High Mountain Areas Research Articles

A method for robust estimation of snow seasonality metrics from Landsat and Sentinel-2 time series data over Atlas Mountains scale using Google Earth Engine

Seasonal snow cover provides the majority of freshwater supplies for human society and natural ecosystems especially in semi-arid regions. For water resource managers, precise data regarding the spatiotemporal variability of snow cover and snow phenology is of paramount importance. Owing to the great spatial and temporal heterogeneity of the snowpack and the inaccessibility of high mountainous areas, gapless satellite remote sensing presents an unprecedented opportunity to monitor snow cover effectively and affordably on a fine scale, from different aspects, and with regular revisit time. This study derives the snow seasonality metrics (first day of snowfall, last day of snow melt; and snow cover duration) over a large semi-arid region in Morocco’s Atlas Mountains. We calculate these metrics by combining over 10,000 images from Landsat 8 and Sentinel 2 satellites for four hydrological years (2016–2021) to create a harmonized product with a time interval of about 3 days using the Google Earth Engine (GEE) platform. This dense and large time series facilitates a gap-filling method to minimize and overcome the effect of cloud cover, and its assessment shows a positive correlation between the masked pixels and the interpolated ones. These methods allowed us to realize a map of the snow cover area and extract a homogeneous Normalized Difference Snow Index (NDSI) profile over the four years whereby we were able to determine the optimal threshold to separate the presence of snow from its absence. The results showed that derived snow cover metrics provide considerable variation in both time and space, where an increase in snowpack measurement values at higher elevations can be noted. Overall, the snow duration ranges between November and April depending on the characteristics of each hydrological year. The retrieved Landsat 8 and Sentinel 2 snow dates had a high level of agreement with in-situ data observations with almost a day-and-a-half delay with an overall accuracy equal to 0.96. The analysis of snow cover dynamics via GEE has offered the ability to calculate the first day of snowfall, last day of snowmelt, and snow cover duration annually at a pixel level, providing the user with the ability to track the seasonal and interannual variability in the timing of snowmelt toward a better understanding of how the hydrological cycles of higher latitude and mountainous regions are responding to climate change.

Landslide and erosion processes in the high-mountain areas of the Greater Caucasus, Azerbaijan

Landslide and erosion processes in the high-mountain areas of the Greater Caucasus, Azerbaijan

Temporal variation in glacier surface area and glacial lakes in glaciated river basins of Arunachal Pradesh

Abstract Climate change-induced glacier recession has sparked a dynamic transformation of glaciers in high-mountain areas worldwide, resulting in genesis, expansion, and dissipation of glacial lakes that pose a potential threat to downstream communities, underscoring the need for regular monitoring. This study incorporates the automated glacier extraction index to improve debris-free glacier mapping accuracy by reducing water and shadow area categorization errors using multi-temporal Landsat-5 Thermal Mapper, Landsat-8 Operational Land Imager, and digital elevation model (Shuttle Radar Topography Mission) to obtain precise glacier extent. Waterbodies were delineated using thresholding techniques applied to water indices: normalized difference water index, modified normalized difference water index, normalized difference turbidity index, and slope information. The study attempted to map and analyze the temporal variations of glaciers and glacier lakes in the glaciated sub-basins of Arunachal Pradesh: Dibang Basin, Mago Basin, and Subansiri Basin. Glaciers receded at a shrinkage rate of 1.08% per year (1988–2017) in Mago Basin, 1.01% per year (2013–2022) in Subansiri Basin, and 1.42% per year (1995–2021) in Dibang Basin. Glacier lakes showed an increasing trend in number and area due to glacier melt, expanding at rates of 3.31% in the Mago Basin, 0.48% in the Subansiri Basin, and 0.68% in the Dibang Basin per year. Findings suggest that global climate change is likely the primary factor driving glacier changes in these basins.

Hydrological responses to the synergistic climate and land-use changes in the upper Lancang river basin

Climate change trends in the upper Lancang river basin (LRB), a high-mountain area, are prominent on a global scale, and climate-induced land use change with increasing cropland and migration has been observed in the past decades and is expected to expand in the future. We assessed land use and sediment yield from the basin in the past and future under the synergistic impact of projected climate change and associated land use change. We found that the transition from grassland and forest to cropland under climatic change favorable to agriculture can be the topmost contributor to the sediment yield increase from the upper LRB, with an increaisng rate of 40.6% from the entire area and as high as 118% in some sub-areas. As the baisn serves as the source area of the Lancang-Mekong River Basin (LMRB), we call for coordinated management throughout the entire LMRB, given the complex sediment dynamics crossing scales, affected by both climate change and socioeconomic development in trans-boundary basin.

Assessment of physical schemes for WRF model in convection-permitting mode over southern Iberian Peninsula

Convection-permitting models (CPMs) enable the representation of meteorological variables at horizontal high-resolution spatial scales (≤ 4 km), where convection plays a significant role. In this regard, physical schemes need to be evaluated considering factors in the studied region such as orography and climate variability. This study investigates the sensitivity of the Weather Research and Forecasting (WRF) model as CPM to the use of different physics schemes on Andalusia, a complex orography region in the southern part of the Iberian Peninsula (IP). To do that, a set of 1-year WRF simulations was completed based on two “one-way” nested domains: the parent domain (d01) spanning the entire IP with 5 km spatial resolution and the nested domain (d02) for the region of Andalusia at 1 km of spatial resolution. 12 physic schemes were examined from combinations of microphysics (MP) schemes including THOMPSON, WRF single moment 6-class (WSM6), and WRF single moment 7-class (WSM7), and different options for the convection in d01, the Grell 3D (G3), Grell-Freitas (GF), Kain-Fritsch (KF), and deactivated cumulus parameterization (OFF). The simulated precipitation and 2-m temperature for the year 2018, characterized to be a very wet year, were compared with observational datasets from different sources to determine the optimal WRF configuration, including point-to-point and station-point comparisons at different time aggregations (from annual to hourly). In general, greater differences were shown when comparing the results of convection schemes in d01. Simulations completed with GF or OFF presented better performance compared to the reference datasets. Concerning the MP, although THOMPSON showed a better fit in high mountain areas, it generally presents a worse agreement with the reference datasets. In terms of temperature, the results were very similar and, therefore, the selection of the “best” configuration was based mainly on the precipitation results with the WSM7-GF scheme being suitable for Andalusia region.

Early husbandry practices in highland areas during the Neolithic: the case of Coro Trasito cave (Huesca, Spain)

Research on animal management strategies in high mountain areas during the early Neolithic (5,700–4,500 cal BC) has been conditioned by the presumption that human occupations in highland areas had a prominent seasonal character and the economic practices focused mainly on the exploitation of wild resources. The results obtained in the framework of research developed recently on settlement dynamics during the early Neolithic in the highland areas indicate the existence of relatively permanent occupations and the exploitation of domestic resources. Regarding livestock, the role of caprine transhumance in highland areas has been highlighted traditionally, conferring a marginal role to husbandry activities and emphasizing principally the temporary maintenance of herds of sheep and goats. In this study, we use the archaeozoological data and δ13C and δ15N stable isotopes composition of the faunal bones collagen to characterize the husbandry practices in Coro Trasito cave (Huesca, Spain). The results obtained demonstrated the presence of diverse herd foddering strategies within husbandry practices characterized by taxonomic diversity and multipurpose exploitation suggests that during the Neolithic, Coro Trasito cave played a more complex role than sheepfold. Moreover, the presence of the four main domestic species indicates the adaptation of herds of Coro Trasito to the cave environment, flocks with diverse dietary needs and reproductive behaviors. The results are discussed with an integrated analysis of the data related to animal management strategies in highland areas (more than 1,500 m. asl) during the early Neolithic, in particular in the central Pyrenees area. This study offers new elements to study the complexity of neolithization processes in the central Pyrenees and how these areas were quickly integrated into a broader economic system.

Airborne microplastics in urban, rural and wildland environments on the Tibetan Plateau

The concentration of airborne microplastics is largely unknown in the remote high mountain area of the Tibetan Plateau. Here we report airborne microplastic concentrations of 2.5–58.8 n/m3 in urban, rural and wildland areas across the Tibetan Plateau, with smaller (∼89% <100 µm) fragments (>80%) dominating. Polyethylene terephthalate, polyethylene, polyamide and polystyrene were the dominant polymers of airborne microplastics on the Tibetan Plateau. Distribution of airborne microplastics was positively correlated with anthropogenic activity indices, such as population density and nighttime light intensity. Although the contribution of long-range atmospheric transport is valid, dispersed villages also appear to be a source of airborne microplastics for wildland areas across the Tibetan Plateau.

High-resolution assessment of retrogressive thaw slump susceptibility in the Qinghai-Tibet Engineering Corridor

Under the rapidly warming climate in the Arctic and high mountain areas, permafrost is thawing, leading to various hazards at a global scale. One common permafrost hazard termed retrogressive thaw slump (RTS) occurs extensively in ice-rich permafrost areas. Understanding the spatial and temporal distributive features of RTSs in a changing climate is crucial to assessing the damage to infrastructure and decision-making. To this end, we used a machine learning-based model to investigate the environmental factors that could lead to RTS occurrence and create a susceptibility map for RTS along the Qinghai-Tibet Engineering Corridor (QTEC) at a local scale. The results indicate that extreme summer climate events (e.g., maximum air temperature and rainfall) contributes the most to the RTS occurrence over the flat areas with fine-grained soils. The model predicts that 13% (ca. 22,948 km2) of the QTEC falls into high to very high susceptibility categories under the current climate over the permafrost areas with mean annual ground temperature at 10 m depth ranging from −3 to −1 °C. This study provides insights into the impacts of permafrost thaw on the stability of landscape, carbon stock, and infrastructure, and the results are of value for engineering planning and maintenance.

Susceptibility analysis of glacier debris flow by investigating glacier changes based on remote sensing imagery and deep learning: A case study

Glacier debris flow is becoming increasingly severe as global warming intensifies. To minimize the catastrophic losses caused by glacier debris flow, it is essential to analyze the susceptibility of glacier debris flow. In this study, we employed remote sensing with deep learning methods to investigate glaciers changes, evaluating the susceptibility of glacier debris flow in Zelongnong ravine, Southeast Tibet. First, we utilized Landsat optical remote sensing imageries to obtain the semantic segmentation dataset and trained a deep learning model to automatically extract the glacier boundary in Zelongnong ravine. Second, by pre-processing the DEMs (Digital Elevation Model) and integrating them with the glacial boundaries, the volume of glacier ablation was measured. Eventually, according to the glacier ablation, the correction coefficient was determined, which modified the geomorphic information entropy theory, and further analyzed the susceptibility of glacier debris flow in Zelongnong ravine. The research results of the study present that the evaluation indices of the deep learning model that extracted glacier boundaries are over 90%. Moreover, the study results confirm the accuracy of the modified susceptibility evaluation method for glacier debris flows, and the susceptibility of glacier debris flows in Zelongnong ravine generally ranges between high and very high. This study reveals the feasibility and progress of using remote sensing and deep learning in glacier boundary extraction, providing a promising reference for the evaluation of the susceptibility and prediction of glacier debris flow in similar high mountainous areas as well.

Organic Matter Content and Standard Material Decomposition Rate in Soils of the High Mountain Plant Communities of the Teberda National Park

Soils of the high mountain areas are very diverse by their organic matter content (SOM), by the factors underlying such diversity are still not fully known. In 16 subalpine, alpine and subnival plant communities of the Teberda national park (the north-western Caucasus) we studied physico-chemical and microbiological soil properties, and estimated parameters of standard material decomposition based on the Tea bag index (TBI): stabilization factor (STBI) and decomposition constant (kTBI). We tested the following hypitheses: (1) the SOM is one of predictors of STBI and kTBI in high mountain zone along with other physico-chemical soil properties; (2) the most of SOM content belongs to high STBI and low kTBI values; (3) the SOM content correlates with below-ground plant productivity. The main gradients of the studied soils are water content (automorphic vs. hydromorphic soils) and the concurrent SOM accumulation, as well as the altitudinal gradient with the decrease of soil basal respiration with elevation. The extent of nitrogen enrichment (e.g. SOM quality) of the labile fraction was the best predictor of the decomposition constant. STBI decreased with the increase of total carbon content and the losses on ignition, while the positive link between kTBI and SOM was observed only in automorphic soils. Thus, the soils rich in organic matter typically have low stabilization factor and relatively high decomposition constant. In the plant communities with herbaceous dominants, the SOM content was positively correlated with fine root production, this stresses the important role of productivity in the accumulation of organic matter.

Holistic rockfall risk assessment in high mountain areas affected by seismic activity: Application to the Uspallata valley, Central Andes, Chile.

Over large regions exposed to natural disasters, cascading effects resulting from complex or concatenated natural processes may represent a large portion of total risk. Populated high-mountain environments are a major concern, and methods for large-scale quantitative risk analyses are urgently required to improve risk mitigation. This article presents a comprehensive quantitative rockfall risk assessment over a large archetypal valley of the Andean mountains, in Central Chile, which integrates a wide spectrum of elements at risk. Risk is expressed as an expected damage both in monetary terms and casualties, at different scales relevant for decision making. Notably, total rockfall risk is divided into its main drivers, which allows quantifying seismically induced rockfall risk. For this purpose, the local seismic hazard is quantified and the yield acceleration, that is, acceleration required to initiate rockfall, is determined at the regional scale. The probability of failure is thereafter derived in terms of annual frequency of rockfall initiation and integrated in the quantitative risk assessment (QRA) process. Our results show the significant role of seismic activity as the triggering mechanism of rockfalls, and highlight elements at risk that have a major contribution to the total risk. Eventually a sensitivity analysis is conducted to (i) assess the robustness of obtained risk estimates to the data and modeling choices and (ii) identify the most influential assumptions. Our approach evidences the feasibility of large-scale QRAs in sensitive environments and opens perspectives for refining QRAs in similar territories significantly affected by cascading effects andmultihazards.

Atmospheric Climatologies Over Isfjorden, Svalbard

AbstractThe Isfjorden region at the west coast of Spitsbergen is the most easily accessible area in the Svalbard Archipelago, making it a perfect outdoor laboratory for Arctic research. Due to its location in the high Arctic together with its complex terrain, the climatic conditions vary substantially both in time and space. Based on a new high‐resolution reanalysis, we present climatologies of five major atmospheric variables over the Isfjorden region during 2011–2021 with special focus on local effects. For example, we find that topographic channeling effects often lead to differences in near‐surface wind speeds of several m s−1 over small horizontal distances. During winter, the fjord acts as a heat and moisture island, ultimately impacting the adjacent low‐elevation land areas. These land–sea gradients reverse during summer. High mountain areas surrounding the fjord experience substantially different climatic conditions, with for example, seasonal precipitation doubling from sea level to approximately 700 m. The spatial variability over the Isfjorden region is in general found to be smaller than its temporal counterpart but larger than the diurnal cycle. Besides these findings, this study furthermore demonstrates the importance of high‐resolution regional atmospheric reanalyses compared to global products for the characterization of the local micro‐climate over Arctic fjords and the interaction with surrounding land areas.

INTERDISCIPLINARY ANALYSIS OFCLIMATE-FORCED LANDSCAPE CHANGES IN THE HIGHLANDS OF ALTAI: NATURAL SCIENTIFIC AND SOCIOLOGICAL EVIDENCE

Mountain territories are the object of close attention of scientists due to the ongoing changes in the cryosphere. Altai is one of the world centers of glaciation, where climatic changes occur most intensively. The article presents the results of an interdisciplinary geographical and sociological study of climatic changes in the highlands of the Altai Republic, conducted in 2022 by scientists from Altai State University and St. Petersburg State University. On the basis of geological-landscape study on the reconstruction and cataloging of glaciers of the Little Ice Age and the forecast of dangerous exogenous processes, landscape changes and socio-economic parameters, settlements for sociological surveys were selected (six settlements of Kosh-Agach and Ulagan districts, n = 347). The research showed that glaciers of the North Chuysky Ridge have lost 61% of their area since the Little Ice Age, with 7% of the area reduced in the last 20 years. There have been qualitative changes in glacier melting - currently, large glaciers are experiencing the greatest degradation. The population of high-mountainous areas perceive climate change as significant, affecting their daily and economic life. Living near changing glaciers is associated with difficulties and additional costs for agriculture, destruction of communication and engineering infrastructure. Meanwhile, the climate agenda is not overly actualized, the population of high-mountainous areas demonstrates a high potential for adaptation, including due to traditional knowledge of nature management and living in harsh climates.

Variation of hydro-climatic extremes in headwater regions of Hei River basin under climate change

Study regionHeadwater regions of Hei River basin, located in the northeast of Tibetan Plateau. Study focusHydro-climatic extremes analysis for historical (1971–2015) and future (2024–2100) period. New hydrological insights for the regionRemarkable climate change has been observed in high mountain areas, which may result in more frequent hydro-climatic extremes. Investigating hydro-climatic extremes variations is important for mitigating hydro-climatic disasters and implementing water resource management. Warm extremes present an increasing trend in frequency and magnitude for historical and future period, while the cold extremes show a decreasing trend in the study area. Meanwhile, frequency and amount of precipitation extremes present an increasing trend for historical and future period. As a result, the intensity of meteorological and hydrological droughts show decreasing trends while floods present an increasing trend, indicating a certain drought relief in the study area. But future occurrence of extreme droughts or floods will increase. Moreover, floods for different return periods will rise with different change rate under different scenarios (SSP 1–2.6, SSP 2–4.5, SSP 3–7.0 and SSP 5–8.5). Therefore, extreme floods or droughts risks should not be underestimated and need be addressed accordingly. The findings highlight the importance of adaptive strategies to cope with more frequent hydro-climatic extremes under climate change.

Surface deformation detection and attribution in the Mountain-Oasis-Desert Landscape in north Tianshan Mountains

ABSTRACT The Mountain-Oasis-Desert System (MODS) is the fundamental landscape component within the vast arid region of Central Asia. Human activities and natural processes cause surface displacement in the MODS, resulting in geoenvironmental issues and hazards. However, surface displacement and its driving mechanisms in the MODS are not understood. In this study, we used the time-series interferometric synthetic aperture radar (InSAR) method to detect deformation in the MODS in north Tianshan Mountain, Xinjiang and investigated its attribution from the geological conditions, groundwater level changes, and climate variability. The results along the vertical gradient indicate that decorrelation is severe in the high mountain areas with ice-marginal environments (over 3600 m above sea level (a.s.l.)) and the forest-covered mid-mountainous belt (1700–2800 m asl), rendering effective detection unfeasible. Dynamic characteristics are identified in subalpine areas with an elevation of 2800–3600 m asl, with maximum horizontal and vertical displacements of −80.2 mm/year and −58.6 mm/year, respectively. The seasonal acceleration is influenced by the combined effects of temperature and precipitation changes. We observed dense subsidence funnels and ground fissures associated with coal mining in the foreland hills (700–1700 m asl). Ground displacements here exceeded −50 mm/year two years after mining activities had ceased. Subsidence has expanded in the oases with elevations of less than 700 m asl, due to extensive groundwater extraction for agricultural irrigation. The correlation coefficient between groundwater level and displacement was 0.89 and 0.45 at wells in the agricultural and desert areas, respectively. The deformation exhibited seasonal variations associated with groundwater level. The deformation remains relatively stable in the surrounding oasis-affected desert areas, with weak fluctuations influenced by seasonal variations in groundwater level.

Evaluation of 12 precipitation products and comparison of 8 multi-model averaging methods for estimating precipitation in the Qilian Mountains, Northwest China

Mountains are the water towers of the world, so it is critical to obtain accurate precipitation data for mountainous areas. Due to the complex topography of high mountainous areas, precipitation ground stations are sparse and unevenly distributed in such areas, so precipitation products such as remote sensing and reanalysis products are used to obtain gridded precipitation data for these areas. However, no single precipitation product performs best in all areas of mountainous regions. Therefore, this study first evaluated the performance of 12 precipitation products in estimating precipitation in the Qilian Mountains at the station scale and sub-basin scale, and then compared the performance of precipitation estimates for the Qilian Mountains generated by 8 multi-model averaging methods. The evaluation results for 29 meteorological stations in the Qilian Mountains showed that the China Meteorological Forcing Dataset product was the best-performing precipitation product, while the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record product was the worst-performing precipitation product. The evaluation results for 18 sub-basins showed that at these sub-basins, the WorldClim was the best-performing precipitation product, while the High Asia Refined analysis was the worst-performing precipitation product. Thus, station-scale evaluations may not necessarily be applicable to the basin scale. Multi-model averaging methods effectively improved the accuracy of precipitation estimates both at station scale and at sub-basin scale. The Granger-Ramanathan variant C was the best multi-model averaging method for estimating precipitation at station scale. As the Granger-Ramanathan methods allow negative weights, they are not recommended to interpolate the Granger-Ramanathan weight values of stations to grids. The Bayesian model averaging (BMA) was found to be the most suitable multi-model averaging method for estimating precipitation in the Qilian Mountains by interpolation of weight values of stations to grids. The precipitation estimates generated by BMA show that the mean annual precipitation in the Qilian Mountains from 2001 to 2018 was approximately 336.1 mm, and the annual precipitation during this period increased linearly by 2.4 mm per year.

Climbing the Alps in a warming world: Perspective of climate change impacts on high mountain areas influences alpinists' behavioural adaptations

Climate change is having a major impact on high mountain areas, with glacier retreat and permafrost warming. Alpinism is deeply affected by this changing environment, which increases the technicality of the routes, their dangers, and the uncertainty of the periods of suitable climbing conditions during the summer. This raises the question of how recreational alpinists perceive and adapt to changing conditions. To answer this question, this paper reports the results of a quantitative social media survey of European alpinists based on the substitutability theory. The results from the 1071 completed questionnaires show that climate change and its impacts are clearly observed and identified by recreational alpinists; the higher the awareness of the changes, the more likely they are to engage in adaptation behaviours such as temporal, activity and spatial substitution, and informational coping. Furthermore, the more respondents perceive that climate change is affecting their practice in terms of degraded routes, increased risk, or increased frequency and magnitude of rockfalls, the more they engage in adaptation behaviours. Although adaptation seems to be sufficient to ensure satisfactory practice conditions, the development of communication for less informed alpinists, as well as the development of climate services, could be valuable to ensure sustainable and safe practices. Management implicationsRecreational alpinists' awareness of the impacts of climate change on alpinism increases their adoption of substitution and coping behaviours. The results highlight the importance for alpine organisations to communicate research on high mountain changes, especially to novice or occasional alpinists who may be less informed. The results also suggest the importance of high mountain climate services to support decision making. This could include proposing maps and topographical guides that specifically show how climate change will affect the most frequently used routes, or developing indicators such as the Rockfall Susceptibility Index.

Fit for the future? Alpine plant responses to climatic stress over two decades of seed bank storage

Climate warming is occurring in high mountain areas faster than the global average, making cold-adapted alpine specialists vulnerable. Ex situ seed conservation is a solution, but little is known about how plants from stored seeds will cope with the altered climate. We grew plants from seeds of the artic-alpine specialist Viscaria alpina, collected from the same location at different time points and held under seed bank conditions over the last 20 years. During this time the site has warmed by 0.3 °C per decade and it has been drier than average. For three old (‘ancestor’) and three recent (‘descendant’) accessions, we exposed juvenile plants to temperature and/or soil moisture stress for one month. To determine plant fitness we measured vegetative traits (above ground biomass, specific leaf area), reproductive performance (flower number, stalk height) and seed traits (number, mass). Descendants had lower above ground biomass than ancestors and produced heavier seeds. In response to drought, compared to the control, ancestors had lower biomass whereas descendants did not, though the actual biomass did not vary between ancestors and descendants. Ancestors had higher seed production under drought than descendants, but the variation was large. We show plant traits in an alpine specialist have changed over 20 years, with plants originating from recent accessions apparently better adapted to drought. These findings indicate that alpine species have adjusted to the changed climate, implying older seed bank stored seeds may be unsuitable for use in plant conservation. Seed banks should therefore increase the frequency of seed collection.

The potential of using the Blue Intensity parameter to assess the climate response of radial tree growth on the Crimean peninsula

The results of assessing the climate signal contained in the width of tree rings and the indicator of optical density of wood (Blue Intensity) of related species of pine trees – black (Pinus nigra Arnold) and Pitsunda (Pinus brutia Ten) growing on the southern coast of the Crimean peninsula are presented. The influence of the cumulative effect of moisture deficiency on the radial growth and lignification processes of late wood of the studied conifer species is shown. A specific reaction of P. nigra in high mountain areas to conditions of prolonged drought was revealed. The prospects for using the Blue Intensity indicator for dendroclimatic studies on the territory of the Crimean Peninsula have been demonstrated.

Genome-Wide Identification of Fatty Acyl-CoA Reductase (FAR) Genes in Dendrobium catenatum and Their Response to Drought Stress

Dendrobium catenatum is a high-value medicinal plant that is predominantly found in high mountain areas, thriving amidst cliffs and rock crevices. However, its wild resources face constant threats from adverse environmental conditions, especially drought stress. Fatty acyl-CoA reductase (FAR) is crucial in plant drought resistance, but there is a lack of research on FAR genes in D. catenatum. In this study, the FAR family genes were identified from the D. catenatum genome. Their genomic characteristics were investigated using bioinformatics techniques, and their expression patterns in different tissues and under 20% PEG8000 conditions mimicking drought stress were analyzed using quantitative real-time RT-PCR (RT-qPCR). Seven DcFAR genes were identified from the D. catenatum genome. The encoded amino acids range between 377 and 587 aa, with molecular weights between 43.41 and 66.15 kD and isoelectric points between 5.55 and 9.02. Based on the phylogenetic relationships, the FAR family genes were categorized into three subgroups, each with similar conserved sequences and gene structures. The cis-acting elements of the promoter regions were assessed, and the results reveal that the DcFAR upstream promoter region contains multiple stress-related elements, suggesting its potential involvement in abiotic stress responses. The RT-qPCR results show distinct expression patterns of DcFAR genes in various plant tissues. It was observed that the expression of most DcFAR genes was upregulated under drought stress. Among them, the expression levels of DcFAR2, DcFAR3, DcFAR5, and DcFAR7 genes under drought stress were 544-, 193-, 183-, and 214-fold higher compared to the control, respectively. These results indicate that DcFAR2/3/5/7 might play significant roles in D. catenatum drought tolerance. This research offers insight into the function of DcFAR genes and provides theoretical support for breeding drought-resistant D. catenatum varieties.