The desert in northern China is one of important sources of loess and one significant source of material for sandstorms in Asia. The sand/dust that is transported from desert when sandstorms occur can destroy the growth of crops, cause serious losses and great harm to the economic construction and life safety, and cause natural environment pollution. Hence, it is very important to deepen the research into heavy metals in surface deposits at vulnerable ecological region of arid land of northern China to guide local industrial and agricultural development and improve environmental protection. In this research, 10 heavy metal elements (Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, Pb, and Th) were tested and analyzed in 33 soil sample sites collected from the hinterland of the Tengger Desert, northern China. The results showed that the average abundance of Th exceeded its background soil value of China by more than 5.2 times, which suggests that the Tengger Desert is polluted by Th. In addition, based on principal component analysis, spatial differentiation, and correlation analysis, we identified the source of element with a coefficient of variation in abundance of greater than 0.5 or exceeding the background soil value of China. Principal component analysis and correlation analysis showed that the sources of heavy metals of Cr, Mn, Fe, Co, Ni, Cu, and Cd were similar, while those of Th and Zn were different. Moreover, based on the contents and spatial distribution characteristics of those heavy metal elements, we found that the formation of heavy metal elements enrichment areas is caused by industrial pollution, development of irrigated agricultural, geological, and geomorphic conditions, and the sedimentary environment in the study area. Our result can provide information on the environmental background values of soils in the hinterland of the Tengger Desert.

Background value of China^a(mg/kg)

Desertification research in arid and semi-arid regions has always been actively pursued. In China, the problem of desertification in Xinjiang has also received extensive attention. Due to its unique geography, many scholars have conducted corresponding research on the desertification status of Xinjiang. In this paper, we comprehensively reviewed desertification in Xinjiang, and compared the underlying mechanisms of desertification and the status of desertification conditions after the implementation of ecological control projects. On a larger scale, desertification in Xinjiang can be divided into soil salinization inside oases and sandy desertification on the edges of oases. Human activities are considered the main cause of desertification, but natural factors also contribute to varying degrees. Research on the mechanisms of desertification has effectively curbed the development of desertification, but unreasonable use of land resources accelerates the risk of desertification. For desertification control, there are several key points. First, desertification monitoring and the early warning of desertification expansion should be strengthened. Second, monitoring and reversing soil salinization also play an important role in the interruption of desertification process. It is very effective to control soil salinization through biological and chemical methods. Third, the management of water resources is also essential, because unreasonable utilization of water resources is one of the main reasons for the expansion of desertification in Xinjiang. Due to the unreasonable utilization of water resources, the lower reaches of the Tarim River are cut off, which leads to a series of vicious cycles, such as the deterioration of ecological environment on both sides of the river and the worsening of desertification. However, in recent years, various desertification control projects implemented in Xinjiang according to the conditions of different regions have achieved remarkable results. For future studies, research on the stability of desert-oasis transition zone is also significantly essential, because such investigations can help to assess the risk of degradation and control desertification on a relatively large scale.

Drought occurs in almost all climate zones and is characterized by prolonged water deficiency due to unbalanced demand and supply of water, persistent insufficient precipitation, lack of moisture, and high evapotranspiration. Drought caused by insufficient precipitation is a temporary and recurring meteorological event. Precipitation in semi-arid regions is different from that in other regions, ranging from 50 to 750 mm. In general, the semi-arid regions in the west and north of Iran received more precipitation than those in the east and south. The Terrestrial Climate (TerraClimate) data, including monthly precipitation, minimum temperature, maximum temperature, potential evapotranspiration, and the Palmer Drought Severity Index (PDSI) developed by the University of Idaho, were used in this study. The PDSI data was directly obtained from the Google Earth Engine platform. The Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) on two different scales were calculated in time series and also both SPI and SPEI were shown in spatial distribution maps. The result showed that normal conditions were a common occurrence in the semi-arid regions of Iran over the majority of years from 2000 to 2020, according to a spatiotemporal study of the SPI at 3-month and 12-month time scales as well as the SPEI at 3-month and 12-month time scales. Moreover, the PDSI detected extreme dry years during 2000-2003 and in 2007, 2014, and 2018. In many semi-arid regions of Iran, the SPI at 3-month time scale is higher than the SPEI at 3-month time scale in 2000, 2008, 2014, 2015, and 2018. In general, this study concluded that the semi-arid regions underwent normal weather conditions from 2000 to 2020. In a way, moderate, severe, and extreme dry occurred with a lesser percentage, gradually decreasing. According to the PDSI, during 2000-2003 and 2007-2014, extreme dry struck practically all hot semi-arid regions of Iran. Several parts of the cold semi-arid regions, on the other hand, only experienced moderate to severe dry from 2000 to 2003, except for the eastern areas and wetter regions. The significance of this study is the determination of the spatiotemporal distribution of meteorological drought in semi-arid regions of Iran using strongly validated data from TerraClimate.

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.

Many arid areas have very severe climates with extremely high summer temperatures, strong solar radiation, and a lack of drinking water during the driest season. Therefore, antelopes living in arid areas are forced to solve two main problems: avoiding overheating and maintaining water balance. Generally, there are physiological, morphological, and behavioral mechanisms for antelope adaptations to arid environments. Among the mechanisms, behavioral adjustments have a minimal cost and are activated first, while physiological mechanisms are the most energetically costly and involve adaptations to high temperatures when other mechanisms are insufficient. In previous publications, some examples of the antelope behavioral adaptations have been described only rarely, while in this review, we try to clarify all available information on the adaptations of antelopes living in arid areas to their native environments, paying particular attention to behavioral adjustments. Behavioral mechanisms, especially daily activity, diet and microclimate selection, and migrations, are so important and commonly used by antelopes in natural conditions, in which physiological mechanisms are usually not involved. Antelopes adjust their behaviors according to environmental changes so successfully that purely physiological mechanisms are discovered under laboratory conditions; for example, adaptive heterothermia or selective brain cooling phenomenon is difficult to observe in their natural habitats. This review provides a better understanding of the main behavioral mechanisms of antelope adaptations to arid environments and allows for the identification of the key factors for successful conservation of antelopes in their natural habitats.

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.

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.

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.

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.

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.

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.

Under the combined influence of climate change and human activities, vegetation ecosystem has undergone profound changes. It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods. Therefore, it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle. Based on the data of climate elements (sunshine hours, precipitation and temperature), human activities (population intensity and GDP intensity) and other natural factors (altitude, slope and aspect), this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method, a trend analysis, and a gravity center model, and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model. The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest. During 1981-2019, the temporal variation of vegetation NDVI showed an overall increasing trend. The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County, Gansu Province, and the center moved northeastwards from 1981 to 2019. During 1981-2000 and 2001-2019, the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest. During the study period (1981-2019), the dominant factors influencing vegetation NDVI shifted from natural factors to human activities. These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.

The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals (UN SDGs). The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover, and the changes in ecological quality in this arid region over the last two decades are not well understood. This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level. In this study, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) products to generate remote sensing ecological index (RSEI) on the Google Earth Engine (GEE) platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades (from 2000 to 2020). We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality. We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products. Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%. The ecological quality in Xinjiang has increased significantly over the last two decades, with the northern part of this region having a better ecological quality than the southern part. The areas with slightly improved ecological quality accounted for 31.26% of the total land area of Xinjiang, whereas only 3.55% of the land area was classified as having a slightly worsen (3.16%) or worsen (0.39%) ecological quality. The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature, precipitation, closed shrublands, grasslands and savannas were the top five environmental factors affecting the changes in RSEI. Environmental factors were allocated different weights for different RSEI categories. In general, the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial. Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.

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.

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.

Competition, spatial pattern, and regeneration are important factors affecting community composition, structure, and dynamics. In this study, we surveyed 300 quadrats from three dunes (i.e., fixed dunes, semifixed dunes, and mobile dunes) in the Gurbantunggut Desert, Northwest China, from late May to early June in 2021. The intraspecific and interspecific competition, spatial pattern, and regeneration of Haloxylon ammodendron and Haloxylon persicum were studied using the Hegyi competition index and point pattern analysis methods. The results showed that the optimal competition distance of the objective tree in the H. ammodendron and H. persicum communities was 6 m. The intraspecific and interspecific competition of H. ammodendron was the greatest in fixed dunes, while the competition intensity of H. persicum in semifixed dunes and mobile dunes was greater than that in fixed dunes. The order of competition intensity of the two populations was seedlings>saplings>adults, and the competition intensity gradually decreased with the increase in plant diameter. The spatial distribution pattern of the three life stages of H. ammodendron and H. persicum was random, and there were no correlations between seedlings and saplings, adults and saplings, and seedlings and adults. The density of regenerated seedlings and saplings of H. ammodendron in the three dunes followed the order of fixed dunes>semifixed dunes>mobile dunes, and that of H. persicum in the three dunes followed the order of mobile dunes>semifixed dunes>fixed dunes. Therefore, when artificially planting H. ammodendron and H. persicum for sand control, the planting interval should be 6 m, and seedlings should be planted next to adults to minimize the competition between plants, which can promote the renewal of H. ammodendron and H. persicum and the stabilization of the ecosystem.

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.

The olive species (Olea europaea L.) is an ancient traditional crop grown under rainfed conditions in the Mediterranean Basin. In response to the growing national and international demand for olive oil, the olive cultivars are introduced into highly arid new bioclimatic areas. Subsequently, the morpho-physiology and phytochemistry of olive trees are potentially changing among cultivar types and geographical conditions. In the present work, we have undertaken an assessment on the impacts of geographical location and cultivar types on the leaf morpho-physiology and phytochemistry of olive trees. Thus, leaves of the two most cultivated olive tree varieties, Chemlal and Sigoise, were collected from three geographical regions (Setif, Batna, and Eloued) with increasing aridity in Algeria. Leaf samples from the geographical regions were analyzed using the standard physiological experiment, colorimetric method, and a chromatography assay. Leaves of both cultivars exhibited a significant variance in terms of the leaf shape index but not for the leaf tissue density, specific leaf weight, and specific leaf area. Photosynthetic pigment contents were affected by both cultivar type and geographical location, with the lowest pigment content recorded in the Sigoise cultivar from the Setif region. Compared with the Setif and Batna regions, dried leaves of both cultivars from the Eloued region showed the higher levels of the total polyphenol, total flavonoid, and total tannin, as well as a better antioxidant capacity. Liquid chromatography-mass spectrometry analysis of all leaf extracts identified the following phenolic acids as major compounds: oleuropein, naringin, apigenin-7-O-glucoside, kaempferol, quercetin, quercitrin, luteolin-7-O-naringenin, and quinic acid. Lower contents were found for p-Coumaric acid, trans-Ferulic acid, hyperoside, rutin, apigenin, caffeic acid, protocatechuic acid, o-Coumaric acid, and gallic acid. Also, epicatechin and catechin+ were not found in the leaf extracts of the Sigoise cultivar. The leaf organic extracts in both cultivars displayed promising anti-cancer activity that was affected by geographical location and organic solvent polarity. Briefly, although increasing aridity and soil organic and mineral deficiency affected the leaf morpho-physiological parameters, both cultivars sustained a chemical richness, a good antioxidant, and an anti-tumoral capacity in leaves. Furthermore, the findings revealed that regardless the olive tree genotype, there was a significant impact of geographical location on the leaf morpho-physiology, bioactivity, and chemical composition, which may consequently modulate the growth and oil production of olive trees.

Altitude affects leaf stoichiometry by regulating temperature and precipitation, and influencing soil properties in mountain ecosystems. Leaf carbon concentration (C), leaf nitrogen concentration (N), leaf phosphorous concentration (P), and their stoichiometric ratios of Leontopodium lentopodioides (Willd.) Beauv., a widespread species in degraded grasslands, were investigated to explore its response and adaptation strategy to environmental changes along four altitude gradients (2500, 3000, 3500, and 3800 m a.s.l.) on the northeastern Qinghai-Tibetan Plateau (QTP), China. The leaf C significantly varied but without any clear trend with increasing altitude. Leaf N showed an increasing trend, and leaf P showed a little change with increasing altitude, with a lower value of leaf P at 3500 m than those at other altitudes. Similarity, leaf C:P and N:P exhibited a little change with increasing altitude, which both had greater values at 3500 m than those at other altitudes. However, leaf C:N exhibited a decreasing trend with increasing altitude. Soil NH+ 4-N, soil pH, soil total phosphorus (STP), mean annual temperature (MAT), and mean annual precipitation (MAP) were identified as the main factors driving the variations in leaf stoichiometry of L. lentopodioides across all altitudes, with NH+ 4-N alone accounting for 50.8% of its total variation. Specifically, leaf C and N were mainly controlled by MAT, soil pH, and NH+ 4-N, while leaf P by MAP and STP. In the study area, it seems that the growth of L. lentopodioides may be mainly limited by STP. The results could help to strengthen our understanding of the plasticity of plant growth to environmental changes and provide new information on global grassland management and restoration.

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.

Information on rare earth elements (REEs) in soils and plants of the Qinghai-Tibet Plateau is very limited. Therefore, in this study, we performed field sampling to explore the geochemical signatures and human health risk of REEs in soils and plants of the northeastern Qinghai-Tibet Plateau, China. A total of 127 soil samples and 127 plant samples were collected from the northeastern Qinghai-Tibet Plateau to acquire the geochemical signatures and related human health risks of REEs. The mean total concentrations of REEs in soils and plants of the study area reached 178.55 and 10.06 mg/kg, respectively. The light REEs in soils and plants accounted for 76% and 77% of the total REEs, respectively. REEs showed significantly homogenous distribution in soils but inhomogeneous distribution in plants of the study area. Characteristic parameters indicated that light REEs were enriched and fractionated significantly, while heavy REEs were moderately fractionated in soils and plants. REEs in soils and plants showed significantly negative Europium anomaly. Cerium showed slightly positive anomaly in plants and slight anomaly in soils. The normalized distribution patterns of REEs were generally similar in the analyzed soils and the corresponding plants of the study area. The average bio-concentration factor of REEs ranged from 0.0478 (Scandium) to 0.0604 (Europium), confirming a small accumulation of REEs by plants. Health risks caused by REEs in soils and plants were negligible, while risks for adults were lower than those for children. This study provides important information on REEs in soils and plants of the northeastern Qinghai-Tibet Plateau.

Manipulated precipitation patterns can profoundly influence the metabolism of soil microorganisms. However, the responses of soil organic carbon (SOC) and nutrient turnover to microbial metabolic limitation under changing precipitation conditions remain unclear in semi-arid ecosystems. This study measured the potential activities of enzymes associated with carbon (C: β-1,4-glucosidase (BG) and β-D-cellobiosidase (CBH)), nitrogen (N: β-1,4-N-acetylglucosaminidase (NAG) and L-leucine aminopeptidase (LAP)) and phosphorus (P: alkaline phosphatase (AP)) acquisition, to quantify soil microbial metabolic limitations using enzymatic stoichiometry, and then identify the implications for soil microbial metabolic limitations and carbon use efficiency (CUE) under decreased precipitation by 50% (DP) and increased precipitation by 50% (IP) in a temperate grassland. The results showed that soil C and P were the major elements limiting soil microbial metabolism in temperate grasslands. There was a strong positive dependence between microbial C and P limitations under manipulated precipitation. Microbial metabolism limitation was promoted by DP treatment but reversed by IP treatment. Moreover, CUE was inhibited by DP treatment but promoted by IP treatment. Soil microbial metabolism limitation was mainly regulated by soil moisture and soil C, N, and P stoichiometry, followed by available nutrients (i.e., NO- 3, NH+ 4, and dissolved organic C) and microbial biomass (i.e., MBC and MBN). Overall, these findings highlight the potential role of changing precipitation in regulating ecosystem C turnover by limiting microbial metabolism and CUE in temperate grassland ecosystems.

Leaf traits can directly reflect the adaptation strategies of plants to the environment. However, there is limited knowledge on the adaptation strategies of heteromorphic leaves of male and female Populus euphratica Oliv. in response to individual developmental stages (i.e., diameter class) and canopy height changes. In this study, morphological and physiological properties of heteromorphic leaves of male and female P. euphratica were investigated. Results showed that both male and female P. euphratica exhibited increased leaf area (LA), leaf dry weight (LDW), leaf thickness (LT), net photosynthetic rate (P_n), transpiration rate (T_r), stomatal conductance (g_s), proline (Pro), and malondialdehyde (MDA) concentration, decreased leaf shape index (LI) and specific leaf area (SLA) with increasing diameter and canopy height. Leaf water potential (LWP) increased with increasing diameter, LWP decreased significantly with increasing canopy height in both sexes, and carbon isotope fraction (δ¹³C) increased significantly with canopy height in both sexes, all of which showed obvious resistance characteristics. However, males showed greater LA, LT, P_n, T_r, and Pro than females at the same canopy height, and males showed significantly higher LA, SLA, LT, P_n, T_r, g_s, and MDA, but lower LWP and δ¹³C than females at the same canopy height, suggesting that male P. euphratica have stronger photosynthetic and osmoregulatory abilities, and are sensitive to water deficiency. Moreover, difference between male and female P. euphratica is closely related to the increase in individual diameter class and canopy height. In summary, male plants showed higher stress tolerance than female plants, and differences in P_n, g_s, T_r, Pro, MDA, δ¹³C, and LWP between females and males were related to changes in leaf morphology, diameter class, and canopy height. The results of this study provide a theory for the differences in growth adaptation strategies during individual development of P. euphratica.

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.

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.

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.

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.

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.

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.

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.

Water risk early warning systems based on the water environmental carrying capacity (WECC) are powerful and effective tools to guarantee the sustainability of rivers. Existing work on the early warning of WECC has mainly concerned the comprehensive evaluation of the status quo and lacked a quantitative prejudgement and warning of future overload. In addition, existing quantitative methods for short-term early warning have rarely focused on the integrated change trends of the early warning indicators. Given the periodicity of the socioeconomic system, however, the water environmental system also follows a trend of cyclical fluctuations. Thus, it is meaningful to monitor and use this periodicity for the early warning of the WECC. In this study, we first adopted and improved the prosperity index method to develop an integrated water risk early warning framework. We also constructed a forecast model to qualitatively and quantitatively prejudge and warn about the development trends of the water environmental system. We selected the North Canal Basin (an essential connection among the Beijing- Tianjin-Hebei region) in China as a case study and predicted the WECC in 25 water environmental management units of the basin in 2018-2023. We found that the analysis of the prosperity index was helpful in predicting the WECC, to some extent. The result demonstrated that the early warning system provided reliable prediction (root mean square error of 0.0651 and mean absolute error of 0.1418), and the calculation results of the comprehensive early warning index (CEWI) conformed to the actual situation and related research in the river basin. From 2008 to 2023, the WECC of most water environmental management units in the basin had improved but with some spatial differences: the CEWI was generally poor in areas with many human disturbances, while it was relatively good in the upstream regions with higher forest and grass covers as well as in the downstream areas with larger water volume. Finally, through a sensitivity analysis of the indicators, we proposed specific management measures for the sustainability of the water environmental system in the North Canal Basin. Overall, the integrated water risk early warning framework could provide an appropriate method for the water environmental administration department to predict the WECC of the basin in the future. This framework could also assist in implementing corresponding management measures in advance, especially for the performance evaluation and the arrangement of key short-term tasks in the River Chief System in China.

Biological invasions can alter soil properties within the range of their introduced, leading to impacts on ecosystem services, ecosystem functions, and biodiversity. To better understand the impacts of biological invasions on soil, we compared topsoil physiochemical properties at sites with invasive alien tree species (Prosopis juliflora), native tree species (Prosopis cineraria, Acacia tortilis, and Acacia ehrenbergiana), and mixed tree species in Hormozgan Province of Iran in May 2018. In this study, we collected 40 soil samples at a depth of 10 cm under single tree species, including P. juliflora, P. cineraria, A. tortilis, and A. ehrenbergiana, as well as under mixed tree species. The results showed that organic matter, moisture, potassium, calcium, nitrogen, and magnesium in topsoil at sites with A. tortilis and A. ehrenbergiana growing in combination with P. cineraria were higher than that at sites where P. juliflora was present (P<0.05). Sodium at sites with A. tortilis and A. ehrenbergiana growing in combination with P. cineraria and P. juliflora was lower as compared to that at sites with just A. tortilis and A. ehrenbergiana. Electrical conductivity was lower at sites with A. tortilis and A. ehrenbergiana growing in combination with P. cineraria, and it was higher at sites with mixed Acacia and P. juliflora trees. Based on the generally more positive effect of native Acacia and P. cineraria on topsoil physiochemical properties as compared to the P. julifora, afforestation with native tree species is preferable for soil restoration. In addition, due to the negative effects of P. julifora on soil properties, P. julifora spread should be better managed.

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.

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.

Water scarcity is the most significant barrier to agricultural development in arid and semi-arid regions. Deficit irrigation is an effective solution for managing agricultural water in these regions. The use of additives such as vermicompost (VC) to improve soil characteristics and increase yield is a popular practice. Despite this, there is still a lack of understanding of the interaction between irrigation water and VC on various crops. This study aimed to investigate the interaction effect of irrigation water and VC on greenhouse cucumber yield, yield components, quality, and irrigation water use efficiency (IWUE). The trials were done in a split-plot design in three replicates in a semi-arid region of southeastern Iran in 2018 and 2019. Three levels of VC in the experiments, i.e., 10 (V₁), 15 (V₂), and 20 t/hm² (V₃), and three levels of irrigation water, i.e., 50% (I₁), 75% (I₂), and 100% (I₃) of crop water requirement were used. The results showed that the amount of irrigation water, VC, and their interaction significantly affected cucumber yield, yield components, quality, and IWUE in both years. Reducing the amount of irrigation water and VC application rates reduced the weight, diameter, length, and cucumber yield. The maximum yield (175 t/hm²) was recorded in full irrigation using 20 t/hm² of VC, while the minimum yield (98 t/hm²) was found in I₁V₁ treatment. The maximum and minimum values of IWUE were recorded for I₁V₃ and I₃V₁ treatments as 36.07 and 19.93 kg/(m³?hm²), respectively. Moreover, reducing irrigation amount decreased chlorophyll a and b, but increased vitamin C. However, the maximum carbohydrate and protein contents were obtained in mild water-stressed conditions (I₂). Although adding VC positively influenced the value of quality traits, no significant difference was observed between V₂ and V₃ treatments. Based on the results, adding VC under full irrigation conditions leads to enhanced yield and IWUE. However, in the case of applying deficit irrigation, adding VC up to a certain level (15 t/hm²) increases yield and IWUE, after which the yield begins to decline. Because of the salinity of VC, using a suitable amount of it is a key point to maximize IWUE and yield when applying a deficit irrigation regime.

Afghanistan is located in the Eurasian loess belt, however, there is little information on the soils in the area. Loess has covered the Herat Plain in western Herat City, Afghanistan. Despite the diversity of landform and parent material, there is no information on the soil and landform evolution in this area. The objectives of this study were to identify the soils along a transect of different landforms in the Herat Plain and determine the role of geomorphic processes on the soil and landform evolution. Five pedons from an alluvial fan, the depression between alluvial fan and piedmont plain, saline and non-saline piedmont plains, and the flood plain of the Hariroud River, were sampled. Then, the physical-chemical properties, mineralogy, and micromorphology of the samples were determined. Results showed that the soil parent material in the piedmont plain is loess, whereas, in the flood plain it is a combination of loess and river alluvial sediments. Calcification, lessivage, salinization, and gleization are the most important pedogenic processes. The calcification and lessivage appear to be the result of a wetter climate during the late Quaternary, whereas the present topography causes the gleization and salinization. Clay coatings on carbonate nodules and iron nodules are abundant pedofeatures in the Btk (argillic-calcic) horizon. Iron oxides nodules are common in the soils of the flood plain. The formation of palygorskite in both alluvial- and loess-derived soils implies the onset of aridity and the trend of increase in environmental aridity in the region. It seems that after the formation of a well developed paleosol on the alluvial fan in a more humid climate in the past, the piedmont plain has been covered by loess deposits, and the calcification, gleization, and salinization cause the formation of weakly developed surficial soils. This study highlights the role of the late Quaternary climatic changes on the evolution of landforms and soils in western Afghanistan.

Globally, many lakes are drying up, leaving exposed lakebeds where wind erosion releases dust and sand rich in salt and harmful heavy metals into the atmosphere. Therefore, understanding the characteristics and spatial distribution of playa surface crusts is important to recognize the manifestation of salt dust storms. The objective of this study was to explore the playa surface crust types as well as their spatial distribution and evolution of Qehan Lake in Inner Mongolia Autonomous Region, China to understand the salt dust release potential of different types of playa surface crusts. Various crust characteristics were investigated by field sampling in Qehan Lake, and playa surface crusts were further divided into five types: vegetated areas, salt crusts, clay flats, curly crusts, and margins. It should be noted that curly crusts were distributed in clay flats and covered only a small area in Qehan Lake. The spatial distribution characteristics of playa surface crust types were obtained by supervised classification of remote sensing images, and the salt dust release potential of crusts was explored by the wind tunnel experiments. The field investigation of Qehan Lake revealed that playa surface crust types had a circum-lake band distribution from the inside to the outside of this lake, which were successively vegetated areas, clay flats, salt crusts, and margins. The spatial distribution patterns of playa surface crust types were mainly controlled by the hydrodynamics of the playa, soil texture, and groundwater. There was a significant negative correlation between crust thickness and electrical conductivity. The results of the wind tunnel experiments showed that the initial threshold of friction wind velocity for the salt dust release was higher in clay flats (0.7-0.8 m/s) than in salt crusts (0.5-0.6 m/s). Moreover, the particle leap impact processes occurring under natural conditions may reduce this threshold value. Salinity was the main factor controlling the difference in the initial threshold of friction wind velocity for the salt dust release of clay flats and salt crusts. This study provides a scientific reference for understanding how salt dust is released from a lakebed, which may be used for ecological restoration of dry salt lakes.

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.

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.

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.