, particularly in Icelandic glacial flour treatments, supporting the potential for crop biofortification. However, Himalayan flour led to arsenic (As) accumulation at higher doses, exceeding food safety limits. Multivariate clustering revealed two distinct element uptake behaviours: oxyanion-mediated and mimicking elements (Mo, Se, Sr, As) and those driven by plant demand (macronutrients, Fe, Mn, Zn). These findings highlight glacial flour’s potential for nutrient enrichment but also of potentially toxic elements, underscoring the need for source-specific screening to ensure safe agricultural application in deglaciating regions. Full article

Wetlands, frequently termed the “kidneys of the Earth,” represent one of the most vital global ecosystems. Despite their limited spatial extent, plateau wetlands function as unique ecological units that play a pivotal role in the global carbon cycle, water resource regulation, and biodiversity conservation, while exhibiting acute sensitivity to climate change. Advances in remote sensing technology—characterized by macro-scale cover-age, temporal efficiency, and non-invasive operations—have established it as a corner-stone for the dynamic monitoring and analysis of these environments. This study presents a bibliometric synthesis of 2138 publications (1982–2024) retrieved from the Web of Science Core Collection. We systematically evaluated publication trajectories, international collaborative networks, disciplinary shifts, core journals, and the spatiotemporal evolution of research hotspots. Our findings reveal an exponential growth in scholarly output alongside a marked diversification of research fields. Geographically, research is predominantly clustered around the Tibetan Plateau, flanked by the Alps and the Himalayas, with sparse representation in other regions. Future endeavors should prioritize underrepresented low-latitude and remote regions through strengthened international synergy and the integration of emerging technologies, such as UAVs and hyperspectral sensors. Full article

The Indian Himalayan Region is an important ecological location, but it is now suffering from serious air pollution due to activities like vehicular emissions, industrial activities, biomass burning, and regional atmospheric circulation, which have led to increased air pollution and threatened ecosystems, human health, and the climate. This paper employs qualitative document analysis through reviews of the national climate policies, institutional frameworks, state documents, and technology-based solutions. It concludes that despite comprehensive national policies, many gaps exist between the policy design and ground-level implementation. Our findings reveal three critical governance gaps: (i) altitude-specific regulatory failures in vehicular emission standards, (ii) Institutional fragmentation limiting enforcement capacity, particularly for diffuse sources, (iii) economic barriers preventing sustained adoption of clean fuels despite subsidy programs. According to this research, we propose a three-pillar framework integrating (i) investment in sustainable technology and green infrastructure, (ii) strengthening institutions and policies, and (iii) fostering behavioral change and public awareness. The study contributes to the limited literature on region-specific air quality governance and offers a strategic framework to support climate resilience in the Himalayas. Full article

Assessment of landslide risk is crucial given the substantial related economic losses and infrastructure damage in mountain areas every year. Particularly, the Sagarmatha National Park (SNP), a key destination for Himalayan glacier tourism, remains relatively understudied in this context. Existing studies primarily focus on regional inventories or simply inventory landslides and lack tourism-specific hazard assessment. This study evaluates landslide distribution, its controlling factors, and the exposure of infrastructure to varying degrees of landslide susceptibility in SNP. A blind inventory of 680 landslides and twelve conditioning factors, including six topographic and six non-topographic variables, were analyzed using Frequency Ratio (FR), Logistic Regression (LR), and Random Forest (RF) models. In addition, spatial overlay analysis was employed to assess the degree of infrastructure exposure. Results indicate that Land Surface Temperature (LST) is the most dominant factor influencing landslides occurrence, followed by rainfall, elevation, and slope, along with specific aspects like south and west and, land cover class like Barren land and Alpine meadows. Random Forest achieved the highest predictive accuracy (91%), outperforming both Logistic Regression (87%) and Frequency Ratio (84%). Exposure assessment of key tourism infrastructure indicates that trekking routes, helipads, buildings, campsites, and bridges are subject to varying levels of landslide risk. Although only 2.73 km (0.52%) of trekking routes intersect active landslide scars, 147 km (28%) lie within high-exposure zones. Consequently, both typical and paraglacial landslides threaten access to glacier tourism destinations, highlighting significant implications for Nepal’s tourism. Full article

Rhododendron arboreum Sm., an ecologically and culturally important Himalayan tree species and a key species in Himalayan forests, is increasingly threatened by forest degradation, climate change, and habitat fragmentation. However, previous studies have mainly focused on predicting climatic suitability, with limited integration of field-based population ecology and future climate projections, particularly in the western Himalayas. Therefore, the current investigation integrates population ecology and species distribution modeling (MaxEnt model) under CMIP6 climate scenarios (2070 and 2090) to identify climatically suitable and ecologically viable habitats for long-term species persistence across Himachal Pradesh, using 95 occurrence points and seven environmental predictors. Field data confirmed R. arboreum as a dominant species, strongly associated with Quercus leucotrichophora and Cedrus deodara. Habitat suitability was primarily driven by temperature seasonality (58.6%) and precipitation seasonality (14.8%), with 4508 km² currently suitable. Future projections forecast a distinct upshift but with high uncertainty regarding total area; projections ranged from potential habitat expansion under optimistic models (BCC-CSM2-MR) to significant contraction under pessimistic models (IPSL-CM6A-LR). Overall, findings prioritize climatically stable refugia (Kalatop-Khajjiar, Chail, and Churdhar wildlife sanctuary) not only for ecological monitoring but also as critical areas for developing socio-ecological management strategies to support community-based conservation and livelihood adaptation. Full article

The Himalayan metallogenic belt is a globally significant province for leucogranites and pegmatites. Recent exploration has yielded major breakthroughs in the exploration of pegmatite-type Li-Be-Nb-Ta rare-metal deposits within its eastern segment. Discoveries such as the Qiongjiagang and Lhozhag deposits underscore the region’s substantial mineralization potential. In contrast, the western Himalayan segment remains comparatively underexplored. This study presents the geology and geochronology of the newly identified Zhaguopu Li-Be-Nb-Ta deposit in the Gyirong area, providing critical new insights. The deposit is centered on the Gyirong granite dome, which features a core of tourmaline-bearing leucogranite surrounded by a peripheral zone of beryl-bearing pegmatites and vein- to lens-shaped spodumene pegmatites, all hosted within metamorphosed sandstone, slate, and marble. The largest individual spodumene pegmatite vein exceeds 400 m in length, with thicknesses ranging from 0.5 to 4 m and a cumulative thickness surpassing 50 m. Principal ore minerals include spodumene, beryl, and columbite-group minerals. U-Pb geochronology of zircon, monazite, and columbite-group minerals from the leucogranite and pegmatite units constrains the rare-metal mineralization to a tight interval of 25–23 Ma, contemporaneous with the Qiongjiagang and Lhozhag deposits. Whole-rock geochemical data define a coherent fractional crystallization sequence from tourmaline granite through beryl pegmatite to spodumene pegmatite, characterized by increasing SiO₂ and peraluminosity, and extreme depletion in Ba, Sr, Eu and Nb/Ta ratios. This geochemical trend underscores the critical role of extreme magmatic differentiation in rare-metal enrichment. Field relationships and these coeval ages strongly support a genetic model in which the mineralized pegmatites originated from the extreme fractional crystallization of a common, cogenetic magmatic suite. The timing of this mineralization event correlates precisely with the post-collisional extension of the Himalayan orogen and the activity of the Southern Tibet Detachment System. We conclude that the interplay between this large-scale tectonism and magmatic differentiation is the fundamental driver for rare-metal enrichment. The discovery of the Zhaguopu deposit highlights the significant and previously underestimated potential for major pegmatite-type rare-metal deposits in the western Himalayan belt. Full article

This study employs cooperative, behavioural, and experimental game theory to examine how forest rights are negotiated among tribal communities, government agencies, and civil society organisations in the western Himalayas. It explores how claims over access, governance, and benefit-sharing regarding forest resources are asserted, contested, and mediated in a complex socio-political environment. This research adopts a mixed-methods approach. Qualitative data from in-depth interviews and focus group discussions. Quantitative data from structured surveys and field-based experiments. The findings underscore the importance of integrating traditional knowledge systems with modern development policies. This study emphasises the need for sustainable and inclusive strategies that protect both the environment and local livelihoods. Full article

Landslides are a persistent hazard in the tectonically active Central Himalaya, frequently affecting roads and settlements. However, quantitative assessments of their spatial drivers have remained limited. This study investigated landslide susceptibility along a 90 km section of the Uttarkashi–Gangotri highway to identify dominant triggering factors and generate a reliable risk map. We applied the AHP–GIS framework, guided by a multi-criteria decision-making approach. Nine thematic parameters, such as slope, geology, lineament density, drainage density, proximity to roads, rainfall, aspect, curvature, and land use/land cover were utilised to quantify their relative influence on slope failure. Results showed that slope (23%), geology (22%), and lineament density (21%) were the most influential factors. Secondary contributions came from drainage density (9%), proximity to roads (8%), and rainfall (>231 mm). The susceptibility map was validated using 105 landslide inventory points, with 64 events (61%) located in very high-risk zones and 31 (30%) in high-risk zones. The model achieved a predictive accuracy of 0.817 based on the Area Under the Curve (AUC) metric. High-risk zones are aligned with steep slopes (30–50°), convex curvatures, and barren land, particularly near infrastructure. These findings provide a scientific tool for hazard mitigation and support disaster risk reduction in similar mountainous regions worldwide, contributing to safer infrastructure development. Full article

Microbial carbonates are globally known petroleum reservoirs. However, the complex interplay between deposition and diagenesis significantly influences the pore network distribution in these microbial carbonate reservoirs. The present study aims to discuss diagenetic alterations in the Jurassic microbial carbonate successions from foreland basins in the NW Himalayas. Geological field observations, petrographic analysis, scanning electron microscopy, and isotopic analysis were applied to highlight the role of diagenesis in reservoir characterization of shallow marine carbonates. The results indicate that dolomitization, dissolution, and fracturing during the early to late phase of diagenesis enhanced the reservoir pore network. However, cementation, micritization, and mechanical compaction considerably reduced the reservoir pore distribution. Furthermore, fractures and stylolites that developed perpendicular to bedding planes indicate the role of convergent tectonics in developing the fracture network that allowed fluid migration and improved the pore spaces in microbial carbonate reservoirs. Isotopic data revealed shallow-burial diagenesis with marine and meteoric influx that provides avenues for the movement of fluids. These fluids are associated with microbial activity in carbonate rocks along the faults and fractures that were developed because of compressional tectonics, evident from the perpendicular fracture network. This study recommends the integration of deposition and diagenesis to refine the pore network distribution and characterization of carbonate reservoirs around the globe. Full article