Pendjari Biosphere Reserve (PBR), a primary component of the W-Arly-Pendjari transboundary biosphere reserve, represents the largest intact wild ecosystem and pristine biodiversity spot in West Africa. This savannah ecosystem has long been affected by fire, which is the main ecological driver for the annual rhythm of life in the reserve. Understanding the fire distribution patterns will help to improve its management plan in the region. This study explores the fire regime in the PRB during 2001-2021 in terms of burned area, seasonality, fire frequency, and mean fire return interval (MFRI) by analysing moderate resolution imaging spectroradiometer (MODIS) burned area product. Results indicated that the fire season in the PBR extends from October to May with a peak in early dry season (November-December). The last two fire seasons (2019-2020 and 2020-2021) recorded the highest areas burned in the PBR out of the twenty fire seasons studied. During the twenty years period, 8.2% of the reserve burned every 10-11 months and 11.5% burned annually. The largest part of the reserve burned every one to two years (63.1%), while 8.3% burned every two to four years, 5.8% burned every four to ten years, and 1.9% burned every ten to twenty years. Only 1.3% of the entire area did not fire during the whole study period. Fire returned to a particular site every 1.39 a and the annual percentage of area burned in the PBR was 71.9%. The MFRI (MFRI<2.00 a) was low in grasslands, shrub savannah, tree savannah, woodland savannah, and rock vegetation. Fire regime must be maintained to preserve the integrity of the PBR. In this context, we suggest applying early fire in tree and woodland savannahs to lower grass height, and late dry season fires every two to three years in shrub savannah to limit the expansion of shrubs and bushes. We propose a laissez-faire system in areas in woodland savannah where the fire frequency is sufficient to allow tree growth. Our findings highlight the utility of remote sensing in defining the geographical and temporal patterns of fire in the PBR and could help to manage this important fire prone area.

Restoration of mining soils is important to the vegetation and environment. This study aimed to explore the variations in soil nutrient contents, microbial abundance, and biomass under different gradients of substrate amendments in mining soils to select effective measures. Soil samples were collected from the Bayan Obo mining region in Inner Mongolia Autonomous Region, China. Contents of soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), available potassium (AK), microbial biomass carbon/microbial biomass nitrogen (MBC/MBN) ratio, biomass, and bacteria, fungi, and actinomycetes abundance were assessed in Agropyron cristatum L. Gaertn., Elymus dahuricus Turcz., and Medicago sativa L. soils with artificial zeolite (AZ) and microbial fertilizer (MF) applied at T0 (0 g/kg), T1 (5 g/kg), T2 (10 g/kg), and T3 (20 g/kg). Redundancy analysis (RDA) and technique for order preference by similarity to ideal solution (TOPSIS) were used to identify the main factors controlling the variation of biomass. Results showed that chemical indices and microbial content of restored soils were far greater than those of control. The application of AZ significantly increases SOM, AN, and AP by 20.27%, 23.61%, and 40.43%, respectively. AZ significantly increased bacteria, fungi, and actinomycetes abundance by 0.63, 3.12, and 1.93 times of control, respectively. RDA indicated that AN, MBC/MBN ratio, and SOM were dominant predictors for biomass across samples with AZ application, explaining 87.6% of the biomass variance. SOM, MBC/MBN ratio, and AK were dominant predictors with MF application, explaining 82.9% of the biomass variance. TOPSIS indicated that T2 was the best dosage and the three plant species could all be used to repair mining soils. AZ and MF application at T2 concentration in the mining soils with M. sativa was found to be the most appropriate measure.

Climate change caused by past, current, and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world. This study modelled future precipitation change by downscaling a set of large-scale climate predictor variables (predictors) from the second generation Canadian Earth System Model (CanESM2) under two Representative Concentration Pathway (RCP) emission scenarios (RCP4.5 and RCP8.5) in the semi-arid Borana lowland, southern Ethiopia. The Statistical DownScaling Model (SDSM) 4.2.9 was employed to downscale and project future precipitation change in the middle (2036-2065; 2050s) and far (2066-2095; 2080s) future at the local scale. Historical precipitation observations from eight meteorological stations stretching from 1981 to 1995 and 1996 to 2005 were used for the model calibration and validation, respectively, and the time period of 1981-2018 was considered and used as the baseline period to analyze future precipitation change. The results revealed that the surface-specific humidity and the geopotential height at 500 hPa were the preferred large-scale predictors. Compared to the middle future (2050s), precipitation showed a much greater increase in the far future (2080s) under both RCP4.5 and RCP8.5 scenarios at all meteorological stations (except Teletele and Dillo stations). At Teltele station, the projected annual precipitation will decrease by 26.53% (2050s) and 39.45% (2080s) under RCP4.5 scenario, and 34.99% (2050s) and 60.62% (2080s) under RCP8.5 scenario. Seasonally, the main rainy period would shift from spring (March to May) to autumn (September to November) at Dehas, Dire, Moyale, and Teltele stations, but for Arero and Yabelo stations, spring would consistently receive more precipitation than autumn. It can be concluded that future precipitation in the semi-arid Borana lowland is predicted to differ under the two climate scenarios (RCP4.5 and RCP8.5), showing an increasing trend at most meteorological stations. This information could be helpful for policymakers to design adaptation plans in water resources management, and we suggest that the government should give more attention to improve early warning systems in drought-prone areas by providing dependable climate forecast information as early as possible.

Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21^st century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI (normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region (northern China) during 1982-2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors, precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world. Under the impacts of climate change and human activities, desertification is becoming increasingly severe on the Mongolian Plateau. Understanding the vegetation dynamics in this region can better characterize its ecological changes. In this study, based on Moderate Resolution Imaging Spectroradiometer (MODIS) images, we calculated the kernel normalized difference vegetation index (kNDVI) on the Mongolian Plateau from 2000 to 2023, and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test. We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis, and quantified the effects of climate change and human activities on kNDVI change by residual analysis. The results showed that kNDVI on the Mongolian Plateau was increasing overall, and the vegetation recovery area in the southern region was significantly larger than that in the northern region. About 50.99% of the plateau showed dominant climate-driven effects of temperature, precipitation, and wind speed on kNDVI change. Residual analysis showed that climate change and human activities together contributed to 94.79% of the areas with vegetation improvement. Appropriate human activities promoted the recovery of local vegetation, and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau. This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas. This study took Gansu Province, China, a typical area with complex terrain and variable climate, as the research subject. Based on Google Earth Engine, we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022, and quantitatively analyzed the main causes of regional differences in surface water area. The findings revealed that surface water area in Gansu Province expanded by 406.88 km² from 1985 to 2022. Seasonal surface water area exhibited significant fluctuations, while permanent surface water area showed a steady increase. Notably, terrestrial water storage exhibited a trend of first decreasing and then increasing, correlated with the dynamics of surface water area. Climate change and human activities jointly affected surface hydrological processes, with the impact of climate change being slightly higher than that of human activities. Spatially, climate change affected the 'source' of surface water to a greater extent, while human activities tended to affect the 'destination' of surface water. Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted. Therefore, we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water 'supply-demand' balance strategies. The study not only sheds light on the dynamics of surface water area in Gansu Province, but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

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

Quantitative assessment of the impact of climate variability and human activities on runoff plays a pivotal role in water resource management and maintaining ecosystem integrity. This study considered six sub-basins in the upper reaches of the Yangtze River basin, China, to reveal the trend of the runoff evolution and clarify the driving factors of the changes during 1956-2020. Linear regression, Mann-Kendall test, and sliding t-test were used to study the trend of the hydrometeorological elements, while cumulative distance level and ordered clustering methods were applied to identify mutation points. The contributions of climate change and human disturbance to runoff changes were quantitatively assessed using three methods, i.e., the rainfall-runoff relationship method, slope variation method, and variable infiltration capacity (Budyko) hypothesis method. Then, the availability and stability of the three methods were compared. The results showed that the runoff in the upper reaches of the Yangtze River basin exhibited a decreasing trend from 1956 to 2020, with an abrupt change in 1985. For attribution analysis, the runoff series could be divided into two phases, i.e., 1961-1985 (baseline period) and 1986-2020 (changing period); and it was found that the rainfall-runoff relationship method with precipitation as the representative of climate factors had limited usability compared with the other two methods, while the slope variation and Budyko hypothesis methods had highly consistent results. Different factors showed different effects in the sub-basins of the upper reaches of the Yangtze River basin. Moreover, human disturbance was the main factor that contributed to the runoff changes, accounting for 53.0%-82.0%; and the contribution of climate factors to the runoff change was 17.0%-47.0%, making it the secondary factor, in which precipitation was the most representative climate factor. These results provide insights into how climate and anthropogenic changes synergistically influence the runoff of the upper reaches of the Yangtze River basin.

The characteristics of drought in Xinjiang Uygur Autonomous Region (Xinjiang), China have changed due to changes in the spatiotemporal patterns of temperature and precipitation, however, the effects of temperature and precipitation—the two most important factors influencing drought—have not yet been thoroughly explored in this region. In this study, we first calculated the standard precipitation evapotranspiration index (SPEI) in Xinjiang from 1980 to 2020 based on the monthly precipitation and monthly average temperature. Then the spatiotemporal characteristics of temperature, precipitation, and drought in Xinjiang from 1980 to 2020 were analyzed using the Theil-Sen median trend analysis method and Mann-Kendall test. A series of SPEI-based scenario-setting experiments by combining the observed and detrended climatic factors were utilized to quantify the effects of individual climatic factor (i.e., temperature and precipitation). The results revealed that both temperature and precipitation had experienced increasing trends at most meteorological stations in Xinjiang from 1980 to 2020, especially the spring temperature and winter precipitation. Due to the influence of temperature, trends of intensifying drought have been observed at spring, summer, autumn, and annual scales. In addition, the drought trends in southern Xinjiang were more notable than those in northern Xinjiang. From 1980 to 2020, temperature trends exacerbated drought trends, but precipitation trends alleviated drought trends in Xinjiang. Most meteorological stations in Xinjiang exhibited temperature-dominated drought trend except in winter; in winter, most stations exhibited precipitation-dominated wetting trend. The findings of this study highlight the importance of the impact of temperature on drought in Xinjiang and deepen the understanding of the factors influencing drought.

The Turpan-Hami (Tuha) Basin in Xinjiang Uygur Autonomous Region of China, holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative, necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover (LULC) to foster sustainable planning that is tailored to the region's unique resource endowments. However, existing LULC classification methods demonstrate inadequate accuracy, hindering effective regional planning. In this study, we established a two-level LULC classification system (8 primary types and 22 secondary types) for the Tuha Basin. By employing Landsat 5/7/8 imagery at 5-a intervals, we developed the LULC dataset of the Tuha Basin from 1990 to 2020, conducted the accuracy assessment and spatiotemporal evolution analysis, and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation (Markov-FLUS) model. The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types, respectively. Compared with the seven mainstream LULC products (GlobeLand30, Global 30-meter Land Cover with Fine Classification System (GLC_FCS30), Finer Resolution Observation and Monitoring of Global Land Cover PLUS (FROM_GLC PLUS), ESA Global Land Cover (ESA_LC), Esri Land Cover (ESRI_LC), China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset (CNLUCC), and China Annual Land Cover Dataset (CLCD)) in 2020, our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features, thereby yielding high-quality data backups for land resource analyses within the basin. In 2020, unused land (78.0% of the study area) and grassland (18.6%) were the dominant LULC types of the basin; although cropland and construction land constituted less than 1.0% of the total area, they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami. Between 1990 and 2020, cropland and construction land exhibited a rapid expansion, and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond. In future scenario simulations, significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario, whereas the wetland area will decrease, suggesting the need for ecological attention under this development pathway. In contrast, the economic development scenario underscores the fast-paced expansion of construction land, primarily from the conversion of unused land, highlighting the significant developmental potential of unused land with a slowing increase in cropland. Special attention should thus be directed toward ecological and cropland protection during development. This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.

Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development. Based on land use data of the Weihe River basin in 2000, 2010, and 2020, with the support of Aeronautical Reconnaissance Coverage Geographic Information System (ArcGIS), GeoDa, and other technologies, this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk. Results showed that land use structure of the Weihe River basin has changed significantly, with the decrease of cropland and the increase of forest land and construction land. In the past 20 a, cropland has decreased by 7347.70 km², and cropland was mainly converted into forest land, grassland, and construction land. The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved, and land use pattern became more concentrated. Meanwhile, landscape ecological risk of the Weihe River basin has been improved. Severe landscape ecological risk area decreased by 19,177.87 km², high landscape ecological risk area decreased by 3904.35 km², and moderate and low landscape ecological risk areas continued to increase. It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious, especially in the contiguous areas of high ecological risk, such as Tianshui, Pingliang, Dingxi areas and some areas of Ningxia Hui Autonomous Region. Landscape ecological risk showed obvious spatial dependence, and high ecological risk area was concentrated. Among the driving factors, population density, precipitation, normalized difference vegetation index (NDVI), and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin. The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin, providing crucial insights for sustainable management in the region.

Land surface temperature (LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer (MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones (the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami (Tuha) Basin, and Pakakuna Mountain Group) using geographical detector (Geodetector) and geographically weighted regression (GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24°C/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09°C/10a in autumn, and showed a warming trend in other seasons. Digital elevation model (DEM), latitude, wind speed, precipitation, normalized difference vegetation index (NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover (LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.

The Ili River Delta (IRD) is an ecological security barrier for the Lake Balkhash and an important water conservation area in Central Asia. In this study, we selected the IRD as a typical research area, and simulated the water yield and water conservation from 1975 to 2020 using the water yield module of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. We further analyzed the temporal and spatial variations in the water yield and water conservation in the IRD from 1975 to 2020, and investigated the main driving factors (precipitation, potential evapotranspiration, land use/land cover change, and inflow from the Ili River) of the water conservation variation based on the linear regression, piecewise linear regression, and Pearson's correlation coefficient analyses. The results indicated that from 1975 to 2020, the water yield and water conservation in the IRD showed a decreasing trend, and the spatial distribution pattern was "high in the east and low in the west"; overall, the water conservation of all land use types decreased slightly. The water conservation volume of grassland was the most reduced, although the area of grassland increased owing to the increased inflow from the Ili River. At the same time, the increased inflow has led to the expansion of wetland areas, the improvement of vegetation growth, and the increase of regional evapotranspiration, thus resulting in an overall reduction in the water conservation. The water conservation depth and precipitation had similar spatial distribution patterns; the change in climate factors was the main reason for the decline in the water conservation function in the delta. The reservoir in the upper reaches of the IRD regulated runoff into the Lake Balkhash, promoted vegetation restoration, and had a positive effect on the water conservation; however, this positive effect cannot offset the negative effect of enhanced evapotranspiration. These results provide a reference for the rational allocation of water resources and ecosystem protection in the IRD.

Since the 1950s, numerous soil and water conservation measures have been implemented to control severe soil erosion in the Liuhe River Basin (LRB), China. While these measures have protected the upstream soil and water ecological environment, they have led to a sharp reduction in the downstream flow and the deterioration of the river ecological environment. Therefore, it is important to evaluate the impact of soil and water conservation measures on hydrological processes to assess long-term runoff changes. Using the Soil and Water Assessment Tool (SWAT) models and sensitivity analyses based on the Budyko hypothesis, this study quantitatively evaluated the effects of climate change, direct water withdrawal, and soil and water conservation measures on runoff in the LRB during different periods, including different responses to runoff discharge, hydrological regime, and flood processes. The runoff series were divided into a baseline period (1956-1969) and two altered periods, i.e., period 1 (1970-1999) and period 2 (2000-2020). Human activities were the main cause of the decrease in runoff during the altered periods, contributing 86.03% (-29.61 mm), while the contribution of climate change was only 13.70% (-4.70 mm). The impact of climate change manifests as a decrease in flood volume caused by a reduction in precipitation during the flood season. Analysis of two flood cases indicated a 66.00%-84.00% reduction in basin runoff capacity due to soil and water conservation measures in the upstream area. Soil and water conservation measures reduced the peak flow and total flood volume in the upstream runoff area by 77.98% and 55.16%, respectively, even with nearly double the precipitation. The runoff coefficient in the reservoir area without soil and water conservation measures was 4.0 times that in the conservation area. These results contribute to the re-evaluation of soil and water conservation hydrological effects and provide important guidance for water resource planning and water conservation policy formulation in the LRB.

Ecological stability is a core issue in ecological research and holds significant implications for humanity. The increased frequency and intensity of drought and wet climate events resulting from climate change pose a major threat to global ecological stability. Variations in stability among different ecosystems have been confirmed, but it remains unclear whether there are differences in stability within the same terrestrial vegetation ecosystem under the influence of climate events in different directions and intensities. China's grassland ecosystem includes most grassland types and is a good choice for studying this issue. This study used the Standardized Precipitation Evapotranspiration Index-12 (SPEI-12) to identify the directions and intensities of different types of climate events, and based on Normalized Difference Vegetation Index (NDVI), calculated the resistance and resilience of different grassland types for 30 consecutive years from 1990 to 2019 (resistance and resilience are important indicators to measure stability). Based on a traditional regression model, standardized methods were integrated to analyze the impacts of the intensity and duration of drought and wet events on vegetation stability. The results showed that meadow steppe exhibited the highest stability, while alpine steppe and desert steppe had the lowest overall stability. The stability of typical steppe, alpine meadow, temperate meadow was at an intermediate level. Regarding the impact of the duration and intensity of climate events on vegetation ecosystem stability for the same grassland type, the resilience of desert steppe during drought was mainly affected by the duration. In contrast, the impact of intensity was not significant. However, alpine steppe was mainly affected by intensity in wet environments, and duration had no significant impact. Our conclusions can provide decision support for the future grassland ecosystem governance.

The recent ecological improvement in the Mu Us Desert of China, largely attributed to large-scale afforestation projects, has created new opportunities for cultivation activities. However, the subsequent rapid increase in reclamation on desertification land and its impact on desertification have raised concerns. In this study, we first extracted data on cultivated land and desertification land in 1975, 1990, 2000, 2005, 2010, 2015, and 2020 through the human-computer interaction visual interpretation method. By overlaying the cultivated land dynamics and desertification land, we subsequently explored the effect of cultivation activities on desertification in the Mu Us Desert during the six periods from 1975 to 2020 (1975-1990, 1990-2000, 2000-2005, 2005-2010, 2010-2015, and 2015-2020). The results showed that cultivated land in the Mu Us Desert showed a fluctuating and increasing trend from 3769.26 km² in 1975 to 4865.73 km² in 2020, with 2010 as the turning point for the recent rapid increase. The main contributors included the large and regular patches distributed in Yuyang District and Shenmu of Shaanxi Province, and relatively smaller patches concentrated in Inner Mongolia Autonomous Region. The increased cultivated land from the reclamation on desertification land was dominated by moderate and severe desertification lands, and the decreased cultivated land that was transferred into desertification land as abandoned cultivated land was dominated by slight and moderate desertification lands. The effect of cultivation activities on desertification reversal (average area proportion of 10.61% for reversed desertification land) was greater than that of the development of desertification (average area proportion of 5.82% for developed desertification land). Nevertheless, compared to reversed desertification land, both the significant increase of developed desertification land during the periods of 2000-2005 and 2005-2010 and the insignificant decrease during the periods of 2005-2010, 2010-2015, and 2015-2020 implied a potential remobilization risk. Therefore, this study provides a significant theoretical reference for the formulation of ecological restoration projects and regional macroeconomic development policies by considering the influence of cultivation activities, to ensure the overall environmental stability and sustainability in desertification land where reclamation and abandonment activities have taken place.

Proposed agroforestry options should begin with the species that farmers are most familiar with, which would be the native multipurpose trees that have evolved under smallholder farms and socioeconomic conditions. The African birch (Anogeissus leiocarpa (DC.) Guill. & Perr.) and pink jacaranda (Stereospermum kunthianum Cham.) trees are the dominant species in the agroforestry parkland system in the drylands of Tigray, Ethiopia. Smallholder farmers highly value these trees for their multifunctional uses including timber, firewood, charcoal, medicine, etc. These trees also could improve soil fertility. However, the amount of soil physical and chemical properties enhanced by the two species must be determined to maintain the sustainable conservation of the species in the parklands and to scale up to similar agro- ecological systems. Hence, we selected twelve isolated trees, six from each species that had similar dendrometric characteristics and were growing in similar environmental conditions. We divided the canopy cover of each tree into three radial distances: mid-canopy, canopy edge, and canopy gap (control). At each distance, we took soil samples from three different depths. We collected 216 soil samples (half disturbed and the other half undisturbed) from each canopy position and soil depth. Bulk density (BD), soil moisture content (SMC), soil organic carbon (SOC), total nitrogen (TN), available phosphorus (AP), available potassium (AK), pH, electrical conductivity (EC), and cation exchange capacity (CEC) were analysed. Results revealed that soil physical and chemical properties significantly improved except for soil texture and EC under both species, CEC under A. leiocarpus, and soil pH under S. kunthianum, all the studied soils were improved under both species canopy as compared with canopy gap. SMC, TN, AP, and AK under canopy of these trees were respectively 24.1%, 11.1%, 55.0%, and 9.3% higher than those soils under control. The two parkland agroforestry species significantly enhanced soil fertility near the canopy of topsoil through improving soil physical and chemical properties. These two species were recommended in the drylands with similar agro-ecological systems.

The effect of global climate change on vegetation growth is variable. Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation, and even regional protection of ecological environments. In this study, we constructed a new drought index (i.e., Vegetation Drought Condition Index (VDCI)) based on precipitation, potential evapotranspiration, soil moisture and Normalized Difference Vegetation Index (NDVI) data, to monitor vegetation drought in the nine major river basins (including the Songhua River and Liaohe River Basin, Haihe River Basin, Yellow River Basin, Huaihe River Basin, Yangtze River Basin, Southeast River Basin, Pearl River Basin, Southwest River Basin and Continental River Basin) in China at 1-month-12-month (T1-T12) time scales. We used the Pearson's correlation coefficients to assess the relationships between the drought indices (the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI) and Self-calibrating Palmer Drought Severity Index (scPDSI)) and the NDVI at T1-T12 time scales, and to estimate and compare the lag times of vegetation response to drought among different drought indices. The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1-T6 time scales. Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales. Potential evapotranspiration shows a higher degree of positive influence on vegetation, and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins. The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin, Haihe River Basin, Yellow River Basin, Huaihe River Basin and Yangtze River Basin at T1-T4 time scales. In general, the VDCI is more sensitive (with shorter lag time of vegetation response to drought) than the traditional drought indices (SPEI, scPDSI and SSMI) in monitoring vegetation drought, and thus it could be applied to monitor short-term vegetation drought. The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate, and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Grassland degradation can alter the structure and function of ecosystem and soil seed bank. Therefore, estimating the role of soil seed bank in vegetation regeneration of degraded grasslands is crucial. We selected grasslands with three levels of degradation, namely non-degraded (ND), mildly degraded (MD), and heavily degraded (HD) to analyze the effect of grassland degradation on soil seed bank, as well as the role of soil seed bank on vegetation regeneration of the alpine grasslands, China. Soil samples from each level were collected in May, before seedling emergence, in August, after completion of transient seed bank germination, and in December, after seed dispersal, to determine the seed density and species composition through germination experiment. Result showed that a total of 35 plant species was identified, including 15 species observed in both soil seed bank and above-ground vegetation. A total of 19, 15, and 14 species of soil seed bank were identified in December, May, and August, respectively. The most abundant species in soil seed bank were Compositae (5 species), followed by Poaceae (4 species), and Cyperaceae (3 species). Degradation level has no significant impact on species richness and Shannon- Wiener index of soil seed bank. In addition, sampling month and grassland degradation affected soil seed bank density, in which December>May>August, and ND>MD>HD, indicating that density of transient seed bank was greater than persistent seed bank. Soil seed bank density of surface layer (0-5 cm) accounting for 42%-72% of the total density, which was significantly higher than that of deep layer (5-10 cm). Similarity of species composition between vegetation and soil seed bank was low, and it increased with degradation level (ranged from 0.14 to 0.69). We concluded that grassland degradation affects soil seed bank density more than species diversity, and soil seed bank contributed slightly to vegetation regeneration of degraded alpine grassland. Therefore, it is unlikely that degraded alpine meadow can be restored solely through soil seed bank.

The wide valley of the Yarlung Zangbo River is one of the most intense areas in terms of aeolian activity on the Tibetan Plateau, China. In the past, the evaluation of the intensity of aeolian activity in the Quxu-Sangri section of the Yarlung Zangbo River Valley was mainly based on data from the old meteorological stations, especially in non-sandy areas. In 2020, six new meteorological stations, which are closest to the new meteorological stations, were built in the wind erosion source regions (i.e., sandy areas) in the Quxu-Sangri section. In this study, based on mathematical statistics and empirical orthogonal function (EOF) decomposition analysis, we compared the difference of the wind regime between new meteorological stations and old meteorological stations from December 2020 to November 2021, and discussed the reasons for the discrepancy. The results showed that sandy and non-sandy areas differed significantly regarding the mean velocity (8.3 (±0.3) versus 7.7 (±0.3) m/s, respectively), frequency (12.9% (±6.2%) versus 2.9% (±1.9%), respectively), and dominant direction (nearly east or west versus nearly north or south, respectively) of sand-driving winds, drift potential (168.1 (±77.3) versus 24.0 (±17.9) VU (where VU is the vector unit), respectively), resultant drift potential (92.3 (±78.5) versus 8.7 (±9.2) VU, respectively), and resultant drift direction (nearly westward or eastward versus nearly southward or northward, respectively). This indicated an obvious spatial variation in the wind regime between sandy and non-sandy areas and suggested that there exist problems when using wind velocity data from non-sandy areas to evaluate the wind regime in sandy areas. The wind regime between sandy and non-sandy areas differed due to the differences in topography, heat flows, and their coupling with underlying surface, thereby affecting the local atmospheric circulation. Affected by large-scale circulations (westerly jet and Indian monsoon systems), both sandy and non-sandy areas showed similar seasonal variations in their respective wind regime. These findings provide a credible reference for re-understanding the wind regime and scientific wind-sand control in the middle reaches of the Yarlung Zangbo River Valley.

Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index (SQI) model in the semi-arid Çorum Basin, situated between the Black Sea and Anatolia Region, Central Turkey. The primary aims of the study are: (1) to determine SQI values of the micro-basin in terms of land degradation and desertification. Moreover, the best-worst method (BWM) was used to determine the weighting score for each parameter; (2) to produce the soils' spatial distribution by utilizing different geostatistical models and GIS (geographic information system) techniques; and (3) to validate the obtained SQI values with biomass reflectance values. Therefore, the relationship of RE-OSAVI (red-edge optimized soil-adjusted vegetation index) and NDVI (normalized difference vegetation index) generated from Sentinel-2A satellite images at different time series with soil quality was examined. Results showed that SQI values were high in the areas that had almost a flat and slight slope. Moreover, the areas with high clay content and thick soil depth did not have salinity problems, and were generally distributed in the middle parts of the basin. However, the areas with a high slope, poor vegetation, high sand content, and low water holding capacity had low SQI values. Furthermore, a statistically high positive correlation of RE-OSAVI and NDVI indices with soil quality was found, and NDVI had the highest correlative value for June (R²=0.802) compared with RE-OSAVI.

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

Rain-on-snow (ROS) events involve rainfall on snow surfaces, and the occurrence of ROS events can exacerbate water scarcity and ecosystem vulnerability in the arid region of Northwest China (ARNC). In this study, using daily snow depth data and daily meteorological data from 68 meteorological stations provided by the China Meteorological Administration National Meteorological Information Centre, we investigated the spatiotemporal variability of ROS events in the ARNC from 1978 to 2015 and examined the factors affecting these events and possible changes of future ROS events in the ARNC. The results showed that ROS events in the ARNC mainly occurred from October to May of the following year and were largely distributed in the Qilian Mountains, Tianshan Mountains, Ili River Valley, Tacheng Prefecture, and Altay Prefecture, with the Ili River Valley, Tacheng City, and Altay Mountains exhibiting the most occurrences. Based on the intensity of ROS events, the areas with the highest risk of flooding resulting from ROS events in the ARNC were the Tianshan Mountains, Ili River Valley, Tacheng City, and Altay Mountains. The number and intensity of ROS events in the ARNC largely increased from 1978 to 2015, mainly influenced by air temperature and the number of rainfall days. However, due to the snowpack abundance in areas experiencing frequent ROS events in the ARNC, snowpack changes exerted slight impact on ROS events, which is a temporary phenomenon. Furthermore, elevation imposed lesser impact on ROS events in the ARNC than other factors. In the ARNC, the start time of rainfall and the end time of snowpack gradually advanced from the spring of the current year to the winter of the previous year, while the end time of rainfall and the start time of snowpack gradually delayed from autumn to winter. This may lead to more ROS events in winter in the future. These results could provide a sound basis for managing water resources and mitigating related disasters caused by ROS events in the ARNC.

The Aral Sea was the fourth largest lake in the world but it has shrunk dramatically as a result of irrational human activities, triggering the "Aral Sea ecological crisis". The ecological problems of the Aral Sea have attracted widespread attention, and the alleviation of the Aral Sea ecological crisis has reached a consensus among the five Central Asian countries (Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan, and Turkmenistan). In the past decades, many ecological management measures have been implemented for the ecological restoration of the Aral Sea. However, due to the lack of regional planning and zoning, the results are not ideal. In this study, we mapped the ecological zoning of the Aral Sea from the perspective of ecological restoration based on soil type, soil salinity, surface water, groundwater table, Normalized Difference Vegetation Index (NDVI), land cover, and aerosol optical depth (AOD) data. Soil salinization and salt dust are the most prominent ecological problems in the Aral Sea. We divided the Aral Sea into 7 first-level ecological restoration subregions (North Aral Sea catchment area in the downstream of the Syr Darya River (Subregion I); artificial flood overflow area in the downstream of the Aral Sea (Subregion II); physical/chemical remediation area of the salt dust source area in the eastern part of the South Aral Sea (Subregion III); physical/chemical remediation area of severe salinization in the central part of the South Aral Sea (Subregion IV); existing water surface and potential restoration area of the South Aral Sea (Subregion V); Aral Sea vegetation natural recovery area (Subregion VI); and vegetation planting area with slight salinization in the South Aral Sea (Subregion VII)) and 14 second-level ecological restoration subregions according to the ecological zoning principles. Implementable measures are proposed for each ecological restoration subregion. For Subregion I and Subregion II with lower elevations, artificial flooding should be carried out to restore the surface of the Aral Sea. Subregion III and Subregion IV have severe salinization, making it difficult for vegetation to grow. In these subregions, it is recommended to cover and pave the areas with green biomatrix coverings and environmentally sustainable bonding materials. In Subregion V located in the central and western parts of the South Aral Sea, surface water recharge should be increased to ensure that this subregion can maintain normal water levels. In Subregion VI and Subregion VII where natural conditions are suitable for vegetation growth, measures such as afforestation and buffer zones should be implemented to protect vegetation. This study could provide a reference basis for future comprehensive ecological management and restoration of the Aral Sea.

Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations, limited access to precipitation data, and significant water scarcity. Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region, which can even improve the performance of hydrological modelling. This study evaluated the applicability of widely used five satellite-based precipitation products (Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), China Meteorological Forcing Dataset (CMFD), Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA)) and a reanalysis precipitation dataset (ECMWF Reanalysis v5-Land Dataset (ERA5-Land)) in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations. Based on this assessment, we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging (DBMA) approach, the expectation-maximization method, and the ordinary Kriging interpolation method. The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability, with an outstanding performance, as indicated by low root mean square error (RMSE=1.40 mm/d) and high Person's correlation coefficient (CC=0.67). Compared with the traditional simple model averaging (SMA) and individual product data, although the DBMA-fused precipitation data were slightly lower than the best precipitation product (CMFD), the overall performance of DBMA was more robust. The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final (IMERG-F) precipitation product, as well as hydrological simulations in the Ebinur Lake Basin, further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region. The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas, and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.

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

Leguminosae are an important part of terrestrial ecosystems and play a key role in promoting soil nutrient cycling and improving soil properties. However, plant composition and species diversity change rapidly during the process of succession, the effect of leguminosae on soil physical-chemical and biological properties is still unclear. This study investigated the changes in the composition of plant community, vegetation characteristics, soil physical-chemical properties, and soil biological properties on five former farmlands in China, which had been abandoned for 0, 5, 10, 18, and 30 a. Results showed that, with successional time, plant community developed from annual plants to perennial plants, the importance of Leguminosae and Asteraceae significantly increased and decreased, respectively, and the importance of grass increased and then decreased, having a maximum value after 5 a of abandonment. Plant diversity indices increased with successional time, and vegetation coverage and above- and below-ground biomass increased significantly with successional time after 5 a of abandonment. Compared with farmland, 30 a of abandonment significantly increased soil nutrient content, but total and available phosphorus decreased with successional time. Changes in plant community composition and vegetation characteristics not only change soil properties and improve soil physical-chemical properties, but also regulate soil biological activity, thus affecting soil nutrient cycling. Among these, Leguminosae have the greatest influence on soil properties, and their importance values and community composition are significantly correlated with soil properties. Therefore, this research provides more scientific guidance for selecting plant species to stabilize soil ecosystem of farmland to grassland in the Loess Plateau, China.

Reclamation of lands abandoned after mining in mountain areas is critical to erosion control, safety from landslides, and ecological protection of mountain ecosystems. However, little is known about alpine coal mine reclamation using the soil seed bank as a potential source for revegetation. We collected samples of persistent soil seed bank for germination experiments from nine reclaimed sites with different soil cover thicknesses and from six control sites in the Qilian Mountains of China. Soil properties of each site were determined (including soil water content, soil available potassium, soil available phosphorus, soil total nitrogen, pH, soil organic matter, soil total phosphorus, and soil total potassium, and soil alkali-hydrolyzable nitrogen), and the relationships of the characteristics of the soil seed bank with soil cover thickness and soil properties were examined. The results showed that the density, number of species, and diversity of the topsoil seed bank were significantly correlated with soil cover thickness, and all increased with the increment of soil cover thickness. Soil cover thickness controlled the soil seed bank by influencing soil properties. With the increase in soil cover thickness, soil properties (e.g., soil organic matter, soil total nitrogen, etc.) content increased while soil pH decreased. The soil seed bank had the potential to restored the pre-mining habitat at reclaimed sites with approximately 20-cm soil cover thickness. Soil properties of reclaimed sites were lower than that of natural sites. The relationship between the soil seed bank and soil cover thickness determined in this study provides a foundation for improving reclamation measures used in coal mines, as well as for the management and monitoring of reclaimed areas.

In the Anthropocene era, human activities have become increasingly complex and diversified. The natural ecosystems need higher ecological resilience to ensure regional sustainable development due to rapid urbanization and industrialization as well as other intensified human activities, especially in arid and semi-arid areas. In the study, we chose the economic belt on the northern slope of the Tianshan Mountains (EBNSTM) in Xinjiang Uygur Autonomous Region of China as a case study. By collecting geographic data and statistical data from 2010 and 2020, we constructed an ecological resilience assessment model based on the ecosystem habitat quality (EHQ), ecosystem landscape stability (ELS), and ecosystem service value (ESV). Further, we analyzed the temporal and spatial variation characteristics of ecological resilience in the EBNSTM from 2010 to 2020 by spatial autocorrelation analysis, and explored its responses to climate change and human activities using the geographically weighted regression (GWR) model. The results showed that the ecological resilience of the EBNSTM was at a low level and increased from 0.2732 to 0.2773 during 2010-2020. The spatial autocorrelation analysis of ecological resilience exhibited a spatial heterogeneity characteristic of "high in the western region and low in the eastern region", and the spatial clustering trend was enhanced during the study period. Desert, Gobi and rapidly urbanized areas showed low level of ecological resilience, and oasis and mountain areas exhibited high level of ecological resilience. Climate factors had an important impact on ecological resilience. Specifically, average annual temperature and annual precipitation were the key climate factors that improved ecological resilience, while average annual evapotranspiration was the main factor that blocked ecological resilience. Among the human activity factors, the distance from the main road showed a negative correlation with ecological resilience. Both night light index and PM2.5 concentration were negatively correlated with ecological resilience in the areas with better ecological conditions, whereas in the areas with poorer ecological conditions, the correlations were positive. The research findings could provide a scientific reference for protecting the ecological environment and promoting the harmony and stability of the human-land relationship in arid and semi-arid areas.

Microorganisms regulate the responses of terrestrial ecosystems to anthropogenic nutrient inputs. The escalation of anthropogenic activities has resulted in a rise in the primary terrestrial constraining elements, namely nitrogen (N) and phosphorus (P). Nevertheless, the specific mechanisms governing the influence of soil microbial community structure and ecological processes in ecologically vulnerable and delicate semi-arid loess agroecosystems remain inadequately understood. Therefore, we explored the effects of different N and P additions on soil microbial community structure and its associated ecological processes in the farmland of Chinese Loess Plateau based on a 36-a long-term experiment. Nine fertilization treatments with complete interactions of high, medium, and low N and P gradients were set up. Soil physical and chemical properties, along with the microbial community structure were measured in this study. Additionally, relevant ecological processes such as microbial biomass, respiration, N mineralization, and enzyme activity were quantified. To elucidate the relationships between these variables, we examined correlation-mediated processes using statistical techniques, including redundancy analysis (RDA) and structural equation modeling (SEM). The results showed that the addition of N alone had a detrimental effect on soil microbial biomass, mineralized N accumulation, and β-1,4-glucosidase activity. Conversely, the addition of P exhibited an opposing effect, leading to positive influences on these soil parameters. The interactive addition of N and P significantly changed the microbial community structure, increasing microbial activity (microbial biomass and soil respiration), but decreasing the accumulation of mineralized N. Among them, N₂₄P₁₂ treatment showed the greatest increase in the soil nutrient content and respiration. N₁₂P₁₂ treatment increased the overall enzyme activity and total phospholipid fatty acid (PLFA) content by 70.93%. N and P nutrient contents of the soil dominate the microbial community structure and the corresponding changes in hydrolytic enzymes. Soil microbial biomass, respiration, and overall enzyme activity are driven by mineralized N. Our study provides a theoretical basis for exploring energy conversion processes of soil microbial community and environmental sustainability under long-term N and P additions in semi-arid loess areas.

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

Gross primary productivity (GPP) of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought. Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks, aiding efforts to mitigate the detrimental effects of climate change. In this study, we utilized the precipitation and temperature data from the Climatic Research Unit, the standardized precipitation evapotranspiration index (SPEI), the standardized precipitation index (SPI), and the simulated vegetation GPP using the eddy covariance-light use efficiency (EC-LUE) model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018. The main findings indicated that vegetation GPP decreased in 50.53% of the plateau, mainly in its northern and northeastern parts, while it increased in the remaining 49.47% area. Specifically, meadow steppe (78.92%) and deciduous forest (79.46%) witnessed a significant decrease in vegetation GPP, while alpine steppe (75.08%), cropland (76.27%), and sandy vegetation (87.88%) recovered well. Warming aridification areas accounted for 71.39% of the affected areas, while 28.53% of the areas underwent severe aridification, mainly located in the south and central regions. Notably, the warming aridification areas of desert steppe (92.68%) and sandy vegetation (90.24%) were significant. Climate warming was found to amplify the sensitivity of coniferous forest, deciduous forest, meadow steppe, and alpine steppe GPP to drought. Additionally, the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased. The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months. The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

Land use change affects the balance of organic carbon (C) reserves and the global C cycle. Microbial residues are essential constituents of stable soil organic C (SOC). However, it remains unclear how microbial residue changes over time following afforestation. In this study, 16-, 23-, 52-, and 62-year-old Mongolian pine stands and 16-year-old cropland were studied in the Horqin Sandy Land, China. We analyzed changes in SOC, amino sugar content, and microbial parameters to assess how microbial communities influence soil C transformation and preservation. The results showed that SOC storage increased with stand age in the early stage of afforestation but remained unchanged at about 1.27−1.29 kg/m² after 52 a. Moreover, there were consistent increases in amino sugars and microbial residues with increasing stand age. As stand age increased from 16 to 62 a, soil pH decreased from 6.84 to 5.71, and the concentration of total amino sugars increased from 178.53 to 509.99 mg/kg. A significant negative correlation between soil pH and the concentration of specific and total amino sugars was observed, indicating that the effects of soil acidification promote amino sugar stabilization during afforestation. In contrast to the Mongolian pine plantation of the same age, the cropland accumulated more SOC and microbial residues because of fertilizer application. Across Mongolian pine plantation with different ages, there was no significant change in calculated contribution of bacterial or fungal residues to SOC, suggesting that fungi were consistently the dominant contributors to SOC with increasing time. Our results indicate that afforestation in the Horqin Sandy Land promotes efficient microbial growth and residue accumulation in SOC stocks and has a consistent positive impact on SOC persistence.

To comprehensively evaluate the alterations in water ecosystem service functions within arid watersheds, this study focused on the Bosten Lake Basin, which is situated in the arid region of Northwest China. The research was based on land use/land cover (LULC), natural, socioeconomic, and accessibility data, utilizing the Patch-level Land Use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to dynamically assess LULC change and associated variations in water yield and water conservation. The analyses included the evaluation of contribution indices of various land use types and the investigation of driving factors that influence water yield and water conservation. The results showed that the change of LULC in the Bosten Lake Basin from 2000 to 2020 showed a trend of increasing in cultivated land and construction land, and decreasing in grassland, forest, and unused land. The unused land of all the three predicted scenarios of 2030 (S1, a natural development scenario; S2, an ecological protection scenario; and S3, a cultivated land protection scenario) showed a decreasing trend. The scenarios S1 and S3 showed a trend of decreasing in grassland and increasing in cultivated land; while the scenario S2 showed a trend of decreasing in cultivated land and increasing in grassland. The water yield of the Bosten Lake Basin exhibited an initial decline followed by a slight increase from 2000 to 2020. The areas with higher water yield values were primarily located in the northern section of the basin, which is characterized by higher altitude. Water conservation demonstrated a pattern of initial decrease followed by stabilization, with the northeastern region demonstrating higher water conservation values. In the projected LULC scenarios of 2030, the estimated water yield under scenarios S1 and S3 was marginally greater than that under scenario S2; while the level of water conservation across all three scenarios remained rather consistent. The results showed that Hejing County is an important water conservation function zone, and the eastern part of the Xiaoyouledusi Basin is particularly important and should be protected. The findings of this study offer a scientific foundation for advancing sustainable development in arid watersheds and facilitating efficient water resource management.

Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation, i.e., the moisture recycling ratio, but various isotope-based models usually lead to different results, which affects the accuracy of local moisture recycling. In this study, a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio. Among the three vapor sources including advection, transpiration, and surface evaporation, the advection vapor usually played a dominant role, and the contribution of surface evaporation was less than that of transpiration. When the abnormal values were ignored, the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9% for transpiration, 0.2% for surface evaporation, and -1.1% for advection, respectively, and the medians were 0.5%, 0.2%, and -0.8%, respectively. The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied, and the contribution of advection was relatively larger. The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios. Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input, and it was important to accurately estimate the isotopes in precipitation vapor. Generally, the Bayesian mixing model should be recommended instead of a linear model. The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.

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

Droughts and soil erosion are among the most prominent climatic driven hazards in drylands, leading to detrimental environmental impacts, such as degraded lands, deteriorated ecosystem services and biodiversity, and increased greenhouse gas emissions. In response to the current lack of studies combining drought conditions and soil erosion processes, in this study, we developed a comprehensive Geographic Information System (GIS)-based approach to assess soil erosion and droughts, thereby revealing the relationship between soil erosion and droughts under an arid climate. The vegetation condition index (VCI) and temperature condition index (TCI) derived respectively from the enhanced vegetation index (EVI) MOD13A2 and land surface temperature (LST) MOD11A2 products were combined to generate the vegetation health index (VHI). The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed, southeastern Tunisia. The revised universal soil loss equation (RUSLE) model was applied to quantitatively estimate soil erosion. The relationship between soil erosion and droughts was investigated through Pearson correlation. Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000-2016. The average soil erosion rate was determined to be 1.8 t/(hm²·a). The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts. The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion. The relationship between droughts and soil erosion had a positive correlation (r=0.3); however, the correlation was highly varied spatially across the watershed. Drought was linked to soil erosion in the Negueb watershed. The current study provides insight for natural disaster risk assessment, land managers, and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.

Land use and cover change (LUCC) is important for the provision of ecosystem services. An increasing number of recent studies link LUCC processes to ecosystem services and human well-being at different scales recently. However, the dynamic of land use and its drivers receive insufficient attention within ecological function areas, particularly in quantifying the dynamic roles of climate change and human activities on land use based on a long time series. This study utilizes geospatial analysis and geographical detectors to examine the temporal dynamics of land use patterns and their underlying drivers in the Hedong Region of the Gansu Province from 1990 to 2020. Results indicated that grassland, cropland, and forestland collectively accounted for approximately 99% of the total land area. Cropland initially increased and then decreased after 2000, while grassland decreased with fluctuations. In contrast, forestland and construction land were continuously expanded, with net growth areas of 6235.2 and 455.9 km², respectively. From 1990 to 2020, cropland was converted to grassland, and both of them were converted to forestland as a whole. The expansion of construction land primarily originated from cropland. From 2000 to 2005, land use experienced intensified temporal dynamics and a shift of relatively active zones from the central to the southeastern region. Grain yield, economic factors, and precipitation were the major factors accounting for most land use changes. Climatic impacts on land use changes were stronger before 1995, succeeded by the impact of animal husbandry during 1995-2000, followed by the impacts of grain production and gross domestic product (GDP) after 2000. Moreover, agricultural and pastoral activities, coupled with climate change, exhibited stronger enhancement effects after 2000 through their interaction with population and economic factors. These patterns closely correlated with ecological restoration projects in China since 1999. This study implies the importance of synergy between human activity and climate change for optimizing land use via ecological patterns in the ecological function area.

Groundwater quality assessment is important to assure safe and durable water use. In semi-arid areas of Algeria, groundwater represents the main water resource for drinking water supply of the rural population as well as for irrigation of agricultural lands. Groundwater samples from wells and springs were collected from the Gargaat Tarf and Annk Djemel sub-watersheds of the Oum El Bouaghi, Algeria, and were analyzed and compared with the World Health Organization (WHO) standards. Results showed that most of the measured physical and chemical parameters exceeded the quality limits according to the WHO standards. Groundwater had a slightly alkaline water pH (7.00-7.79), electrical conductivity>1500 µS/cm, chloride>500 mg/L, calcium>250 mg/L, and magnesium>155 mg/L. Water quality index (WQI) results showed that 68% of the area had excellent water quality, 24% of the samples fell into good category, and only 8% were of poor quality and unsuitable for human consumption. Six wells in the area showed bacterial contamination. Total coliforms (453.9 (±180.3) CFU (colony-forming units)/100 mL), fecal coliforms (243.2 (±99.2) CFU/100 mL), and fecal streptococci (77.9 (±32.0) CFU/100 mL) loads were above the standard limits set by the WHO. These results confirmed that water resources in the study area were strongly influenced by anthropogenic activities and were not recommended for consumption as drinking water.

Analysing runoff changes and how these are affected by climate change and human activities is deemed crucial to elucidate the ecological and hydrological response mechanisms of rivers. The Indicators of Hydrologic Alteration and the Range of Variability Approach (IHA-RVA) method, as well as the ecological indicator method, were employed to quantitatively assess the degree of hydrologic change and ecological response processes in the Yellow River Basin from 1960 to 2020. Using Budyko's water heat coupling balance theory, the relative contributions of various driving factors (such as precipitation, potential evapotranspiration, and underlying surface) to runoff changes in the Yellow River Basin were quantitatively evaluated. The results show that the annual average runoff and precipitation in the Yellow River Basin had a downwards trend, whereas the potential evapotranspiration exhibited an upwards trend from 1960 to 2020. In approximately 1985, it was reported that the hydrological regime of the main stream underwent an abrupt change. The degree of hydrological change was observed to gradually increase from upstream to downstream, with a range of 34.00%-54.00%, all of which are moderate changes. However, significant differences have been noted among different ecological indicators, with a fluctuation index of 90.00% at the outlet of downstream hydrological stations, reaching a high level of change. After the mutation, the biodiversity index of flow in the middle and lower reaches of the Yellow River was generally lower than that in the base period. The research results also indicate that the driving factor for runoff changes in the upper reach of the Yellow River Basin is mainly precipitation, with a contribution rate of 39.31%-54.70%. Moreover, the driving factor for runoff changes in the middle and lower reaches is mainly human activities, having a contribution rate of 63.70%-84.37%. These results can serve as a basis to strengthen the protection and restoration efforts in the Yellow River Basin and further promote the rational development and use of water resources in the Yellow River.