Search Results (775)

Hippophae neurocarpa S. W. Liu & T. N. Ho exhibits established medicinal characteristics, valuable dietary attributes, and remarkable adaptability, displaying strong resistance to cold, drought, and to acidic and alkaline soils. These traits and others make it a valuable species for soil erosion control and a distinctive economic forest tree in western China. However, research on its geographic distribution remains limited. To address this gap, we employed the MaxEnt model to map its current distribution and to predict the future geographic distribution of suitable habitats for this species under SSP1-2.6, SSP2-4.5, and SSP5-8.5 climate scenarios. Collectively, these data suggest that the species’ current and future suitable habitats are predominantly concentrated at the junction of the northeastern Qinghai-Tibet Plateau and the Loess Plateau. Under present climatic conditions, highly suitable habitats are primarily located in the northeastern Qinghai-Tibet Plateau, with smaller patches in the Hengduan and Himalaya mountains. The AUC value of this model reached 0.954; projections under three future emission scenarios indicate an overall expansion trend in suitable habitat area. Notably, by the 2070s under the SSP2-4.5 scenario, the total suitable habitat area is projected to increase by 11.64%—the highest among all scenarios. Additionally, climate change is expected to drive a slight northward shift in the species’ distribution center toward higher latitudes. Key environmental factors influencing its projected distribution include elevation (elev), temperature seasonality (bio04), mean temperature of the coldest quarter (bio11), and precipitation of the warmest quarter (bio18). These insights are critical for conserving H. neurocarpa’s genetic resources and guiding future biodiversity conservation strategies. Full article

Maturity estimation before seed collection is necessary in reducing the costs of seed collection; it allows vigorous seeds to be collected, ensuring that maximum germination will be reached and producing quality planting stock. In addition to this, appropriate temperature, seed size, pH, light, and stress conditions also influence germination. Cones of Cedrus deodara were collected at different intervals to estimate the maturity of the cones. A seed germination test was conducted in the laboratory under constant temperature, seed size, pH, light conditions, and water and salinity stress conditions. Significant (p < 0.05) variations in cones, such as seed morphological characteristics, germination, and related parameters, of C. deodara at different maturity periods were observed. The morphological traits of cones, such as seed weight, seed length, seed width, and seed germination, increased with increasing maturity, while the cone weight, moisture contents, specific gravity, and seed moisture decreased with increasing maturity. A constant temperature of 15 °C to 20 °C (98.0% to 92.0%) and the use of large-sized seeds (99.0%) led to maximum germination. Lower concentrations of Polyethylene glycol (98.0%) and NaCl (78.0%) contributed to maximum seed germination. The germination of C. deodara is temperature-dependent and seed size, light, and high water and salinity stress significantly influence seed germination. Full article

The Third Pole region, particularly the Hindu–Kush–Himalaya (HKH), is highly prone to lightning, causing thousands of fatalities annually. Skillful prediction and timely communication are essential for mitigating lightning-related losses in such observationally data-sparse regions. Therefore, this study evaluates kilometer-scale ICON-CLM-simulated atmospheric variables using six machine learning (ML) models to detect lightning activity over the Third Pole. Results from the ensemble boosting ML models show that ICON-CLM simulated variables such as relative humidity (RH), vorticity (vor), 2m temperature (t_2m), and surface pressure (sfc_pres) among a total of 25 variables allow better spatial and temporal prediction of lightning activities, achieving a Probability of Detection (POD) of ∼0.65. The Lightning Potential Index (LPI) and the product of convective available potential energy (CAPE) and precipitation (prec_con), referred to as CP (i.e., CP = CAPE × precipitation), serve as key physics aware predictors, maintaining a high Probability of Detection (POD) of ∼0.62 with a 1–2 h lead time. Sensitivity analyses additionally using climatological lightning data showed that while ML models maintain comparable accuracy and POD, climatology primarily supports broad spatial patterns rather than fine-scale prediction improvements. As LPI and CP reflect cloud microphysics and atmospheric stability, their inclusion, along with spatiotemporal averaging and climatology, offers slightly lower, yet comparable, predictive skill to that achieved by aggregating 25 atmospheric predictors. Model evaluation using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) highlights XGBoost as the best-performing diagnostic classification (yes/no lightning) model across all six ML tested configurations. Full article

Heavy rainfall events, characterized by extreme downpours that exceed 100 mm per day, pose an intensifying hazard to the densely settled valleys of the western Himalaya; however, their coupling with expanding urban land cover remains under-quantified. This study mapped the spatiotemporal exposure of built-up areas to heavy-day rainfall (HDR) across Jammu, Kashmir, and Ladakh and the adjoining areas by integrating daily Climate Hazards Group InfraRed Precipitation with Stations product (CHIRPS) precipitation (0.05°) with Global Human Settlement Layer (GHSL) built-up fractions within the Google Earth Engine (GEE). Given the limited sub-hourly observations, a daily threshold of ≥100 mm was adopted as a proxy for HDR, with sensitivity evaluated at alternative thresholds. The results showed that HDR is strongly clustered along the Kashmir Valley and the Pir Panjal flank, as demonstrated by the mean annual count of threshold-exceeding pixels increasing from 12 yr⁻¹ (2000–2010) to 18 yr⁻¹ (2011–2020), with two pixel-scale hotspots recurring southwest of Srinagar and near Baramulla regions. The cumulative high-intensity areas covered 31,555.26 km², whereas 37,897.04 km² of adjacent terrain registered no HDR events. Within this hazard belt, the exposed built-up area increased from 45 km² in 2000 to 72 km² in 2020, totaling 828 km². The years with the most expansive rainfall footprints, 344 km² (2010), 520 km² (2012), and 650 km² (2014), coincided with heavy Western Disturbances (WDs) and locally vigorous convection, producing the largest exposure increments. We also performed a forecast using a univariate long short-term memory (LSTM), outperforming Autoregressive Integrated Moving Average (ARIMA) and linear baselines on a 2017–2020 holdout (Root Mean Square Error, RMSE 0.82 km²; measure of errors, MAE 0.65 km²; R² 0.89), projecting the annual built-up area intersecting HDR to increase from ~320 km² (2021) to ~420 km² (2030); 95% prediction intervals widened from ±6 to ±11 km² and remained above the historical median (~70 km²). In the absence of a long-term increase in total annual precipitation, the projected rise most likely reflects continued urban encroachment into recurrent high-intensity zones. The resulting spatial masks and exposure trajectories provide operational evidence to guide zoning, drainage design, and early warning protocols in the region. Full article

This article examines the evolution and potential cross-cultural adaptations of the “Goddess of the Flaming Mouth”, Jvālāmukhī (Skt.) or Kha ‘bar ma (Tib.), in Indic and Tibetan traditions. A minor figure in medieval Hindu Tantras, Jvālāmukhī is today best known through her tangible manifestation as natural flames in a West Himalayan temple complex in the valley of Kangra, Himachal Pradesh, India. The gap between her sparse portrayal in Tantric texts and her enduring presence at this local “seat of power” (śakti pīṭha) raises questions regarding her historical development and sectarian affiliations. To address these questions, we examine mentions of Jvālāmukhī’s Tibetan counterpart, Kha ‘bar ma, across a wide range of textual sources: canonical Buddhist texts, original Tibetan works of the Bön and Buddhist traditions, and texts on sacred geography. Regarded as a queen of ghost spirits (pretas) and field protector (kṣetrapāla) in Buddhist sources, her portrayal in Bön texts contain archaic motifs that hint at autochthonous and/or non-Buddhist origins. The assessment of Indic material in conjunction with Tibetan texts point to possible transformations of the goddess across these culturally proximate Himalayan settings. In presenting and contextualizing these transitions, this article contributes critical data to ongoing efforts to map the development, adaptation, and localization of Tantric deities along the Indo-Tibetan interface. Full article

The distribution of forest aboveground biomass density (AGBD) is a key indicator of carbon stock and ecosystem health in the Eastern Himalayas, which represents a global biodiversity hotspot that sustains diverse forest types across an elevation gradient from lowland rainforests to alpine meadows and contributes to the livelihoods of more than 200 distinct indigenous communities. This study aimed to identify the key factors influencing forest AGBD across this region by analyzing the underlying biophysical and anthropogenic drivers through machine learning (random forest). We processed AGBD data from the Global Ecosystem Dynamics Investigation (GEDI) spaceborne LiDAR and applied filtering to retain 30,257 high-quality footprints across ten ecoregions. We then analyzed the relationship between AGBD and 17 climatic, topographic, soil, and anthropogenic variables using random forest regression models. The results revealed significant spatial variability in AGBD (149.6 ± 79.5 Mg ha⁻¹) across the region. State-wise, Sikkim recorded the highest mean AGBD (218 Mg ha⁻¹) and Manipur the lowest (102.8 Mg ha⁻¹). Within individual ecoregions, the Himalayan subtropical pine forests exhibited the highest mean AGBD (245.5 Mg ha⁻¹). Topographic factors, particularly elevation and latitude, were strong determinants of biomass distribution, with AGBD increasing up to elevations of 2000 m before declining. Protected areas (PAs) consistently showed higher AGBD than unprotected forests for all ecoregions, while proximity to urban and agricultural areas resulted in lower AGBD, pointing towards negative anthropogenic impacts. Our full model explained 41% of AGBD variance across the Eastern Himalayas, with better performance in individual ecoregions like the Northeast India-Myanmar pine forests (R² = 0.59). While limited by the absence of regionally explicit stand-level forest structure data (age, stand density, species composition), our results provide valuable evidence for conservation policy development, including expansion of PAs, compensating avoided deforestation and modifications in shifting cultivation. Future research should integrate field measurements with remote sensing and use high-resolution LiDAR with locally derived allometric models to enhance biomass estimation and GEDI data validation. Full article

Given that the Sunkoshi River watershed (located in the southern foot of the Himalayas) is sensitive to climate change and its mountain ecosystem provides important services, we aim to evaluate its spatial and temporal variation patterns of vegetation, represented by the Normalized Difference Vegetation Index (NDVI), during 2000–2021 and identify the dominant driving factors of vegetation change. Based on the NDVI dataset (MOD13A1), we used the simple linear trend model, seasonal and trend decomposition using loess (STL) method, and Mann–Kendall test to investigate the spatiotemporal variation features of NDVI during 2000–2021 on multiple scales (annual, seasonal, monthly). We used the partial correlation coefficient (PCC) to quantify the response of the NDVI to land surface temperature (LST), precipitation, humidity, and soil moisture. The results indicate that the annual NDVI in 52.6% of the study area (with elevation of 1–3 km) increased significantly, while 0.9% of the study area (due to urbanization) degraded significantly during 2000–2021. Daytime LST dominates NDVI changes on spring, summer, and winter scales, while precipitation, soil moisture, and nighttime LST are the primary impact factors on annual NDVI changes. After removing the influence of soil moisture, the contributions of climate factors to NDVI change are enhanced. Precipitation shows a 3-month lag effect and a 5-month cumulative effect on the NDVI; both daytime LST and soil moisture have a 4-month lag effect on the NDVI; and humidity exhibits a 2-month cumulative effect on the NDVI. Overall, the study area turned green during 2000–2021. The dominant driving factors of NDVI change may vary on different time scales. The findings will be beneficial for climate change impact assessment on the regional eco-environment, and for integrated watershed management. Full article

The present study provides a detailed compilation and analysis of the bulk density and magnetic susceptibility of the rocks from the northwest Himalayas, Pakistan. The area is tectonically extremely complex and comprises sedimentary, metamorphic, and igneous rocks. These rocks range in age from Early Proterozoic to Recent. During the fieldwork, 476 rock samples were collected for density measurements and 410 for magnetic susceptibility measurements from the major rock units exposed in the study area. The measured physical parameters reveal a significant difference in the density and susceptibility of the rocks present in the investigated area. The sedimentary rock units belonging to the Indian Plate show the lowest mean values for bulk density, followed by metasedimentary rocks, Early Proterozoic rocks, igneous and metaigneous rock units of the Indian Plate, Indus Suture Melange Zone, and Kohistan Island Arc rocks, respectively. The magnetic susceptibility of sedimentary rock units of the Indian Plate has the lowest mean values, followed by metasedimentary rocks of the Indian Plate, igneous and metaigneous rock units of the Indian Plate, Early Proterozoic rocks of the Indian Plate, Kohistan Island Arc rocks, and Indus Suture Melange Zone. In brief, the sedimentary rocks of the Indian Plate have the lowest bulk density and magnetic susceptibility values, whereas the Kohistan Island Arc rocks have the highest values. Overall, the bulk density and magnetic susceptibility of rock units in the study area follow those predicted for different types of rocks. These measurements can be used to develop possible potential field models of the northwest Himalayas to better understand the tectonics of the ongoing continental-to-continental collision, as well as for many other geological analyses. Full article

This article considers the dilemma between advocating for a religion-based environmentalism in the Himalayas and recognising that the different cultural traditions in the region make a uniform religious environmentalism difficult to uphold. Conservationists often attempt to mobilise local communities for environmental protection by building on their religious and cultural beliefs. Yet, such forms of mobilisation tend to homogenise plural traditions by forcing them within a single fold. What is the way out of this dilemma? I offer some reflections, drawing on my empirical work in the Buddhist Himalayas, and focusing on the case studies of the yak and the black-necked crane respectively, two species which hold a special significance in Arunachal Pradesh, India. Examining these multispecies relations in Arunachal Pradesh reveal not only Buddhist values at work, but plural and evolving entanglements. The question, then, is not to see if the value is religious but if the value is more-than-human in its orientation, taking into account the entangled lives of human and non-human habitations. My broad argument is that an ethics of the environment need neither to be removed from religious ethics, nor enclosed by it. Rather than force environmental thought and behaviour into silos of particular religious traditions or conservation science paradigms, how can one see these as the function of plural habitations? Full article

Some of the most intense thunderstorms and extreme weather events on Earth occur in the Hindu Kush Himalaya (HKH) region of Southern Asia. The need to provide end users, stakeholders, and decision makers with accurate forecasts and alerts of extreme weather is critical. To that end, a cutting edge weather modeling framework coined the High Impact Weather Assessment Toolkit (HIWAT) was created through the National Aeronautics and Space Administration (NASA) SERVIR Applied Sciences Team (AST) effort, which consists of a suite of varied numerical weather prediction (NWP) model runs to provide probabilities of straight-line damaging winds, hail, frequent lightning, and intense rainfall as part of a daily 54 h forecast tool. The HIWAT system was first deployed in 2018, and the recently released model archive hosted by the Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) provides daily model outputs for the years of 2018–2022. With a nested modeling domain covering Nepal, Bangladesh, Bhutan, and Northeast India, the HIWAT archive spans the critical pre-monsoon and monsoon months of March–October when severe weather and flooding are most frequent. As part of NASA’s Transformation To Open Science (TOPS), this data archive is freely available to practitioners and researchers. Full article

Forest fires in the Hindu Kush Himalaya (HKH) region are increasing in frequency and severity, driven by climate variability, prolonged dry periods, and human activity. Nepal, a critical part of the HKH, recorded over 22,700 forest fire events in the past decade, with fire incidence nearly doubling in 2023. Despite this growing threat, operational early warning systems remain limited. This study presents Nepal’s first high-resolution early fire risk outlook system, developed by adopting the Canadian Fire Weather Index (FWI) using meteorological forecasts from the High-Impact Weather Assessment Toolkit (HIWAT). The system generates daily and two-day forecasts using a fully automated Python-based workflow and publishes results as Web Map Services (WMS). Model validation against MODIS, VIIRS, and ground fire records for 2023 showed that over 80% of fires occurred in zones classified as Moderate to Very High risk. Spatiotemporal analysis confirmed fire seasonality, with peaks in mid-April and over 65% of fires occurring in forested areas. The system’s integration of satellite data and high-resolution forecasts improves the spatial and temporal accuracy of fire danger predictions. This research presents a novel, scalable, and operational framework tailored for data-scarce and topographically complex regions. Its transferability holds substantial potential for strengthening anticipatory fire management and climate adaptation strategies across the HKH and beyond. Full article

The elongated tortoise (Indotestudo elongata), a Critically Endangered (CR) species, faces numerous threats across its range. Yet, the ecological and anthropogenic factors affecting its conservation in fragmented habitats remain poorly understood. This study integrated field surveys and community questionnaires to assess the distribution drivers and local perceptions, such as attitudes, knowledge, conservation practices, and perceived threats, in the Jalthal Forest, one of the last remnants of suitable habitat for the elongated tortoise in eastern Nepal. Using ArcMap, we established 138 randomly selected grids (500 m × 500 m) to evaluate the environmental covariates of tortoise occurrence and anthropogenic pressures. Generalized linear models revealed that tortoise occurrence was negatively associated with dense ground cover (β = −3.50, p = 0.017) and human disturbance (β = −8.11, p = 0.019). Surveys of local residents from community forest user groups (n = 236 respondents) indicated strong local support for tortoise conservation (69% willing to protect the species). Despite this, the respondents identified persistent threats, including hunting for bushmeat and traditional medicine (74%), habitat degradation (65%), and forest fires. While 60% of the respondents recognized the threatened species status, significant knowledge gaps regarding that status and ongoing illegal exploitation persisted. These findings underscore the need for targeted habitat management, reduced anthropogenic pressures, and community-led initiatives to align local attitudes with conservation actions. This study provides critical baseline data for conserving the elongated tortoise in human-modified landscapes and emphasizes the necessity of integrated ecological and socio-cultural strategies for its long-term survival. Full article

The nocturnal, flightless camel crickets (Rhaphidophoridae) have a global distribution and are believed to have originated prior to the breakup of Pangea. We investigated the phylogeny and the timing of the radiation of East Asian species with mitogenomic data. Initially we analyzed a large taxon dataset (n = 117) using available partial mitochondrial and nuclear DNA sequences to confirm the monophyly of subfamilies and current taxonomy. Our findings support the monophyly of each genus within the subfamily Aemodogryllinae, with a minor inconsistency between taxonomy and phylogeny resolved by resurrection of the genus Gymnaeta Adelung. Fossil-calibrated molecular clock analysis used 11,124 bp alignment of 13 complete mitochondrial protein-coding genes for 20 species of Rhaphidophoridae, with a focus on the neglected Rhaphidophorinae and Aemodogryllinae lineages. Divergence time estimates suggest that the most recent common ancestor of the family lived during the Early Jurassic (189 Mya ± 23 Mya) before Pangea broke into the supercontinents or possibly during the early stage of breakup when Gondwana and Laurasia were still connected by land. The two subfamilies, Rhaphidophorinae and Aemodogryllinae, that overlap in Asia are estimated to have diverged 138 Mya ± 17 Mya, well before the Late Cretaceous northern connection between America and Asia (the Bering Land Bridge). Thus, our extended sampling of species from East Asia and Oceania refutes the importance of continental drift in the evolution of this wingless orthopteran family. Full article

The Cretaceous oceanic red beds (CORBs) and their implications for “oceanic oxic events” have been widely studied by geologists globally. In southern Tibet, CORBs are extensively distributed within the Upper Cretaceous strata of the northern Tethyan Himalaya (NTH). A well-exposed, CORB-bearing, mixed carbonate–shale sequence is found in the Zhangguo section of Rilang Township, Gyangze County. The Chuangde Formation in this section is characterized by well-preserved CORBs, which include reddish shale, limestone, marlstone, and interbedded siltstone. These CORBs are stratigraphically overlain by the Jiabula/Gyabula Formation (predominantly shale) and underlain by the Zongzhuo Formation (“mélange”). However, the precise age, depositional environments, and regional/global correlations of these CORBs, as well as their implications for synchronous versus diachronous oceanic oxic events, remain to be fully understood. In this study, a comprehensive analysis of foraminiferal biostratigraphy and microfacies is conducted for the CORB-bearing Chuangde Formation and the upper Jiabula (Gyabula) Formation in the Zhangguo section. Five planktic foraminiferal biozones including Dicarinella asymetrica, Globotruncanita elevata, Contusotruncana plummerae, Radotruncana calcarata, and Globotruncanella havanensis are identified through detailed biostratigraphic analysis, confirming a Campanian age for the Chuangde Formation and its CORBs. These findings are broadly correlated with typical Upper Cretaceous CORBs in pelagic–hemipelagic settings across the NTH in southern Tibet. Nine microfacies and four facies associations are identified within the Upper Cretaceous strata of Gyangze and adjacent areas through field and petrographic analyses. Notably, it is indicated that planktic foraminiferal packstone/grainstone CORBs were deposited in outer shelf to upper slope environments, while radiolarian chert CORBs are inferred to have formed in deep-water, basinal settings below the carbonate compensation depth (CCD). Full article

Gridded precipitation datasets (GPDs) have complemented gauge-based measurements in global hydrology by providing spatiotemporally continuous rainfall estimates for streamflow prediction. However, these datasets suffer from uncertainties in space and time, particularly in complex terrains like the Himalayas. Merging multi-GPDs offers a potential solution to reduce such uncertainties, but the actual contribution of the merged product to hydrological modeling remains underexplored in data-scarce and topographically complex regions. Here, we applied a gauge-independent merging technique called Signal-to-Noise Ratio optimization (SNR-opt) to merge three precipitation products: ERA5, SM2RAIN, and IMERG-late. The resulting Merged Gridded Precipitation Dataset (MGPD) was evaluated using the hydrological model (HYMOD) across three major river basins in the Central Himalayas (Koshi, Narayani, and Karnali). The results show that MGPD significantly outperforms the individual GPDs in streamflow simulation. This is evidenced by higher Nash–Sutcliffe Efficiency (NSE) values, 0.87 (Narayani) and 0.86 (Karnali), compared to ERA5 (0.83, 0.82), SM2RAIN (0.83, 0.85), and IMERG-Late (0.82, 0.78). In Koshi, the merged product (NSE = 0.80) showed slightly lower performance than SM2RAIN (NSE = 0.82) and ERA5 (NSE = 0.81), likely due to the poor performance of IMERG-Late (NSE = 0.69) in this basin. These findings underscore the value of merging precipitation datasets to enhance the accuracy and reliability of hydrological modeling, especially in ungauged or data-scarce mountainous regions, offering important implications for water resource management and forecasting. Full article