Search Results (181)

The depletion of water resources caused by climate change and human activities is a pressing global issue. Lake Ereen is one of the ten natural landmarks of the Gobi-Altai of western Mongolia is included in the list of “important areas for birds” recognized by the international organization Birdlife. However, the construction of the Taishir Hydroelectric Power Station, aimed at supplying electricity to the western provinces of Mongolia, had a detrimental effect on the flow of the Zavkhan River, resulting in a drying-up and pollution of Lake Ereen, which relies on the river as its water source. This study assesses the pollution levels in Ereen Lake and determines the feasibility of its rehabilitation by redirecting the flow of the Zavkhan River. Field studies included the analysis of water quality, sediment contamination, and the composition of flora. The results show that the concentrations of ammonium, chlorine, fluorine, and sulfate in the lake water exceed the permissible levels set by the Mongolian standard. Analyses of elements from sediments revealed elevated levels of arsenic, chromium, and copper, exceeding international sediment quality guidelines and posing risks to biological organisms. Furthermore, several species of diatoms indicative of polluted water were discovered. Lake Ereen is currently in a eutrophic state and, based on a water quality index (WQI) of 49.4, also in a “polluted” state. Mass balance calculations and box model analysis determined the period of pollutant replacement for two restoration options: drying-up and complete removal of contaminated sediments and plants vs. dilution-flushing without direct interventions in the lake. We recommend the latter being the most efficient, eco-friendly, and cost-effective approach to rehabilitate Lake Ereen. Full article

The Inner Mongolia Plateau (IMP), situated in the arid and semi-arid ecological transition zone of northern China, is particularly vulnerable to both climate change and human activities. Understanding the spatiotemporal vegetation dynamics and their driving forces is essential for regional ecological management. This study employs Sen’s slope estimation, BFAST analysis, residual trend method and Geodetector to analyze the spatial patterns of Normalized Difference Vegetation Index (NDVI) variability and distinguish between climatic and anthropogenic influences. Key findings include the following: (1) From 1982 to 2022, vegetation cover across the IMP exhibited a significant greening trend. Zonal analysis showed that this spatial heterogeneity was strongly regulated by regional hydrothermal conditions, with varied responses across land cover types and pronounced recovery observed in high-altitude areas. (2) In the western arid regions, vegetation trends were unstable, often marked by interruptions and reversals, contrasting with the sustained greening observed in the eastern zones. (3) Vegetation growth was primarily temperature-driven in the eastern forested areas, precipitation-driven in the central grasslands, and severely limited in the western deserts due to warming-induced drought. (4) Human activities exerted dual effects: significant positive residual trends were observed in the Hetao Plain and southern Horqin Sandy Land, while widespread negative residuals emerged across the southern deserts and central grasslands. (5) Vegetation change was driven by climate and human factors, with recovery mainly due to climate improvement and degradation linked to their combined impact. These findings highlight the interactive mechanisms of climate change and human disturbance in regulating terrestrial vegetation dynamics, offering insights for sustainable development and ecosystem education in climate-sensitive systems. Full article

Grazing is a free-range farming model commonly practiced in low-external-input agricultural systems. The widespread use of veterinary antibiotics in livestock farming has led to significant environmental accumulation of antibiotic residues and antibiotic resistance genes (ARGs), posing global health risks. This study investigated the antibiotic residues, bacterial community, ARG profiles, and mobile genetic elements (MGEs) in cattle feces from three provinces in western China (Ningxia, Xinjiang, and Inner Mongolia) under grazing modes. The HPLC-MS detection showed that the concentration of tetracycline antibiotics was the highest in all three provinces. Correlation analysis revealed a significant negative correlation between antibiotic residues and the diversity and population abundance of intestinal microbiota. However, the abundance of ARGs was directly proportional to antibiotic residues. Then, the Sankey analysis revealed that the ARGs in the cattle fecal samples were concentrated in 15 human pathogenic bacteria (HPB) species, with 9 of these species harboring multiple drug resistance genes. Metagenomic sequencing revealed that carbapenemase-resistant genes (bla_KPC and bla_VIM) were also present in considerable abundance, accounting for about 10% of the total ARGs detected in three provinces. Notably, Klebsiella pneumoniae strains carrying bla_CTX-M-55 were detected, which had a possibility of IncFII plasmids harboring transposons and IS19, indicating the risk of horizontal transfer of ARGs. This study significantly advances the understanding of the impact of antibiotic residues on the fecal microbiota composition and ARG profiles in grazing cattle from northwestern China. Furthermore, it provides critical insights for the development of rational antibiotic usage strategies and comprehensive public health risk assessments. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

Understanding the interplay between climate change, landscape patterns, and carbon sequestration is critical for sustainable ecosystem management. This study investigates the spatiotemporal evolution of vegetation Net Primary Productivity (NPP) and landscape patterns in Inner Mongolia, China, from 2000 to 2020, and evaluates their implications for carbon sink capacity under climate change. Using remote sensing data, meteorological records, and landscape metrics (CONTAG, SPLIT, IJI), we quantified the relationships between vegetation productivity, landscape connectivity, and fragmentation. Results reveal a northeast-to-southwest gradient in NPP, with high values concentrated in forested regions of the Greater Khingan Range and low values in arid western deserts. Over two decades, NPP increased by 73% in high-productivity zones, driven by rising temperatures and ecological restoration policies. Landscape aggregation (CONTAG) and patch connectivity showed strong positive correlations with NPP, while higher fragmentation values (SPLIT, IJI) negatively impacted carbon sequestration. Climate factors, particularly precipitation variability, emerged as critical drivers of NPP fluctuations, with human activities amplifying regional disparities. We propose targeted strategies—enhancing landscape connectivity, regional differentiation management, and optimizing patch structure—to bolster climate-resilient carbon sinks. These findings underscore the necessity of integrating climate-adaptive landscape planning into regional carbon neutrality frameworks, offering feasible alternatives for mitigating climate impacts in ecologically vulnerable regions. Full article

The escalation in the population of livestock coupled with inadequate precipitation has caused a reduction in pasture biomass, thereby resulting in diminished grassland carrying capacity (GCC) and pasture degradation. In this research, net primary productivity (NPP) data, sourced from the Global Land Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets from 1982 to 2020, were initially transformed into aboveground biomass (AGB) estimates. These estimates were subsequently utilized to evaluate and assess the long-term trends of GCC across Mongolia. The MODIS data indicated an upward trend in AGB from 2000 to 2020, whereas the GLASS data reflected a downward trend from 1982 to 2018. Between 1982 and 2020, climatic analysis uncovered robust positive correlations between AGB and precipitation (R > 0.80) and negative correlations with temperature (R < −0.60). These climatic alterations have led to a reduction in AGB, further impairing the regenerative capacity of grasslands. Concurrently, livestock numbers have generally increased since 1982, with a decrease in certain years due to dzud and summer drought, leading to the increase in the GCC. GCC assessment found that 37.5% of grasslands experienced severe overgrazing and 31.9–40.7% was within sustainable limits. Spatially, the eastern region of Mongolia could sustainably support current livestock numbers; the western and southern regions, as well as parts of northern Mongolia, have exhibited moderate to critical levels of grassland utilization. A detailed analysis of GCC dynamics and its climatic impacts would offer scientific support for policymakers in managing grasslands in the Mongolian Plateau. Full article

The China–Mongolia arid region adjacent to the Altai Mountain (CMA) has a sensitive ecosystem that relies heavily on both terrestrial water (TWS) and groundwater storage (GWS). However, during the 2003–2016 period, the CMA experienced significant glacier retreat, lake shrinkage, and grassland degradation. To illuminate the TWS and GWS dynamics in the CMA and the dominant driving factors, we employed high-resolution (0.1°) GRACE (Gravity Recovery and Climate Experiment) data generated through random forest (RF) combined with residual correction. The downscaled data at a 0.1° resolution illustrate the spatial heterogeneity of TWS and GWS depletion. The highest TWS and GWS decline rates were both on the north slope of the Tianshan River Basin (NTRB) of the Junggar Basin of Northwestern China (JBNWC) (27.96 mm/yr and −32.98 mm/yr, respectively). Human impact played a primary role in TWS decreases in the JBNWC, with a relative contribution rate of 62.22% compared to the climatic contribution (37.78%). A notable shift—from climatic (2002–2010) to anthropogenic factors (2011–2020)—was observed as the primary driver of TWS decline in the Great Lakes Depression region of western Mongolia (GLDWM). To maintain ecological stability and promote sustainable regional development, effective action is urgently required to save essential TWS from further depletion. Full article

Scientific and rational monitoring of eco-environmental effects induced by mining activities is a prerequisite for optimizing mining planning and contributes to the advancement of ecological civilization. Remote sensing and multi-source data provide advanced methods for long-term dynamic evaluation of mining-induced eco-environmental effects. This study systematically constructs eco-environmental effect indicators tailored to mining characteristics and establishes quantitative extraction methods based on Landsat data and spectral indices. The Mine Eco-environmental Effect Index (MEEI) was developed using kernel principal component analysis (KPCA). The Heidaigou Open-pit Coal Mine in Jungar Banner was selected as the study area to validate the MEEI’s performance and analyze ecological dynamics across five key temporal phases. Results indicate the following: (1) the KPCA-based MEEI effectively integrates multi-indicator features, offering an objective representation of comprehensive eco-environmental impacts; (2) from 1990 to 2020, the ecological trajectory of the coal mine followed a pattern of “sharp deterioration → gradual slowdown → relative stabilization”, with post-mining restoration and management measures significantly mitigating negative impacts and improving regional ecological quality. This study provides a methodological framework for dynamic evaluation of mining-related eco-environmental effects, supporting sustainable mining practices and ecological governance. Full article

Hippophae rhamnoides L. is an ecologically and medicinally significant species widely distributed across Eurasia, the suitable habitat of H. rhamnoides subsp. sinensis (is hereinafter referred to as sinensis) is concentrated in Northwest and Southwest China (approximately 34–40° N, 100–115° E). H. rhamnoides subsp. yunnanensis (hereinafter referred to as yunnanensis) is mainly distributed in the Hengduan Mountains and surrounding areas (approximately 25–30° N, 98–103° E). H. rhamnoides subsp. mongolica (hereinafter referred to as mongolica) is native to Central Asia to Siberia and is mainly distributed in Northern Xinjiang and Western Inner Mongolia in China (approximately 40–50° N, 100–120° E). H. rhamnoides subsp. turkestanica (hereinafter referred to as turkestanica) is mainly distributed in Western Xinjiang (approximately 40–45° N, 70–85° E). Climate change poses a considerable challenge, affecting its distribution and leading to shifts in its habitat ranges. This study applies the MaxEnt model to assess climate-driven distribution patterns of Hippophae species in China, and predicts current and future suitable habitats under climate change scenarios. This study employs the MaxEnt model and ArcGIS to simulate the potential distribution of four subspecies of H. rhamnoides during the current period and future projections under scenarios SSP1–2.6 and SSP5–8.5. The analysis reveals that the distributions of sinensis, mongolica, yunnanensis, and turkestanica are influenced primarily by climate variables such as temperature and precipitation, while yunnanensis is predominantly restricted by altitude. Future projections indicate that under the extreme climate of SSP5–8.5, centroid migration will be disrupted; specifically, sinensis is expected to migrate northeast or oscillate, mongolica will expand southwest but be limited by desert steppe zones, and turkestanica may face risks associated with groundwater depletion. This study advocates for integrating climate, ecological, and genetic data into conservation planning, with an emphasis on groundwater restoration and exploring genetic resources for stress resilience. The insights offered here contribute significantly to understanding climate adaptation mechanisms in arid and mountainous ecosystems and guide biodiversity conservation efforts. Full article

Miracle tales are almost the sole source for the investigation of the emergence and spread of the relic cult in the early phase of Chinese Buddhism. The earliest excavated relic casket dates back to 453 CE, over four centuries after Buddhism was introduced to China. Through a critical textual analysis of Ji Shenzhou Sanbao Gantonglu, it is evident that the initial form of relic veneration was based on miraculous responses. Legends about imperial relic worship before the 3rd century are all later fabrications. Two archeological finds—the alleged relic murals in a Han tomb at Horinger, Inner Mongolia, and the stūpa-shaped bronze vessel in Gongyi, Henan—are not directly related to relic veneration. Based on the available evidence, it is tentatively concluded that relic worship first emerged around the 3rd century in the vicinity of Luoyang, the capital of the Western Jin, and later spread to the south of the Yangtze River after the Yongjia chaos. The early worshippers included both monks and lay Buddhists, such as merchants and lower-ranking officials. Royal interest in relics did not arise until the 5th century. The rise of relic veneration in China occured two or three centuries later than that in Gandhāra, from which Chinese Buddhism was significantly influenced. Compared to the cult of images or scriptures, relic veneration also emerged relatively late in China. The reluctance to adopt relics as worship objects can be partly explained by (the mahāyāna) Buddhist doctrines and the Chinese cultural mentality. Full article

Inner Mongolia’s grasslands, covering 22% of China’s total grassland area, face critical challenges in balancing livestock production with carbon sequestration under climate change pressures. This study establishes an integrated assessment framework combining remote sensing monitoring, InVEST modeling, and life cycle assessment to analyze the spatial–temporal evolution of grassland ecological carrying capacity and livestock-related carbon emissions from 2000 to 2020. Key findings reveal a 78.8% increase in actual livestock carrying capacity (from 53.09 to 94.94 million sheep units), with Tongliao experiencing 185% growth, while Alxa League showed a 229,500 sheep unit decrease. The theoretical carrying capacity grew by 50.6%, yet severe ecological pressure emerged in western regions, as evidenced by Alxa League’s grass–livestock balance index exceeding 2100%. Carbon sequestration exhibited a northeast–southwest spatial pattern, decreasing by 7.4% during 2015–2020, while greenhouse gas emissions from intensive livestock systems reached 6.40 million tons CO₂-eq in Tongliao by 2020. The results demonstrate that regions combining high-intensity husbandry with low carbon storage require urgent intervention. We propose three pathways: adaptive grazing management to reduce overloading in western pastoral zones, carbon monitoring systems to enhance sequestration in vulnerable ecosystems, and emission reduction technologies for intensive farming systems. These strategies provide actionable solutions for reconciling grassland sustainability with China’s dual carbon goals, offering insights for global pastoral ecosystem management. Full article

The Gobi Wall is a 321 km-long structure made of earth, stone, and wood, located in the Gobi highland desert of Mongolia. It is the least understood section of the medieval wall system that extends from China into Mongolia. This study aims to determine its builders, purpose, and chronology. Additionally, we seek to better understand the ecological implications of constructing such an extensive system of walls, trenches, garrisons, and fortresses in the remote and harsh environment of the Gobi Desert. Our field expedition combined remote sensing, pedestrian surveys, and targeted excavations at key sites. The results indicate that the garrison walls and main long wall were primarily constructed using rammed earth, with wood and stone reinforcements. Excavations of garrisons uncovered evidence of long-term occupation, including artifacts spanning from 2nd c. BCE to 19th c. CE. According to our findings, the main construction and usage phase of the wall and its associated structures occurred throughout the Xi Xia dynasty (1038–1227 CE), a period characterized by advanced frontier defense systems and significant geopolitical shifts. This study challenges the perception of such structures as being purely defensive, revealing the Gobi Wall’s multifunctional role as an imperial tool for demarcating boundaries, managing populations and resources, and consolidating territorial control. Furthermore, our spatial and ecological analysis demonstrates that the distribution of local resources, such as water and wood, was critical in determining the route of the wall and the placement of associated garrisons and forts. Other geographic factors, including the location of mountain passes and the spread of sand dunes, were strategically utilized to enhance the effectiveness of the wall system. The results of this study reshape our understanding of medieval Inner Asian imperial infrastructure and its lasting impact on geopolitical landscapes. By integrating historical and archeological evidence with geographical analysis of the locations of garrisons and fortifications, we underscore the Xi Xia kingdom’s strategic emphasis on regulating trade, securing transportation routes, and monitoring frontier movement. Full article

Carbon lock-in (CLI), defined as the structural persistence of fossil-fuel-based systems, poses a significant barrier to decarbonization. As CLI continues to impede China’s progress toward carbon neutrality, understanding the role of next-generation productive forces (NGPFs) in breaking this path dependence has become increasingly urgent; however, it remains underexplored in empirical research. This study examines the impact of NGPFs on CLI using provincial panel data from 2012 to 2022. Composite indices for NGPFs and CLI are constructed using the entropy weight method. The analysis applies instrumental variable estimation (IV-GMM) to address potential endogeneity, feasible generalized least squares (FGLS) to account for heteroskedasticity, and spatial Durbin models (SDMs) to capture spatial dependence. In addition, quantile regression is used to explore distributional effects, and subsample regressions are conducted to assess regional heterogeneity. The results show that (1) a 1% increase in NGPFs leads to approximately a 0.9643% reduction in CLI, effectively mitigating CLI. (2) NGPF levels are high in Beijing, Shanghai, and Guangdong, while being constrained in Heilongjiang, Gansu, and Qinghai. Provinces like Jiangsu, Zhejiang, and Shandong are rapidly catching up. (3) Shanxi, Inner Mongolia, and Shandong struggle with high comprehensive CLI from carbon-heavy industries; in contrast, Beijing, Shanghai, and Hainan show low CLI. (4) As CLI levels increase (90th percentile), the effectiveness of NGPFs in reducing CLI gradually diminishes (−0.2724). (5) The impact of NGPFs on CLI is not significant in the Eastern region, while in the Central and Western regions, the effects are −1.1365 and −1.0137, respectively. This study offers vital insights for shaping policies that promote sustainable growth and mitigate CLI in China. Full article

Background: Paratuberculosis (PTB) is a chronic wasting disease mainly caused by Mycobacterium avium subsp. paratuberculosis (MAP) in ruminants. It is difficult to diagnose, prevent, treat, and eradicate, thereby causing serious economic losses to the livestock industry. Therefore, finding a detection method with high sensitivity and specificity is crucial to preventing and controlling PTB. Methods: A total of 1585 fresh fecal samples were collected from 12 prefectures and cities across Inner Mongolia between March 2022 and October 2024. The samples were subjected to pretreatment, followed by DNA extraction. Subsequently, MAP detection and genotyping were performed using a two-step qPCR method. Results: The overall prevalence of MAP in ovines was 3.34% (53/1585), with the prevalence in 12 prefectures and cities ranging from 0% (0/100) to 7.73% (15/194). In the eastern, central, and western regions, the prevalence rates were 4.74% (31/654), 3.68% (14/394), and 1.49% (8/537); in small-scale and intensive farms, they were 3.23% (22/682), and 3.56% (31/903); and in goats and sheep, they were 0.91% (2/219) and 4.98% (36/723), respectively. The overall prevalence rates of C- and S-type MAP were 2.90% (46/1585) and 0.44% (7/1585), respectively. Conclusions: To the best of our knowledge, this study is the first to conduct an epidemiological investigation of PTB in sheep across all nine cities and three leagues in Inner Mongolia and to perform MAP typing on a large scale. It elucidated the differences in the prevalence of PTB in different regions of Inner Mongolia and found that geographical location and sheep breed are potential risk factors for the differences in MAP prevalence. Furthermore, it has been shown that C- and S-type MAP coexist in the eastern and central regions of Inner Mongolia. Full article

Under global climate change, the ecological vulnerability issue in Mongolia has become increasingly severe. However, the change process of the ecological environment and the dominant driving factors in different periods and sub-regions of Mongolia are not clear. In this paper, we propose a new ecological vulnerability index for Mongolia using MODIS data, combined with the Geographical Detector and the gravity center model, to reveal the spatiotemporal changes and driving mechanisms of ecological vulnerability in Mongolia from 2000 to 2022. The results show the following: (1) the newly proposed remote sensing ecological vulnerability index has high applicability in ecosystems mainly in Mongolia, with an accuracy rate of 89.39%; (2) Mongolia belongs to the category of moderate vulnerability, with an average ecological vulnerability index of 1.57, and the center of vulnerability is shifting toward the southwest direction; (3) Tmax is the leading driving factor of ecological vulnerability in Mongolia, especially at high altitudes and in arid regions, where it directly affects vegetation growth, desertification, and water availability. The dominant interactive factors have shifted from Tmax ∩ Tmin to Tmin ∩ PRE, with PRE being the leading factor in the eastern, central, and southern regions of Mongolia, Tmax being the leading factor in the western region, and Tmin being the leading factor in the northwestern region. This study provides an index system for constructing the ecological vulnerability system in Mongolia and offers scientific references for the regional protection of the ecological environment in Mongolia. Full article