Abstract Accurate accounting of aquatic methane emissions is critical for climate change mitigation, yet current global budgets overlook a key driver: the elevation-regulated atmospheric pressure. Here, we present the first large-scale investigation of methane ebullition across 164 shallow waters spanning elevations from sea level to 4886 meters. We demonstrate that ebullition rate increases with elevation-over four times higher at >3000 m a.s.l. than at sea level-due to two synergistic, pressure-dependent physical mechanisms: a ‘degas’ effect (enhanced bubble formation) and a ‘trigger’ effect (facilitated bubble ascent). Independent theoretical prediction of the combined effects shows near-perfect agreement with the empirical elevation trend, quantitatively confirming that these physical mechanisms are the primary drivers of enhanced ebullition at high elevations. Our findings reveal that mountain aquatic ecosystems represent unaccounted methane hotspots that have been systematically underestimated in global inventories.We therefore call for urgent integration of these ecosystems into IPCC assessments and targeted mountain mitigation and sustainable management strategies.

ABSTRACT Motivation The database initiated by the Mountain Invasion Research Network (MIREN) is one of the few globally implemented standardized vegetation surveys in mountains. The focus is on collecting plant species occurrences at 5‐year intervals along and adjacent to mountain roads spanning elevational gradients, with the goal of providing critical information about the ongoing spread of non‐native plants and the potential impacts of climate and human‐caused disturbance in the form of road infrastructure on mountain vegetation. Main Types of Variables Contained To date, the database contains almost 170,000 georeferenced records of plant species. Overall, 6854 vascular plant species were observed in 3364 plots across 25 regions, with many of these plots being revisited every 5 years. Each plot is identified by its coordinates, elevation and distance to the road. The status of each individual species (native, non‐native or unknown) is determined in accordance with regional databases. Spatial Location and Grain Plant species were surveyed at 20 sample sites, placed at regular elevational intervals along each mountain road, with typically three roads selected per region. Each sample site is subdivided into three 2 m × 50 m plots, one parallel to the road and two perpendicular to it, extending into adjacent vegetation. The 25 studied regions cover all continents except Antarctica. Time Period and Grain Data were collected between 2007 and 2023, with surveys being repeated at 5‐year intervals in a subset of regions. Three regions include four time‐steps, while seven and three regions were sampled three times or twice, respectively. In most regions, long‐term monitoring is ongoing. Major Taxa and Level of Measurement All vascular plant species. Software Format Data are available through a .csv file on Zenodo ( https://doi.org/10.5281/zenodo.15749536 ).

Plant opal particles, known as phytoliths, play a significant role in taxonomic research, and their long-term preservation in sediments makes them a valuable tool for reconstructing ancient plant communities and understanding past plant–human interactions. To strengthen species-level reference data for such applications, this study characterizes the silica content and phytolith assemblages of selected Asteraceae species. Phytolith extraction and silica content estimation were done using the dry ashing method, and morphotypes were identified following International Code for Phytolith Nomenclature (ICPN)-2 guidelines. Results showed that Anthemis cotula and Bellis perennis had the highest silica content, followed by Inula racemosa, Saussurea costus, and Artemisia absinthium. Each species exhibited distinct dominant phytolith morphotypes, including ACUTE in A. cotula, TRAPEZIFORM in B. perennis, ELONGATE ENTIRE in A. absinthium, BLOCKY in I. racemosa and ELONGATE FACETED in S. costus. The presence of diagnostic phytolith morphotypes at higher frequency highlights the potential of phytolith profiling as a reliable tool for species identification and for enriching reference datasets used in taxonomic and paleoecological research. Furthermore, the comparatively high silica content in A. cotula and B. perennis suggests that silica accumulation may contribute to the invasive tendencies of these species, a possibility that demands further investigation.

Forest fragmentation and landscape degradation are major ecological concerns in the Himalaya, yet long-term integrated assessments for the Kashmir Valley remain scarce . This study quantified forest cover change, fragmentation dynamics, and landscape condition across ten districts from 1978 to 2021 using multi-temporal land-cover data and landscape metrics. Forest cover declined from 4,583.58 km² (33.98%) in 1978 to 4,306.94 km² (31.93%) in 2021, with a net loss of 276.65 km² (-6.04%). Non-forest areas expanded steadily, indicating persistent land-use conversion. Fragmentation intensified substantially: the Fragmentation Index increased threefold (25.0 to 75.0), while the Integrity Index and Landscape Condition Index declined by 74.4% and 71.1%, respectively, reflecting a severe deterioration in forest connectivity and ecological integrity. Edge density increased markedly, indicating rising anthropogenic pressure and habitat dissection. A shift in fragmentation drivers was evident, with dominance shifting from largest patch loss in 1978 to increasing influence of edge density, patch number, and patch-size variability by 2021. This reflects a transition from broad forest contraction to finer-scale subdivision and edge proliferation. Strong spatial heterogeneity emerged across districts. Anantnag, Kulgam, and Baramulla showed the highest increases in fragmentation, while Budgam and Ganderbal recorded the sharpest declines in landscape condition and integrity. Kupwara retained the highest forest cover despite moderate losses, whereas Shupiyan experienced the greatest proportional decline (11.2%). At the class level, degraded and dense forests showed disproportionately higher losses than sparse forests, indicating selective degradation of structurally important forest types. Transition analysis confirmed persistence of non-forest and sparse forest classes, alongside conversion of dense and degraded forests into lower-quality or non-forest categories. Overall, the landscape metrics consistently indicate increasing edge dominance, patch subdivision, and declining landscape cohesion, highlighting the progressive ecological destabilization of forest ecosystems in the Kashmir Himalaya,Overall, results demonstrate a long-term trajectory of progressive forest fragmentation and ecological degradation driven by sustained anthropogenic pressure. Declining forest integrity and connectivity highlight increasing risks to biodiversity and ecosystem resilience, providing a spatial baseline for conservation and restoration planning under ongoing land-use and climate pressures.

Glacial lakes in the Kashmir Himalaya have remained understudied despite their destructive potential for outburst floods. This study presents a comprehensive, manually delineated glacial lake inventory of 155 glacial lakes and a baseline for glacial lake outburst flood (GLOF) hazard across the region. Lakes are characterized by type and assessed for long-term spatio-temporal dynamics using a multi-temporal Landsat series in a GIS environment from 1992 to 2024. The area of ice-contact proglacial lakes increased by 26% during the 32-year observation period. A multi-criteria analysis-based framework validated by historical GLOFs in the Himalayan region is employed to evaluate the lake outburst susceptibility. Key factors such as dam material, slope gradient, upstream cascades, seismic activity and permafrost occurrence, are integrated in the susceptibility framework. Potential outburst events from five lakes categorised as having very high GLOF susceptibility threaten several thousand buildings, 15 major bridges, roads and a hydroelectric power project. The study also highlights the potential for GLOF process chains in the region, where upstream lake outbursts could trigger secondary events downstream. The five most susceptible lakes identified here may require intensive monitoring and risk management initiatives to protect vulnerable downstream communities and infrastructure.

Biological invasions provide unique insights into how ecological strategies and population genetic processes contribute to species success. However, decoupling the effects of functional trait divergence from population genetic structure remains challenging, particularly in biodiversity hotspots where invasive and endemic congeners coexist. This study evaluated the concordance between SSR-based population-genetic structure and field-expressed functional trait variation in invasive and endemic species of two distinct genera in the Kashmir Himalaya. We compared two invasive taxa (Ranunculus distans and Artemisia absinthium) with two narrowly endemic congeners (R. palmatifidus and A. amygdalina), combining population genetic analyses based on 12 polymorphic microsatellite loci (six per genus) with individual-level measurements of growth, leaf morphology, and biomass traits across natural populations. Invasive taxa generally maintained higher or more widely distributed genetic variation, but species-specific AMOVA showed that population structuring differed in a genus-specific manner rather than being uniformly lower in invasive congeners. In Artemisia, among-population variation was higher in the endemic A. amygdalina than in the invasive A. absinthium, whereas in Ranunculus, the invasive R. distans showed higher among-population variation than the endemic R. palmatifidus. Functional analyses revealed clear, trait-specific differentiation between invasive and endemic congeners. Invasive taxa generally occupied a more acquisitive region of trait space, particularly through greater leaf area and biomass accumulation, whereas endemic taxa showed more restricted trait distributions. Multivariate analyses indicated that functional differentiation was concordant with SSR-based population structure. Because the functional traits were measured under field conditions and SSR markers represent neutral population-level variation, these results are interpreted as associative rather than as direct evidence of genetic control over trait expression. Overall, the study suggests that demographic connectivity, lineage-specific population structuring and field-expressed functional strategies jointly contribute to the contrasting ecological performance of invasive and endemic congeners in the Himalayan Mountain ecosystems.

Glaciers in the Himalayan region have undergone rapid shrinkage owing to climate change, posing significant challenges to regional hydrology, dependent ecosystems, and socioeconomic sectors. In addition to temperature warming, surface albedo is a key parameter that influences glacier melt. In this study, spatiotemporal variability of albedo on four benchmark glaciers, Kolahoi, Machoi, Parkachik, and Drang Drung, in the northwest Himalaya was analyzed using MODIS (Moderate Resolution Imaging Spectroradiometer) and Landsat-8 OLI data over 22 years (2001–2022) in Google Earth Engine (GEE). Furthermore, changes in glacier albedo were correlated with geodetic surface lowering. The glacier albedo varied with time and space. Drang Drung showed the highest mean albedo at 55

Ecological research is undergoing rapid change, driven both by the urgency of the environmental crisis and by the expanded opportunities for collaboration and networking in an increasingly interconnected world. Global collaborative efforts in ecology are needed to address large scale questions and draw strong inferences, but there is no simple recipe for success in scientific ecological networking. This perspective celebrates 20 years of the Mountain Invasion Research Network (MIREN), highlighting its key achievements in advancing the study of plant invasions and plant redistributions in mountain ecosystems and how these results may inform today’s most pressing ecological and conservation issues. As a decentralized global monitoring network built around regional nodes, MIREN has been able to generate replicated evidence across environmental gradients and biogeographical contexts. By surveying non-native plants in mountain regions around the world, the network has produced a uniquely comparable and robust dataset that allows fundamental ecological ideas to be tested with greater consistency and generality and contributes to conservation actions from local to global scales. Maintaining MIREN over the long term requires encouraging a new generation of researchers and conservation practitioners who can build on the network’s legacy while also addressing gaps in resourcing, technical capacity, and regional coverage.

Pastoralism is central to mountain livelihoods in the Kashmir Himalayas, historically sustained through transhumant mobility and a rich body of traditional ecological knowledge (TEK). This system is now threatened by three interacting pressures: climate change, the upward spread of invasive plant species, and the erosion of TEK. Rising temperatures, altered precipitation, and shifting snowmelt are reshaping pasture phenology, shortening migration windows and destabilising fodder security. Meanwhile, invasive species once limited to lower elevations are expanding into higher rangelands, displacing palatable forage and reducing carrying capacity. These ecological stresses intersect with socio-economic change, including youth outmigration and weakening customary institutions, which diminish the transmission and practice of TEK. Collectively, these dynamics are transforming historically resilient pastoral systems into increasingly vulnerable socio-ecological assemblages. This review synthesises recent evidence on climate variability, invasive plant expansion and TEK erosion and calls for climate-responsive rangeland governance that revitalises TEK, supports mobility-based adaptation and protects high-altitude biodiversity.

The phytolith study of sedimentary deposits serves as a valuable tool for reconstructing past vegetation and environmental changes. In this study, we carried out a phytolith analysis of a palaeosol and a clay bed from the Pliocene Lower Karewa deposits of the Kashmir Himalaya, India. The palaeosol lies directly over the hard rock basement. The material that forms the palaeosol is thought to represent sedimentation at the time of Kashmir Valley formation around 4 Ma owing to the uplift of the Pir Panjal Range. The phytolith assemblages suggest the area supported a complex vegetation structure during palaeosol formation and clay bed deposition. The phytolith assemblages, commonly associated with C4 grasses - characteristic of warm, arid, and low CO2 environments, and some woody plants and shrubs, suggest warmer and drier climatic conditions during palaeosol formation. However, micromorphological analysis and detailed field observations suggest that the material that forms the palaeosol was deposited much later than the commencement of valley formation. The co-occurrence of phytoliths of diverse climate and vegetation types along the depth of palaeosol indicates a thorough mixing of material during its deposition, possibly by pedogenic, glaciotectonic or mass-wasting processes. Our study provides a renewed viewpoint on the oxidized palaeosol, suggesting that previous interpretations about its formation during basin formation need reconsideration. On the other hand, the clay bed depicts less diverse phytolith assemblages, suggesting a possibly harsher, colder environment. The phytolith morphotypes of the clay bed depict amore controlled climate, and each lamina suggests the phytolith of a particular time period. (c) 2025 The Geologists' Association. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Silicon (Si) is a significant stress reliever in plants, since it improves both biotic and abiotic stress situations. To see the efficacy of Si, wheat plants were subjected to three different silicon treatments (150, 250 and 500 mg/L). We assessed the effect of different silicon concentrations on feeding preferences of Rhophalosiphum padi in both laboratory as well as greenhouse conditions until 72 h. Aphid development was determined by analysing reproductive, lifespan, fecundity and mortality. The findings demonstrated that the increasing silicon concentrations were less preferred by aphids in both free choice and pair choice tests after 48 h. Aphid fecundity, longevity and mortality are affected by higher silicon concentrations. High silicon concentrations showed low LC50 values and high toxicity index. Our findings demonstrate that the impact of silicon on the feeding preferences and development of R. padi could be used as a possible substitute for pesticides in integrated pest management practices.

The Pir Panjal mountain range of the Kashmir Himalaya represents a climatically sensitive transition zone influenced by both the Indian Summer Monsoon and mid-latitude Western Disturbances, making it vulnerable to hydroclimatic fluctuations. Understanding long-term summer rainfall variability in this region is essential for assessing water-resource sustainability, ecosystem dynamics, and future climate risks. Here, we developed a 245-year (1780-2023 C.E.) tree-ring chronology of Pinus wallichiana based on 180 increment cores from the Pir Panjal Range to decipher long-term climatic evolution. This chronology was significantly correlated with May-August precipitation (r = 0.61, p < 0.05). The linear regression model was used to reconstruct May-August precipitation for the period 1802-2023 C.E., explaining 38% of the variance of observed precipitation records at Srinagar. The reconstruction reveals substantial interannual-to-multidecadal hydroclimatic variability, with the most severe droughts occurring during 1904, 1934, 1970-1971, 1802-1809 C.E. Major wet phases were identified during 1810-1816 C.E., 1974-1982 C.E., 2003-2011 C.E., and 2013-2023 C.E. Reconstructed wet and dry phases correspond closely with historical records and previously published hydroclimatic reconstructions, indicating regional coherence across the northwestern Himalaya. Wavelet analyses identified periodicities within the ∼8-12, ∼12-20, and ∼64-80 year bands, highlighting climatic variability operating across multiple temporal scales. Spatial correlation analysis further demonstrated that the reconstruction captures a strong regional precipitation signal. Such long-term records are essential for understanding hydroclimatic extremes and for supporting climate adaptation, water-resource management, assessing water-resource sustainability, and ecosystem dynamics in the Himalayan region.

This study provides a comprehensive permafrost distribution map of Jammu and Kashmir based on the mean annual air temperature derived from MODIS land surface temperature products between 2002 and 2023. The landscape elements susceptible to permafrost degradation and associated cascading hazards were also delineated through proximity analysis in a GIS environment. The permafrost map was validated using available rock glacier inventories over the study area. The analysis revealed that permafrost covers 64.8% of the total geographic area, with 26.7 % classified as continuous permafrost, 23.8% as discontinuous, 14.3% as sporadic, and 35.2% as non-permafrost. Region-wise, the Ladakh Plateau contains the highest proportion (87%) of permafrost, while the Foothill Plains, Shigar Valley, and Siwaliks do not host any permafrost. The susceptibility analysis indicated that a 193 km road stretch, 2415 households, 903 alpine lakes and 8 hydropower projects are potentially prone to permafrost degradation-related hazards in the region. The results revealed a substantial overlap (similar to 99.6%) between the rock glaciers and the delineated permafrost providing a strong validation metric. This research provides first-hand insights for detailed monitoring of the permafrost across the Himalayan region and serves as baseline information for implementing agencies so that robust action policies aimed at mitigating the impact of permafrost degradation-related hazards in the region are framed.

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Accurate estimates of forest dynamics and above-ground forest biomass for the topographically challenging Himalaya are crucial for understanding carbon storage potential, assessing ecosystem services, and guiding conservation efforts in response to climate change. This dataset provides a manually delineated multi-temporal forest inventory and a comprehensive record of above-ground biomass (AGB) across the Kashmir Himalaya, generated from field observations, advanced remote sensing and machine learning. Data were collected and generated through remote sensing techniques and extensive in-situ measurements of 6220 trees (n=275 plots), including tree diameter at breast height, species composition, and tree density to map forest area and model AGB across varied terrain. The dataset captures major forest types and species-specific AGB variation influenced by elevation, slope, and aspect. Additionally, newly developed species-specific allometric models, improved through the integration of normalized difference vegetation index (NDVI) and topographical augmentation are provided to improve AGB estimation accuracy. This dataset serves as a crucial resource for forest management, carbon monitoring, and ecological modeling, with broad applications in regional conservation strategies, biodiversity planning, and climate policy development in mountainous ecosystems.

Corn leaf aphid, Rhopaloshium maidis Fitch (Hemiptera: Aphididae), is a prevalent maize pest, causing significant yield losses by affecting all crop stages. To mitigate such losses, current management relies on the application of chemical insecticides, posing environmental degradation risks and promoting insecticide-resistant aphid populations. These challenges necessitate the development of environment friendly and effective alternatives. One such promising alternative is silicon (Si) supplementation, which alleviates a variety of abiotic and biotic stresses in plants including insect herbivory, though it’s specific effects on corn leaf aphids are poorly understood. Against this back drop, this study investigated the effect of Si supplementation in mitigating corn leaf aphid infestations in maize. Plants were treated with three Si doses (T1: 500, T2: 750 and T3: 1000 mg L⁻1) and infested by corn leaf aphids. Then, performance of aphids was determined by measuring their feeding preferences, fecundity and mortality rates. Si accumulation in maize plants was also determined, with the highest concentration observed in T3 plants, followed by T2 and T1 plants. Correspondingly, aphid number were lowest in T3 (0.65 in free-choice and 0.30 in paired-choice tests) and T2 (0.78 in free-choice and 0.40 in paired-choice tests). Aphid fecundity was significantly reduced in T3 (6.85 nymphs, representing a 78.94

Understanding the anthropogenic impacts, hydro-climatological variability, and adaptive practices in the Indian Himalayan Region (IHR) is essential for promoting sustainable development. Given the ecological fragility and livelihood dependence of the region on hydro-climatic systems, this study contributes to SDG 6 (Clean Water), SDG 13 (Climate Action), SDG 15 (Life on Land), SDG 1 (No Poverty), and SDG 11 (Sustainable Communities) by linking climate, land use, and community resilience. Despite growing research on climate-induced hydrological shifts, existing studies often lack basin-specific, multi-decadal evaluations integrating both climatic and land use land cover (LULC) dynamics with community-level insights. This study addresses this gap by evaluating hydro-climatic extremes and LULC changes on hydrological responses in five different river basins (i.e., Sindh, Parbati, Dhauliganga, Ranganadi, and Imphal) of the IHR using gridded datasets, field-gauging stations, and LISS-III/IV satellite data (2005, 2013, 2017). Principal Component Analysis (PCA) identifies temperature as the key driver in snow-fed basins, while precipitation governs rainfall-dependent processes in the Ranganadi basin. Canonical Correlation Analysis (CCA) corroborates these findings, highlighting temperature and precipitation as the primary climatic drivers. Hydrological responses were assessed using the Soil and Water Assessment Tool (SWAT). The results show increased extreme hydro-climatic events (1978–2020), with flash floods affecting these basins. LULC analysis reveals forest and glacier cover declines, coupled with expansions in barren, agricultural, and urban areas, indicating environmental degradation. SWAT simulations achieved strong model fits (R2 > 0.8), showing snowmelt contributing 17–44 This graphical abstract illustrates climate change research in the Indian Himalayan Region, examining hydroclimatic extremes and their impacts on headwater basins. Input variables are categorized as hydro-meteorological data (precipitation, temperature, relative humidity, solar radiation, wind speed, and streamflow), spatial data (digital elevation maps, land use land cover, soil maps, slope), and socio-economic data (questionnaire surveys from the Himalayan villages about climate change and anthropogenic impacts). The study area is depicted through basin maps showing river systems with color classifications. The methodology integrates these datasets, distinguishing between snow-fed and rain-fed regions with their specific characteristics. The results show observed versus simulated discharge patterns for Dhauliganga, Parbati, Sindh, and Ranganadi river basins, revealing temporal variations and model accuracy. The analysis identifies impacts including LULC changes, increased mining, forest burning, altered streamflow, hydroelectric project development, and biodiversity loss. The research offers policy recommendations and mitigation measures to enhance livelihood options through green skill development, address human vulnerability (especially women's adaptation and resilience), and implement effective communication strategies.

Glacial lake monitoring is urgently needed across the Himalaya due to the threat of glacial lake outburst floods (GLOFs). Furthermore, both the population and the infrastructure exposed to or dependent on these glacial lakes are increasing. However, there are a substantial number of glacial lakes in the Himalaya with potential transboundary GLOF impacts, and their remote, high-altitude locations make monitoring extremely challenging, so existing field measurements are limited. Here, we propose a benchmark Himalayan glacial lake monitoring network "HiGLMN" that will characterize glacial lakes by combining geomorphological signatures of GLOFs, monitoring triggers and mechanisms of dam failure, and downstream impacts using in situ observations, remote sensing, and hydrodynamic modeling, and feed into early warning for disaster mitigation. We also provide existing practices to support the effectiveness and necessity and propose strategies for future data management. The monitoring network will contribute to robust GLOF risk management, early warning, and mitigation. SIGNIFICANCE STATEMENT: The proposed glacial lake monitoring network aims to mitigate the escalating threat of glacial lake outburst floods in the Himalaya, where growing populations and infrastructure are at risk. The network will use a combination of in situ observations, remote sensing, and hydrodynamic modeling to better understand and predict outburst floods. The resulting data will support early warning systems and strengthen disaster risk management strategies. We also propose effective data management approaches to ensure the long-term success of the network in mitigating the damage caused by glacial lake outburst floods.

Silicon (Si) enhances stress tolerance in plants, though its effects can vary across different genotypes. However, most studies on silicon use efficiency have overlooked the genotypic differences in silicon accumulation and its associated benefits. In this study, we screened various wheat genotypes with differing Si accumulation potentials, and selected two contrasting genotypes to understand their physiological responses to different silicon concentrations and the resulting changes in growth and yield in silicon deficient peat soil. Twenty wheat genotypes were screened for silicon accumulation potential by Molybdenum Blue method. Two contrasting wheat genotypes, viz., WW-101 (high Si-accumulator) and SW-2 (low Si-accumulator) were finally selected to investigate the effect of different silicon concentrations on various growth, photosynthetic and yield parameters in silicon deficient peat soil. Significant differences in silicon accumulation were observed among the selected wheat genotypes. Silicon fertilization enhanced plant height, leaf area, biomass, and yield of both wheat genotypes in silicon deficient peat soil. Additionally, silicon supplementation improved the photosynthetic efficiency of both the genotypes by enhancing photosynthetic pigments, increasing water use efficiency, and reducing transpiration rate. The silicon-derived benefits were more pronounced in the ‘WW-101’ genotype compared to ‘SW-2’, indicating genotype-specific differences in silicon uptake and utilization. The observed variation in silicon accumulation among wheat genotypes highlights the critical role of genotype-specific differences in silicon uptake efficiency. Silicon fertilization enhanced the growth and yield of both contrasting genotypes by improving photosynthetic efficiency through increased pigment concentrations and water use efficiency. Notably, the high Si-accumulator genotype WW-101 derived greater benefits from silicon supplementation than SW-2, emphasizing the importance of prioritizing silicon-efficient genotypes to enhance crop productivity in silicon-deficient soils.