Eco-environmental quality is a measure of the suitability of the ecological environment for human survival and socioeconomic development. Understanding the spatial-temporal distribution and variation trend of eco-environmental quality is essential for environmental protection and ecological balance. The remote sensing ecological index (RSEI) can quickly and objectively quantify eco-environmental quality and has been extensively utilized in regional ecological environment assessment. In this paper, Moderate Resolution Imaging Spectroradiometer (MODIS) images during the growing period (July-September) from 2000 to 2020 were obtained from the Google Earth Engine (GEE) platform to calculate the RSEI in the three northern regions of China (the Three-North region). The Theil-Sen median trend method combined with the Mann-Kendall test was used to analyze the spatial-temporal variation trend of eco-environmental quality, and the Hurst exponent and the Theil-Sen median trend were superimposed to predict the future evolution trend of eco-environmental quality. In addition, ten variables from two categories of natural and anthropogenic factors were analyzed to determine the drivers of the spatial differentiation of eco-environmental quality by the geographical detector. The results showed that from 2000 to 2020, the RSEI in the Three-North region exhibited obvious regional characteristics: the RSEI values in Northwest China were generally between 0.2 and 0.4; the RSEI values in North China gradually increased from north to south, ranging from 0.2 to 0.8; and the RSEI values in Northeast China were mostly above 0.6. The average RSEI value in the Three-North region increased at an average growth rate of 0.0016/a, showing the spatial distribution characteristics of overall improvement and local degradation in eco-environmental quality, of which the areas with improved, basically stable and degraded eco-environmental quality accounted for 65.39%, 26.82% and 7.79% of the total study area, respectively. The Hurst exponent of the RSEI ranged from 0.20 to 0.76 and the future trend of eco-environmental quality was generally consistent with the trend over the past 21 years. However, the areas exhibiting an improvement trend in eco-environmental quality mainly had weak persistence, and there was a possibility of degradation in eco-environmental quality without strengthening ecological protection. Average relative humidity, accumulated precipitation and land use type were the dominant factors driving the spatial distribution of eco-environmental quality in the Three-North region, and two-factor interaction also had a greater influence on eco-environmental quality than single factors. The explanatory power of meteorological factors on the spatial distribution of eco-environmental quality was stronger than that of topographic factors. The effect of anthropogenic factors (such as population density and land use type) on eco-environmental quality gradually increased over time. This study can serve as a reference to protect the ecological environment in arid and semi-arid regions.

The impact of socioeconomic development on land-use and land-cover change (LUCC) in river basins varies spatially and temporally. Exploring the spatiotemporal evolutionary trends and drivers of LUCC under regional disparities is the basis for the sustainable development and management of basins. In this study, the Weihe River Basin (WRB) in China was selected as a typical basin, and the WRB was divided into the upstream of the Weihe River Basin (UWRB), the midstream of the Weihe River Basin (MWRB), the downstream of the Weihe River Basin (DWRB), the Jinghe River Basin (JRB), and the Luohe River Basin (LRB). Based on land-use data (cultivated land, forestland, grassland, built-up land, bare land, and water body) from 1985 to 2020, we analyzed the spatiotemporal heterogeneity of LUCC in the WRB using a land-use transfer matrix and a dynamic change model. The driving forces of LUCC in the WRB in different periods were detected using the GeoDetector, and the selected influencing factors included meteorological factors (precipitation and temperature), natural factors (elevation, slope, soil, and distance to rivers), social factors (distance to national highway, distance to railway, distance to provincial highway, and distance to expressway), and human activity factors (population density and gross domestic product (GDP)). The results indicated that the types and intensities of LUCC conversions showed considerable disparities across different sub-basins, where complex conversions among cultivated land, forestland, and grassland occurred in the LRB, JRB, and UWRB, with higher dynamic change before 2000. The conversion of other land-use types to built-up land was concentrated in the UWRB, MWRB, and DWRB, with substantial increases after 2000. Additionally, the driving effects of the influencing factors on LUCC in each sub-basin also exhibited distinct diversity, with the LRB and JRB being influenced by the meteorological and social factors, and the UWRB, MWRB, and DWRB being driven by human activity factors. Moreover, the interaction of these influencing factors indicated an enhanced effect on LUCC. This study confirmed the spatiotemporal heterogeneity effects of socioeconomic status on LUCC in the WRB under regional differences, contributing to the sustainable development of the whole basin by managing sub-basins according to local conditions.

Extreme precipitation events are one of the most dangerous hydrometeorological disasters, often resulting in significant human and socio-economic losses worldwide. It is therefore important to use current global climate models to project future changes in precipitation extremes. The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs). The results were derived using the modified Mann-Kendall test, Sen's slope estimator, student's t-test, and probability density function approach. Eight extreme precipitation indices were assessed, including wet days (RR1mm), heavy precipitation days (RR10mm), very heavy precipitation days (RR20mm), severe precipitation days (RR50mm), consecutive wet days (CWD), consecutive dry days (CDD), maximum 5-day precipitation amount (RX5day), and simple daily intensity index (SDII). The future changes were estimated in two time periods for the 21^st century (i.e., near future (NF; 2021-2060) and far future (FF; 2061-2100)) under two Shared Socioeconomic Pathway (SSP) scenarios (SSP2-4.5 and SSP5-8.5). The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^st century (2061-2100). Moreover, from the results of multimodel ensemble means (MMEMs), extreme precipitation indices of RR1mm, RR10mm, RR20mm, CWD, and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario. The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part. The probability density function of extreme precipitation indices suggests a frequent (intense) occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario, with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD. The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding, soil erosion, water resource management, food security, and agriculture development.

Lake Urmia, Northwest Iran, has confronted a drying procedure in recent years with losing 90% of its water body. The authorities concerned about desertification processes and possible dust events throughout the region. In this regard, the Iranian Natural Resources and Watershed Management Organization has taken ecological measures to plant vegetation using salt cedar (Tamarix ramosissima Ledeb.) shrubs to combat desertification. This study aimed to investigate the vegetation and soil characteristics of natural and plantation stands of salt cedar on the western shores of Lake Urmia. To this end, 7 transects were randomly selected with 15 shrubs in natural stands, and 7 transects were randomly selected with 15 shrubs in the plantation parts along the planting rows. Then, vegetative characteristics were examined. Also, soil samples were taken from the vicinity of the shrubs. The results indicated that there was no significant difference between the mean diameter at breast height (DBH) of salt cedar in natural sites. There was a significant difference between the mean number of sprouts per sprout-clumps, mean crown diameter, collar diameter, total height, and also between mean crown diameter and freshness of shrubs among different sites (P<0.05). It was also found that soil variables, such as clay content, organic matter, electrical conductivity (EC), Na⁺, specific absorption rate (SAR), Cl^-, SO2- 4, Na⁺, K⁺, and PO2- 4 are the most significant variable parameters between studied sites. As the results shown, the values of EC, SAR, Na⁺, and Cl^- are 6 times higher in the planted stands than in the natural stands of T. ramosissima. Also, the colonization of T. ramosissima in the planted stands is unsuccessful by dramatic drop in the total height and average diameter. Considering the role of soil characteristics in explaining the variance of data and site separation, it seems that these indicators can be applied in executive plans as important indicators to identify suitable planting sites for combating desertification.

A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring. However, traditional methods for studying gravels are low-efficiency and have many errors. This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map (SOM) and multivariate statistical methods in the grassland of northern Tibetan Plateau. Moreover, the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed. The results showed that the morphological characteristics of gravels in northern region (cluster C) and southern region (cluster B) of the Tibetan Plateau were similar, with a low gravel coverage, small gravel diameter, and elongated shape. These regions were mainly distributed in high mountainous areas with large topographic relief. The central region (cluster A) has high coverage of gravels with a larger diameter, mainly distributed in high-altitude plains with smaller undulation. Principal component analysis (PCA) results showed that the gravel distribution of cluster A may be mainly affected by vegetation, while those in clusters B and C could be mainly affected by topography, climate, and soil. The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels, providing a new mode for gravel research.

The reconstruction of paleovegetation and paleoclimate requires an understanding of the relationships between surface pollen assemblages and modern vegetation and climate. Here, we analyzed the characteristics of surface pollen assemblages across different vegetation zones in the Tianshan Mountains. Using surface pollen analysis and vegetation sample surveys at 75 sites on the northern slopes of the Tianshan Mountains, we determined the correlation between the percentage of dominant pollen types and the corresponding vegetation cover. Redundancy analysis was used to investigate the relationships between surface pollen assemblages and environmental factors. Our results show that the Tianshan Mountains contain several distinct ecological regions, which can be divided into five main vegetation zones from low to high altitudes: mountain desert zone (Hutubi County (HTB): 500-1300 m; Qitai County (QT): 1000-1600 m), mountain steppe zone (HTB: 1400-1600 m; QT: 1650-1800 m), mountain forest zone (HTB: 1650-2525 m; QT: 1850-2450 m), subalpine meadow zone (HTB: 2550-2600 m; QT: 2500-2600 m), and alpine mat vegetation zone (HTB: 2625-2700 m; QT: 2625-2750 m). The surface pollen assemblages of different vegetation zones can accurately reflect the characteristics of the mountainous vegetation patterns on the northern slopes of the Tianshan Mountains when excluding the widespread occurrence of Chenopodiaceae, Artemisia, and Picea pollen. Both average annual precipitation (P_ann) and annual average temperature (T_ann) affect the distribution of surface pollen assemblages. Moreover, P_ann is the primary environmental factor affecting surface pollen assemblages in this region. A significant correlation exists between the pollen percentage and vegetation cover of Picea, Chenopodiaceae, Artemisia, and Asteraceae. Moreover, Picea, Chenopodiaceae, and Artemisia pollen are over-represented compared with their corresponding vegetation cover. The Asteraceae pollen percentage roughly reflects the distribution of a species within the local vegetation. These results have important implications for enhancing our understanding of the relationship between surface pollen assemblages and modern vegetation and climate.

Soil organic carbon (SOC) and its stable isotope composition reflect key information about the carbon cycle in ecosystems. Studies of carbon fractions in oasis continuous cotton-cropped fields can elucidate the SOC stability mechanism under the action of the human-land relationship during the oasification of arid land, which is critical for understanding the carbon dynamics of terrestrial ecosystems in arid lands under global climate change. In this study, we investigated the Alar Reclamation Area on the northern edge of the Tarim Basin, Xinjiang Uygur Autonomous Region of China, in 2020. In original desert and oasis farmlands with different reclamation years, including 6, 10, 18, and 30 a, and different soil depths (0-20, 20-40, 40-60 cm), we analyzed the variations in SOC, very liable carbon (C_VL), liable carbon (C_L), less liable carbon (C_LL), and non-liable carbon (C_NL) using the method of spatial series. The differences in the stable carbon isotope ratio (δ¹³C) and beta (β) values reflecting the organic carbon decomposition rate were also determined during oasification. Through redundancy analysis, we derived and discussed the relationships among SOC, carbon fractions, δ¹³C, and other soil physicochemical properties, such as the soil water content (SWC), bulk density (BD), pH, total salt (TS), total nitrogen (TN), available phosphorus (AP), and available potassium (AK). The results showed that there were significant differences in SOC and carbon fractions of oasis farmlands with different reclamation years, and the highest SOC was observed at the oasis farmland with 30-a reclamation year. C_VL, C_L, C_LL, and C_NL showed significant changes among oasis farmlands with different reclamation years, and C_VL had the largest variation range (0.40-4.92 g/kg) and accounted for the largest proportion in the organic carbon pool. The proportion of C_NL in the organic carbon pool of the topsoil (0-20 cm) gradually increased. δ¹³C varied from -25.61‰ to -22.58‰, with the topsoil showing the most positive value at the oasis farmland with 10-a reclamation year; while the β value was the lowest at the oasis farmland with 6-a reclamation year and then increased significantly. Based on the redundancy analysis results, the soil physicochemical properties, such as TN, AP, AK, and pH, were significantly correlated with C_L, and TN and AP were positively correlated with C_VL. However, δ¹³C was not significantly influenced by soil physicochemical properties. Our analysis advances the understanding of SOC dynamics during oasification, revealing the risk of soil carbon loss and its contribution to terrestrial carbon accumulation in arid lands, which could be useful for the sustainable development of regional carbon resources and ecological protection in arid ecosystem.

Qilian Mountains in Northwest China is a significant ecological security barrier due to its distinctive geographic setting, which has significant biological resource and gene pool. In order to assess the soil quality and ecosystem health in this area, we identified the structural characteristics and functional groups of soil microbial communities. This study focused on Amidongsuo, a typical watershed of the Qilian Mountains, and researched the vertical distribution and dominant populations of soil microorganisms in different habitats, and the relationship between soil microorganisms and environmental factors. Soil microorganisms from three grassland plots, five shrubland plots, and five forest plots in Amidongsuo were studied using high-throughput sequencing. The Venn diagram showed that the types of bacteria were fewer than those of fungi in Amidongsuo. Soil bacteria Acidobacteriota, Proteobacteria, and Methylomirabilota as well as fungi Basidiomycota, Ascomycota, and Mortierellomycota played dominant roles in Amidongsuo, according to the LEfSe (linear discriminant analysis (LDA) effect size) and community structure analyses. According to the ANOSIM (analysis of similarities) result, for both bacteria and fungi, R values of grassland and shrubland were small (R²=0.045 and R²=0.256, respectively), indicating little difference between these two ecosystems. RDA (redundancy analysis) showed a closer relationship between soil nutrients and fungi, and a gradually decreasing correlation between soil nutrients and microorganisms with increasing soil depth. Bacteria were mainly affected by pH, nitrogen (N), and potassium (K), while fungi were mainly affected by K. Overall, fungi had more effect on soil quality than bacteria. Therefore, adjustment of soil K content might improve the soil environment of Amidongsuo in the Qilian Mountains.