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.

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.

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.

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.

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

The 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.

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.

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.

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.

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.

Mining activity affects the vegetation and soils of the ecosystems. However, the effects of mining activity on saxicolous lichen communities are less concerned. Thus, the aim of this study was to characterize saxicolous lichen communities in three basins (Vis-Vis River basin, Poteros River basin, and Capillitas River basin) surrounding metalliferous mining projects of different types of operation and at different stages of exploitation. A large-scale mine (Bajo de la Alumbrera) with more than 25 a of open-pit mining located in the Vis-Vis River basin (CRV). A pre-exploitation mine (Agua Rica) located in the Poteros River basin (CRP), and a small-scale mine (Minas Capillitas) with more than 160 a of underground mining located in the Capillitas River basin (CAC). In each basin, species richness, cover, and frequency of lichen communities were measured on 40 rock outcrops. Also, explanatory variables were recorded, i.e., altitude, slope, aspect, vegetation cover, rock, and soil cover around the rocky area sampled. Richness and total cover of lichen communities were analysed using linear models, and species composition was explored using multivariate ordination analysis. Results showed that a total of 118 lichen species were identified. The species richness differed among basins and the lichen composition present in areas close to mining sites responded mainly to basins, altitude, and microsite variables. The lichen cover showed no difference among basins, but it changed under different rock and vegetation cover. It was not possible to quantify the effects of mining activity on species richness and composition. However, the low richness values found in the downstream of Minera Alumbrera could be associated with the negative impact of open-pit mining. Moreover, the effects of large-scale mining activity on lichen communities needs more investigation.

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 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.

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

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.

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.

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.

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

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

Infiltration is an important part of the hydrological cycle, and it is one of the main abstractions accounted for in the rainfall-runoff modeling. The main purpose of this study is to compare the infiltration models that were used to assess the infiltration rate of the Mitidja Plain in Algeria. Field infiltration tests were conducted at 40 different sites using a double ring infiltrometer. Five statistical comparison criteria including root mean squared error (RMSE), normalized root mean squared error (NRMSE), coefficient of correlation (CC), Nash-Sutcliffe efficiency (NSE), and Kling-Gupta efficiency (KGE) were used to determine the best performing infiltration model and to confirm anomalies between predicted and observed values. Then we evaluated performance of five models (i.e., the Philip model, Kostiakov model, Modified Kostiakov model, Novel model, and Horton model) in simulating the infiltration process based on the adjusted performance parameters cited above. Results indicated that the Novel model had the best simulated water infiltration process in the Mitidja Plain in Algeria. However, the Philip model was the weakest to simulate the infiltration process. The conclusion of this study can be useful for estimating infiltration rate at various sites using a Novel model when measured infiltration data are not available and are useful for planning and managing water resources in the study area.

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 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.

Methane (CH₄) is a potent greenhouse gas that has a substantial impact on global warming due to its substantial influence on the greenhouse effect. Increasing extreme precipitation events, such as drought, attributable to global warming that caused by greenhouse gases, exert a profound impact on the intricate biological processes associated with CH₄ uptake. Notably, the timing of extreme drought occurrence emerges as a pivotal factor influencing CH₄ uptake, even when the degree of drought remains constant. However, it is still unclear how the growing season regulates the response of CH₄ uptake to extreme drought. In an effort to bridge this knowledge gap, we conducted a field manipulative experiment to evaluate the impact of extreme drought on CH₄ uptake during early, middle, and late growing stages in a temperate steppe of Inner Mongolia Autonomous Region, China. The result showed that all extreme drought consistently exerted positive effects on CH₄ uptake regardless of seasonal timing. However, the magnitude of this effect varied depending on the timing of season, as evidenced by a stronger effect in early growing stage than in middle and late growing stages. Besides, the pathways of CH₄ uptake were different from seasonal timing. Extreme drought affected soil physical-chemical properties and aboveground biomass (AGB), consequently leading to changes in CH₄ uptake. The structural equation model showed that drought both in the early and middle growing stages enhanced CH₄ uptake due to reduced soil water content (SWC), leading to a decrease in NO₃^--N and an increase in pmoA abundance. However, drought in late growing stage primarily enhanced CH₄ uptake only by decreasing SWC. Our results suggested that seasonal timing significantly contributed to regulate the impacts of extreme drought pathways and magnitudes on CH₄ uptake. The findings can provide substantial implications for understanding how extreme droughts affect CH₄ uptake and improve the prediction of potential ecological consequence under future climate change.

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.

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.

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.

Globally, groundwater contamination by nitrate is one of the most widespread environmental problems, particularly in arid and semiarid areas, which are characterized by low amounts of rainfall and groundwater recharge. The stable isotope composition of groundwater (δ²H-H₂O and δ¹⁸O-H₂O) and dissolved nitrate (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) and factor analysis (FA) were applied to explore groundwater provenance, pollution, and chemistry evolution in the northwestern part of the Amman-Al Zarqa Basin, Jordan. In this study, we collected 23 samples from the Lower Ajloun aquifer in 2021, including 1 sample from a groundwater well and 22 samples from springs. These samples were tested for electrical conductivity, total dissolved solids, pH, temperature, dissolved oxygen, the concentration of major ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃^-, Cl^-, SO₄^2-, and NO₃^-), and the stable isotope composition of groundwater and dissolved nitrate. The results revealed that groundwater in the study area is mainly Ca-Mg-HCO₃ type and can be classified as fresh water, hard water, and very hard water. The range and average concentration of NO₃^- were 3.5-230.8 and 50.9 mg/L, respectively. Approximately 33% of the sampling points showed NO₃^- levels above the maximum allowable concentration of 50.0 mg/L set by the World Health Organization (WHO) guidelines for drinking water quality. The values of δ¹⁸O-H₂O and δ²H-H₂O showed that groundwater in the study area is part of the current water cycle, originating in the Mediterranean Sea, with significant evaporation, orographic, and amount effects. The values of the stable isotope composition of NO₃^- corresponded to δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- values produced by the nitrification process of manure or septic waste and soil NH₄⁺. The FA performed on the hydrochemical parameters and isotope data resulted in three main factors, with Factor 1, Factor 2, and Factor 3, accounting for 50%, 21%, and 11% of the total variance, respectively. Factor 1 was considered human-induced factor, named "pollution factor", whereas Factor 2, named "conservative fingerprint factor", and Factor 3, named "hardness factor", were considered natural factors. This study will help local researchers manage groundwater sustainably in the study area and other similar arid and semiarid areas in the world.

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.

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.

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.

Livestock grazing is the most extensive land use in global drylands and one of the most extensive stressors of biological soil crusts (biocrusts). Despite widespread concern about the importance of biocrusts for global carbon (C) cycling, little is known about whether and how long-term grazing alters soil organic carbon (SOC) stability and stock in the biocrust layer. To assess the responses of SOC stability and stock in the biocrust layer to grazing, from June to September 2020, we carried out a large scale field survey in the restored grasslands under long-term grazing with different grazing intensities (represented by the number of goat dung per square meter) and in the grasslands strictly excluded from grazing in four regions (Dingbian County, Shenmu City, Guyuan City and Ansai District) along precipitation gradient in the hilly Loess Plateau, China. In total, 51 representative grassland sites were identified as the study sampling sites in this study, including 11 sites in Guyuan City, 16 sites in Dingbian County, 15 sites in Shenmu City and 9 sites in Ansai District. Combined with extensive laboratory analysis and statistical analysis, at each sampling site, we obtained data on biocrust attributes (cover, community structure, biomass and thickness), soil physical-chemical properties (soil porosity and soil carbon-to-nitrogen ratio (C/N ratio)), and environmental factors (mean annual precipitation, mean annual temperature, altitude, plant cover, litter cover, soil particle-size distribution (the ratio of soil clay and silt content to sand content)), SOC stability index (SI) and SOC stock (SOCS) in the biocrust layer, to conduct this study. Our results revealed that grazing did not change total biocrust cover but markedly altered biocrust community structure by reducing plant cover, with a considerable increase in the relative cover of cyanobacteria (23.1%) while a decrease in the relative cover of mosses (42.2%). Soil porosity and soil C/N ratio in the biocrust layer under grazing decreased significantly by 4.1%-7.2% and 7.2%-13.3%, respectively, compared with those under grazing exclusion. The shifted biocrust community structure ultimately resulted in an average reduction of 15.5% in SOCS in the biocrust layer under grazing. However, compared with higher grazing (intensity of more than 10.00 goat dung/m²), light grazing (intensity of 0.00-10.00 goat dung/m² or approximately 1.20-2.60 goat/(hm²·a)) had no adverse effect on SOCS. SOC stability in the biocrust layer remained unchanged under long-term grazing due to the offset between the positive effect of the decreased soil porosity and the negative effect of the decreased soil C/N ratio on the SOC resistance to decomposition. Mean annual precipitation and soil particle-size distribution also regulated SOC stability indirectly by influencing soil porosity through plant cover and biocrust community structure. These findings suggest that proper grazing might not increase the CO₂ release potential or adversely affect SOCS in the biocrust layer. This research provides some guidance for proper grazing management in the sustainable utilization of grassland resources and C sequestration in biocrusts in the hilly regions of drylands.

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.

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.

Root pullout performance of plants is an important mechanical basis for soil reinforcement by plant roots in the semi-arid areas. Studies have shown that it is affected by plant factors (species, ages, root geometry, etc.) and soil factors (soil types, soil moisture, soil bulk densities, etc.). However, the effects of loading rates on root pullout performance are not well studied. To explore the mechanical interactions under different loading rates, we conducted pullout tests on Medicago sativa L. and Hippophae rhamnoides L. roots under five loading rates, i.e., 5, 50, 100, 150, and 200 mm/min. In addition, tensile tests were conducted on the roots in diameters of 0.5-2.0 mm to compare the relationship between root tensile properties and root pullout properties. Results showed that two root failure modes, slippage and breakage, were observed during root pullout tests. All M. sativa roots were pulled out, while 72.2% of H. rhamnoides roots were broken. The maximum fracture diameter and fracture root length of H. rhamnoides were 1.22 mm and 7.44 cm under 100 mm/min loading rate, respectively. Root displacement values were 4.63% (±0.43%) and 8.91% (±0.52%) of the total root length for M. sativa and H. rhamnoides, respectively. The values of maximum pullout force were 14.6 (±0.7) and 17.7 (±1.8) N under 100 mm/min for M. sativa and H. rhamnoides, respectively. Values of the maximum pullout strength for M. sativa and H. rhamnoides were 38.38 (±5.48) MPa under 150 mm/min and 12.47 (±1.43) MPa under 100 mm/min, respectively. Root-soil friction coefficient under 100 mm/min was significantly larger than those under other loading rates for both the two species. Values of the maximum root pullout energy for M. sativa and H. rhamnoides were 87.83 (±21.55) mm·N under 100 mm/min and 173.53 (±38.53) mm·N under 200 mm/min, respectively. Root pullout force was significantly related to root diameter (P<0.01). Peak root pullout force was significantly affected by loading rates when the effect of root diameter was included (P<0.01), and vice versa. Except for the failure mode and peak pullout force, other pullout parameters, including root pullout strength, root displacement, root-soil friction coefficient, and root pullout energy were not significantly affected by loading rates (P>0.05). Root pullout strength was greater than root tensile strength for the two species. The results suggested that there was no need to deliberately control loading rate in root pullout tests in the semi-arid soil, and root pullout force and pullout strength could be better parameters for root reinforcement model compared with root tensile strength as root pullout force and pullout strength could more realistically reflect the working state of roots in the semi-arid soil.

Wolfberry (Lycium barbarum L.) is important for health care and ecological protection. However, it faces problems of low productivity and resource utilization during planting. Exploring reasonable models for water and nitrogen management is important for solving these problems. Based on field trials in 2021 and 2022, this study analyzed the effects of controlling soil water and nitrogen application levels on wolfberry height, stem diameter, crown width, yield, and water (WUE) and nitrogen use efficiency (NUE). The upper and lower limits of soil water were controlled by the percentage of soil water content to field water capacity (θ_f), and four water levels, i.e., adequate irrigation (W0, 75%-85% θ_f), mild water deficit (W1, 65%-75% θ_f), moderate water deficit (W2, 55%-65% θ_f), and severe water deficit (W3, 45%-55% θ_f) were used, and three nitrogen application levels, i.e., no nitrogen (N0, 0 kg/hm²), low nitrogen (N1, 150 kg/hm²), medium nitrogen (N2, 300 kg/hm²), and high nitrogen (N3, 450 kg/hm²) were implied. The results showed that irrigation and nitrogen application significantly affected plant height, stem diameter, and crown width of wolfberry at different growth stages (P<0.01), and their maximum values were observed in W1N2, W0N2, and W1N3 treatments. Dry weight per plant and yield of wolfberry first increased and then decreased with increasing nitrogen application under the same water treatment. Dry weight per hundred grains and dry weight percentage increased with increasing nitrogen application under W0 treatment. However, under other water treatments, the values first increased and then decreased with increasing nitrogen application. Yield and its component of wolfberry first increased and then decreased as water deficit increased under the same nitrogen treatment. Irrigation water use efficiency (IWUE, 8.46 kg/(hm²·mm)), WUE (6.83 kg/(hm²·mm)), partial factor productivity of nitrogen (PFPN, 2.56 kg/kg), and NUE (14.29 kg/kg) reached their highest values in W2N2, W1N2, W1N2, and W1N1 treatments. Results of principal component analysis (PCA) showed that yield, WUE, and NUE were better in W1N2 treatment, making it a suitable water and nitrogen management mode for the irrigation area of the Yellow River in the Gansu Province, China and similar planting areas.

Changes in precipitation and nitrogen (N) addition may significantly affect the processes of soil carbon (C) cycle in terrestrial ecosystems, such as soil respiration. However, relatively few studies have investigated the effects of changes in precipitation and N addition on soil respiration in the upper soil layer in desert steppes. In this study, we conducted a control experiment that involved a field simulation from July 2020 to December 2021 in a desert steppe in Yanchi County, China. Specifically, we measured soil parameters including soil temperature, soil moisture, total nitrogen (TN), soil organic carbon (SOC), soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), and contents of soil microorganisms including bacteria, fungi, actinomyces, and protozoa, and determined the components of soil respiration including soil respiration with litter (R_S+L), soil respiration without litter (R_S), and litter respiration (R_L) under short-term changes in precipitation (control, increased precipitation by 30%, and decreased precipitation by 30%) and N addition (0.0 and 10.0 g/(m²·a)) treatments. Our results indicated that short-term changes in precipitation and N addition had substantial positive effects on the contents of TN, SOC, and SMBC, as well as the contents of soil actinomyces and protozoa. In addition, N addition significantly enhanced the rates of R_S+L and R_S by 4.8% and 8.0% (P<0.05), respectively. The increase in precipitation markedly increased the rates of R_S+L and R_S by 2.3% (P<0.05) and 5.7% (P<0.001), respectively. The decrease in precipitation significantly increased the rates of R_S+L and R_S by 12.9% (P<0.05) and 23.4% (P<0.001), respectively. In contrast, short-term changes in precipitation and N addition had no significant effects on R_L rate (P>0.05). The mean R_L/R_S+L value observed under all treatments was 27.63%, which suggested that R_L is an important component of soil respiration in the desert steppe ecosystems. The results also showed that short-term changes in precipitation and N addition had significant interactive effects on the rates of R_S+L, R_S, and R_L (P<0.001). In addition, soil temperature was the most important abiotic factor that affected the rates of R_S+L, R_S, and R_L. Results of the correlation analysis demonstrated that the rates of R_S+L, R_S, and R_L were closely related to soil temperature, soil moisture, TN, SOC, and the contents of soil microorganisms, and the structural equation model revealed that SOC and SMBC are the key factors influencing the rates of R_S+L, R_S, and R_L. This study provides further insights into the characteristics of soil C emissions in desert steppe ecosystems in the context of climate change, which can be used as a reference for future related studies.