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The freshwater Buir Lake in Khalkh Gol soum, Dornod aimag, is located (47° 51' 47° N, 117° 51' 29° E) on the border of Mongolia and Inner Mongolia, China. The northwest and northeast part of the lake is swampy, and is flat in the rest part. This research paper reveals the lithology and some major elements content (SiO2, Al2O3, TiO2, Fe2O3, MgO, K2O, Na2O, MnO and P2O5) of the core sediments and their distribution along the depth and the Chemical Index of Alteration (CIA), which will be a significant factor in restoring environmental change. According to the data of analysis of major elements of Buir Lake sediments, the concentration of SiO2 ranges from 42.92 to 58.29%; Al2O3 = 9.25-12.83%; Fe2O3 = 3.66-4.79%; TiO2 = 0.46-0.62%; MnO = 0.08-0.13%; CaO = 5.73-11.56%; MgO = 1.34-1.81%; Na2O = 0.72-1.50%; K2O = 1.58-2.31%; and P2O5 = 0.14-0.26% respectively. The chemical index of alteration is basically the same as the distribution of SiO2, Al2O3, TiO2, Fe2O3, MgO, K2O and Na2O in the sediments of the lake, but their content at 32.5 cm interval of the core sharply decreases and also increases. This is perhaps due to global climate change. The content and distribution patterns of water-soluble elements, such as CaO, MnO, and P2O5, are negatively correlated with the chemical index of alteration. These lead to conclude that major elements of Buir Lake sediment and Chemical Index of Alteration are closely related to climatic changes in eastern Mongolia pertaining to the Upper Pleistocene and the Holocene epochs. [ABSTRACT FROM AUTHOR]

Climate change caused by land use/cover change (LUCC) is becoming a hot topic in current global change, especially the changes caused by the grassland degradation. In this paper, based on the baseline underlying surface data of 1993, the predicted underlying surface data which can be derived through overlaying the grassland degradation information to the map of baseline underlying surface, and the atmospheric forcing data of RCP 6.0 from CMIP5, climatological changes caused by future grassland changes for the years 2010-2020 and 2040-2050 with the Weather Research Forecast model (WRF) are simulated. The model-based analysis shows that future grassland degradation will significantly result in regional climate change. The grassland degradation in future could lead to an increasing trend of temperature in most areas and corresponding change range of the annual average temperature of -0.1°C- 0.4°C, and it will cause a decreasing trend of precipitation and corresponding change range of the annual average precipitation of 10 mm-50 mm. This study identifies lines of evidence for effects of future grassland degradation on regional climate in Mongolia which provides meaningful decision-making information for the development and strategy plan making in Mongolia. [ABSTRACT FROM AUTHOR]

The Inner Mongolia grassland of China is representative of semi-arid grasslands in temperate zones. Studying land surface processes in this region will improve the understanding of regional climate formation and the feedback with global climate change. Satellite remote sensing provides an excellent opportunity to study land-atmosphere interactions at the regional scale. It is necessary to develop feasible and reasonable remote sensing-based methods to map surface energy fluxes for a specific study area. In this paper, previously published algorithms and empirical formulae were tested with Landsat 7 ETM+ data to derive the regional distributions of land surface reflectance, surface temperature, NDVI and land surface energy fluxes (net radiation, soil heat flux, sensible heat flux and latent heat flux) over the upper Xilin River watershed in Inner Mongolia, China. A new land use/land cover classification was developed and applied for regionalization analysis. Validation of remote sensing derived surface reflectance, surface temperature, net radiation and sensible heat flux with field measurements shows differences of about 13, 4, 1, and 28%, respectively. This study provides valuable guidance for further investigation of the whole watershed. [ABSTRACT FROM AUTHOR]

• High spatial resolution data has a higher accuracy in acquiring SOS. • The SOS changes are mainly affected by spring temperature and winter precipitation. • At lower elevations, advancing SOS increased spring and summer growth. • At higher elevations, delayed SOS leads to decreased spring growth and increased summer growth. • The effect of SOS on vegetation growth weakens from the spring to summer seasons. Vegetation spring phenology in mountains has undergone profound changes due to climate change. In this paper, which made use of the Harmonic Analysis of Time Series (HANTS) smoothing algorithm and logistic models, the start of the vegetation growing season (SOS) inferred from MODIS datasets with different spatial resolutions from 2001 to 2018 was extracted. The MODIS data closest to the ground-truth observation data were then selected to reflect spring phenology. Combined with temperature and precipitation data, the spatio-temporal patterns and elevation-dependent change mechanisms of the SOS and its legacy effect on vegetation growth in the mountains of northwest Mongolia was examined and the following results were obtained: (1) Compared with the MOD13A1 and MOD13A2 datasets, the high spatial resolution MOD13Q1 dataset provided stronger correlations and the lowest errors with ground-truth observation data. (2) In this study, the SOS usually occurred between 120 and 152 day-of-year (DOY) with the earlier SOS detected in the low-elevation areas. Later SOS occurred mostly in the higher elevation areas. (3) The spatio-temporal variations in the SOS are mainly influenced by both spring temperature and winter precipitation, with increasing precipitation in winter tending to delay the SOS, while increasing spring temperature tended to advance the SOS. (4) At elevation gradient, the spring temperature showed a significant negative effect on SOS at all elevations, except between 1037 m and 1137 m and 3337 m to 3437 m above sea level (ASL), with a significant positive correlation between SOS and winter precipitation between 1337 m and 2937 m ASL. It is expected that spring temperature is closely linked to the heat accumulation of plants, while winter precipitation indirectly affects the temperature in spring. (5) In lower elevation areas (below 1437 m ASL), the SOS was found to be negatively correlated with spring and summer growth, with advancing SOS leading to increased vegetation growth during spring and summer. In higher elevation areas (above 1437 m ASL), the SOS was significantly negatively correlated with spring growth and positively correlated with summer growth. Hence, delayed SOS leads to decreased spring growth and increased summer growth. Also, we found the effect of SOS on vegetation growth gradually weakened from spring to summer. These findings can help to determine the mechanisms and functional consequences of spring phenological changes in mountain regions. [ABSTRACT FROM AUTHOR]

• In the Mongolian Plateau, wildfires occurred frequently from 2001 to 2015. • Advancing spring phenology more obvious in the Inner Mongolian than in Mongolia. • Preseason temperature has the greatest impact on the spring phenology. • In a typical fire area, the SOS in the fire zone shifted to earlier in the year. The variation of land surface phenology (LSP) in natural ecosystems has received much attention at the regional and global scales. In this paper, we explore the relationship between variations in the start of the growing season (SOS) and their direct and indirect drivers for the Mongolian Plateau. Our results show that wildfire events mainly occurred in 2001, 2002, 2006, 2008, 2011, and 2016. The frequency of Mongolian wildfires is lower in the south and west, but higher in the east and north. The frequency of wildfires in Inner Mongolia (China) shows a spatial gradient, with a higher frequency in the northeast and a lower frequency in the southwest. Late SOS was most widely distributed in the southeast of Mongolia and the south of Inner Mongolia. The vegetation in the grassland or forest areas showed a comparatively early SOS, between the 110th and 130th day-of-year (DOY). The advancing trends of the SOS were mainly distributed around the northeast Mongolian Plateau, which is more obvious in Inner Mongolia (China) than in Mongolia. Under the control of precipitation (pre) and solar radiation, the preseason average temperature (T mean) in most areas of the study area is from 0 to 3 months. In the Mongolian Plateau, negative partial correlations between the SOS and preseason T mean was mainly concentrated in the northern and northeastern parts of the study area, while positive correlations were mainly distributed in the central and southeastern parts. We also found that in addition to climate factors, wildfires have an impact on the SOS. After wildfires, the enhanced vegetation index (EVI), T mean and SOS showed a significant difference in the greening period between the reference region and the burned area. Compared with the reference zone, the SOS in the fire zone shifted to being earlier. This study, therefore, provides a scientific basis and reference for understanding variations in the SOS in the study area and the response of the SOS to climate change and wildfires. [ABSTRACT FROM AUTHOR]