Indian Himalaya Research Articles

Introduction pages, Nova Geodesia 3(2), 2023

Nova Geodesia (https://novageodesia.ro), Issue 2, Volume 3, 2023: The papers published in this issue represent interesting novelties in different topics of geodetic science or related fields. Nova Geodesia publishes significant papers in geodesy and close topics related to cartography, engineering projects and construction, planetology, hydrography, geography, sociodemographic factors, urban planning, environmental administration, landscape, biodiversity, and ecology. Among the exciting articles, we invite readers to find news about: Assessing ethno-veterinary practices in Kashmir Himalayas: Traditional knowledge and its role in animal healthcare; Bryomonitoring of atmospheric elements in Sphagnum sp. commonly growing bryophyte in the Indian Himalayan region of Uttarakhand; GIS-remote sensing-based village-level hydrological balance approach for agricultural water planning.

Bryomonitoring of atmospheric elements in Sphagnum sp. commonly growing bryophyte in the Indian Himalayan region of Uttarakhand

For a range of metals originating from both natural and anthropogenic sources, bryophytes are helpful biological markers of environmental contamination. This research focuses on recent changes in air quality and uses a passive biomonitoring technique to estimate atmospheric metal deposition and its seasonal trend in Sphagnum sp., as well as its substrate, from Nainital, Bhimtal, and Mangoli of Uttarakhand, India. Bryophyte samples from the summer, winter and monsoon seasons were collected from equally spaced locations. Due to the large volume of travel, a high metal concentration was discovered in Nainital. The metal deposition loads were reported in the following order: Zn > Cu > Pb > Cd. Quantitative analysis of these elements in vegetative/plants and substrate/soil showed an increase in metallic content during summer. The results indicate this moss may serve as an important tool in estimation of both aerial pollution and mineral enrichment in soil. Such research is vital since development is frequently accompanied by unfavourable changes in air quality and negative impacts of air pollution on human health, agricultural production, and natural ecosystems that need to be monitored and mitigated.

The complete mitogenome of blue sheep (Pseudois nayaur) from the Indian Himalayan Region and its comparative phylogenetic relationship with other related species

The ‘Bharal’ or ‘Himalayan Blue Sheep’ (Pseudois nayaur) is endemic to the Himalayan and Tibetan Regions. There are gaps in the available database for the blue sheep mitogenome sequencing from the Indian region. We sequenced and characterized the whole mitogenome of one blue sheep individual using the Illumina Nova-seq 6000 platform, which was 16,718 bp in length. It included 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs), and one non-coding control region (D loop). It was compared with other complete mitochondrial DNA sequences of blue sheep from the NCBI database. The whole mitogenome of blue sheep was found to be highly AT-biased (60%) and had a positive AT skew (0.121) and a negative GC skew (−0.341). In 13 PCGs of blue sheep, Leucine (15.58%) and tryptophan (2.72%) occurred most frequently. A typical secondary cloverleaf structure was observed for all tRNA genes except for tRNA-Ser, where a stable structure of dihydrouridine did not develop. The phylogenetic analysis showed Indian blue sheep population formed a separate clade with a genetic distance of 3.7 to 4.1% from the Chinese blue sheep population, suggesting it to be of a different lineage and genetically qualifies the status of distinct subspecies. The results of this study will help in further phylogenetic analysis of Indian blue sheep populations in the Western and Eastern Himalayan regions and in understanding lineage identification and evolution for further research.

IHM-DB: a curated collection of metagenomics data from the Indian Himalayan Region, and automated pipeline for 16S rRNA amplicon-based analysis (AutoQii2).

Indian Himalayan metagenome database (IHM-DB) is a web-based database consisting of information on metagenomic datasets from various databases and publications that are specifically reported from the Indian Himalayan Region (IHR). The online interface allows users to view or download the dataset-specific information for the respective states, category-wise, or according to the hypervariable region. The IHM-DB also provides an opportunity for the users to access the metagenomic publications from the IHR as well as upload their microbiome information to the website. Additionally, an open-source 16S rRNA amplicon-based automated bioinformatics pipeline, AutoQii2, allows users to analyze the single-end and paired-end raw reads. AutoQii2 provides an automated approach for performing analysis such as quality check, adapter and chimera removal and exploits the latest ribosomal database project classifier for taxonomic assignments. The source code of the AutoQii2 pipeline is available at https://gitlab.com/khatriabhi2319/autoqii2. Database URL https://ham.ihbt.res.in/ihmdb and https://fgcsl.ihbt.res.in/ihmdb.

Ghar ki tension: domesticity and distress in India's aspiring middle class

AbstractTensionis a polysemic term used across South Asia to describe the strains and scrapes of life, like ‘worry’ or ‘stress’ in Euro‐American discourse. Yet in the formerly agro‐pastoralist and upwardly mobile Gaddi community of Himalayan India, it is used by women with the qualifyingghar ki – ‘household’ – to indicate a deeper disruption to bodily humours, intimate relations, and household materiality. This article takesghar ki tension, with a particular focus on the layered qualifierghar, as a window into the precarity of middle‐class domestic life as it is experienced in the bodies of the women who pursue it. Rather than focusing on the communicative functions of women's distress within the household, this article looks to the relational, affective, and material ways in which women see their bodies and houses as mutually constituted and disrupted. This approach reveals how women's domestic labour is both a source of dignity and a burden. This burden is experienced inghar ki tension, in bodily symptoms of overheating, and visits from supernatural beings. This article suggests thatghar ki tensionmight offer a novel way of looking at distress as the psychic and embodied cost of upward social mobility beyond the Gaddi context.

Informing watershed management in data-scarce Indian Himalayas

Anthropogenic water stress, especially in mountain habitats worldwide, affects water supply and threatens water security. Evaluating past trends, assessing current conditions, and anticipating future change is paramount for the sustainable use of increasingly scarce freshwater resources. This study simulates water yield using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to generate reliable information for decision-making related to watershed management programs in data-scarce Himalayan regions. The results are translated into watershed indices easily communicable to watershed managers, stakeholders and administrative agencies. The analysis demonstrates the utility of hydrological modeling using limited data within a scoping protocol for the pre-implementation phase of any watershed management program.

Role of Different Moisture Sources in Driving the Western Himalayan Past-glacier Advances

The fragmented pattern and the rapidly declining preservation of older glacial features/evidences limits the precision, with which glacial chronologies can be established. The challenge is exacerbated by the scarcity of datable material and limitations of dating methods. Nevertheless, the preserved glacial landforms have been fairly utilized to establish glacial chronologies from different sectors of the Indian Himalayas. The existing Himalayan glacial chrono-stratigraphies have revealed that in a single valley, past glacial advances rarely surpass four stages. Thus, local and regional glacial chronologies must be synthesized to understand glacial dynamics and potential forcing factors. This research presents an overview of glacier responses to climate variations revealed by glacial chrono-stratigraphies in the western Indian Himalayan region over the Quaternary (late). The synthesis demonstrated that, although the glacial advances were sporadic, glaciers in western Himalayas generally advanced during the Marine isotope stage (MIS)-3/4, MIS-2, late glacial, Younger Dryas (YD) and Holocene periods. The Holocene has witnessed multiple glacial advances and the scatter is significant. While previous glacial research revealed that Himalayan glaciers were out of phase with the global last glacial maximum (gLGM), weak Indian Summer Monsoon (ISM) has been implicated (ISM was reduced by roughly 20%). Recent research, however, has shown that gLGM glaciation responded to the global cooling associated with the enhanced mid-latitude westerlies (MLW). Further, the magnitude of gLGM glacier advance varied along and across the Himalayas particularly the transitional valleys located between the ISM and MLW influence. It is also evident that both the ISM and MLW have governed the late Quaternary glacial advances in the western Himalayan region. However, the responses of glaciers to ISM changes are more prominent. The insights gained from this synthesis will help us understand the dynamics of glacier response to climate change, which will be valuable for future climate modelling.

Different GCMs yet similar outcome: predicting the habitat distribution of Shorea robusta C.F. Gaertn. in the Indian Himalayas using CMIP5 and CMIP6 climate models.

Climate change impact on the habitat distribution of umbrella species presents a critical threat to the entire regional ecosystem. This is further perilous if the species is economically important. Sal (Shorea robusta C.F. Gaertn.), a climax forest forming Central Himalayan tree species, is one of the most valuable timber species and provides several ecological services. Sal forests are under threat due to over-exploitation, habitat destruction, and climate change. Sal's poor natural regeneration and its unimodal density-diameter distribution in the region illustrate the peril to its habitat. We, modelled the current as well as future distribution of suitable sal habitats under different climate scenarios using 179 sal occurrence points and 8 bioclimatic environmental variables (non-collinear). The CMIP5-based RCP4.5 and CMIP6-based SSP245 climate models under 2041-2060 and 2061-2080 periods were used to predict the impact of climate change on sal's future potential distribution area. The niche model results predict the mean annual temperature and precipitation seasonality as the most influential sal habitat governing variables in the region. The current high suitability region for sal was 4.36% of the total geographic area, which shows a drastic decline to 1.31% and 0.07% under SSP245 for 2041-60 and 2061-80, respectively. The RCP-based models predicted more severe impact than SSP; however, both RCP and SSP models showed complete loss of high suitability regions and overall shift of species northwards in the Uttarakhand state. We could identify the current and future suitable habitats for conserving sal population through assisted regeneration and management of other regional issues.

Phytochemical and genetic marker (SCoT and CBDP) based study of genetic diversity and population structure in natural populations of Cannabis sativa L.: A high-value sustainable biodiversity of North-Indian Himalaya

Cannabis sativa is a versatile, sustainable cash crop grown in vast agro-climatic zones of India. The present study used comprehensive datasets involving phytochemical and molecular genotyping to characterize forty-two wild cannabis accessions collected from fourteen geographical locations of the North Indian Himalayas. Two gene-targeted dominant molecular markers, i.e., start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP), were used for molecular genotyping to evaluate genetic assortment and interrelatedness among and within wild inhabitants of C.sativa. Multiple t-tests indicated significant differences among the studied cannabis populations for the phytochemical traits. Five major cannabinoids were identified in Indian Cannabis sativa germplasm, and most of the populations were of drug/marijuana types. The considerable diversity in drug types was observed at the chemical and genetic levels. Twenty-six SCoT and twenty-one CBDP markers generated a sum of 134, and 80 alleles averaged with 3.08 and 6.65 alleles per primer, respectively. The average polymorphic information content (PIC) and resolving power per primer indicated both SCoT and CBDP as ideal markers system for genetic diversity study in Cannabis sativa. The population diversity analysis based on SCoT, CBDP, and cumulative marker dataset revealed a high genetic differentiation (Gst>0.15), and a low estimated gene flow (Nm<1.0) between the studied populations. The highest gene diversity (H) and Shannon diversity Index (I) were observed for the population of Matiyal location (Pop3) using SCoT and cumulative marker dataset. However, Population 7 (Pop7) of location Kanatal was found to be highly diverse using the CBDP marker dataset. The multivariate analyses, i.e., Neighbour-joining tree based phenetic analysis, Principal Coordinate Analysis (PCoA), and Structure, revealed that there was no individual geographical location based grouping among the cannabis populations using both markers data set individually and their cumulative datasets. However, the allocation of accessions in common groups corresponding to their geographical locations was maximum in the case of Analysis with a cumulative marker data set. Analysis of molecular variance (AMOVA) also demonstrated a maximum percentage of molecular variation at the intra-population level (77–86%) rather than the inter-population level (14–23%). Altogether, our data suggest that both SCoT and CBDP markers are the ideal markers to study the genetic relationship among geographically different populations of C.sativa, and populations identified as highly diverse can be utilized as parents in Indian cannabis breeding programs.

Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India

This study presents the source apportionment of coarse-mode particulate matter (PM10) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM10 were analyzed over the IHR. Nainital (62 ± 39 µg m−3) had the highest annual average mass concentration of PM10 (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m−3) and Darjeeling (54 ± 18 µg m−3). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m−3) &gt; Mohal-Kullu (13.75 ± 10.21 µg m−3) &gt; Nainital (10.20 ± 6.30 µg m−3), contributing to 15–30% of the PM10 mass. The dominant secondary ions (NH4+, SO42−, and NO3−) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM10 at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM10 identified by these models at all study sites. Air mass backward trajectories illustrated that PM10, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites.

The ethnic food system of Jaad Bhotiya tribal community in the Gangotri landscape of western Himalaya: a transition in traditional practices

Traditional foods of Indigenous peoples are composed of ingredients from the local environment that are culturally acceptable. The Indian Himalayan region is known for its diverse tribal population, and each of them exhibits a distinct food culture. The present study has been conducted first time to document the diverse traditional food practices of Jaad Bhotiya, a lesser-known tribe of the Gangotri landscape, Uttarakhand, India. The community holds a varied range of ethnic foods; however, 13 traditional dishes are described in the present article. This study reflects a clear understanding of their preference, importance, and causes of transitions. It is noteworthy that the elders were highly attached to ethnic foods while the younger generation has limited fondness for it. The current transitional pattern is an issue of concern for policymakers, anthropologists, and the community itself. Nonetheless, a holistic policy approach to conserve traditional foods may provide an opportunity to sustain these unique practices.

Status of homestay tourism in Indian Himalayan region: Analysis of customer review and policy support for sustainable tourism

Homestays, which have emerged as a popular idea in the growing tourism industry, act as the most suitable alternative to encourage sustainable tourism activities in the Indian Himalayan Region (IHR). Homestay tourism not only provides economic benefits to rural communities but also promotes local art, architecture, traditions, and food habits. The objective of this study was to determine the distribution of homestays in the IHR and to evaluate and compare homestay management facilities between states; between rural and urban homestays; and based on reviews and ratings from previous guests. The study included all of IHR’s states and union territories. The data for the number of homestays, ratings, and reviews of guests were taken from the popular travel booking sites with the help of a data extracting tool. According to the findings, Himachal Pradesh had the highest number of homestays (968), while Tripura had the least number of homestays (3), compared to all other states and union territories. The homestays in Jammu and Kashmir received the highest ratings. In Himachal Pradesh, homestays were available at a variety of pricing points, ranging from 300 to 38,000 INR a night. Overall, it was observed that rural homestays were equally good as their counterparts in urban areas when the hospitality standards of the rural and urban homestays were compared. To boost the effectiveness of this programme in IHR, the study’s findings may be used to design local policies, rules, and incentive programmes for the areas in which they will be put into practise.

Correction: Nagahama et al. Critical Aspects of People’s Participation in Community-Based Forest Management from the Case of Van Panchayat in Indian Himalaya. Forests 2022, 13, 1667

After publication of the research paper [...]

First Report on Rhizospheric Silicate Mineral Weathering Bacteria from Indian Himalayas and Their Roles for Plant Growth Promotion of Tomato (Solanum lycopersium L.)

First Report on Rhizospheric Silicate Mineral Weathering Bacteria from Indian Himalayas and Their Roles for Plant Growth Promotion of Tomato (Solanum lycopersium L.)

PM10 within Indian standard is achievable by mitigating the sources of PM1: A thirteen years (2009–2021) long study and future prediction (2024) over the eastern Himalayas, India

A thirteen years-long (2009–2021) study was conducted on PM10 pollution over a high-altitude station, Darjeeling (27.1° N and 88.15° E, 2000 m amsl) in the eastern Himalayas in India. To better understand the sources and build a proper mitigation strategy for PM10, we have segregated PM10 into PM1 and PM1-10 using the Anderson cascade impactor. A total of 620 sets of samples were collected during the entire study period. PM10 was found to remain within its Indian standard (60 μg m−3) in every year of the study period (long-term average PM10: 46 ± 8 μg m−3). PM10 pollution during winter (74.0 ± 15.1 μg m−3) and premonsoon (73.1 ± 12.1 μg m−3) was highest compared to other seasons. Bi-modal mass size distribution of composite PM10 was observed for all the seasons with maximum peak intensity at the finer mode (PM1). Most of the anthropogenic water-soluble ionic components as well as carbonaceous aerosols exhibited maximum intensity at PM1 too. PM10 exhibited a steady decrease from 2009 to 2013 but since 2014, a sharp rise was observed. Further, we have observed that premonsoon and winter-time PM1 pollution was the key factor for a such high rise in PM10. PM1 increased sharply at a rate of 4.1 μg m−3 yr−1 in premonsoon and 3.3 μg m−3 yr−1 in winter since 2014. Auto regressive integrated moving average (ARIMA) model for future prediction revealed that PM10 would cross its Indian standard and PM1 alone would cross the PM2.5 standard in 2024 if the current scenario remains the same and the city would be enlisted among the “non-attainment” cities of the country under “National Clean Air Program (NCAP)” of Government of India. The Positive matrix factorization (PMF) model was run to apportion the sources of PM1 and PM10. It was observed that the vehicular emissions in premonsoon (33% in PM1; 28% in PM10; contribution of vehicular emission in PM1 to PM10 > 90%) and biomass burning in winter (27% in PM1; 23% in PM10; contribution of PM1 to PM10 > 80%) are the most influencing sources that need to be curbed to mitigate PM1 and hence PM10 pollution over Darjeeling.

Land use/land cover classification using hyperspectral soil reflectance features in the Eastern Himalayas, India

Information on periodic land use/land cover (LULC) changes are imperative for regional agricultural planning and policymaking. In this study, 332 soil samples were collected across five LULC types (coal mine degraded land, grassland, shifting cultivation or Jhum, plantation, and upland agriculture) of Eastern Indian Himalayas and subsequently characterized via traditional laboratory protocols and hyperspectral sensor. The soil physicochemical data and spectral data were separately used to classify six LULC types using three machine learning (ML) algorithms [support vector machine (SVM), random forest (RF), and K-nearest neighbors (KNN)]. Results indicated that the change in LULC directly impacted the dynamics of soil properties. The principal component analysis highlighted the interrelationships between the suite of soil physicochemical properties in classifying soil samples from different LULC types. All three ML algorithms exhibited that the physicochemical properties of the soil can perfectly classify LULC types. Spectral data from the hyperspectral sensor also demonstrated good classification accuracy. Overall, SVM performed better than RF and KNN, producing 93% and 78% classification accuracy using soil properties and spectral data, respectively. Moreover, the RF algorithm could select the influential soil and spectral variables for classifying LULC types. In the future, the approach tested herein can be used to classify several LULC types into the archived national soil spectral database. More research is needed to include a wide range of soil data and more LULC classes for a comprehensive classification using advanced deep learning tools.

Energy and Development: Assessing the Viability of Hydroelectricity Trade in the Himalayas

The Himalayan region is renowned as a powerhouse of Asia. Despite its abundant natural resources, youthful population, and strategic location between two rapidly developing Asian economies, the social and economic conditions in the Himalayan region, particularly in Nepal and Bhutan, have remained consistently underdeveloped. Various factors contribute to this, including climate change-induced disasters, political instability, strained bilateral relations between lower and upper riparian countries, and inadequate resource management. This article aims to address the existing research gap by exploring the energy potential of the Himalayan region and its viability for sustainable economic growth in the face of increasing global temperatures and climate-induced energy crises. The article asserts that, unless the region diversifies its energy sources to include other renewables, the Himalayan region (comprising Nepal, Bhutan, and the Indian Himalayan States-IHS) may not be able to serve as a stable hydro energy supplier to the South Asian region. This is due to inherent challenges and the strategic competition between India and China, both regionally and globally.

Compositional change in vascular plant diversity in the alpine mountainous region of Indian north-western Himalaya indicate effects of warming

Compositional change in vascular plant diversity in the alpine mountainous region of Indian north-western Himalaya indicate effects of warming

Land Degradation : Finding solution through Agroforestry in the Indian Himalayan Agro-Climatic Zones

Land Degradation : Finding solution through Agroforestry in the Indian Himalayan Agro-Climatic Zones

Baseline metagenome-assembled genome (MAG) data of Sikkim hot springs from Indian Himalayan geothermal belt (IHGB) showcasing its potential CAZymes, and sulfur-nitrogen metabolic activity.

Here we present the construction and characterization of metagenome assembled genomes (MAGs) from two hot springs residing in the vicinity of Indian Himalayan Geothermal Belt (IHGB). A total of 78 and 7 taxonomic bins were obtained for Old Yume Samdong (OYS) and New Yume Samdong (NYS) hot springs respectively. After passing all the criteria only 21 and 4 MAGs were further studied based on the successful prediction of their 16S rRNA. Various databases were used such as GTDB, Kaiju, EzTaxon, BLAST XY Plot and NCBI BLAST to get the taxonomic classification of various 16S rRNA predicted MAGs. The bacterial genomes found were from both thermophilic and mesophilic bacteria among which Proteobacteria, Chloroflexi, Bacteroidetes and Firmicutes were the abundant phyla. However, in case of OYS, two genomes belonged to archaeal Methanobacterium and Methanocaldococcus. Functional characterization revealed the richness of CAZymes such as Glycosyl Transferase (GT) (56.7%), Glycoside Hydrolase (GH) (37.4%), Carbohydrate Esterase family (CE) (8.2%), and Polysaccharide Lyase (PL) (1.9%). There were negligible antibiotic resistance genes in the MAGs however, a significant heavy metal tolerance gene was found in the MAGs. Thus, it may be assumed that there is no coexistence of antibiotic and heavy metal resistance genes in these hot spring microbiomes. Since the selected hot springs possess good sulfur content thus, we also checked the presence of genes for sulfur and nitrogen metabolism. It was found that MAGs from both the hot springs possess significant number of genes related to sulfur and nitrogen metabolism.