Search Results (53)

Soil fugitive dust (SFD) emissions pose a significant threat to both human health and the environment, highlighting the need for accurate and reliable estimation and assessment in the desert regions of northwest China. This study used climate, soil, and vegetation data from Bayingolin Prefecture (2001–2022) and applied the WEQ model to analyze temporal and spatial variations in total suspended particulate (TSP), PM₁₀, and PM_2.5 emissions and their driving factors. The region exhibited high emission factors for TSP, PM₁₀, and PM_2.5, averaging 55.46 t km⁻² a⁻¹, 27.73 t km⁻² a⁻¹, and 4.14 t km⁻² a⁻¹, respectively, with pronounced spatial heterogeneity and the highest values observed in Yuli, Qiemo, and Ruoqiang. The annual average emissions of TSP, PM₁₀, and PM_2.5 were 3.23 × 10⁷ t, 1.61 × 10⁷ t, and 2.41 × 10⁶ t, respectively. Bare land was the dominant source, contributing 72.55% of TSP emissions. Both total emissions and emission factors showed an overall upward trend, reaching their lowest point around 2012, followed by significant increases in most counties during 2012–2022. Annual precipitation, wind speed, and temperature were identified as the primary climatic drivers of soil dust emissions across all counties, and their influences exhibited pronounced spatial heterogeneity in Bazhou. In Ruoqiang, Bohu, Korla, and Qiemo, dust emissions are mainly limited by precipitation, although dry conditions and sparse vegetation can amplify the role of wind. In Heshuo, Hejing, and Yanqi, stable vegetation helps to lessen wind’s impact. In Yuli, wind speed and temperature are the main drivers, whereas in Luntai, precipitation and temperature are both important constraints. These findings highlight the need to consider emission intensity, land use, or surface condition changes, and the potential benefits of increasing vegetation cover in severely desertified areas when formulating regional dust mitigation strategies. Full article

In recent years, the energy policies of both Spain and the European Union have pursued the development of renewable energies, including solar power. One way these installations will appear in the Region of Murcia is on bodies of water, which do not alter existing land uses, but ground-mounted solar energy installations do bring about such changes. The Region of Murcia is located in the south-eastern quadrant of the Iberian Peninsula. Positioned on the leeward side of the westerly zonal circulation, characteristic of mid-latitudes, and influenced by the layout of the Betic mountain ranges that cross it from north-west to south-east, it experiences significant scarcity and irregularity of rainfall. In contrast, it benefits from an abundance of sunlight, with more than 3400 h of sunshine per year. This makes it one of the most productive locations for capturing solar energy and converting it into electricity. As a result, the land occupied by photovoltaic parks has increased at the expense of dry farming areas, irrigated land, and woodland. High energy prices have also led to self-consumption measures, with solar panels being installed on the roofs of industrial buildings, floating panels in irrigation reservoirs, photovoltaic solar farms associated with desalination and lift irrigation pumps, and pressure required by localized irrigation, etc. Full article

In the context of rising temperatures and increasing humidity in Northwest China, substantial gaps remain in understanding the mechanisms of land–atmosphere cloud–precipitation coupling across the northeastern Tibetan Plateau (TP), Loess Plateau (LP), and Huangshui Valley (HV). This study addresses these gaps by investigating cloud properties and precipitation patterns utilizing the Fengyun-4 Satellite Quantitative Precipitation Estimation Product (FY4A-QPE) and ERA5 datasets. We specifically focus on Lanzhou, a pivotal city within the LP, and Xining, which epitomizes the HV. Our findings reveal that diurnal variations in precipitation are significantly less pronounced in the eastern regions compared to northeastern TP. This discrepancy is attributed to marked diurnal fluctuations in convective available potential energy (CAPE) and wind shear between 200 and 500 hPa. While both cities share similar wind shear patterns and moisture transport directions, Xining benefits from enhanced snowmelt and effective water retention in surrounding mountains, resulting in higher precipitation levels. Conversely, Lanzhou suffers from moisture deficits, with dry, hot winds exacerbating the situation. Notably, precipitation in Xining is strongly correlated with CAPE, influenced by diurnal variability, and intensified by valley and lake–land breezes, which drive afternoon convection. In contrast, Lanzhou’s precipitation exhibits a weak relationship with CAPE, as even elevated values fail to generate significant cloud formation due to insufficient moisture. The ongoing trends of warming and humidification may lead to improved precipitation patterns, especially in the HV, with potential ecological benefits. However, concentrated rainfall during summer afternoons and midnights raises concerns regarding extreme weather events, highlighting the susceptibility of the HV to geological hazards. This research underscores the need to further explore the uncertainties inherent in precipitation dynamics in these regions. Full article

Straw mulching cultivation technology can improve the soil environment of farmland, and it is applied in the dry farming area of Northwestern China. There are few studies on the effect of corn straw mulching on the soil temperature and yield of potato fields in dry land in Northwestern China. In this paper, three treatments, black film ridge (HM), corn straw mulching mechanized no-tillage planting (JG) and no-covering open field flat planting (CK), were set up in the period of 2022 to 2023. A field plot experiment was carried out to determine the soil temperature, growth index, and yield data during the key growth period. The statistical analysis results show that JG and HM significantly increased the potato yield, by 12.27~18.30% and 13.09~18.10%, compared with CK, but there was no significant difference between JG and HM. The yield was significantly positively correlated with tuber weight per plant at the tuber expansion stage, starch accumulation stage, and harvest stage (0.47 *~0.60 **), and significantly negatively correlated with the number of tubers at the harvest stage (−0.54 *). Compared with CK, HM increased the average soil temperature over the whole growth period by 0.27~0.92 °C. In 2022, the increase in the 5 cm soil layer in the tuber expansion period was the largest, reaching 0.83 °C. In 2023, the increase in the 5 cm soil layer in the starch accumulation period was the largest, reaching 3.08 °C. JG reduced the soil temperature over the whole growth period by 0.52 °C, and the 20 cm soil layer in the tuber formation period decreased the most, reaching 1.45 °C, which aggravated the soil temperature change over the whole growth period (the amplitude was 4.13~4.53 °C). The temperature difference between day and night in different growth periods in 2022 was 2.14~5.41 °C, and the soil temperature in some growth periods in 2022 even exceeded that with HM. The results showed that JG could regulate soil temperature and optimize the relationship between tuber weight per plant, tuber number per plant, and biomass allocation during tuber formation, which are beneficial for the improvement of the potato yield in the dry farming area of Northwestern China. Full article

The Ili River Basin (IRB) is located in the northwest of China. With its large-scale zone and abundant resources, it is believed to be a “wet island” and a biotic resource storehouse in the dry regions of Eurasia. The IRB has stable ecological conditions and abundant water resources, providing natural conditions for agricultural production and human settlements. With the population increasing and economic development advancing, the competition for land resources is becoming fierce, leading to some ecological problems in this region. Therefore, understanding the spatiotemporal changes and driving mechanisms of the “three-zone space” (TZS) in the IRB is of significant practical importance for promoting sustainable development and optimizing the territorial spatial pattern. This study first analyzes the characteristics and intensity of the TZS changes from 2000 to 2020. Then, it utilizes the optimized parameter Geodetector (OPGD) to analyze the driving mechanisms behind these changes. The results show the following. Firstly, the agricultural space (AS) increased by a total of 837.5 km², the urban space (US) increased by 519.64 km², and other ecological space (OES) increased by 1518.83 km². Green ecological space (GES) decreased by 2875.97 km². Secondly, intensity analysis indicated that the total TZS change in IRB was 11.07%. At the spatial-type level, the increased intensities of OES, US, and AS were active. In spatial transformation intensity, US and OES tended to transform into AS; AS tended to transform into US; and OES and GES had a mutual transformation tendency. Thirdly, AS converted into US around emerging cities like Khorgas and Cocodala. The conversion towards GES was scattered. The mutual conversion between OES and GES showed spatial distribution consistency, mainly occurring in the Borohoro ranges and the Halik ranges. Lastly, regarding the driving mechanisms, the evolution of US in the IRB was driven by social and economic factors. Location and climate factors accelerated agricultural development, facilitating the transformation of GES and OES into AS. Climate and economic factors played a crucial role in the scale of conversions between OES and GES. The findings can provide a basis for the governance and protection of the IRB, help to form a rational territorial spatial pattern, and offer scientific guidance for sustainable land management. Full article

Compound extreme events pose more grave threats to human health, the natural environment, and socioeconomic systems than do individual extreme events. However, the drivers and spatiotemporal change characteristics of compound extreme events under climate transition remain poorly understood, especially in the arid region of Northwest China. This study examined the spatiotemporal change characteristics and driving mechanisms of extreme temperature and precipitation compound events in Northwest China based on data from 86 national meteorological stations and 11 climate models of the Coupled Model Intercomparison Project, Phase 6. The results indicated that (1) the frequency values of heat extremity–dry (1.60/10a) and heat extremity–heavy precipitation (0.60/10a) events increased from 1961 to 2020, and showed a faster uptrend after 1990 than before. (2) Under four shared socioeconomic pathway scenarios, there is also the likelihood of an upward trend in heat extremity–dry and heat extremity–heavy precipitation events in Northwest China by the end of 21 century, especially under SSP585, with probability values of 1.70/10a and 1.00/10a, respectively. (3) A soil moisture deficit leads to decreased evaporation and increased sensible heat by reduction in the soil–atmosphere exchange; the non-adiabatic heating process leads to a higher frequency of hot days. This land–air interaction feedback mechanism is a significant driver of heat extremity–dry events in Northwest China. (4) In the Northwest China region, the warmer trend surpasses the wetter trend, contributing to increased specific humidity, and the vapor pressure deficit may lead to an increasing frequency of extreme precipitation, consequently increasing heat extremity–heavy precipitation events. These results provide new insights for the understanding of compound extreme events, in order to cope with their risks. Full article

The Shendong Mining Area, being the largest coal base in the world, has significant challenges in the intensive development and utilization of coal resources, as well as the impact of a dry climate, which can have serious negative effects on the growth of flora in the region. Investigating the spatial and temporal patterns of how meteorological drought affects vegetation in the Shendong Mining Area at various time scales can offer a scientific foundation for promoting sustainable development and ecological restoration in the region. This study utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) data from 1986 to 2020 in the Shendong Mining Area. It employs Slope trend analysis, a Mann–Kendall test, a Geographic Detector, and other methods to examine the spatiotemporal distribution characteristics of meteorological drought at various time scales. Additionally, the study investigates the influence of these drought patterns on vegetation growth in the Shendong Mining Area. Across the mining area, there was a general decrease in the monthly average SPEI on an annual basis. However, on a seasonal, semi-annual, and annual basis, there was a gradual increase in the annual average SPEI, with a higher rate of increase in the southern region compared to the northern region. When considering the spatial variation trend in different seasons, both positive and negative trends were observed in winter and summer. The negative trend was mainly observed in the western part of the mining area, while the positive trend was observed in the eastern part. In spring, the mining area generally experienced drought, while in autumn, it generally experienced more precipitation. The mining area exhibits a prevailing distribution of vegetation, with a greater extent in the southeast and a lesser extent in the northwest. The vegetation coverage near the mine is insufficient, resulting in a low NDVI value, which makes the area prone to drought. Over the past few years, the mining area has experienced a significant increase in vegetation coverage, indicating successful ecological restoration efforts. Various forms of land use exhibit distinct responses to drought, with forests displaying the most positive correlation and barren land displaying the strongest negative correlation. Various types of landforms exhibit varying responses to drought. Loess ridge and hill landforms demonstrate the most pronounced positive association with monthly-scale SPEI values, whereas alluvial and floodplain landforms display the poorest positive correlation with yearly scale SPEI values. The general findings of this research can be summarized as follows: (1) The mining area exhibits a general pattern of increased humidity, with the pace of humidity increase having intensified in recent times. Seasonal variations exhibit consistent cyclic patterns. (2) There are distinct regional disparities in NDVI values, with a notable peak in the southeast and a decline in the northwest. The majority of the mining area exhibits a positive trend in vegetation recovery. (3) Regional meteorological drought is a significant element that influences changes in vegetation coverage in the Shendong Mining Area. Nevertheless, it displays complexity and is more obviously impacted by other factors at a small scale. (4) It should be noted that forests and barren land exert a more significant influence on SPEI values, despite their relatively lesser spatial coverage. The predominant land use type in most locations is grasslands; however, they have a relatively minor influence on SPEI. (5) A shorter time period, higher elevation, and steeper slope gradient all contribute to a larger correlation with drought. Full article

The Tibetan Plateau (TP) serves as a crucial ecological barrier in Asia, with vegetation playing a pivotal role in the terrestrial ecosystem by facilitating energy exchange between the land and atmosphere, regulating climate, and participating in the carbon cycle. In this study, we analyze the characteristics of surface vegetation on the TP in the growing season during 1982–2018 using satellite remote sensing data obtained from the National Oceanic and Atmospheric Administration (NOAA) and China Meteorological Forcing Dataset (CMFD). We investigate how these characteristics respond to climate change under different warming and humidification conditions across the TP. The main conclusions are as follows. (1) The normalized difference vegetation index (NDVI) values on the TP exhibit a gradual decrease from southeast to northwest during the growing season. There is a significant overall increasing trend at a climate tendency rate of 0.01·decade⁻¹ (p < 0.01) from 1982 to 2018, characterized by a notable mutation of around 1998. Over the past 37 years, a polarized trend of vegetation was observed on the TP, with notable improvement in its central and eastern regions. However, there has been noticeable degradation in northwestern TP, specifically within the Kunlun Mountains and Qaidam Basin. (2) The climate of the TP demonstrates distinct regional disparities in terms of warming and humidification characteristics before and after 1998. During the period of 1982–1998 (1998–2018), the temperature increase is primarily concentrated in the northern (southern) TP, while precipitation increase is mainly observed in the southern and northwestern (northeastern and western) regions of the TP. (3) The responses of surface vegetation to climate factors exhibit significant variations across diverse climatic backgrounds. It is noteworthy that moisture conditions have a substantial impact on the response of vegetation to air temperature on the TP. During the period of 1982–1998, under relatively insufficient moisture conditions, a positive correlation was observed between air temperature and surface vegetation in the humid and semi-humid regions of the southeastern TP, while a negative correlation was found in the semi-arid regions of northeastern TP. During 1998–2018, as moisture conditions became relatively sufficient, surface vegetation in the semi-arid regions showed positive correlations with both temperature and precipitation. However, surface vegetation in the humid and semi-humid regions exhibited a significant negative correlation with precipitation. During this period, the synergistic effects between warm and humid climates in the semi-arid regions of northeastern TP and warm and dry climates in humid and semi-humid regions of southeastern TP substantially enhanced surface vegetation on the TP. Furthermore, our results indicate that thermal factors (air temperature) primarily influence variations in surface vegetation within the high-altitude arid region of the TP. During 1998–2018, a significant cooling trend was observed in the northwestern TP, which could potentially account for the degradation of surface vegetation in the Kunlun Mountains. The findings of this study establish a scientific basis for the sustainable development of grassland ecosystems on the TP. Full article

Northeast China’s sandy region is an arid and semi-arid zone highly susceptible to climate change. Investigating the long-term changes in the Northeast China sandy land (Northeast China sandy land, DBSL) landscape can provide an important basis for the ecological restoration of this region. This study analyzed long-term remote sensing data of the DBSL from 1980 to 2022 and explored the spatial pattern, evolution, and driving mechanisms. In 2022, vegetation was mainly distributed in the northwest, center, and southwest, covering a total area of 30,508.82 km². Areas with high and medium vegetation cover showed strong aggregation characteristics and were mainly distributed in the southwest, whereas those with low vegetation coverage were highly dispersed and widely distributed in the central region. Lakes were widely distributed in the northwest and central regions, with a total area of 2736.43 km². In the last 42 years, the vegetation cover decreased by 24.48%. Areas with high and medium vegetation coverage decreased in size, and those with low vegetation coverage first increased and then decreased, with overall decreases of 35.35%, 19.16%, and 6.88%, respectively. The overall area of the DBSL showed various degrees of degradation. Shrinking and dry lakes were concentrated in the sandy hinterland. The lake landscape changed significantly from 1990 to 2010, with a decrease in lake area of 27.41%. In contrast, the sandy area increased by 25.65%, indicating a high degree of desertification. However, from 2005 to 2022, desertification decelerated. The most important factors driving the evolution of the DBSL were socio-economic factors. The increase in human disturbance will have a certain impact on the landscape changes in the region in the short term. The national policy of returning farmland to fields and grasslands will affect the increase of vegetation and lake landscape area in the short term, and the sand area and excessive animal husbandry will be reduced. This study provides a scientific basis for ecological restoration and sustainable development in Northeast China. Full article

Significant temporal and spatial variability in soil moisture (SM) is observed during the warm season in China and its surrounding regions. Because of the existence of two different evapotranspiration regimes, i.e., soil moisture-limited and energy-limited, averaging the land–atmosphere (L–A) coupling strength for all soil wetness scenarios may result in the loss of coupling signals. This study examines the daytime-only L–A interactions under different soil moisture conditions, by using two-legged metrics in the warm season from May to September 1981–2020, partitioning the interactions between SM and latent heat flux (SM–LH, the land leg) from the interactions between latent heat flux and the lifting condensation level (LH–LCL, the atmospheric leg). The statistical results reveal large regional differences in warm-season daytime L–A feedback in China and its surrounding areas. As the soil becomes wetter, the positive SM–LH coupling strength increases in arid regions (e.g., northwest China, Hetao, and the Great Indian Desert) and the positive feedback shifts to the negative one in semi-arid/semi-humid regions (northeast and northern China). The negative LH–LCL coupling is most pronounced in wet soil months in arid regions, while the opposite is true for the Tibetan Plateau. In terms of intraseasonal variation, the large variability of SM in north China, the Tibetan Plateau, and India due to the influence of the summer monsoon leads to the sign change in the land segment coupling index, comparing pre- and post-monsoon periods. To further examine the impact of SM anomalies on L–A coupling and to explore evapotranspiration regimes in the North China Plain, four sets of sensitivity experiments with different soil moisture levels over a period of 10 years were conducted. Under relatively dry soil conditions, evapotranspiration is dominated by the soil moisture-limited regime with positive L–A coupling, regardless of external moisture inflow. The critical soil moisture value separating a soil moisture-limited and an energy-limited regime lies between 0.24 m³/m³ and 0.29 m³/m³. Stronger positive feedback under negative soil moisture anomalies may increase the risk of drought in the North China Plain. Full article

Climate change and land use/cover change (LUCC) are two major factors that alter hydrological processes. The upper reaches of the Tarim River, situated in the northwest region of China, experience a dry and less rainy climate and are significantly influenced by human activities. This study comprehensively assessed the impacts of individual and combined climate changes and LUCCs on streamflow. Three general circulation models (GCMs) were utilized to predict future climate changes under three shared socioeconomic pathways (SSP119, SSP245, and SSP585). Cellular Automata–Markov (CA–Markov) was employed to predict future LUCC under three scenarios (i.e., ecological protection, historical trend, and farmland development). Streamflow for the period 2021–2050 was simulated using the calibrated MIKE SHE model with multiple scenarios. The results showed that from 2021 to 2050, increments in both average annual precipitation and average annual temperature under the three SSPs were predicted to lead to an increased streamflow. In comparison to the conditions observed in 2000, under three LUCC scenarios for 2030, the grassland area decreased by 1.04% to 1.21%, while the farmland area increased by 1.97% to 2.26%, resulting in reduced streamflow. The related changes analysis indicated that the variation in streamflow during winter is most significant, followed by spring. The study predicted that climate change would increase streamflow, while LUCC would decrease it. Due to the greater impact of LUCC, considering the combined effect of both factors, runoff would decrease. The contribution analysis indicated that climate change contributed between −7.16% and −18.66%, while LUCC contributed between 107.16% and 118.66%. Full article

The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of paddy land and irrigated land in the same region. Thus, according to the third land survey data, this research first estimated the NGPRs of cropland, paddy land, irrigated land, and dry land at different scales in Shandong Province, China in 2019. Then, their spatial characteristics at a county scale were identified by combining the standard deviation ellipse model and spatial autocorrelation analysis. Finally, the potential driving factors of the NGPR of cropland were explored with the geographical weight regression model. Results are as follows: (1) The NGPR of cropland is at relatively lower level in Shandong Province and is dominated by that of irrigated land, and the NGPR of dry land is higher than those of other cropland types; (2) Significant regional differences exist in the NGPR of cropland, with profound severity in the southeast and much lower in the northwest; (3) At the provincial scale, the total power of agricultural machinery per capita and utilization degree of cropland factors can relieve the NGPR of cropland in nearly the entire research area. The proportion of GDP of the primary industry in GDP, urban population rate, and DEM are the main obstacles for NGPR decrease. At the county scale, the influences of driving factors varied across regions. This research can provide targeted and regional differentiated references for policy improvement and NGPR management. Full article

Land desertification is a key environmental problem in China, especially in Northwest China, where it seriously affects the sustainable development of natural resources. In this paper, we combine high-resolution satellite remote sensing images and UAV (unmanned aerial vehicle) visible light images to extract desert vegetation data and quickly locate and accurately monitor land desertification in relevant areas according to changes in vegetation coverage. Due to the strong light and dry climate of deserts in Northwest China, which results in deeper vegetation shadow texture and mostly dry shrubs with fewer stems and leaves, the accuracy of the vegetation index commonly used in visible remote sensing image classification is not able to meet the requirements for monitoring and evaluating land desertification. For this reason, in this paper, we took the Hangjin Banner in Bayannur as an example and constructed a new vegetation index, the HSVGVI (hue–saturation–value green enhancement vegetation index), based on the HSV (hue–saturation–value) color space using channel enhancement that can improve the extraction accuracy of desert vegetation and reduce misclassification. In addition, in order to further test the extraction accuracy, samples of densely vegetated and multi-shaded areas were divided in the study area according to the accuracy-influencing factors. At the same time, the HSVGVI was compared with the vegetation indices EXG (excess green index), RGBVI (red–green–blue vegetation index), MGRVI (modified green–red vegetation index), NGBDI (normalized green–red discrepancy index), and VDVI (visible-band discrepancy vegetation index) constructed based on the RGB (red–green–blue) color space. The experimental results show that the extraction accuracy of the EXG and other vegetation indices constructed in RGB color space can only reach 70%, while the extraction accuracy of the HSVGVI can reach more than 95%. In summary, the HSVGVI proposed in this paper can better realize the extraction of desert vegetation data and can provide a reliable technical tool for monitoring and evaluating land desertification. Full article

Ecosystem services (ESs) serve as a fundamental cornerstone for upholding global biodiversity and promoting human well-being. ESs trade-off and synergy are supposed to be significantly affected by climate change (CC) and land use/cover change (LULC). However, the limited availability of finely classified future land-use data and integrated landscape change models incorporating climate change scenarios has hindered our understanding of the trade-off and synergistic patterns and controls of ESs at multiple scales, particularly in arid areas. Here, a future multi-scenario ESs trade-off/collaborative assessment framework (SD-PLUS-InVEST model) for multi-scale conversion and refined land-use classification was developed by coupling the patch-generated land-use simulation (PLUS) model, system dynamics (SD) model, InVEST model, geographically weighted regression (GWR) model, optimal parameter geographical detector (OPGD) model, and structural equation model (SEM). The four ESs, namely carbon storage (CS), habitat quality (HQ), water conservation (WC), and soil conservation (SC), were assessed. Further, multi-scale ESs were evaluated under different climate change and development scenarios (i.e., the SSP1-2.6 and ecological protection scenario, SSP1-2.6-EP; SSP2-4.5 and natural development scenario, SSP2-4.5-ND; SSP5-8.5 and economic growth scenario, SSP5-8.5-EG). The results demonstrated that the arid region of northwest China (ANWC) was experiencing a significant and continuous warming trend accompanied by increased humidity. There will be a significant decrease in the areas occupied by paddy fields, natural forests, and permanent glaciers among the 24 LULC types. Conversely, there will be a substantial increase in dry land, high-coverage grassland, and urban construction land areas. According to the SSP1-2.6-EP, SSP2-4.5-ND, and SSP5-8.5-EG scenarios, the comprehensive land-use dynamic degrees were estimated to reach 2.58%, 4.08%, and 4.74%, respectively. The LULC resulting from CC exacerbates the differences in the four ESs of ANWC. In particular, CS and HQ experience significant reductions in 2100. Conversely, WC and SC show notable increases during the same period. The changes in CS, HQ, WC, and SC reach 11.36 × 10⁸ m³, 1735.25 × 10⁸ t, −1.29 × 10⁸ t, and −0.009, respectively. The four ESs of CS, HQ, WC, and SC in ANWC display a synergistic relationship. This synergy is influenced by the heterogeneous spatial distribution of CS, HQ, WC, and SC, with the strongest synergy observed between CS and HQ and the weakest between CS and WC. Interestingly, the distribution differences in ESs synergy were amplified at watershed, county, and grid scales in mountainous areas, with the most significant detection differentiation occurring at the grid scale. Furthermore, the detection of spatial heterogeneity in the four ESs can be attributed to various factors. These factors include the drought index (q = 0.378), annual average precipitation (q = 0.375), economic density (q = 0.095), vegetation coverage (q = 0.262), and soil bulk density (q = 0.077). Our results highlight the importance of CC in influencing ESs. The spatial variations in ESs trade-offs and coordination at different scales, particularly the pronounced differences observed in mountainous areas, underscore the need to prioritize the conservation of arid mountainous regions in terms of future policy making. Full article

Alxa League of Inner Mongolia Autonomous Region is a concentrated desert distribution area in China, and the latest desertification process and its driving mechanism under the comprehensive influence of the extreme dry climate and intense human activities has attracted much attention. Landsat data, including ETM+ images obtained in 2000, TM images obtained in 2010, and OLI images obtained in 2020, were used to extract three periods of desertification land information using the classification and regression tree (CART) decision tree classification method in Alxa League. The spatio-temporal variation characteristics of desertification land were analyzed by combining the transfer matrix and barycenter migration model; the effects of climate change and human activities on regional desertification evolution were separated and recombined using the multiple regression residual analysis method and by considering the influence of non-zonal factors. The results showed that from 2000 to 2020, the overall area of desertification land in Alxa League was reduced, the desertification degree was alleviated, the desertification trend was reversed, and the desertification degree in the northern part of the region was more serious than in the southern part. The barycenter of the slight, moderate, and severe desertification land migrated to the southeast, whereas the serious desertification land’s barycenter migrated to the northwest in the period of 2000–2010; however, all of them hardly moved from 2010 to 2020. The degree of desertification reversal in the south was more significant than in the north. Regional desertification reversal was mainly influenced by the combination of human activities and climate change, and the area accounted for 61.5%; meanwhile, the localized desertification development was mainly affected by human activities and accounted for 76.8%. Full article