High Mountain Regions Research Articles

Advancement, Simplification and Piloting of Electrical Proso Millet De-Husker (Chino Kutak)

Proso millet is a minor cereal crop commonly cultivated in rain fed marginal uplands particularly in the mid and far western mountain region of Nepal. It is potential crop for ensuring food and nutrition security and conservation of local crop biodiversity in high mountain region. Traditionally Proso millet (locally as chino) is processed manually on Mortar and Pestle (Okhal) by using muscular power. However, de-husking (pearling) of Proso millet is very tedious job. The traditional method of processing takes 1 hour to dehusk 2 kg – 3 kg of Proso millet for two women and cause lots of physical exertion to them. Therefore, GEF UNEP Local Crop Project in collaboration with Agricultural Engineering Divisionof NARC initiated program in 2017to design, fabricate and test electric Proso Millet de-husking machine (called chino kutak) that is safe and economical in operation for the use of the local farmers of remote Himalayan region. The model-1 designed, fabricated and piloted at Humla (Chhipra, Kharpunath Rural Municipality) in 2018 was improvised version of Finger millet processing machine. The Model-2 was based on the Centrifugal type working on impact principle was developed in January 2020. The Model-2 was very much successful in all variety of Proso millet and higher capacity up to 52.5 kg/hr.it is equally applicable to other millets.

Landslide susceptibility mapping with GIS in high mountain area of Nepal: a comparison of four methods

Landslide susceptibility mapping (LSM) assists identifying and targeting landslide preventive measures, thereby minimizing potential losses. Multiple approaches are employed for LSM in various physiographic regions; however, their applicability has differed across studies, with limited understanding on the most suitable approach for LSM in high mountain areas. Hence, we conducted LSM in the Indrawati watershed, a high mountain area of Central Nepal, employing four approaches: frequency ratio, logistic regression, artificial neural network, and support vector machine. Nine landslide causal factors (slope, aspect, elevation, geological formation, proximity to river, proximity to road, land cover, soil type, and curvature) were considered for LSM. Rainfall-induced landslides were mapped by the on-screen digitization of satellite images and field observations. The landslides were randomly split into a ratio of 80:20 for training and validating the susceptibility maps. The LSMs obtained by four methods were then validated and compared using area under curve (AUC), kappa index, and statistical inferences (sensitivity, specificity, positive predictive value, negative predictive value, and accuracy). Our study showed that Eutric Cambisols, a class of soil type, has a strong association with landslide occurrence among the 52 classes of the nine causal factors. We found that the artificial neural network approach possessed the best prediction capability (AUC value = 86.9%) among the four methods, followed by logistic regression (85.6%), support vector machine (81.2%), and frequency ratio (80.1%) approaches. However, Kappa index and other statistical inferences suggested the support vector machine approach to be the second-best method. Overall, we found that the artificial neural network yields more accurate and reliable results and hence considered as a promising approach for susceptibility mapping in high mountainous region of Hindu-Kush Himalaya. The findings of this study might be useful for landslide analysts, development planners and decision-makers in conducting LSM and development planning in high mountain regions.

Is New Always Better? Frontiers in Global Climate Datasets for Modeling Treeline Species in the Himalayas

Comparing and evaluating global climate datasets and their effect on model performance in regions with limited data availability has received little attention in ecological modeling studies so far. In this study, we aim at comparing the interpolated climate dataset Worldclim 1.4, which is the most widely used in ecological modeling studies, and the quasi-mechanistical downscaled climate dataset Chelsa, as well as their latest versions Worldclim 2.1 and Chelsa 1.2, with regard to their suitability for modeling studies. To evaluate the effect of these global climate datasets at the meso-scale, the ecological niche of Betula utilis in Nepal is modeled under current and future climate conditions. We underline differences regarding methodology and bias correction between Chelsa and Worldclim versions and highlight potential drawbacks for ecological models in remote high mountain regions. Regarding model performance and prediction plausibility under current climatic conditions, Chelsa-based models significantly outperformed Worldclim-based models, however, the latest version of Chelsa contains partially inherent distorted precipitation amounts. This study emphasizes that unmindful usage of climate data may have severe consequences for modeling treeline species in high-altitude regions as well as for future projections, if based on flawed current model predictions. The results illustrate the inevitable need for interdisciplinary investigations and collaboration between climate scientists and ecologists to enhance climate-based ecological model quality at meso- to local-scales by accounting for local-scale physical features at high temporal and spatial resolution.

Chemical Characteristics of Cloud Water and Sulfate Production Under Excess Hydrogen Peroxide in a High Mountainous Region of Central Japan

Over the last two decades, atmospheric sulfur dioxide (SO2) concentrations have decreased in air-polluted regions. However, this decrease was accompanied by a rise in cloud water acidity (pH), which remains below 5. With this change, gas-phase hydrogen peroxide (H2O2) exceeded SO2 in most of these regions. These conditions where SO2 10) in our observation site, which was due to power plant restrictions in Japan since the 1970s. The ion species concentrations in cloud water indicated that cloud acidification resulted from dissolution of gaseous HNO3 and SO2, whereas gaseous hydrochloric acid and organic acid had a minor contribution to the acidification. Significant losses of Cl− and Mg2+ were observed in some of the cloud water. The excess value of non-sea-salt sulfate (nss-SO42−) over NH4+ in cloud water implies the in-cloud oxidation of gaseous SO2 to aqueous SO42−. A Se tracer technique was used to conduct in-situ measurements of in-cloud SO42− production. The results showed that the in-cloud production varied in a range between 7 ± 2 and 41 ± 14%. This temporal variation might be due to ambient SO2 concentrations based on Henry’s law.

Reconstructing high-resolution gridded precipitation data using an improved downscaling approach over the high altitude mountain regions of Upper Indus Basin (UIB)

Understanding the basin-scale hydrology and the spatiotemporal distribution of regional precipitation requires high precision, as well as high-resolution precipitation data. We have made an attempt to develop an Integrated Downscaling and Calibration (IDAC) framework to generate high-resolution (1 km × 1 km) gridded precipitation data. Traditionally, GWR (Geographical weighted regression) model has widely been applied to generate high-resolution precipitation data for regional scales. The GWR model generally assumes a spatially varied relationships between precipitation and its associated environmental variables, however, the relationships need to remain constant (fixed) for some variables over space. In this study, a Mixed Geographically Weighted Regression (MGWR) model, capable of dealing with the fixed and spatially varied environmental variables, is proposed to downscale the Original-TRMM precipitation data from a coarse resolution (0.25o × 0.25o) to a high-resolution (1 km × 1 km) for the period of 2000–2018 over the Upper Indus Basin (UIB). Additionally, accuracy of the downscaled precipitation data was further improved by merging it with the recorded data from rain gauge stations (RGS) using two calibration approaches such as Geographical Ratio Analysis (GRA) and Geographical Difference Analysis (GDA). We found MGWR to perform better given its higher R2 and lower RMSE and bias values (R2 = 0.96; RMSE = 56.01 mm, bias = 0.014) in comparison to the GWR model (R2 = 0.95; RMSE = 60.76 mm, bias = 0.094). It was observed that the GDA and GRA calibrated-downscaled precipitation datasets were superior to the Original-TRMM, yet GRA outperformed GDA. Annual precipitation from downscaled and calibrated-downscaled datasets was further temporally downscaled to obtain high-resolution monthly and daily precipitations. The results revealed that the monthly-downscaled precipitation (R2 = 0.82, bias = −0.02 and RMSE = 11.93 mm/month) and the calibrated-downscaled (R2 = 0.89, bias = −0.006 and RMSE = 9.19 mm/month) series outperformed the Original-TRMM (R2 = 0.72, bias = 0.14 and RMSE = 19.8 mm/month) as compared to the RGS observations. The results of daily calibrated-downscaled precipitation (R2 = 0.79, bias = 0.001 and RMSE = 1.7 mm/day) were better than the Original-TRMM (R2 = 0.64, bias = − 0.12 and RMSE = 6.82 mm/day). In general, the proposed IDAC approach is suitable for retrieving high spatial resolution gridded data for annual, monthly, and daily time scales over the UIB with varying climate and complex topography.

Micro-nutrient pools and their mobility in relation to land-use system in a cold high altitude Himalayan mountainous region

Land-use change significantly impacts soil micro-nutrients distribution and transformations due to their inefficient scale- and location-specific management in different ecosystems. We studied the changes in micro-nutrients (viz. Zn, Cu, Fe and Mn) availability and their transformations in soils of hilly landscapes under five distinct land-use systems including mono cropping, double cropping, agroforestry, orchards and the vegetable crops to explore relationship between different fractions of variable solubility and their mobility in response to land-use change. Among the compared land-use systems, DTPA-Zn, Fe, Mn and Cu comprised ~ 3.0 to 8.2%, ~ 0.21 to 0.35%, ~ 1.2 to 6.3% and ~ 7.6 to 17.5% of their respective total content in soils. The agroforestry system had significantly (p < 0.05) higher DTPA-Zn and Mn, compared with mono-and double cropping system. However, the orchard soils had ~ 2.1, 2.0 and 3.4-times higher DTPA-Zn, Fe and Cu concentration than the agroforestry system. The agroforestry system was distinct with significantly highest proportion of total Cu retrieved as amorphous oxide bound (~ 20.5%), crystalline oxide bound (~ 33.6%), organic matter bound (~ 2.1%), while the lowest proportion was accumulated as residual form (~ 43.8%), compared with the other studied land-use systems. The mobility factor that explicit micro-nutrient transformations among soluble and stable pool revealed that monocropping had the significantly lowest (~ 3.3%), while the agroforestry system had the highest Zn mobility factor (~ 4.9%). On the other hand, agroforestry system had significantly lowest (~ 1.8%), while the soils under vegetable crops had the highest Mn mobility factor (~ 7.5%). The principle component analysis (PCA) elucidated residual micro-nutrient (Zn, Fe and Mn) fraction as significant contributors to discern land-use change in fragile hilly landscapes. These results highlight the importance of micro-nutrients management through robust interventions for long-term sustainability different land-use systems in a cold high altitude Himalayan mountainous region.

The 2020 glacial lake outburst flood process chain at Lake Salkantaycocha (Cordillera Vilcabamba, Peru)

Glacial lakes represent a threat for the populations of the Andes and numerous disastrous glacial lake outburst floods (GLOFs) occurred as a result of sudden dam failures or dam overtoppings triggered by landslides such as rock/ice avalanches into the lake. This paper investigates a landslide-triggered GLOF process chain that occurred on February 23, 2020, in the Cordillera Vilcabamba in the Peruvian Andes. An initial slide at the SW slope of Nevado Salkantay evolved into a rock/ice avalanche. The frontal part of this avalanche impacted the moraine-dammed Lake Salkantaycocha, triggering a displacement wave which overtopped and surficially eroded the dam. Dam overtopping resulted in a far-reaching GLOF causing fatalities and people missing in the valley downstream. We analyze the situations before and after the event as well as the dynamics of the upper portion of the GLOF process chain, based on field investigations, remotely sensed data, meteorological data and a computer simulation with a two-phase flow model. Comparison of pre- and post-event field photographs helped us to estimate the initial landslide volume of 1–2 million m3. Meteorological data suggest rainfall and/or melting/thawing processes as possible causes of the landslide. The simulation reveals that the landslide into the lake created a displacement wave of 27 m height. The GLOF peak discharge at the dam reached almost 10,000 m3/s. However, due to the high freeboard, less than 10% of the lake volume drained, and the lake level increased by 10–15 m, since the volume of landslide material deposited in the lake (roughly 1.3 million m3) was much larger than the volume of released water (57,000 m3, according to the simulation). The model results show a good fit with the observations, including the travel time to the uppermost village. The findings of this study serve as a contribution to the understanding of landslide-triggered GLOFs in changing high-mountain regions.

Forest Land Quality Evaluation and the Protection Zoning of Subtropical Humid Evergreen Broadleaf Forest Region Based on the PSO-TOPSIS Model and the Local Indicator of Spatial Association: A Case Study of Hefeng County, Hubei Province, China

Forest land is the carrier for growing forests. It is of great significance to evaluate the forest land quality scientifically and delineate forestland protection zones reasonably for realizing better forest land management, promoting ecological civilization construction, and coping with global climate change. In this study, taking Hefeng County, Hubei Province, a subtropical humid evergreen broad-leaved forest region in China, as the study area, 14 indicators were selected from four dimensions—climatic conditions, terrain, soil conditions, and socioeconomics—to construct a forest land quality evaluation index system. Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model, we introduced the Particle Swarm Optimization (PSO) algorithm to design the evaluation model to evaluate the forest land quality and analyze the distribution of forest land quality in Hefeng. Further, we used the Local Indicator of Spatial Association (LISA) to explore the spatial distribution of forest land quality and delineate the forest land protection zones. The results showed the following: (1) the overall quality of forest land was high, with some variability between regions. The range of Forest Land Quality Index (FLQI) in Hefeng was 0.4091–0.8601, with a mean value of 0.6337. The forest land quality grades were mainly first and second grade, with the higher-grade forest land mainly distributed in the central and southeastern low mountain regions of Zouma, Wuli, and Yanzi. The lower-grade forest land was mainly distributed in the northwestern middle and high mountain regions of Zhongying, Taiping, and Rongmei. (2) The global spatial autocorrelation index of forest land quality in Hefeng County was 0.7562, indicating that the forest land quality in the county had a strong spatial similarity. The spatial distribution of similarity types high-high (HH) and low-low (LL) was more clustered, while the spatial distribution of dissimilarity types high-low (HL) and low-high (LH) was generally dispersed. (3) Based on the LISA of forest land quality, forest land protection zones were divided into three types: key protection zones (KPZs), active protection zones (APZs), and general protection zones (GPZs). The forest land protection zoning basically coincided with the forest land quality. Combining the characteristics of self-correlated types in different forestland protection zones, corresponding management and protection measures were proposed. This showed that the PSO-TOPSIS model can be effectively used for forest land quality evaluation. At the same time, the spatial attributes of forest land were incorporated into the development of forest land protection zoning scheme, which expands the method of forest land protection zoning, and can provide a scientific basis and methodological reference for the reasonable formulation of forest land use planning in Hefeng County, while also serving as a reference for similar regions and countries.

Public Perceptions of Climate Change in the Peruvian Andes

How people subjectively perceive climate change strongly influences how they respond to its challenges. To date, relatively little is known about such perceptions in the Global South. This research examines public perceptions of climate change in the Peruvian Andes, a semi-arid high-mountain region that is highly exposed and vulnerable to adverse effects of climate change. Based on questionnaire data collected through face-to-face interviews (N = 1316), we found that respondents identify various climate-related issues as the most important challenges for their country. Many of these issues are related to water. Respondents also noticed more subtle changes and expected them to continue (e.g., extreme temperatures, food shortages). Climate impacts were clearly seen as negative, which was also reflected in the presence of emotions. When compared to previous research, more respondents had personally experienced extreme weather events (80%) and they were more certain that the climate is already changing, is caused by human activity, and is affecting distant and close places similarly. A comparison of the perceptions along different socioeconomic characteristics suggests that more vulnerable groups (e.g., rural, low income and education levels) tended to perceive climate change as more consequential, closer, and as a more natural (vs. anthropogenic) phenomenon than those from less vulnerable groups. The salience of water-related problems and personal experiences of climate-related events, as well as differences between various subgroups, could be used to improve measures to adapt to the consequences of climate change by correcting misconceptions of the population and of decisionmakers.

Can a dam type of an alpine lake be derived from lake geometry? A negative result

Glacial lake outburst floods (GLOFs) represent one of the most serious hazard and risk in deglaciating high mountain regions worldwide and the need for GLOF hazard and risk assessment is apparent. As a consequence, numerous region- and nation-wide GLOF assessment studies have been published recently. These studies cover large areas and consider hundreds to thousands of lakes, prioritizing the hazard posed by them. Clearly, certain simplification is required for executing such studies, often resulting in neglecting qualitative characteristics which would need manual assignment. Different lake dam types (e.g., bedrock-dammed, moraine-dammed) are often not distinguished, despite they control GLOF mechanism (dam overtopping/dam breach) and thus GLOF magnitude. In this study, we explore the potential of easily measurable quantitative characteristics and four ratios to approximate the lake dam type. Our dataset of 851 lakes of the Cordillera Blanca suggests that while variances and means of these characteristics of individual lake types differ significantly (F-test, t-test), value distribution of different geometrical properties can’t be used for the originally proposed purpose along the spectra. The only promising results are obtained for extreme values (selected bins) of the ratios. For instance, the low width to length ratio indicates likely moraine-dammed lake while the high value of ratio indicating round-shape of the lake indicates increased likelihood of bedrock-dammed lake. Overall, we report a negative result of our experiment since there are negligible differences of relative frequencies in most of the bins along the spectra.

Multi-sensor analysis of monthly gridded snow precipitation on alpine glaciers

Abstract. Accurate and reliable solid precipitation estimates for high mountain regions are crucial for many research applications. Yet, measuring snowfall at high elevation remains a major challenge. In consequence, observational coverage is typically sparse, and the validation of spatially distributed precipitation products is complicated. This study presents a novel approach using reliable daily snow water equivalent (SWE) estimates by a cosmic ray sensor on two Swiss glacier sites to assess the performance of various gridded precipitation products. The ground observations are available during two and four winter seasons. The performance of three readily-available precipitation data products based on different data sources (gauge-based, remotely-sensed, and re-analysed) is assessed in terms of their accuracy compared to the ground reference. Furthermore, we include a data set, which corresponds to the remotely-sensed product with a local adjustment to independent SWE measurements. We find a large bias of all precipitation products at a monthly and seasonal resolution, which also shows a seasonal trend. Moreover, the performance of the precipitation products largely depends on in situ wind direction during snowfall events. The varying performance of the three precipitation products can be partly explained with their compilation background and underlying data basis.

Source forensics of inorganic and organic nitrogen using \u03b415N for tropospheric aerosols over Mt. Tai

Nitrogen-containing species are major components in atmospheric aerosols. However, little is known about the sources of N-containing aerosols over high mountainous regions, especially for organic nitrogen (ON). This study aims to reveal the emission sources of both inorganic and organic nitrogen in tropospheric aerosols atop Mt. Tai, China, and to improve our understanding of the N cycle imbalance in the North China Plain (NCP). Total suspended particle (TSP) samples were collected on a daytime/nighttime basis in spring 2017 and were investigated for the concentrations and stable N isotopic compositions of total nitrogen, NH4+, NO3− and ON. Our results show that the concentrations of N-containing compounds were higher in daytime than nighttime, mainly resulting from mountain–valley breezes and the changes of planetary boundary layer height. However, no significant day/nighttime changes were found for their corresponding δ15N values, indicating similar contributions from different N sources between day and night. The MixSIAR Bayesian stable isotope mixing model results suggest that the most important emission source of NH3 for aerosol NH4+ was agriculture, followed by fossil fuel-related sources, human waste and biomass burning. Aerosol NO3− was mainly formed from combustion and mobile emitted NOx. Interestingly, the isotopes of ON suggest that ON were very likely firstly of primary origin. Our study reveals the characteristics of reactive N emission sources and helps understand the regional transport of tropospheric N-containing aerosols in the NCP.

Ashworthius sidemi Schulz, 1933 (Trichostrongylidae: Haemonchinae) in mountain ecosystems - a potential risk for the Tatra chamois Rupicapra rupicapra tatrica (Blahout, 1971/1972).

The Asian native Ashworthius sidemi is now in Europe, and several dozen years after its introduction, it is a widespread parasite of all wild cervids. For bovids, the nematode is a significant threat to the European bison (Bison bonasus) population and has also been found in mouflon (Ovis ariesmusimon). Our study aimed to assess the risk of infection for the endemic subspecies of northern (Alpine) chamois (Rupicapra rupicapra) – the Tatra chamois (R. r. tatrica), which has a critically endangered status. We conducted the investigation in the mountainous areas of Slovakia and Poland occupied by Tatra chamois (R. r. tatrica), Alpine chamois (R. r. rupicapra), red deer (Cervus elaphus) and roe deer (Capreolus capreolus). Animals (n = 93) shot during licensed hunting and killed in road accidents (roe deer, red deer), or which had died of natural causes (chamois) were post-mortem examined for the presence of Haemonchinae. The investigation confirmed the expansion of Ashworthius sidemi to high mountain regions via Cervidae. A. sidemi affected all of the examined roe deer and 90.0% of the red deer. As for the chamois, A. sidemi was found in one R. rupicapra originating from the Low Tatras, but not in any pure R. r. tatrica individuals living in the High and Western Tatras. Our work is the first confirmation of northern chamois infection with this alien and highly pathogenic blood-sucking nematode. Due to the important health hazard of A. sidemi infection for the Tatra chamois (R. r. tatrica), appropriate measures should be taken to reduce the possibility of parasite transmission between various cervid species living in the Tatra region, as well as the affected population of chamois and the pure Tatra chamois population inhabiting the higher parts of the mountains, constituting their natural habitat.

Структура и оценка состояния древесных пород буковых лесов Дагестана

Aim. To identify the structural features and assess the current condition of woody species in the beech forests of Dagestan, Russia.Material and Methods. Research was based on the analysis of data from 69 sampling areas located in various physical-geographical regions of Dagestan. A detailed accounting of individual specimens of all age groups of each species was undertaken in the sampling areas. The total area surveyed was 43,125 m2. In total, 11,446 individuals of different species were involved in the statistical analysis, of which 1,974 form a tree tier, in which each individual is evaluated according to a scale of condition categories.Results. A study of the structure of beech forests showed the participation rate of Fagus orientalis Lipsky to be from 7.5 to 8.5 points. The average age of the upper sub-level of beech in the foothills was 110 years and in the highlands 160 years. For most woody species the age spectrum was sinistral and incomplete. Beech with a full-membered age spectrum were observed in the beech forests of the southwestern sub-region and in the high mountain region. A general trend is observed of deterioration of the condition of individuals in the transition from the upper to the lower sub-level. The average condition of beech individuals within the tree tier is 1.4 points. The condition categories of other species are characterized as being generally closer to 'weakened'.Conclusion. The results obtained regarding the structure and condition of woody species in the beech forests of Dagestan confirm the highly edifying role of beech. The greatest negative impact is exerted by the anthropogenic factor, which is confirmed by the incompleteness of the beech age spectrum and the low participation rate of the old-growth generative group and of the post-generative period.

A dual state-parameter updating scheme using the particle filter and high-spatial-resolution remotely sensed snow depths to improve snow simulation

Snow varies widely in space and time over high mountain regions. Accurately representing the spatial distribution of snow water equivalent (SWE) is critically important for improving our understanding of snow accumulation and melt processes. Despite its importance, in situ observations are lacking in poorly gauged regions such as the headwater region of the Yangtze River (HRYR). Traditional remotely sensed retrievals are highly uncertain due to the effect of cloudiness (e.g., optical remote sensing-derived snow cover area) and the coarse spatial resolution (e.g., passive microwave remote sensing-derived snow depth). Hydrological modeling is a powerful way to understand the snow processes, but uncertainty still exists due to model deficiency and errors of forcing data. Assimilating high-spatial-resolution remotely sensed snow data into a snowmelt model may be potentially valuable for more accurate snow predictions. In this study, a high-spatial-resolution remotely sensed snow depth data set (500 m, derived by integrating snow cover area, land surface temperature, and passive microwave brightness temperature products) was assimilated into a snowmelt model within a particle filter (PF) assimilation framework, which updates both model state variables and parameters simultaneously. After assimilation, the time series of basin-averaged SWE estimation showed an appreciable improvement with respect to the simulation with the traditional calibration (TC) method, in terms of the Nash-Sutcliffe efficiency (NSE) coefficient increased by ~ 10–20% and root‐mean‐square error (RMSE) decreased by ~ 7–18%. The PF approach also greatly improved the spatial distribution of SWE estimation with RMSE decreased by ~ 15–30%. The SWE estimation from the PF was also comparable or even better than that from another assimilation scheme, namely, the direct insertion. Comparison with in situ snowfall data indicated that the simulated snowfall from the PF outperformed the TC, with RMSE decreased by ~ 15–32% and correlation coefficient increased by ~ 58–83%. Furthermore, the evolution of parameters suggested the applicability of the PF method with spatially variable parameters. With spatiotemporally variable parameters in the PF, the snow model could perfectly simulate the actual snow distribution particularly over high elevation regions where the average temperature was lower than 0 °C, while fixed parameters in the TC cannot simulate the variable snow distribution. The proposed data assimilation framework has large potential of improving the accuracy of snow prediction across poorly gauged high mountain areas.

ФОРМИРОВАНИЕ ЛАНДШАФТНОГО РАЗНООБРАЗИЯ В СУБНИВАЛЬНО-НИВАЛЬНОМ ПОЯСЕ АЗЕРБАЙДЖАНСКОЙ ЧАСТИ БОЛЬШОГО КАВКАЗА

This article analyzes the features of the landscapes of the subnival-nival belt of the Greater Caucasus within Azerbaijan, compiled schematic maps of individual high-mountain massifs using materials from the interpretation of large-scale aerial photographs. The main landscape units of the territory, as well as exogenous factors of relief formation, influencing their formation and the possibilities of carrying out economic activities in high-mountainous regions, have been identified.

Изменение температурного режима в различных климатических зонах Кабардино-Балкарской Республики

Currently, much attention is paid to the study of climate change. The climate of Kabardino- Balkaria is formed under the influence of the following main climate-forming factors: latitude, terrain, direction of prevailing winds, underlying surface. The mountainous relief causes high-altitude climate zoning, which is especially pronounced in the high-mountainous region of the Central Caucasus. The general change in air temperature and humidity with height is superimposed by a change in air circulation in the high layers of the atmosphere. In the mountains, from an altitude of about 2000 m, the leading role belongs to the western air transport. This paper presents the results of a study based on instrumental observation data at 3 m / stations located in different climatic zones of the Kabardino-Balkarian Republic.

The nitrogen and carbon footprints of vegetable production in the subtropical high elevation mountain region

Mountain vegetable production has become a critical source of low heat-resistance vegetables in summer in subtropical regions, but evaluations based on life-cycle assessment (LCA) that are relevant to the environment and economics have not been reported. We conducted a survey to compare the cabbage yield and resource inputs for small-holder farms at a high (HEL, 900–1500 m) and low (LEL, 200–600 m) elevations in a subtropical region in Southwest China. We used LCA to quantify the nitrogen (N) and carbon (C) footprints, and used the yield and environmental impacts gap method to determine the potential to mitigate the environmental impacts of farming at HELs and LELs. The results show that the respective average reactive N (Nr) and greenhouse gas (GHG) emissions for the HEL and LEL were 137.0 kg N ha−1 and 6785 kg CO2-eq ha−1, and 126.7 kg N ha−1 and 6153 kg CO2-eq ha−1, respectively. The N and C footprints for the HEL were 17.3% and 16.2% lower, respectively, than those for the LEL due to the higher yield at the HEL. The average cabbage yield was 26.5% greater at the HEL (53.2 t ha−1) than at the LEL (42.0 t ha−1). The average total N application rate at the HEL was 455 kg N ha−1, which was 6.0% greater than that at the LEL. There was great potential for yield increases and the mitigation of N and C footprints by farmers at both the HEL and LEL. Compared to the average of all surveyed farmers for HEL and LEL, those farmers whose yields and N fertilizer production efficiency were both higher than the average of all surveyed farmers (HH groups) reduced their N and C footprints by 44.7–49.4% and 44.4–51.2%, respectively, with 34.4–52.3% higher yield and 9.2–19.8% lower N application rate. This study indicates that high yield, low environmental cost, and high economic benefit can be achieved by advancing agronomic management based on the best farmers’ practices for vegetable production in a subtropical high-elevation mountain region.

Mediation in Georgia. Development perspectives and challenges

The article discusses the legal and systemic issues of the creation of a modern mediation institution in Georgia. It discusses Georgia’s historic experience traditions of settlements of disputes by means of peaceful methods, part of which are still preserved in the high mountainous regions of the country. In 2013, the country was also introduced to the mediation for settlement of collective labour disputes, which is implemented by active involvement from the government. Already existing statistics demonstrate that mediation in the given sphere is effective and actually serves for the settlement of disputes between employers and groups of employees. In 2019, Georgia adopted the law on mediation, which regulates the issue of private mediation conduction andexecution of achieved agreements. Mediators training and professional development system were created. By the adoption of the given Law ended the almost eightyear phase of mediation legal and institutional regulation,which, according to the opinion of the author of the article, was a process prolonged in time. Unified Law could have been adopted at the early stage of the reform which would have made the process of extensive usage of mediation in the country faster. As reason for introduction of mediation institution in Georgia is named the obligations of the country in the process of integration with the European Union, overloading of civil courts in the country and prolonged disputes.

Complex causes of landslides after ice sheet retreat: Post-LGM mass movements in the Northern Patagonian Icefield region

Although the dynamics of individual rock-slope failures above recently shrinking glaciers have received increasing study, less is known about the spatial distribution of landslides in paraglacial settings. Here, we present a landslide inventory for large deglaciated area (~100,000 km2) situated within the Last Glacial Maximum (LGM) limits of the Northern Patagonian Icefield (NPI). Using satellite images and the TanDEM-X digital elevation model, we mapped a total of 15,543 landslides, among which 1006 are deep-seated landslides (DSLs) with area ≥0.01 km2. The distribution of DSLs is highly asymmetric in a W-E transect of the NPI region, with pronounced clustering along the semi-arid eastern front of the Patagonian Andes. The most strongly affected domain is volcanic tablelands overlying weak Miocene sedimentary rocks, but DSLs tend to also cluster along recently deglaciated (i.e. since the end of the 19th century) eastern margin of the NPI. Compared with other high mountain regions, alpine valleys of the Patagonian Andes are affected by DSLs only in <1% of their area, an order of magnitude lower than in other reported deglaciated mountains. The modest incidence of DSLs in the Patagonian Andes is due to dominance of hard granitoid rocks and relatively weak historical seismic activity. We conclude that 1) geological conditions control the distribution of DSLs and their types in the NPI region; 2) paraglacial effects play secondary (although locally important) roles in the origin of DSLs; 3) local clusters of large DSLs originate due to specifics of the post-LGM landscape evolution, involving drawdowns of glacial lakes and incision of rivers into the unconsolidated deposits; and 4) increased abundance of landslides above the recently shrinking margin of the NPI results from the repeated Holocene fluctuations of glacier snouts around the Little Ice Age (LIA) glacier limits and the spatial coincidence of glacial debuttressing effects with the presence of active faults.