With the acceleration of urbanization, changes in the urban ecological environment and landscape pattern have led to a series of prominent ecological environmental problems. In order to better coordinate the balanced relationship between city and ecological environment, we selected land use change data to evaluate the habitat quality in Hohhot City of China, which is of great practical significance for regional urban and economic development. Thus, the integrated valuation of ecosystem services and tradeoffs (InVEST) and Cellular Automata-Markov (CA-Markov) models were used to analyze, predict, and explore the Spatiotemporal evolution path and characteristics of urban land use, and forecast the typical evolution pattern of land use in 2030. The results showed that the land use types in Hohhot City changed significantly from 2000 to 2020, and the biggest change took place in cultivated land, grassland, shrub, and artificial surface. The decrease of cultivated land area and the increase of artificial surface area were the main impact trend of land use change. The average value of habitat quality had been decreasing continuously from 2000 to 2020, and the values of habitat degradation were 0.2605, 0.2494, and 0.2934 in 2000, 2010, and 2020, respectively, showing a decreasing trend. The decrease of habitat quality was caused by the needs of economic development and urban construction, as well as the impact of land occupation. During this evolution, many cultivated land and urban grassland had been converted into construction land. The simulated land use changes in 2030 are basically the same as those during 2000-2020, and the habitat quality will still be declining. The regional changes are influenced by the urban rapid development and industrial layout. These results can provide decision-making reference for regional urban planning and management as well as habitat quality evaluation.

Check dams are widely used on the Loess Plateau in China to control soil and water losses, develop agricultural land, and improve watershed ecology. Detailed information on the number and spatial distribution of check dams is critical for quantitatively evaluating hydrological and ecological effects and planning the construction of new dams. Thus, this study developed a check dam detection framework for broad areas from high-resolution remote sensing images using an ensemble approach of deep learning and geospatial analysis. First, we made a sample dataset of check dams using GaoFen-2 (GF-2) and Google Earth images. Next, we evaluated five popular deep-learning-based object detectors, including Faster R-CNN, You Only Look Once (version 3) (YOLOv3), Cascade R-CNN, YOLOX, and VarifocalNet (VFNet), to identify the best one for check dam detection. Finally, we analyzed the location characteristics of the check dams and used geographical constraints to optimize the detection results. Precision, recall, average precision at intersection over union (IoU) threshold of 0.50 (AP₅₀), IoU threshold of 0.75 (AP₇₅), and average value for 10 IoU thresholds ranging from 0.50-0.95 with a 0.05 step (AP_50-95), and inference time were used to evaluate model performance. All the five deep learning networks could identify check dams quickly and accurately, with AP_50-95, AP₅₀, and AP₇₅ values higher than 60.0%, 90.0%, and 70.0%, respectively, except for YOLOv3. The VFNet had the best performance, followed by YOLOX. The proposed framework was tested in the Yanhe River Basin and yielded promising results, with a recall rate of 87.0% for 521 check dams. Furthermore, the geographic analysis deleted about 50% of the false detection boxes, increasing the identification accuracy of check dams from 78.6% to 87.6%. Simultaneously, this framework recognized 568 recently constructed check dams and small check dams not recorded in the known check dam survey datasets. The extraction results will support efficient watershed management and guide future studies on soil erosion in the Loess Plateau.

Land use/land cover (LULC) change and climate change are two major factors affecting the provision of ecosystem services which are closely related to human well-being. However, a clear understanding of the relationships between these two factors and ecosystem services in Central Asia is still lacking. This study aimed to comprehensively assess ecosystem services in Central Asia and analyze how they are impacted by changes in LULC and climate. The spatiotemporal patterns of three ecosystem services during the period of 2000-2015, namely the net primary productivity (NPP), water yield, and soil retention, were quantified and mapped by the Carnegie-Ames-Stanford Approach (CASA) model, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and Revised Universal Soil Loss Equation (RUSLE). Scenarios were used to determine the relative importance and combined effect of LULC change and climate change on ecosystem services. Then, the relationships between climate factors (precipitation and temperature) and ecosystem services, as well as between LULC change and ecosystem services, were further discussed. The results showed that the high values of ecosystem services appeared in the southeast of Central Asia. Among the six biomes (alpine forest region (AFR), alpine meadow region (AMR), typical steppe region (TSR), desert steppe region (DSR), desert region (DR), and lake region (LR)), the values of ecosystem services followed the order of AFR>AMR>TSR>DSR> DR>LR. In addition, the values of ecosystem services fluctuated during the period of 2000-2015, with the most significant decreases observed in the southeast mountainous area and northwest of Central Asia. LULC change had a greater impact on the NPP, while climate change had a stronger influence on the water yield and soil retention. The combined LULC change and climate change exhibited a significant synergistic effect on ecosystem services in most of Central Asia. Moreover, ecosystem services were more strongly and positively correlated with precipitation than with temperature. The greening of desert areas and forest land expansion could improve ecosystem services, but unreasonable development of cropland and urbanization have had an adverse impact on ecosystem services. According to the results, ecological stability in Central Asia can be achieved through the natural vegetation protection, reasonable urbanization, and ecological agriculture development.

Exploring the current runoff characteristics after the large-scale implementation of the Grain for Green (GFG) project and investigating its sensitivities to potential drivers are crucial for water resource prediction and management. Based on the measured runoff data of 62 hydrological stations in the Weihe River Basin (WRB) from 2006 to 2018, we analyzed the temporal and spatial runoff characteristics in this study. Correlation analysis was used to investigate the relationships between different runoff indicators and climate-related factors. Additionally, an improved Budyko framework was applied to assess the sensitivities of annual runoff to precipitation, potential evaporation, and other factors. The results showed that the daily runoff flow duration curves (FDCs) of all selected hydrological stations fall in three narrow ranges, with the corresponding mean annual runoff spanning approximately 1.50 orders of magnitude, indicating that the runoff of different hydrological stations in the WRB varied greatly. The trend analysis of runoff under different exceedance frequencies showed that the runoff from the south bank of the Weihe River was more affluent and stable than that from the north bank. The runoff was unevenly distributed throughout the year, mainly in the flood season, accounting for more than 50.00% of the annual runoff. However, the trend of annual runoff change was not obvious in most areas. Correlation analysis showed that rare-frequency runoff events were more susceptible to climate factors. In this study, daily runoff under 10%-20% exceeding frequencies, consecutive maximum daily runoff, and low-runoff variability rate had strong correlations with precipitation, aridity index, and average runoff depth on rainy days. In comparison, daily runoff under 50%-99% exceeding frequencies, consecutive minimum daily runoff, and high-runoff variability rate had weak correlations with all selected impact factors. The sensitivity analysis results suggested that the sensitivity of annual runoff to precipitation was always higher than that to potential evaporation. The runoff about 87.10% of the selected hydrological stations were most sensitive to precipitation changes, and 12.90% were most sensitive to other factors. The spatial pattern of the sensitivity analysis indicated that in relatively humid southern areas, runoff was more sensitive to potential evaporation and other factors, and less sensitive to precipitation.

Drought, which restricts the sustainable development of agriculture, ecological health, and social economy, is affected by a variety of factors. It is widely accepted that a single variable cannot fully reflect the characteristics of drought events. Studying precipitation, reference evapotranspiration (ET₀), and vegetation yield can derive information to help conserve water resources in grassland ecosystems in arid and semi-arid regions. In this study, the interactions of precipitation, ET₀, and vegetation yield in Darhan Muminggan Joint Banner (DMJB), a desert steppe in Inner Mongolia Autonomous Region, China were explored using two-dimensional (2D) and three-dimensional (3D) joint distribution models. Three types of Copula functions were applied to quantitatively analyze the joint distribution probability of different combinations of precipitation, ET₀, and vegetation yield. For the precipitation-ET₀ dry-wet type, the 2D joint distribution probability with precipitation≤245.69 mm/a or ET₀≥959.20 mm/a in DMJB was approximately 0.60, while the joint distribution probability with precipitation≤245.69 mm/a and ET₀≥959.20 mm/a was approximately 0.20. Correspondingly, the joint return period that at least one of the two events (precipitation was dry or ET₀ was wet) occurred was 2 a, and the co-occurrence return period that both events (precipitation was dry and ET₀ was wet) occurred was 5 a. Under this condition, the interval between dry and wet events would be short, the water supply and demand were unbalanced, and the water demand of vegetation would not be met. In addition, when precipitation remained stable and ET₀ increased, the 3D joint distribution probability that vegetation yield would decrease due to water shortage in the precipitation-ET₀ dry-wet years could reach up to 0.60-0.70. In future work, irrigation activities and water allocation criteria need to be implemented to increase vegetation yield and the safety of water resources in the desert steppe of Inner Mongolia.

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 mineral dust emitted from Central Asia has a significant influence on the global climate system. However, the history and mechanisms of aeolian activity in Central Asia remain unclear, due to the lack of well-dated records of aeolian activity and the intense wind erosion in some of the dust source areas (e.g., deserts). Here, we present the records of aeolian activity from a sedimentary sequence in the southern Gurbantunggut Desert of China using grain size analysis and optically stimulated luminescence (OSL) dating, based on field sampling in 2019. Specifically, we used eight OSL dates to construct chronological frameworks and applied the end-member (EM) analysis for the grain size data to extract the information of aeolian activity in the southern Gurbantunggut Desert during the last 900 a. The results show that the grain size dataset can be subdivided into three EMs (EM1, EM2, and EM3). The primary modal sizes of these EMs (EM1, EM2, and EM3) are 126.00, 178.00, and 283.00 μm, respectively. EM1 represents a mixture of the suspension components and saltation dust, while EM2 and EM3 show saltation dust transported over a shorter distance via strengthened near-surface winds, which can be used to trace aeolian activity. Combined with the OSL chronology, our results demonstrate that during the last 900 a, more intensive and frequent aeolian activity occurred during 450-100 a BP (Before Present) (i.e., the Little Ice Age (LIA)), which was reflected by a higher proportion of the coarse-grained components (EM2+EM3). Aeolian activity decreased during 900-450 a BP (i.e., the Medieval Warm Period (MWP)) and 100 a BP-present (i.e., the Current Warm Period (CWP)). Intensified aeolian activity was associated with the strengthening of the Siberian High and cooling events at high northern latitudes. We propose that the Siberian High, under the influence of temperature changes at high northern latitudes, controlled the frequency and intensity of aeolian activity in Central Asia. Cooling at high northern latitudes would have significantly enhanced the Siberian High, causing its position to shift southward. Subsequently, the incursion of cold air masses from high northern latitudes resulted in stronger wind regimes and increased dust emissions from the southern Gurbantunggut Desert. It is possible that aeolian activity may be weakened in Central Asia under future global warming scenarios, but the impact of human activities on this region must also be considered.

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.

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.

Soil erosion is a serious issue in the sandy-hilly region of Shanxi Province, Northwest China. There has been gradual improvement due to vegetation restoration, but soil microbial community characteristics in different vegetation plantation types have not been widely investigated. To address this, we analyzed soil bacterial and fungal community structures, diversity, and microbial and soil environmental factors in Caragana korshinskii Kom., Populus tomentosa Carr., Populus simonii Carr., Salix matsudana Koidz, and Pinus tabulaeformis Carr. forests. There were no significant differences in the dominant bacterial community compositions among the five forest types. The alpha diversity of the bacteria and fungi communities showed that ACE (abundance-based coverage estimator), Chao1, and Shannon indices in C. korshinskii forest were significantly higher than those in the other four forest types (P<0.05). Soil organic matter, total nitrogen, and urease had a greater impact on bacterial community composition, while total nitrogen, β-glucosidase, and urease had a greater impact on fungal community composition. The relative abundance of beneficial and pathogenic microorganisms was similar across all forest types. Based on microbial community composition, diversity, and soil fertility, we ranked the plantations from most to least suitable as follows: C. korshinskii, S. matsudana, P. tabulaeformis, P. tomentosa, and P. simonii.

Numerous ecological factors influence a plant's ability to live and grow, in which dryness is a substantial constraint on plant growth in arid and semi-arid areas. In response to a specific environmental stress, plants can use the most effective bacteria to support and facilitate their growth and development. Today, plant growth promoting rhizobacteria (PGPR) is widely used to reduce drought stress on plant growth. In this study, the effects of drought on Festuca ovina L. germination, growth, and nutrient absorption were investigated using PGPR in a factorial test with a completely random design under four water regimes. Soil water content was kept at 100% FC (field capacity), 70% FC (FC), 50% FC, and 30% FC. The treatments were inoculated with Azotobacter vinelandii, Pantoea agglomerans+Pseudomonas putida, and a mixture of bio-fertilizers. Results showed that the effects of drought stress were significantly reduced (P<0.05) when A. vinelandii and P. agglomerans+P. putida were used separately, however, the combined treatment of bio-fertilizers had a greater influence on seed germination than the single application. P. agglomerans+P. putida under 30% FC condition resulted in higher increases in stem, root length, and plant dry biomass. The highest uptake of nutrients was observed for the combined treatment of bio-fertilizers under 30% FC condition. Therefore, the use of A. vinelandii and P. agglomerans+P. putida, applied separately or combined, increased tolerance to drought stress in F. ovina by increased germination indices, dry weight, stem length, and root length. Because of the beneficial effects of PGPR on the growth characteristics of plants under drought conditions and the reduction of negative effects of drought stress, inoculating F. ovina seeds with Azotobacter and Pseudomonas is recommended to improve their growth and development characteristics under drought conditions. PGPR, as an affordable and environmentally friendly method, can improve the production of forage in water-stress rangelands.

Stipagrostis ciliata (Desf.) De Winter is a pastoral C₄ grass grown in arid regions. This research work focused on assessing the growth of S. ciliata accessions derived from two different climate regions (a wet arid region in the Bou Hedma National Park in the central and southern part of Tunisia (coded as WA), and a dry arid region from the Matmata Mountain in the south of Tunisia (coded as DA)) under water stress conditions. Specifically, the study aimed to investigate the phenological and physiological responses of potted S. ciliata seedlings under different water treatments: T₁ (200 mm/a), T₂ (150 mm/a), T₃ (100 mm/a) and T₄ (50 mm/a). Growth phenology, net photosynthesis (P_n), stomatal conductance (g_s), midday leaf water potential (Ψ_md), predawn leaf water potential (Ψ_pd), soil water content (SWC) and soil water potential (Ψ_s) were observed during the water stress cycle (from December 2016 to November 2017). The obtained results showed that the highest growth potential of the two accessions (WA and DA) was recorded under treatment T₁. The two accessions responded differently and significantly to water stress. Photosynthetic parameters, such as P_n and g_s, decreased sharply under treatments T₂, T₃ and T₄ compared to treatment T₁. The higher water stress increased the R/S ratio (the ratio of root dry biomass to shoot dry biomass), with values of 1.29 and 2.74 under treatment T₄ for accessions WA and DA, respectively. Principal component analysis (PCA) was applied, and the separation of S. ciliata accessions on the first two axes of PCA (PC1 and PC2) suggested that accession DA was detected in the negative extremity of PC1 and PC2 under treatments T₁ and T₂. This accession was characterized by a high number of spikes. For treatments T₃ and T₄, both accessions were detected in the negative extremity of PC1 and PC2. They were characterized by a high root dry biomass. Therefore, S. ciliata accessions responded to water stress by displaying significant changes in their behaviours. Accession WA from the Bou Hedma National Park (wet arid region) showed higher drought tolerance than accession DA from the Matmata Mountain (dry arid region). S. ciliata exhibits a significant adaptation capacity for water limitation and may be an important species for ecosystem restoration.

Green development of agriculture is important for achieving coordinated and high-quality regional development for China. Using provincial data from 1990 to 2020, this work explored the dynamics of agricultural green development efficiency of 31 provinces in China, its spatiotemporal characteristics, and its driving factors using a super-efficiency slacks-based measure (Super-SBM), the Malmquist productivity index (MPI), spatial autocorrelation, and a geographic detector. Results showed that the overall agricultural green development efficiency showed a U-shaped trend, suggesting a low level of efficiency. Although a gradient difference was visible among eastern, central, and western regions, the efficiency gap narrowed each year. Technological progress and efficiency both promoted agricultural green development efficiency, especially technological progress. Agricultural green development efficiency had significant spatial aggregation characteristics, but Moran's I result showed a downward trend from 2015 to 2020, indicating a risk of spatial dispersion in the later stage. The provinces with high agricultural green development efficiency were mainly concentrated in the eastern region, while those with low efficiency were concentrated in the central and western regions. Agricultural green development efficiency was influenced by various factors, which showed differences according to time and region. The impact of the labor force's education level and technological progress increased during the study period, and significantly facilitated agricultural green development efficiency in the eastern region, while the central and western regions were still affected by the scale level and environmental regulation, reflecting the advantages of the eastern region in terms of economy and technology. In the future, strengthening agricultural scientific and technological innovation and deepening interprovincial cooperation can help further improve the level of green agricultural development. In addition, local governments should formulate more precise local agricultural support policies based on macro-level policies and local conditions.

In recent years, deep convolution neural network has exhibited excellent performance in computer vision and has a far-reaching impact. Traditional plant taxonomic identification requires high expertise, which is time-consuming. Most nature reserves have problems such as incomplete species surveys, inaccurate taxonomic identification, and untimely updating of status data. Simple and accurate recognition of plant images can be achieved by applying convolutional neural network technology to explore the best network model. Taking 24 typical desert plant species that are widely distributed in the nature reserves in Xinjiang Uygur Autonomous Region of China as the research objects, this study established an image database and select the optimal network model for the image recognition of desert plant species to provide decision support for fine management in the nature reserves in Xinjiang, such as species investigation and monitoring, by using deep learning. Since desert plant species were not included in the public dataset, the images used in this study were mainly obtained through field shooting and downloaded from the Plant Photo Bank of China (PPBC). After the sorting process and statistical analysis, a total of 2331 plant images were finally collected (2071 images from field collection and 260 images from the PPBC), including 24 plant species belonging to 14 families and 22 genera. A large number of numerical experiments were also carried out to compare a series of 37 convolutional neural network models with good performance, from different perspectives, to find the optimal network model that is most suitable for the image recognition of desert plant species in Xinjiang. The results revealed 24 models with a recognition Accuracy, of greater than 70.000%. Among which, Residual Network X_8GF (RegNetX_8GF) performs the best, with Accuracy, Precision, Recall, and F1 (which refers to the harmonic mean of the Precision and Recall values) values of 78.33%, 77.65%, 69.55%, and 71.26%, respectively. Considering the demand factors of hardware equipment and inference time, Mobile NetworkV2 achieves the best balance among the Accuracy, the number of parameters and the number of floating-point operations. The number of parameters for Mobile Network V2 (MobileNetV2) is 1/16 of RegNetX_8GF, and the number of floating-point operations is 1/24. Our findings can facilitate efficient decision-making for the management of species survey, cataloging, inspection, and monitoring in the nature reserves in Xinjiang, providing a scientific basis for the protection and utilization of natural plant resources.

Since Pb is a non-biodegradable inorganic pollutant and a non-essential metal, its long-term presence in soil poses a great threat to the environment. Iris lactea Pall. var. chinensis (Fisch.) Koidz., a perennial dense bush herb with high resistance of Pb and wide adaptability, was used in pot experiments to study the effects of exogenous nitrate N ($\text{NO}_{3}^{-}-\text{N}$) on the absorption and transportation of Pb and plant growth under different Pb concentrations. Then, the mechanism of $\text{NO}_{3}^{-}-\text{N}$ affecting Pb and nutrient uptake and transport was explored. The concentration of Pb in the experiment ranged from 0 to 1600 mg/kg, and the added concentration of $\text{NO}_{3}^{-}-\text{N}$ was 0.0-0.3 g/kg. The results showed that I. lactea was highly tolerant to Pb, and the shoot fraction was more sensitive to varied Pb concentrations in the soil than the root fraction. This protective function became more pronounced under the condition of raised Pb concentration in the soil. When the concentration of Pb in the soil reached 800 mg/kg, the highest Pb content of I. lactea was found under the condition of 0.1 g/kg of $\text{NO}_{3}^{-}-\text{N}$ addition. When Pb concentration in the soil increased to 1600 mg/kg, the increase in $\text{NO}_{3}^{-}-\text{N}$ addition promoted Pb uptake by the root. To ensure the well growth of I. lactea and the effect of remediation of Pb-contaminated soil, the recommended concentration of $\text{NO}_{3}^{-}-\text{N}$ in the soil is 0.1 g/kg. This result provides a theoretical basis for exogenous N regulation of phytoremediation of Pb-contaminated soil.

Malus sieversii (wild apple tree), only distributed in the Tianshan Mountains in Central Asia, is a tertiary relic species and an ancestral species of cultivated apples. However, existing natural populations of wild apple trees have been declining. To date, spatiotemporal variations in the growth status of declining wild apple trees and influencing factors in the narrow valley areas in the Tianshan Mountains remain unclear. In this study, field investigation and sampling were carried out in three years (2016-2018) at four elevations (1300, 1400, 1500, and 1600 m) in the Qiaolakesai Valley (a typical longitudinal narrow valley in the Yili River Valley) of the western Tianshan Mountains in Xinyuan County, Xinjiang Uygur Autonomous Region, China. Projective coverage, dead branch percentage, and 18 twig traits (these 20 parameters were collectively referred to as plant traits) were determined to comprehensively reflect the growth status of declining wild apple trees. The values of dead branch percentage ranged from 36% to 59%, with a mean of 40%. Year generally showed higher impact on plant traits than elevation. In 2017 and 2018, projective coverage, leaf size, leaf nitrogen concentration, and nitrogen to phosphorous ratio were markedly higher than those in 2016. However, dead branch percentage and leaf and stem phosphorous concentrations showed the opposite trend. Most of the topological parameters of plant trait networks differed in the three years, but the strength of trait-trait association increased year by year. The mean difference between day and night temperatures (MDT), annual accumulative precipitation, soil electrical conductivity, and soil pH had the greatest impact on the plant trait matrix. The growth status of declining wild apple trees was directly and positively affected by MDT and leaf size. In conclusion, the growth of declining wild apple trees distributed in the narrow valley areas was more sensitive to interannual environmental changes than elevation changes. The results are of great significance for further revealing the decline mechanism of wild apple trees in the Tianshan Mountains.

Visible and near-infrared (vis-NIR) spectroscopy technique allows for fast and efficient determination of soil organic matter (SOM). However, a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the effective removal of redundant information. Therefore, this study aims to select three wavelength selection strategies for obtaining the spectral response characteristics of SOM. The SOM content and spectral information of 110 soil samples from the Ogan-Kuqa River Oasis were measured under laboratory conditions in July 2017. Pearson correlation analysis was introduced to preselect spectral wavelengths from the preprocessed spectra that passed the 0.01 level significance test. The successive projection algorithm (SPA), competitive adaptive reweighted sampling (CARS), and Boruta algorithm were used to detect the optimal variables from the preselected wavelengths. Finally, partial least squares regression (PLSR) and random forest (RF) models combined with the optimal wavelengths were applied to develop a quantitative estimation model of the SOM content. The results demonstrate that the optimal variables selected were mainly located near the range of spectral absorption features (i.e., 1400.0, 1900.0, and 2200.0 nm), and the CARS and Boruta algorithm also selected a few visible wavelengths located in the range of 480.0-510.0 nm. Both models can achieve a more satisfactory prediction of the SOM content, and the RF model had better accuracy than the PLSR model. The SOM content prediction model established by Boruta algorithm combined with the RF model performed best with 23 variables and the model achieved the coefficient of determination (R²) of 0.78 and the residual prediction deviation (RPD) of 2.38. The Boruta algorithm effectively removed redundant information and optimized the optimal wavelengths to improve the prediction accuracy of the estimated SOM content. Therefore, combining vis-NIR spectroscopy with machine learning to estimate SOM content is an important method to improve the accuracy of SOM prediction in arid land.

Opuntia ficus-indica (L.) Miller is a CAM (crassulacean acid metabolism) plant with an extraordinary capacity to adapt to drought stress by its ability to fix atmospheric CO₂ at nighttime, store a significant amount of water in cladodes, and reduce root growth. Plants that grow in moisture-stress conditions with thick and less fine root hairs have a strong symbiosis with arbuscular mycorrhizal fungi (AMF) to adapt to drought stress. Water stress can limit plant growth and biomass production, which can be rehabilitated by AMF association through improved physiological performance. The objective of this study was to investigate the effects of AMF inoculations and variable soil water levels on the biomass, photosynthesis, and water use efficiency of the spiny and spineless O. ficus-indica. The experiment was conducted in a greenhouse with a full factorial experiment using O. ficus-indica type (spiny or spineless), AMF (presence or absence), and four soil water available (SWA) treatments through seven replications. Water treatments applied were 0%-25% SWA (T1), 25%-50% SWA (T2), 50%-75% SWA (T3), and 75%-100% SWA (T4). Drought stress reduced biomass and cladode growth, while AMF colonization significantly increased the biomass production with significant changes in the physiological performance of O. ficus-indica. AMF presence significantly increased biomass of both O. ficus-indica plant types through improved growth, photosynthetic water use efficiency, and photosynthesis. The presence of spines on the surface of cladodes significantly reduced the rate of photosynthesis and photosynthetic water use efficiency. Net photosynthesis, photosynthetic water use efficiency, transpiration, and stomatal conductance rate significantly decreased with increased drought stress. Under drought stress, some planted mother cladodes with the absence of AMF have not established daughter cladodes, whereas AMF-inoculated mother cladodes fully established daughter cladodes. AMF root colonization significantly increased with the decrease of SWA. AMF caused an increase in biomass production, increased tolerance to drought stress, and improved photosynthesis and water use efficiency performance of O. ficus-indica. The potential of O. ficus-indica to adapt to drought stress is controlled by the morpho-physiological performance related to AMF association.

The shrinkage of the Aral Sea, which is closely related to the Amu Darya River, strongly affects the sustainability of the local natural ecosystem, agricultural production, and human well-being. In this study, we used the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) model to detect the historical change points in the variation of the Aral Sea and the Amu Darya River and analyse the causes of the Aral Sea shrinkage during the 1950-2016 period. Further, we applied multifractal detrend cross-correlation analysis (MF-DCCA) and quantitative analysis to investigate the responses of the Aral Sea to the runoff in the Amu Darya River, which is the main source of recharge to the Aral Sea. Our results showed that two significant trend change points in the water volume change of the Aral Sea occurred, in 1961 and 1974. Before 1961, the water volume in the Aral Sea was stable, after which it began to shrink, with a shrinkage rate fluctuating around 15.21 km³/a. After 1974, the water volume of the Aral Sea decreased substantially at a rate of up to 48.97 km³/a, which was the highest value recorded in this study. In addition, although the response of the Aral Sea's water volume to its recharge runoff demonstrated a complex non-linear relationship, the replenishment of the Aral Sea by the runoff in the lower reaches of the Amu Darya River was identified as the dominant factor affecting the Aral Sea shrinkage. Based on the scenario analyses, we concluded that it is possible to slow down the retreat of the Aral Sea and restore its ecosystem by increasing the efficiency of agricultural water use, decreasing agricultural water use in the middle and lower reaches, reducing ineffective evaporation from reservoirs and wetlands, and increasing the water coming from the lower reaches of the Amu Darya River to the 1961-1973 level. These measures would maintain and stabilise the water area and water volume of the Aral Sea in a state of ecological restoration. Therefore, this study focuses on how human consumption of recharge runoff affects the Aral Sea and provides scientific perspective on its ecological conservation and sustainable development.

Velocity is an important component of glacier dynamics and directly reflects the response of glaciers to climate change. As a result, an accurate determination of seasonal variation in glacier velocity is very important in understanding the annual variation in glacier dynamics. However, few studies of glacier velocity in the High Mountain Asia (HMA) region were done. Along these lines, in this work, based on Sentinel-1 glacier velocity data, the distribution of glacier velocity in the HMA region was plotted and their seasonal variations during 2015-2020 were systematically analysed. The average glacier velocity in the HMA region was 0.053 m/d, and was positively correlated with the glacier area and slope. Glaciers in the Karakoram Mountains had the fastest average flow velocity (0.060 m/d), where the glaciers exhibited the largest average area and average slope. Moreover, glaciers in the Gangdisê Mountains had the slowest velocity (0.022 m/d) and the smallest average glacier area. The glacier flows were the fastest in spring (0.058 m/d), followed by summer (0.050 m/d), autumn (0.041 m/d), and winter (0.040 m/d). In addition, the glacier flows were the maximum in May, being 1.4 times of the annual average velocity. In some areas, such as the Qilian, Altun, Tibetan Interior, Eastern Kunlun, and Western Kunlun mountains, the peak glacier velocities appeared in June and July. The glacier velocity in the HMA region decreased in midsummer and reached the minimum in December when it was 75% of the annual average. These results highlight the role of meltwater in the seasonal variation in glacier flows in late spring and early summer. The seasonal velocity variation of lake-terminating glaciers was similar to that of land-terminating ones, but the former flowed faster. The velocity difference close to the mass balance line between the lake- and land-terminating glaciers was obviously greater in spring than in other seasons. In summer, the difference between the lake- and land-terminating glaciers at a normalized distance of 0.05-0.40 from the terminus was significantly greater than those of other seasons. The velocity difference between the lake- and land-terminating glaciers is closely related to the variable of ice thickness, and also to the frictional force of the terminal base reduced by proglacial lakes. Thus, it can be concluded that in addition to the variation of the glacier thickness and viscosity, the variation of glacier water input also plays a key role in the seasonal variation of glacier velocity.

Vegetation growth status is an important indicator of ecological security. The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment. Assessing the vegetation net primary productivity (NPP) of the Tarim River Basin can provide insights into the vegetation growth variations in the region. Therefore, based on the Google Earth Engine (GEE) cloud platform, we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin (except for the eastern Gobi and Kumutag deserts) from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors (air temperature and precipitation) using the Sen slope estimation method, coefficient of variation, and rescaled range analysis method. In terms of temporal characteristics, vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020, with the smallest value of 118.99 g C/(m²?a) in 2001 and the largest value of 155.07 g C/(m²?a) in 2017. Regarding the spatial characteristics, vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area. The annual average value of vegetation NPP was 133.35 g C/(m²?a), and the area with annual average vegetation NPP values greater than 100.00 g C/(m²?a) was 82,638.75 km², accounting for 57.76% of the basin. The future trend of vegetation NPP was dominated by anti-continuity characteristic; the percentage of the area with anti-continuity characteristic was 63.57%. The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74% of the regions that passed the significance test, while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68% of the regions that passed the significance test. Hence, the effect of precipitation on vegetation NPP was greater than that of air temperature. The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.

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.

In grassland ecosystems, the aerodynamic roughness (Z₀) and frictional wind speed (u^*) contribute to the aerodynamic impedance of the grassland canopy. Thus, they are often used in the studies of wind erosion and evapotranspiration. However, the effect of wind speed and grazing measures on the aerodynamic impedance of the grassland canopy has received less analysis. In this study, we monitored wind speeds at multiple heights in grazed and grazing-prohibited grasslands for 1 month in 2021, determined the transit wind speed at 2.0 m height by comparing wind speed differences at the same height in both grasslands, and divided these transit wind speeds at intervals of 2.0 m/s to analyze the effect of the transit wind speed on the relationship among Z₀, u^*, and wind speed within the grassland canopy. The results showed that dividing the transit wind speeds into intervals has a positive effect on the logarithmic fit of the wind speed profile. After dividing the transit wind speeds into intervals, the wind speed at 0.1 m height (V_0.1) gradually decreased with the increase of Z₀, exhibiting three distinct stages: a sharp change zone, a steady change zone, and a flat zone; while the overall trend of u^* increased first and then decreased with the increase of V_0.1. Dividing the transit wind speeds into intervals improved the fitting relationship between Z₀ and V_0.1 and changed their fitting functions in grazed and grazing-prohibited grasslands. According to the computational fluid dynamic results, we found that the number of tall-stature plants has a more significant effect on windproof capacity than their height. The results of this study contribute to a better understanding of the relationship between wind speed and the aerodynamic impedance of vegetation in grassland environments.

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.

Investigating the effect of geocells on the erosion and deposition distribution of ephemeral gullies in the black soil area of Northeast China can provide a scientific basis for the allocation of soil and water conservation measures in ephemeral gullies. In this study, an artificial simulated confluence test and stereoscopic photogrammetry were used to analyze the distribution characteristics of erosion and deposition in ephemeral gullies protected by geocells and the effect of different confluence flows on the erosion process of ephemeral gullies. Results showed that when the confluence flow was larger, the effect of geocell was more evident, and the protection against ephemeral gully erosion was stronger. When the confluence flow rates were 0.6, 1.8, 2.4, and 3.0 m³/h, ephemeral gully erosion decreased by 37.84%, 26.09%, 21.40%, and 35.45%. When the confluence flow rates were 2.4 and 3.0 m³/h, the average sediment yield rate of the ephemeral gully was close to 2.14 kg/(m²?min), and the protective effect of ephemeral gully erosion was enhanced. When the flow rate was higher, the surface fracture of the ephemeral gully was more serious. With an increase in confluence flow rate, the ratio of erosion to deposition increased gradually, the erosion area of ephemeral gullies was expanded, and erosion depth changed minimally. In conclusion, geocell measures changed erosion patterns by altering the rill erosion/deposition ratio, converting erosion from rill erosion to sheet erosion.

Groundwater overexploitation is a serious problem in the Turpan Basin, Xinjiang Uygur Autonomous Region of China, causing groundwater level declines and ecological and environmental problems such as the desiccation of karez wells and the shrinkage of lakes. Based on historical groundwater data and field survey data from 1959 to 2021, we comprehensively studied the evolution of groundwater recharge and discharge terms in the Turpan Basin using the groundwater equilibrium method, mathematical statistics, and GIS spatial analysis. The reasons for groundwater overexploitation were also discussed. The results indicated that groundwater recharge increased from 14.58×10⁸ m³ in 1959 to 15.69×10⁸ m³ in 1980, then continued to decrease to 6.77×10⁸ m³ in 2021. Groundwater discharge increased from 14.49×10⁸ m³ in 1959 to 16.02×10⁸ m³ in 1989, while continued to decrease to 9.97×10⁸ m³ in 2021. Since 1980, groundwater recharge-discharge balance has been broken, the decrease rate of groundwater recharge exceeded that of groundwater discharge and groundwater recharge was always lower than groundwater discharge, showing in a negative equilibrium, which caused the continuous decrease in groundwater level in the Turpan Basin. From 1980 to 2002, groundwater overexploitation increased rapidly, peaking from 2003 to 2011 with an average overexploitation rate of 4.79×10⁸ m³/a; then, it slowed slightly from 2012 to 2021, and the cumulative groundwater overexploitation was 99.21×10⁸ m³ during 1980-2021. This research can provide a scientific foundation for the restoration and sustainable use of groundwater in the overexploited areas of the Turpan Basin.

Maintaining the stability of exotic sand-binding shrub has become a large challenge in arid and semi-arid grassland ecosystems in northern China. We investigated two kinds of shrublands with different BSCs (biological soil crusts) cover in desert steppe in Northwest China to characterize the water sources of shrub (Caragana intermedia Kuang et H. C. Fu) and grass (Artemisia scoparia Waldst. et Kit.) by stable ¹⁸O isotopic. Our results showed that both shrublands were subject to persistent soil water deficiency from 2012 to 2017, the minimum soil depth with CV (coefficient of variation) <15% and SWC (soil water content) <6% was 1.4 m in shrubland with open areas lacking obvious BSC cover, and 0.8 m in shrubland covered by mature BSCs. For C. intermedia, a considerable proportion of water sources pointed to the surface soil. Water from BSCs contributed to averages 22.9% and 17.6% of the total for C. intermedia and A. scoparia, respectively. C. intermedia might use more water from BSCs in rainy season than dry season, in contrast to A. scoparia. The relationship between shrub (or grass) and soil water by δ¹⁸O shown significant differences in months, which partly verified the potential trends and relations covered by the high variability of the water source at seasonal scale. More fine roots at 0-5 cm soil layer could be found in the surface soil layer covered by BSCs (8000 cm/m³) than without BSCs (3200 cm/m³), which ensured the possibility of using the surface soil water by C. intermedia. The result implies that even under serious soil water deficiency, C. intermedia can use the surface soil water, leading to the coexistence between C. intermedia and A. scoparia. Different with the result from BSCs in desert areas, the natural withdrawal of artificial C. intermedia from desert steppe will be a long-term process, and the highly competitive relationship between shrubs and grasses also determines that its habitat will be maintained in serious drought state for a long time.

Lakes play important roles in sustaining the ecosystem and economic development in Inner Mongolia Autonomous Region of China, but the spatial patterns and driving mechanisms of water quality in lakes so far remain unclear. This study aimed to identify the spatial changes in water quality and the driving factors of seven lakes (Juyanhai Lake, Ulansuhai Lake, Hongjiannao Lake, Daihai Lake, Chagannaoer Lake, Hulun Lake, and Wulannuoer Lake) across the longitudinal axis (from the west to the east) of Inner Mongolia. Large-scale research was conducted using the comprehensive trophic level index (TLI (Σ)), multivariate statistics, and spatial analysis methods. The results showed that most lakes in Inner Mongolia were weakly alkaline. Total dissolved solids and salinity of lake water showed obvious zonation characteristics. Nitrogen and phosphorus were identified as the main pollutants in lakes, with high average concentrations of total nitrogen and total phosphorus being of 4.05 and 0.21 mg/L, respectively. The values of TLI (Σ) ranged from 49.14 to 71.77, indicating varying degrees of lake eutrophication, and phosphorus was the main driver of lake eutrophication. The lakes of Inner Mongolia could be categorized into lakes to the west of Daihai Lake and lakes to the east of Daihai Lake in terms of salinity and TLI (Σ). The salinity levels of lakes to the west of Daihai Lake exceeded those of lakes to the east of Daihai Lake, whereas the opposite trend was observed for lake trophic level. The intensity and mode of anthropogenic activities were the driving factors of the spatial patterns of lake water quality. It is recommended to control the impact of anthropogenic activities on the water quality of lakes in Inner Mongolia to improve lake ecological environment. These findings provide a more thorough understanding of the driving mechanism of the spatial patterns of water quality in lakes of Inner Mongolia, which can be used to develop strategies for lake ecosystem protection and water resources management in this region.

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.

Railways built in cold, snowy, and lightly populated areas are subjected to wind and snow disasters. In this study, we selected a snow hazard prevention and control section of the Altay-Zhundong Railway in Xinjiang Uygur Autonomous Region of China as the research object. We investigated the deposited snowfall variation characteristics on the two sides and in the embankment pavement area of snow fences with different porosities, fence heights, and arrangement distances using single-factor tests and orthogonal tests based on global atmospheric reanalysis climate data, field survey data, and a multi-phase flow analysis model. The results showed significant differences in the characteristics of snow cover distribution and snow cover thickness between the embankment and the cutting in the absence of snow protection measures. The maximum snow cover thickness of the embankment pavement decreased by 12.6% relative to the cutting pavement. The snow cover thickness of the embankment exhibited an increasing trend from windward shoulder to leeward shoulder, whereas the snow cover thickness of the cutting presented a declining trend from windward shoulder to leeward toe. In the collaborative prevention and control of snow fences and embankments, the three factors can be ranked in terms of their sensitivity to deposited snowfall within the influence scope of snow fences as follows: fence height>arrangement distance>porosity. At the same time, fence height yielded a significant relationship for the influence scope of snow fences (P<0.05). The three factors can also be ranked in terms of their sensitivity to deposited snowfall on the pavement as follows: porosity>fence height>arrangement distance. For the embankment protection of the Altay-Zhundong Railway against wind and snow, snow fence with a porosity of 75%, a fence height of 4.8 m, and an arrangement distance from the embankment of 60 m produced the best snow control effect. By revealing the characteristics of snow cover distribution along railway subgrade and the protective effect of snow fences, this study provides valuable references for the engineering applications of railway construction in areas prone to wind and snow disasters.

Soil erosion is one of the most serious environmental issues constraining the sustainable development of human society and economies. Soil compound erosion is the result of the alternation or interaction between two or more erosion forces. In recent years, fluctuations and extreme changes in climatic factors (air temperature, precipitation, wind speed, etc.) have led to an increase in the intensity and extent of compound erosion, which is increasingly considered in soil erosion research. First, depending on the involvement of gravity, compound erosion process can be divided into compound erosion with and without gravity. We systematically summarized the research on the mechanisms and processes of alternating or interacting soil erosion forces (wind, water, and freeze-thaw) considering different combinations, combed the characteristics of compound erosion in three typical regions, namely, high-elevation areas, high-latitude areas, and dry and wet transition regions, and reviewed soil compound erosion research methods, such as station observations, simulation experiments, prediction models, and artificial neural networks. The soil erosion model of wind, water, and freeze-thaw interaction is the most significant method for quantifying and predicting compound erosion. Furthermore, it is proposed that there are several issues such as unclear internal mechanisms, lack of comprehensive prediction models, and insufficient scale conversion methods in soil compound erosion research. It is also suggested that future soil compound erosion mechanism research should prioritize the coupling of compound erosion forces and climate change.

Whether millennial- to centennial-scale climate variations throughout the Holocene convey universal climate change is still widely debated. In this study, we aimed to obtain a set of high-resolution multi-proxy data (1343 particle size samples, 893 total organic carbon samples, and 711 pollen samples) from an alluvial-lacustrine-aeolian sequence based on an improved age-depth model in the northwestern margin of the East Asian monsoon region to explore the dynamics of climate changes over the past 30 ka. Results revealed that the sequence not only documented the major climate events that corresponded well with those reported from the North Atlantic regions but also revealed many marked and high-frequency oscillations at the millennial- and centennial-scale. Specifically, the late stage of the last glacial lasting from 30.1 to 18.1 cal. ka BP was a dry and cold period. The deglacial (18.1-11.5 cal. ka BP) was a wetting (probably also warming) period, and three cold and dry excursions were found in the wetting trend, i.e., the Oldest Dryas (18.1-15.8 cal. ka BP), the Older Dryas (14.6-13.7 cal. ka BP), and the Younger Dryas (12.5-11.5 cal. ka BP). The Holocene can be divided into three portions: the warmest and wettest early portion from 11.5 to 6.7 cal. ka BP, the dramatically cold and dry middle portion from 6.7 to 3.0 cal. ka BP, and the coldest and driest late portion since 3.0 cal. ka BP. Wavelet analysis results on the total pollen concentration revealed five substantially periodicities: c. 5500, 2200, 900, 380, and 210 a. With the exception of the c. 5500 a quasi-cycle that was causally associated with the Atlantic meridional overturning circulation, the other four quasi-cycles (i.e., c. 2200, 900, 380, and 210 a) were found to be indirectly causally associated with solar activities. This study provides considerable insight into the dynamic mechanism of the Asian climate on a long-time scale and future climatic change.

Otindag Sandy Land in China is an important ecological barrier to Beijing; the changes in its ecological quality are major concerns for sustainable development and planning of this area. Based on principal component analysis and path analysis, we first generated a modified remote sensing ecological index (MRSEI) coupled with satellite and ground observational data during 2001-2020 that integrated four local indicators (greenness, wetness, and heatness that reflect vegetation status, water, and heat conditions, respectively, as well as soil erosion). Then, we assessed the ecological quality in Otindag Sandy Land during 2001-2020 based on the MRSEI at different time scales (i.e., the whole year, growing season, and non-growing season). MRSEI generally increased with an upward rate of 0.006/a during 2001-2020, with clear seasonal and spatial variations. Ecological quality was significantly improved in most regions of Otindag Sandy Land but degraded in the southern part. Regions with ecological degradation expanded to 18.64% of the total area in the non-growing season. The area with the worst grade of MRSEI shrunk by 15.83% of the total area from 2001 to 2020, while the area with the best grade of MRSEI increased by 9.77% of the total area. The temporal heterogeneity of ecological conditions indicated that the improvement process of ecological quality in the growing season may be interrupted or deteriorated in the following non-growing season. The implementation of ecological restoration measures in Otindag Sandy Land should not ignore the seasonal characteristics and spatial heterogeneity of local ecological quality. The results can explore the effectiveness of ecological restoration and provide scientific guides on sustainable development measures for drylands.

Investigation of the climate change effects on drought is required to develop management strategies for minimizing adverse social and economic impacts. Therefore, studying the future meteorological drought conditions at a local scale is vital. In this study, we assessed the efficiency of seven downscaled Global Climate Models (GCMs) provided by the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), and investigated the impacts of climate change on future meteorological drought using Standard Precipitation Index (SPI) in the Karoun River Basin (KRB) of southwestern Iran under two Representative Concentration Pathway (RCP) emission scenarios, i.e., RCP4.5 and RCP8.5. The results demonstrated that SPI estimated based on the Meteorological Research Institute Coupled Global Climate Model version 3 (MRI-CGCM3) is consistent with the one estimated by synoptic stations during the historical period (1990-2005). The root mean square error (RMSE) value is less than 0.75 in 77% of the synoptic stations. GCMs have high uncertainty in most synoptic stations except those located in the plain. Using the average of a few GCMs to improve performance and reduce uncertainty is suggested by the results. The results revealed that with the areas affected by wetness decreasing in the KRB, drought frequency in the North KRB is likely to increase at the end of the 21^st century under RCP4.5 and RCP8.5 scenarios. At the seasonal scale, the decreasing trend for SPI in spring, summer, and winter shows a drought tendency in this region. The climate-induced drought hazard can have vast consequences, especially in agriculture and rural livelihoods. Accordingly, an increasing trend in drought during the growing seasons under RCP scenarios is vital for water managers and farmers to adopt strategies to reduce the damages. The results of this study are of great value for formulating sustainable water resources management plans affected by climate change.

Analysis of environmental significance and hydrochemical characteristics of river water in mountainous regions is vital for ensuring water security. In this study, we collected a total of 164 water samples in the western region of the Altay Mountains, China, in 2021. We used principal component analysis and enrichment factor analysis to examine the chemical properties and spatiotemporal variations of major ions (including F^-, Cl^-, NO₃^-, SO₄^2-, Li⁺, Na⁺, NH₄⁺, K⁺, Mg²⁺, and Ca²⁺) present in river water, as well as to identify the factors influencing these variations. Additionally, we assessed the suitability of river water for drinking and irrigation purposes based on the total dissolved solids, soluble sodium percentage, sodium adsorption ratio, and total hardness. Results revealed that river water had an alkaline aquatic environment with a mean pH value of 8.00. The mean ion concentration was ranked as follows: Ca²⁺>SO₄^2->Na⁺>NO₃^->Mg²⁺>K⁺>Cl^->F^->NH₄⁺>Li⁺. Ca²⁺, SO₄^2-, Na⁺, and NO₃^- occupied 83% of the total ion concentration. In addition, compared with other seasons, the spatial variation of the ion concentration in spring was obvious. An analysis of the sources of major ions revealed that these ions originated mainly from carbonate dissolution and silicate weathering. The recharge impact of precipitation and snowmelt merely influenced the concentration of Cl^-, NO₃^-, SO₄^2-, Ca²⁺, and Na⁺. Overall, river water was in pristine condition in terms of quality and was suitable for both irrigation and drinking. This study provides a scientific basis for sustainable management of water quality in rivers of the Altay Mountains.

In the past few decades, meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers. Based on the literature, meteorological datasets are not more accurate than synoptic stations, but their various advantages, such as spatial coverage, time coverage, accessibility, and free use, have made these techniques superior, and sometimes we can use them instead of synoptic stations. In this study, we used four meteorological datasets, including Climatic Research Unit gridded Time Series (CRU TS), Global Precipitation Climatology Centre (GPCC), Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications (AgMERRA), Agricultural Climate Forecast System Reanalysis (AgCFSR), to estimate climate variables, i.e., precipitation, maximum temperature, and minimum temperature, and crop variables, i.e., reference evapotranspiration, irrigation requirement, biomass, and yield of maize, in Qazvin Province of Iran during 1980-2009. At first, data were gathered from the four meteorological datasets and synoptic station in this province, and climate variables were calculated. Then, after using the AquaCrop model to calculate the crop variables, we compared the results of the synoptic station and meteorological datasets. All the four meteorological datasets showed strong performance for estimating climate variables. AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature. However, their normalized root mean square error was inferior to CRU for minimum temperature. Furthermore, they were all very efficient for estimating the biomass and yield of maize in this province. For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR. But for the estimation of biomass and yield, all the four meteorological datasets were reliable. To sum up, GPCC and AgCFSR were the two best datasets in this study. This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.

North Africa is one of the most regions impacted by water shortage. The implementation of controlled drainage (CD) in the northern Nile River delta of Egypt is one strategy to decrease irrigation, thus alleviating the negative impact of water shortage. This study investigated the impacts of CD at different levels on drainage outflow, water table level, nitrate loss, grain yield, and water use efficiency (WUE) of various wheat cultivars. Two levels of CD, i.e., 0.4 m below the soil surface (CD-0.4) and 0.8 m below the soil surface (CD-0.8), were compared with subsurface free drainage (SFD) at 1.2 m below the soil surface (SFD-1.2). Under each drainage treatment, four wheat cultivars were grown for two growing seasons (November 2018-April 2019 and November 2019-April 2020). Compared with SFD-1.2, CD-0.4 and CD-0.8 decreased irrigation water by 42.0% and 19.9%, drainage outflow by 40.3% and 27.3%, and nitrate loss by 35.3% and 20.8%, respectively. Under CD treatments, plants absorbed a significant portion of their evapotranspiration from shallow groundwater (22.0% and 8.0% for CD-0.4 and CD-0.8, respectively). All wheat cultivars positively responded to CD treatments, and the highest grain yield and straw yield were obtained under CD-0.4 treatment. Using the initial soil salinity as a reference, the soil salinity under CD-0.4 treatment increased two-fold by the end of the second growing season without negative impacts on wheat yield. Modifying the drainage system by raising the outlet elevation and considering shallow groundwater contribution to crop evapotranspiration promoted water-saving and WUE. Different responses could be obtained based on the different plant tolerance to salinity and water stress, crop characteristics, and growth stage. Site-specific soil salinity management practices will be required to avoid soil salinization due to the adoption of long-term shallow groundwater in Egypt and other similar agroecosystems.

Soil water content is a key controlling factor for vegetation restoration in sand dunes. The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand dune ecosystems. To determine the influence of vegetation on the hydrological regulation function of sand dunes, we examined the deep seepage and lateral migration of dune water with different vegetation coverages during the growing season in the Horqin Sandy Land, China. The results showed that the deep seepage and lateral migration of water decreased with the increase in vegetation coverage on the dunes. The accumulated deep seepage water of mobile dunes (vegetation coverage<5%) and dunes with vegetation coverage of 18.03%, 27.12%, and 50.65% accounted for 56.53%, 51.82%, 18.98%, and 0.26%, respectively, of the rainfall in the same period. The accumulated lateral migration of water in these dunes accounted for 12.39%, 6.33%, 2.23%, and 7.61% of the rainfall in the same period. The direction and position of the dune slope affected the soil water deep seepage and lateral migration process. The amounts of deep seepage and lateral migration of water on the windward slope were lower than those on the leeward slope. The amounts of deep seepage and lateral migration of water showed a decreasing trend from the bottom to the middle and to the top of the dune slope. According to the above results, during the construction of sand-control projects in sandy regions, we suggest that a certain area of mobile dunes (>13.75%) should be retained as a water resource reservoir to maintain the water balance of artificial fixed dune ecosystems. These findings provide reliable evidence for the accurate assessment of water resources within the sand dune ecosystem and guide the construction of desertification control projects.

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.

Variations of precipitation have great impacts on soil carbon cycle and decomposition of soil organic matter. Soil bacteria are crucial participants in regulating these ecological processes and vulnerable to altered precipitation. Studying the impacts of altered precipitation on soil bacterial community structure can provide a novel insight into the potential impacts of altered precipitation on soil carbon cycle and carbon storage of grassland. Therefore, soil bacterial community structure under a precipitation manipulation experiment was researched in a semi-arid desert grassland in Chinese Loess Plateau. Five precipitation levels, i.e., control, reduced and increased precipitation by 40% and 20%, respectively (referred here as CK, DP40, DP20, IP40, and IP20) were set. The results showed that soil bacterial alpha diversity and rare bacteria significantly changed with altered precipitation, but the dominant bacteria and soil bacterial beta diversity did not change, which may be ascribed to the ecological strategy of soil bacteria. The linear discriminate analysis (LDA) effect size (LEfSe) method found that major response patterns of soil bacteria to altered precipitation were resource-limited and drought-tolerant populations. In addition, increasing precipitation greatly promoted inter-species competition, while decreasing precipitation highly facilitated inter-species cooperation. These changes in species interaction can promote different distribution ratios of bacterial populations under different precipitation conditions. In structural equation model (SEM) analysis, with changes in precipitation, plant growth characteristics were found to be drivers of soil bacterial community composition, while soil properties were not. In conclusion, our results indicated that in desert grassland ecosystem, the sensitive of soil rare bacteria to altered precipitation was stronger than that of dominant taxa, which may be related to the ecological strategy of bacteria, species interaction, and precipitation-induced variations of plant growth characteristics.