National University of Mongolia
Recent publications
New experimental measurements for 16O + 12C elastic scattering angular distribution at Elab = 27 MeV were performed at the cyclotron DC-60 INP RK. The measured data as well as the previous measurements for 16O + 12C angular distributions in the energy range Elab = 20–140 MeV are subjected to detailed analysis using the double folding optical potential. For this purpose, different models of interaction potentials are used, such as the BDM3Y1-Reid and the CDM3Y1-Paris based on the M3Y interactions. The new B3Y-Fetal potentials are also tested, and the efficiency of the DDB3Y1-Fetal interaction to increase the saturation properties of cold nuclear matter was studied in comparison with the well-known BDM3Y1-Reid and CDM3Y1-Paris interactions.
Grassland ecosystem dominates in the Mongolian Plateau, mostly located in its arid and semi-arid regions. Although the ecosystem is an important source for agriculture, it is also a fragile system ecologically. This system is one of the most sensitive areas to global climate change. Precipitation (PPT) and soil moisture (SM) are important water sources in the grassland ecosystem, and their changes would greatly affect vegetation growth. This paper generates the precipitation use efficiency (PUE) and soil water use efficiency (SWUE) of Mongolian Plateau grassland based on multi-source remote sensing data to investigate the spatio-temporal distribution pattern and identify the driving factors. Results showed four main findings. Firstly, two water use efficiency (WUE) indicators show a generally increasing trend from 2000 to 2018, with average PUE and SWUE 1.07 gC·m⁻²·mm⁻¹ and 1.03 gC/kg·H2O, respectively. They have similar spatial distribution patterns, consistent with the available water resources, decreasing from northeast to southwest. However, grassland vegetation growth is more sensitive to soil moisture than precipitation, and the dynamic change of SWUE is smoother and more significant than PUE. Secondly, due to the higher species richness, better vegetation biological characteristics and less severe growth environment, meadow grassland has the highest PUE and SWUE, followed by typical grassland and desert steppe. Thirdly, PUE and SWUE are relatively low in extremely arid and humid regions. In areas with relatively moderate water conditions (PPT in 148–360 mm, SM in 0.14–0.35 cm³/cm³), two indicators increase with the abundance of moisture conditions and reach the maximum. Fourthly, there is a positive linear relationship between PUE (SWUE) with precipitation and a unimodal correlation between PUE (SWUE) with temperature across the entire grassland. However, a varying correlation exists in different grassland ecosystems, especially meadow grassland. Together with analyzing past and future trends, this study provides strong evidence to reflect the impact of global climate change and the management and protection of the grassland ecosystems in arid and semi-arid regions.
The sucking louse fauna associated with Mongolian mammals is inadequately known. We provide a list of 25 species of sucking lice recorded from Mongolian rodents including previously published records, and new records of specimens collected during an expedition to northwestern Mongolia in 2015. Hoplopleura inagakii Ono and Hasegawa and Polyplax cricetulis Chin are newly recorded from Mongolia and 2 new host associations in Mongolia are recorded for Hoplopleura acanthopus (Burmeister). We describe Hoplopleura altaiensis n. sp., from the Gobi Altai mountain vole, Alticola barakshin Bannikov (type host) with an additional specimen from Alticola strelzowi (Kastchenko) (Strelzow's mountain vole). Both sexes of the new species are illustrated with scanning electron micrographs and line drawings. We note small morphological differences in the shape of the female subgenital plate between specimens prepared for scanning electron microscopy versus those prepared for light microscopy following DNA extraction.
Drawing on social media context such as Facebook of international students from the Global South – Mongolia – in Australia, this article indicates that the diversity of “languaging” practices of migrants who come to settle in Australia from the Global South are better understood from the perspective of the “normativity of diversity”. The notion of “languaging” is vital in capturing the current complexity of mixed and hybrid language practices fundamentally produced by the amalgamation of linguistic and cultural resources intersecting with Global South and North social, cultural and political landscapes. However, these languaging practices in Australia are neither non-normal nor substandard linguistic productions as mostly imagined in the local monolingual ideology. Instead, languaging practices of the migrants from the Global South in Australia should be understood as part of the new settlers’ normative daily linguistic practices that cut across both online and offline settings. Consequently, it is crucial for language educators and language policy-makers in Australia to reconsider migrants’ linguistic diversity in globalisation through the eyes of the “normativity of diversity”.
Studying the spatial and temporal water distribution in the Lake Baikal Basin, which hosts the freshwater lake with the most water storage in the world, is essential to understand the water resources and environment of the basin and its impact and influence in terms of climate change and disaster prevention and mitigation. The basin spans two countries, Russia and Mongolia, which, along with its vastness, makes it challenging to accurately automate the acquisition of large-scale and long-term series data. The Google Earth Engine (GEE) is capable of processing large amounts of remote sensing imagery but does not support the computation and application of deep learning models. This study uses a combination of local deep learning training and GEE cloud-based big data intelligent computing to empower GEE with deep learning computing power, enabling it to rapidly automate the deployment of deep learning models. Visible light, near infrared (NIR), modified normalized difference water index (MNDWI), short-wave infrared 1 (SWIR1), linear enhancement band (LEB), and digital elevation model (DEM), which are more sensitive to water bodies, were selected as input features, along with the optimized input features of the existing pixel-based convolutional neural network (CNN) model. This method corrects the initial water labels from the Landsat quality assessment bands to reduce the time cost of manually drawing the labels and improving the classification accuracy of the water bodies. On average, only 1–2 h are required to generate the results for each water body product for each period in Lake Baikal Basin. The extraction of water bodies from the Lake Baikal Basin was achieved for nine yearly periods between 2013 and 2021. The validation accuracy was 92.9 %, 92.7 %, and 92.4 % for the three years 2013, 2017 and 2021, respectively. The results showed that the mean area of water bodies in the basin was 37,500 km² and that the area of water bodies in the basin fluctuated without significant change from 2013 to 2021. This study provides methodological support for the continuous monitoring and assessment of water body dynamics at more catchment scales and other large scenarios.
This book provides an overview of lakes in Mongolia from scientific, economic and scenic points of view, presenting lake area changes, their sedimentological and geochemical characteristics, valuable economic and geoheritage resources and paleoclimate change reconstruction. The book emphasizes internationally well-known lakes of Mongolia, but it also describes far less popular lakes which have remained unrecognized for scientific importance. The book offers modern, qualitative, process-oriented approaches and quantitative analytic results-based implications to understand the geomorphological, sedimentological and geochemical evolution of lake basins in Mongolia, and past and present climate changes in Mongolia and Eurasia. Insights into the interpretation of data obtained from the lake basins in the fields of geomorphology, sedimentology, geochemistry, geochronology and paleoclimatology are developed from theoretical principles, empirical observations, correlative illustrations, analytic measurements and conscious hypotheses. Based on the application of a combined compilation of recent Landsat 8 images of the lakes and topographic maps of them in 1970, this book presents enriched results and implications derived from remote sensing together with field measurements and laboratory analyses. This data compilation belongs to a research team at the Laboratory of Geochemistry and Geomorphology (LGG), National University of Mongolia (NUM).
In this study, we assessed the functional and architectural traits in the coarse roots of Ulmus pumila trees, which are used for afforesting the semi-arid steppe of Mongolia. Tree growth was supported by different watering regimes (no watering, 2, 4, and 8 L h−1) and by two types of soil fertilization (NPK and compost). In July, 2019, for each of these treatments six trees, outplanted in 2011 as 2-year-old seedlings from a container nursery, were randomly selected, excavated by hand, and digitized. The build-up of root length correlated positively with increasing levels of watering for both soil depths analyzed. The application of fertilizers led to root growth suppression resulting in a general reduction of root length in a lowered rooting depth. When root system characteristics were analyzed in relation to wind direction, unfertilized trees showed higher root diameter values in both soil layers of leeward quadrants, likely a response to mechanical forces to improve stability. On the contrary, fertilized trees did not show differences in root diameter among the different quadrants underscoring a strong reduction in root plasticity with a lack of morpho- architectural response to the mechanical forces generated by the two prevailing winds. Finally, the root branching density, another important trait for fast dissipation of mechanical forces, was significantly reduced by the fertilization, independently of the quadrants and watering regime. Our results suggest that knowledge of the root response to the afforestation techniques applied in the semi-arid steppe of Mongolia is a necessary step for revealing the susceptibility of this forest shelterbelt to the exacerbating environmental conditions caused by climate change and, thus, to the development of a sustainable and successful strategy to restore degraded lands.
To establish the biogeographic affinities of the caddisfly fauna of Mongolia, published records and results of our faunistic studies were analyzed. This study captured more than 47,000 adults collected from 386 locations beside lakes, ponds, streams/rivers, and springs in ten sub-basins of Mongolia using Malaise traps, aerial sweeping, and ultraviolet lights. In total, 201 species have been recorded, and approximately 269 species may occur in Mongolia according to our estimation. In a comparison of species richness for the family level, the Limnephilidae and Leptoceridae were the richest in species. The families Brachy-centridae, Glossosomatidae, and Psychomyiidae had low species richness, but they included the most dominant species in terms of abundance and/or the percentage of occurrence in the samples from multiple sub-basins. Comparing the sub-basins, the Selenge had the highest Shannon diversity (H' = 3.3) and the Gobi sub-basin had the lowest (H' = 1.5). According to the Jaccard index of similarity, caddisfly species assemblages of Mongolia's ten sub-basins were divided into two main groups: One group includes the Selenge, Shishkhed, Bulgan, Tes, and Depression of Great Lakes sub-basins; the other group includes the Kherlen, Onon, Khalkh Gol, Valley of Lakes, and Gobi sub-basins. The majority of Mongolian species were composed of East Palearctic taxa, with a small percentage of West Palearctic and Nearctic representatives and an even smaller percentage from the Oriental region, suggesting that the Mongolian Gobi Desert is, and has been, a significant barrier to the distribution of caddisfly species between China and Mongolia.
School climate measures are important tools that assist educators in evaluating the “norms, values, and expectations that support people feeling socially, emotionally and physically safe” (National School Climate Council, 2007, p. 4). Positive school climate is associated with academic performance indicators such as grade point average, achievement-related markers such as school satisfaction and identification, and student mental health and psychosocial outcomes. In Mongolia, no school climate measures have been developed or translated and evaluated for use in Mongolian schools. We adapted and validated of the What’s Happening in This School (WHITS), a self-report measure for secondary schools, for use in Mongolia. After conducting a thorough literature review, we selected, translated and administered the WHITS to 1,471 students in grades 8–12 at seven schools in three of the largest cities in Mongolia. Exploratory and confirmatory factor analyses confirmed a six-factor structure that includes 36 of the original 48 items. The adapted measure, WHITS-Mongolia, is reliable and valid for use in Mongolian secondary schools. This study underscores the importance of evaluating the utility and validity of specific measures within a country.
Rather than relying on a potentially poor point estimate of a coefficient break date when forecasting, this paper proposes averaging forecasts over sub-samples indicated by a confidence interval or set for the break date. Further, we examine whether explicit consideration of a possible variance break and the use of a two-step methodology improves forecast accuracy compared with using heteroskedasticity robust inference. Our Monte Carlo results and empirical application to US productivity growth show that averaging using the likelihood ratio-based confidence set typically performs well in comparison with other methods, while two-step inference is particularly useful when a variance break occurs concurrently with or after any coefficient break.
China's Zhundong region is rich in coal resources. However, the high content of AAEMs and Fe (Na, Mg, Ca and Fe) in the coal leads to serious equipment fouling and slagging problems during combustion. In this paper, eco-friendly acidic ionic liquid [Bmim]HSO4 was used as a pretreatment solvent for the removal of AAEMs and Fe from Zhundong coal. The effects of [Bmim]HSO4 concentration on the removal of Na, Mg, Ca and Fe were comprehensively investigated. The changes of occurrence modes of four metal elements were systematically analyzed. The removal mechanism of AAEMs and Fe from Zhundong coal was expounded. The results showed that the ash content and B/A of coal treated by [Bmim]HSO4 were significantly lower than those of water leached coal and raw coal. The content of Na2O in coal ash treated by [Bmim]HSO4 was as low as 0.939%, which met the standard of power coal. The removal rate of AAEMs and Fe increased with the increment of [Bmim]HSO4 solution concentration. At the optimum concentration of 5%, the removal rate of Na, Mg, Ca and Fe were 92.89%, 81.11%, 79.31% and 48.27%, respectively. Compared with deionized water, [Bmim]HSO4 solution showed an excellent removal effect on NH4Ac-soluble and HCl-soluble metal elements. It was mainly attributed to the following two points: Firstly, [Bmim]HSO4 destroyed the ionic force and coordination interaction between metal ions and organic oxygen-containing functional groups in coal, carboxylates and phenates were protonated and H⁺ replaced metal ions. Secondly, the swelling effect of [Bmim]HSO4 on coal was beneficial to the removal of tiny acid soluble minerals embedded in the coal matrix, which further enhanced the removal of AAEMs and Fe in Zhongdong coal by [Bmim]HSO4.
The impact of nickel (Ni²⁺) on the performance of anodic electroactive biofilms (EABs) in the bioelectrochemical system (BES) was investigated in this study. Although it has been reported that Ni²⁺ influences microorganisms in a number of ways, it is unknown how its presence in the anode of a BES affects extracellular electron transfer (EET) of EABs, microbial viability, and the bacterial community. Results revealed that the addition of Ni²⁺ decreased power output from 673.24 ± 12.40 mW/m² at 0 mg/L to 179.26 ± 9.05 mW/m² at 80 mg/L. The metal and chemical oxygen demand removal efficiencies of the microbial fuel cells (MFCs) declined as Ni²⁺ concentration increased, which could be attributed to decreased microbial viability as revealed by SEM and CLSM. FTIR analysis revealed the involvement of various microbial biofilm functional groups, including hydroxyl, amides, methyl, amine, and carboxyl, in the uptake of Ni²⁺. The presence of Ni²⁺ on the anodic biofilms was confirmed by SEM-EDS and XPS analyses. CV demonstrated that the electron transfer performance of the anodic biofilms was negatively correlated with the various Ni²⁺ concentrations. EIS showed that the internal resistance of the MFCs increased with increasing Ni²⁺ concentration, resulting in a decrease in power output. High-throughput sequencing results revealed a decrease in Geobacter and an increase in Desulfovibrio in response to Ni²⁺ concentrations of 10, 20, 40, and 80 mg/L. Furthermore, the various Ni²⁺ concentrations decreased the expression of EET-related genes. The Ni²⁺-fed MFCs had a higher abundance of the nikR gene than the control group, which was important for Ni²⁺ resistance. This work advances our understanding of Ni²⁺ inhibition on EABs, as well as the concurrent removal of organic matter and Ni²⁺ from wastewater.
Lake Ulaan is a terminal lake at the eastern end of the Valley of Lakes in the northernmost Govi region, and the lake plays a valuable role in surface water resource of southern Mongolia. Lake Ulaan basin has been strengthened with the warming and drying since the mid-1970s. Lake Ulaan experienced changes of its area and sedimentation dynamics during the Holocene. The lake lost an area of 18.2 km2 during the last four to five decades, and it disappeared between the mid-1980s and the mid-2010s. In short, Lake Ulaan has been a playa lake during the last half century. The playa lake condition coincides with regional climate change and local warming since 1975 and drying since 1974. The linear regression analysis shows that the lake area between 1986 and 2014 had no clear relationships with the annual average air temperature (R2 = 0.0833) and precipitation (R2 = 0.0063). The correlation analysis shows that the lake area during 1986–2014 had a weak positive correlation with air temperature (r = 0.288) but no clear correlation with precipitation (r = 0.07). The geochemical analysis shows the dominance of alkali and alkaline earth metals in Lake Ulaan sediments and the higher degree of chemical weathering in the lake margin than the lake center. The chemical maturity of the Lake Ulaan sediments shows the shift from semiarid to arid climate conditions in the lake basin. Lake Ulaan contributes to the understanding of the response of the local hydrological system to climate change, and it helps in revealing the landscape evolution of the Valley of Lakes in southern Mongolia over geological time scales.
In the earliest stage of research, lakes of Mongolia were investigated primarily by Russian scientists. In the nineteenth century, the lakes of Mongolia were studied in the context of physical geography. Physiographic conditions and geneses of lakes were presented with documentation of their geographical locations, and evolutionary history and paleogeography of lake basins were hypothesized based on paleoterraces and paleoshorelines. In the early twentieth century, the lakes of Mongolia began to be studied individually on the genesis, water regime, and morphometric components of lakes in fields of geomorphology and hydrochemistry besides physical geography. Since the late twentieth century, research of lakes has stretched into hydrogeology and hydrobiology. Mongolian scientists, besides the Russian scholars, have conducted lake studies, and they developed fields of limnology and hydrology in Mongolia. During the last half of the twentieth century, lake study of Mongolia extensively covered morphometric features and physical and chemical characteristics. However, in the twenty-first century, study of lakes in Mongolia has been scientifically upgraded with high-resolution multi-proxy data, advanced methods, and new techniques. The research area has rapidly widened and multiplied in the contexts such as lake level fluctuations, spatial and temporal changes of lake area, geomorphological evolution of lake basins, geochemical and sedimentological implications from lake deposits, paleolake reconstructions, and paleoclimate and paleoenvironmental changes. The present study of lakes in Mongolia has expanded beyond limnology and hydrology into geomorphology, sedimentology, geochemistry, geochronology, and paleoclimatology forming interdisciplinary fields. Since the late 1990s and early 2000s, foreign scientists or international research teams have been in the leading positions for the lake study of Mongolia.
Landscape in southern Mongolia, specifically the Govi shows an outstanding variety as the result of the region’s long-term geotectonic evolution and climate changes over geological time scales. In southern Mongolia, the number of lakes is second in the country (24.7%), and they are mainly aeolian, volcanic, and tectonic lakes. Lakes in the Govi are important and useful archives for reconstructing paleoclimate and paleoenvironmental changes in southern Mongolia because they preserve information on hydrological and geomorphological processes. The recent significant changes of lake areas in southern Mongolia indicate how rapid the Govi landscape has been responding and how sensitive the lakes are to the present climatic warming. The warming-induced aridity strengthened in the Govi region during the last century has been controlling the landscape evolution and also disappearance and reappearance of the lakes. Sedimentological and geochronological data obtained from the Govi contribute to our understanding of the paleogeographical histories in Mongolia and Central Asia.
Lake Terkhiin Tsagaan, a volcanic freshwater lake, occurs in the Terkh River valley of the Khangai Mountain Range in central Mongolia. The lake plays an important role in the hydrological system of the North Arctic Ocean drainage basin through the activities of Terkh, Suman, Chuluut, Ider, and Selenge Rivers and Lake Baikal the lake constitutes an extraordinary scenery in the Khangai region, and Terkh River in the west, Suman River in the east, and the basaltic landscape of Mt. Khorgo in the northeast are notable. Lake Terkhiin Tsagaan responds to the climate change with a slow rate as the lake gained an area for only 0.51 km2 during the last 45 years. The short-term changes of the lake area are directly related to the fluctuations of annual and winter precipitations. Meanwhile, the long-term changes of the lake area are related to the rises in annual, summer, autumn, and spring average air temperatures, leading to thawing of snow cover and permafrost in the Khangai Mountain Range to discharge into the lake. The linear regression analysis shows that the lake area between 1970 and 2015 was moderately related to the annual precipitation (R2 = 0.47), but not clearly related to the annual average air temperature (R2 = 0.0186). The correlation analysis shows that the lake area during 1970–2015 had a moderate positive correlation with the precipitation (r = 0.685) and a weak negative correlation with the air temperature (r = −0.136). Physical and chemical properties of stratigraphic sequences of sediments in Lake Terkhiin Tsagaan indicate this lake to be a montane type with high contents of organic matter and biogenic silica and fine sediments, implying warm and humid climate conditions in the Khangai region within central Mongolia at that time of their deposition.
Central Mongolia plays an important role in climatology, hydrology, and geomorphology of Mongolia and Central Asia because it borders the North Arctic Ocean and Central Asian internal drainage basins through the Khangai Mountain Range, one of global interfluves. The extraordinary landscape of central Mongolia is characterized by the Khangai Mountain Range, a wide intermontane valley between Khangai and Khentii mountain ranges, large rivers, and many small lakes. Central Mongolia is physiographically a transition region from the Siberian high-pressure cell to the Central Asian low-pressure cell. The region is geologically diverse with the presence of Quaternary formations with igneous rocks in the north, northeast, and east of the Khangai Mountain Range. Large rivers such as Ider, Chuluut, Khanui, Tamir, and Orkhon draining the northern and northeastern Khangai and Tuul, Kharaa, and Yeruu draining the southwestern and northwestern Khentii feed Selenge River, which is a major headwater of Lake Baikal in the North Arctic Ocean drainage basin. Lakes in central Mongolia occupy only 2.9% of the total lake area (the lowest in the country), and they have primarily tectonic, fluvial, and karst origins. Lakes in this region would provide valuable information regarding the paleogeographical history of the region and paleoclimate changes within Mongolia and Central Asia.
Lake Khargal is one of geotectonically, geomorphologically, and geochemically important lakes in the taiga forest region of northern Mongolia. Lake Khargal represents dynamic changes of surface water in the region. The lake also plays an important role in the hydrological system of the North Arctic Ocean drainage basin. This is because it is a paleo-oxbow lake of Eg River, one of tributaries of Selenge River, a major headwater of Lake Baikal. Lake Khargal enlarged its area by 1.7 km2 during 1970–2010 and reduced by 0.3 km2 during 2010–2018. The changes in lake area during the last 50 years imply that Lake Khargal is sensitive to the present climate change indicated by the gradually rising annual average air temperature and fluctuating annual average precipitation since 1985. The linear regression analysis shows that the lake area between 1986 and 2018 was weakly related to the annual precipitation (R2 = 0.139), but it was not clearly related to the annual average air temperature (R2 = 0.0187). The correlation analysis shows that the lake area during 1986–2018 had a weak positive correlation with air temperature (r = 0.136) and a weak negative correlation with precipitation (r = −0.372). The A-CN-K ternary plot shows that Lake Khargal sediments were derived from the source rocks enriched in plagioclase, gabbro, tonalite, and granodiorite under a low degree of chemical weathering condition in the lake basin suggesting that a cool and arid climate dominated in the source area. The climate condition of the lake basin is shown in the chemical maturity plot, shifting from semiarid to arid. Geochronological records from Lake Khargal sediments show Holocene paleoclimate changes in northern Mongolia and Eurasia.
Lakes of Mongolia are genetically dependent on tectonic setting, volcanism, landscape, and landform evolution. Since the initial formation during the early Paleozoic Era (see Chap. 3), lakes of Mongolia have experienced diverse paths of evolution (e.g., dominant presence in the Triassic, maximum sizes in the Cretaceous, decrease in size since the Paleogene, stabilization of existence in the Neogene reaching the present conditions since the late Pliocene and early Pleistocene). Throughout the Quaternary period, lakes of Mongolia have been dramatically changing in terms of water level, area, and sedimentation dynamics (see Part II). Present lakes of Mongolia are classified to have seven major types of origins, and they can be called tectonic, volcanic, landslide, glacial, karst (and thermokarst), fluvial, and aeolian lakes. Tectonic, volcanic, glacial, and landslide lakes are commonly found in high mountains such as the Mongolian Altai, Govi Altai, Khangai, Khentii, and Khuvsgul Mountain Ranges in western, northern, and central Mongolia. Aeolian, fluvial, and karst lakes are widely distributed in lowlands, valleys, and depressions within the plains and the Govi Desert regions in eastern and southern Mongolia.
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Batbold Tserendorj
  • Department of Mathematics
Bazartseren Boldgiv
  • Department of Ecology
Ganbat Baasantseren
  • Electronics and Communication Engineering
Namsrai Tsogbadrakh
  • Department of Physics
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