The southern margin of the Gurbantunggut Desert, China, is characterized by alternating layers of aeolian and alluvial deposits. Investigating the characteristics of arenaceous sediment in this area is of significant importance for understanding the interactive processes of wind and water forces, as well as the provenance of sediment. However, there are relatively few investigations on the characteristics of such sediment at present. In this study, we researched three aeolian-alluvial interactive stratigraphic profiles and different types of surface sediment on the desert-oasis transitional zone of southern margin of the Gurbantunggut Desert. Based on the optically stimulated luminescence (OSL) dating of aeolian sand and analyses of quartz sand grain size and surface micro-texture, we explored the aeolian-alluvial environmental change at southern margin of the desert in Holocene, as well as the provenance of sediment. The results indicated that the grain size characteristics of different types of sediment in the stratigraphic profiles were similar to those of modern dune sand, interdune sand, muddy desert surface soil, and riverbed sand. Their frequency curves were unimodal or bimodal, and cumulative probability curves were two-segment or three-segment, mainly composed of suspension load and saltation load. The quartz sand in the sediment at southern margin of the desert had undergone alternating transformation of various exogenic forces, with short transportation distance and time, and sedimentary environment was relatively humid. In Holocene, southern margin of the desert primarily featured braided river deposits, and during intermittent period of river activity, there were also aeolian deposits such as sand sheet deposits, stabilized dune deposits, and mobile dune deposits. The provenance for Holocene alluvial deposits at southern margin of the desert remains relatively constant, with the debris of the Tianshan Mountains being the primary provenance. Aeolian sand is mainly near-source recharge, which is formed by in situ deposition of fluvial or lacustrine materials in southern margin of the desert transported by wind erosion, and its provenance was still the weathered debris of the Tianshan Mountains. In addition, the sand in interior of the desert may be transported by northwest wind in desert-scale, thus affecting the development of dunes in southern margin of the desert. The results of this study provide a reference for understanding the composition and provenance changes of desert sand in the context of global climate change.

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 desert-oasis transition zone (DOTZ) serves as a buffer area between the desert and oasis. Understanding its wind field characteristics is of great significance for the prevention and control of aeolian disasters in the oasis. In this study, we used meteorological data during 2013-2019 from the portable meteorological stations at five sites (site A on the edge of the oasis, sites B, C, and D in the DOTZ, and site O in the desert) in Dunhuang, China to analyze the near-surface wind field characteristics and their causes, as well as to reveal the key role of the DOTZ in oasis protection. The results showed that the mean wind speed, frequency of sand-driving wind, and directional variability of wind decreased from west to east within the DOTZ, and wind speed was significantly affected by air temperature. The terrain influenced the prevailing winds in the region, mainly from northeast and southwest. Only some areas adjacent to the oasis were controlled by southeasterly wind. This indicated that the near-surface wind field characteristics of the DOTZ were caused by the combined effects of local terrain and surface hydrothermal difference. At site D, the annual drift potential (DP) was 24.95 vector units (VU), indicating a low wind energy environment, and the resultant drift direction (RDD) showed obvious seasonal differences. Additionally, the DOTZ played an important buffering role between the desert and oasis. Compared with the desert, the mean wind speed in the oasis decreased by 64.98%, and the prevailing wind direction was more concentrated. The results of this study will be useful in interpreting the aeolian activity of the DOTZ in Dunhuang.

In the Loess Plateau of China, land-use pattern is a major factor in controlling underlying biological processes. Additionally, the process of land-use pattern was accompanied by abandoned lands, potentially impacting soil microbe. However, limited researches were conducted to study the impacts of land-use patterns on the diversity and community of soil microorganisms in this area. The study aimed to investigate soil microbial community diversity and composition using high-throughput deoxyribonucleic acid (DNA) sequencing under different land-use patterns (apricot tree land, apple tree land, peach tree land, corn land, and abandoned land). The results showed a substantial difference (P<0.050) in bacterial alpha-diversity and beta-diversity between abandoned land and other land-use patterns, with the exception of Shannon index. While fungal beta-diversity was not considerably impacted by land-use patterns, fungal alpha-diversity indices varied significantly. The relative abundance of Actinobacteriota (34.90%), Proteobacteria (20.65%), and Ascomycota (77.42%) varied in soils with different land-use patterns. Soil pH exerted a dominant impact on the soil bacterial communities' composition, whereas soil available phosphorus was the main factor shaping the soil fungal communities' composition. These findings suggest that variations in land-use pattern had resulted in changes to soil properties, subsequently impacting diversity and structure of microbial community in the Loess Plateau. Given the strong interdependence between soil and its microbiota, it is imperative to reclaim abandoned lands to maintain soil fertility and sustain its function, which will have significant ecological service implications, particularly with regards to soil conservation in ecologically vulnerable areas.

It is of great significance to study the effects of desert plants on soil enzyme activities and soil organic carbon (SOC) for maintaining the stability of the desert ecosystem. In this study, we studied the responses of soil enzyme activities and SOC fractions (particulate organic carbon (POC) and mineral-associated organic carbon (MAOC)) to five typical desert plant communities (Convolvulus tragacanthoides, Ephedra rhytidosperma, Stipa breviflora, Stipa tianschanica var. gobica, and Salsola laricifolia communities) in the proluvial fan in the eastern foothills of the Helan Mountain in Ningxia Hui Autonomous Region, China. We recorded the plant community information mainly including the plant coverage and herb and shrub species, and obtained the aboveground biomass and plant species diversity through sample surveys in late July 2023. Soil samples were also collected at depths of 0-10 cm (topsoil) and 10-20 cm (subsoil) to determine the soil physicochemical properties and enzyme activities. The results showed that the plant coverage and aboveground biomass of S. laricifolia community were significantly higher than those of C. tragacanthoides, S. breviflora, and S. tianschanica var. gobica communities (P<0.05). Soil enzyme activities varied among different plant communities. In the topsoil, the enzyme activities of alkaline phosphatase (ALP) and β-1,4-glucosidas (βG) were significantly higher in E. rhytidosperma and S. tianschanica var. gobica communities than in other plant communities (P<0.05). The topsoil had higher POC and MAOC contents than the subsoil. Specifically, the content of POC in the topsoil was 18.17%-42.73% higher than that in the subsoil. The structural equation model (SEM) indicated that plant species diversity, soil pH, and soil water content (SWC) were the main factors influencing POC and MAOC. The soil pH inhibited the formation of POC and promoted the formation of MAOC. Conversely, SWC stimulated POC production and hindered MAOC formation. Our study aimed to gain insight into the effects of desert plant communities on soil enzyme activities and SOC fractions, as well as the drivers of SOC fractions in the proluvial fan in the eastern foothills of the Helan Mountain and other desert ecosystems.

Improving cultivated land use eco-efficiency (CLUE) can effectively promote agricultural sustainability, particularly in developing countries where CLUE is generally low. This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model. In addition, given the undesirable outputs of agricultural production, we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure (GB-US-SBM) model, which combines global benchmark technology, undesirable output, super efficiency, and slacks-based measure. The results indicated that there was an upward trend in CLUE in China from 2000 to 2020, with an increase rate of 2.62%. The temporal evolution of CLUE in China could be classified into three distinct stages: a period of fluctuating decrease (2000-2007), a phase of gradual increase (2008-2014), and a period of rapid growth (2015-2020). The major grain-producing areas (MPAs) had a lower CLUE than their counterparts, namely, non-major grain-production areas (non-MPAs). The spatial agglomeration effect followed a northeast-southwest strip distribution; and the movement path of barycentre revealed a "P" shape, with Luoyang City, Henan Province, as the centre. In terms of influencing factors of CLUE, investment in science and technology played the most vital role in improving CLUE, while irrigation index had the most negative effect. It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs. Therefore, relevant departments should formulate policies to enhance the level of science and technology, improve irrigation condition, and promote sustainable utilization of cultivated land.

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 unique geomorphological features and farming methods in the Mollisol region of Northeast China increase water catchment flow and aggravate the erosion of ephemeral gully (EG). Vegetation suffers from rain erosion and damage during the growth stage, which brings serious problems to the restoration of grass in the early stage. Therefore, effects of coir geotextile and geocell on EG erosion under four confluence intensities were researched in this study. Results of the simulated water discharge erosion test showed that when the confluence strength was less than 30 L/min, geocell and coir geotextile had a good effect on controlling EG erosion, and sediment yield of geocell and coir geotextile was reduced by 25.95%-37.82% and 73.73%-88.96%, respectively. However, when confluence intensity increased to 40 L/min, protective effect of coir geotextile decreased, and sediment yield rate increased sharply by 189.03%. When confluence intensity increased to 50 L/min, the protective effect of coir geotextile was lost. On the other hand, geocell showed that the greater the flow rate, the better the protective effect. In addition, with the increase in confluence intensity, erosion pattern of coir geotextile developed from sheet erosion to intermittent fall and then to completion of main rill, and the protective effect was gradually weakened. In contrast, the protective effect of EG under geocell was gradually enhanced from the continuous rill to the intermittent rill and finally to the intermittent fall. This study shows that coir geotextile and geocell can prevent EG erosion, and the effect of geocell is better than that of coir geotextile on the surface of EG.

The development of bare patches typically signifies a process of ecosystem degradation. Within the protection system of Shapotou section of the Baotou-Lanzhou railway, the extensive emergence of bare sand patches poses a threat to both stability and sustainability. However, there is limited knowledge regarding the morphology, dynamic changes, and ecological responses associated with these sand patches. Therefore, we analyzed the formation and development process of sand patches within the protection system and its effects on herbaceous vegetation growth and soil nutrients through field observation, survey, and indoor analysis methods. The results showed that sand patch development can be divided into three stages, i.e., formation, expansion, and stabilization, which correspond to the initial, actively developing, and semi-fixed sand patches, respectively. The average dimensions of all sand patch erosional areas were found to be 7.72 m in length, 3.91 m in width, and 0.32 m in depth. The actively developing sand patches were the largest, and the initial sand patches were the smallest. Throughout the stage of formation and expansion, the herbaceous community composition changed, and the plant density decreased by more than 50.95%. Moreover, the coverage and height of herbaceous plants decreased in the erosional area and slightly increased in the depositional lobe; and the fine particles and nutrients of soils in the erosional area and depositional lobe showed a decreasing trend. In the stabilization phases of sand patches, the area from the inlet to the bottom of sand patches becomes initially covered with crusts. Vegetation and 0-2 cm surface soil condition improved in the erosional area, but this improvement was not yet evident in the depositional lobe. Factors such as disturbance, climate change, and surface resistance to erosion exert notable influences on the formation and dynamics of sand patches. The results can provide evidence for the future treatment of sand patches and the management of the protection system of Shapotou section of the Baotou-Lanzhou railway.

Human activities lead to the accumulation of a large amount of nitrogen and phosphorus in sediments in rivers. Simultaneously, nitrogen and phosphorus can be affected by environment and re-enter the upper water body, causing secondary pollution of the river water. In this study, laboratory simulation experiments were conducted initially to investigate the release of nitrogen and phosphorus from river sediments in Urumqi City and the surrounding areas in Xinjiang Uygur Autonomous Region of China and determine the factors that influence their release. The results of this study showed significant short-term differences in nitrogen and phosphorus release characteristics from sediments at different sampling points. The proposed secondary kinetics model (i.e., pseudo-second-order kinetics model) better fitted the release process of sediment nitrogen and phosphorus. The release of nitrogen and phosphorus from sediments is a complex process driven by multiple factors, therefore, we tested the influence of three factors (pH, temperature, and disturbance intensity) on the release of nitrogen and phosphorus from sediments in this study. The most amount of nitrate nitrogen (NO₃^--N) was released under neutral conditions, while the most significant release of ammonia nitrogen (NH₄⁺-N) occurred under acidic and alkaline conditions. The release of nitrite nitrogen (NO₂^--N) was less affected by pH. The dissolved total phosphorus (DTP) released significantly in the alkaline water environment, while the release of dissolved organic phosphorus (DOP) was more significant in acidic water. The release amount of soluble reactive phosphorus (SRP) increased with an increase in pH. The sediments released nitrogen and phosphorus at higher temperatures, particularly NH₄⁺-N, NO₃^--N, and SRP. The highest amount of DOP was released at 15.0°C. An increase in disturbance intensity exacerbated the release of nitrogen and phosphorus from sediments. NH₄⁺-N, DTP, and SRP levels increased linearly with the intensity of disturbance, while NO₃^--N and NO₂^--N were more stable. This study provides valuable information for protecting and restoring the water environment in arid areas and has significant practical reference value.

Climate warming profoundly affects hydrological changes, agricultural production, and human society. Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting. The Chinese Tianshan Mountains (CTM) have a high climate sensitivity, rendering the region particularly vulnerable to the effects of climate warming. In this study, we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset (1961-2014) and 24 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale. Based on this, we conducted a systematic review of the interannual trends, dry-wet transitions (based on the standardized precipitation index (SPI)), and spatial distribution patterns of climate change in the CTM during 1961-2014. We further projected future temperature and precipitation changes over three terms (near-term (2021-2040), mid-term (2041-2060), and long-term (2081-2100)) relative to the historical period (1961-2014) under four shared socio-economic pathway (SSP) scenarios (i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). It was found that the CTM had experienced significant warming and wetting from 1961 to 2014, and will also experience warming in the future (2021-2100). Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble (MME) from the CMIP6 GCMs. The MME simulation results indicated an apparent wetting in 2008, which occurred later than the wetting observed from the CN05.1 in 1989. The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM. Warming and wetting are more rapid in the northern part of the CTM. By the end of the 21^st century, all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions. However, the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future, so the nature of the drought in the CTM will not change at all. Additionally, the projected summer precipitation shows negative correlation with the radiative forcing. This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

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.

Land use and cover change (LUCC) is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface, with significant impacts on the environment and social economy. Rapid economic development and climate change have resulted in significant changes in land use and cover. The Shiyang River Basin, located in the eastern part of the Hexi Corridor in China, has undergone significant climate change and LUCC over the past few decades. In this study, we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991, 1995, 2000, 2005, 2010, 2015, and 2020 based on Landsat images. We validated the land use and cover data in 2015 from the random forest classification results (this study), the high-resolution dataset of annual global land cover from 2000 to 2015 (AGLC-2000-2015), the global 30 m land cover classification with a fine classification system (GLC_FCS30), and the first Landsat-derived annual China Land Cover Dataset (CLCD) against ground-truth classification results to evaluate the accuracy of the classification results in this study. Furthermore, we explored and compared the spatiotemporal patterns of LUCC in the upper, middle, and lower reaches of the Shiyang River Basin over the past 30 years, and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural (evapotranspiration, precipitation, temperature, and surface soil moisture) and anthropogenic (nighttime light, gross domestic product (GDP), and population) factors. The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015, GLC_FCS30, and CLCD datasets in both overall and partial validations. Moreover, the classification results in this study exhibited a high level of agreement with the ground truth features. From 1991 to 2020, the area of bare land exhibited a decreasing trend, with changes primarily occurring in the middle and lower reaches of the basin. The area of grassland initially decreased and then increased, with changes occurring mainly in the upper and middle reaches of the basin. In contrast, the area of cropland initially increased and then decreased, with changes occurring in the middle and lower reaches. The LUCC was influenced by both natural and anthropogenic factors. Climatic factors and population contributed significantly to LUCC, and the importance values of evapotranspiration, precipitation, temperature, and population were 22.12%, 32.41%, 21.89%, and 19.65%, respectively. Moreover, policy interventions also played an important role. Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years, with the ecological environment improving in the last 10 years. This suggests that governance efforts in the study area have had some effects, and the government can continue to move in this direction in the future. The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar 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.

Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern, and drought directly impacts urban site selection, growth processes, and future scenarios. Spatial simulation and projection based on cellular automata (CA) models is important to achieve sustainable urban development in arid areas. We developed a new CA model using bat algorithm (BA) named bat algorithm-probability-of-occurrence-cellular automata (BA-POO-CA) model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas, located in Xinjiang Uygur Autonomous Region, China. We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data, and finally projected its urban scenarios in 2030. The results showed that BA-POO-CA model yielded overall accuracy of 97.70% and figure-of-merits (FOMs) of 35.50% in 2010, and 97.70% and 26.70% in 2020, respectively. The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs, with increases of 5.50% in 2010 and 7.90% in 2020 than the model excluding drought intensity factor. This suggested that the urban growth of Urumqi City was affected by drought, and therefore taking drought intensity factor into account would contribute to simulation accuracy. The BA-POO-CA model including drought intensity factor was used to project two possible scenarios (i.e., business-as-usual (BAU) scenario and ecological scenario) in 2030. In the BAU scenario, the urban growth dominated mainly in urban fringe areas, especially in the northern part of Toutunhe District, Xinshi District, and Midong District. Using exceptional and extreme drought areas as a spatial constraint, the urban growth was mainly concentrated in the "main urban areas-Changji-Hutubi" corridor urban pattern in the ecological scenario. The results of this research can help to adjust urban planning and development policies. Our model is readily applicable to simulating urban growth and future scenarios in global arid areas such as Northwest China and Africa.

One of the goals of grazing management in the desert steppe is to improve its ecosystem. However, relatively little is known about soil microbe communities in the desert steppe ecosystem under grazing management. In this study, we investigated the diversity and aboveground biomass of Caragana korshinskii Kom. shrub communities in long-term fencing and grazing areas, combined with an analysis of soil physical-chemical properties and genomics, with the aim of understanding how fence management affects plant-soil-microbial inter-relationships in the desert steppe, China. The results showed that fence management (exclosure) increased plant diversity and aboveground biomass in C. korshinskii shrub area and effectively enhanced soil organic carbon (233.94%), available nitrogen (87.77%), and available phosphorus (53.67%) contents. As well, the Shannon indices of soil bacteria and fungi were greater in the fenced plot. Plant-soil changes profoundly affected the alpha- and beta-diversity of soil bacteria. Fence management also altered the soil microbial community structure, significantly increasing the relative abundances of Acidobacteriota (5.31%-8.99%), Chloroflexi (3.99%-5.58%), and Glomeromycota (1.37%-3.28%). The soil bacterial-fungal co-occurrence networks under fence management had higher complexity and connectivity. Based on functional predictions, fence management significantly increased the relative abundance of bacteria with nitrification and nitrate reduction functions and decreased the relative abundance of bacteria with nitrate and nitrite respiration functions. The relative abundances of ecologically functional fungi with arbuscular mycorrhizal fungi, ectomycorrhizal fungi, and saprotrophs also significantly increased under fence management. In addition, the differential functional groups of bacteria and fungi were closely related to plant-soil changes. The results of this study have significant positive implications for the ecological restoration and reconstruction of dry desert steppe and similar 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.

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.

Phyllosphere microorganisms are a crucial component of environmental microorganisms, highly influenced by host characteristics, and play a significant role in plant health and productivity. Nonetheless, the impact of host characteristics on shaping phyllosphere microbial communities of plants with different life forms remains ambiguous. Utilizing high-throughput sequencing technology, this study analyzed the diversity and community composition of phyllosphere epiphytic microorganisms (e.g., bacteria and fungi) of various plant life forms in the hinterland of the Gurbantunggut Desert, Northwest China. Functional annotation of prokaryotic taxa (FAPROTAX) and fungi function guild (FUNGuild) were employed to assess the ecological functions of microorganisms and to investigate the role of stochastic and deterministic processes in shaping phyllosphere microbial communities. Result showed a diverse array of phyllosphere epiphytic microorganisms in the desert plants, with Proteobacteria, Cyanobacteria, and Actinobacteriota dominating bacterial community, while Ascomycota and Basidiomycota were prevalent in fungal community. Comparison across different plant life forms highlighted distinct microbial communities, indicating strong filtering effects by plant characteristics. FAPROTAX prediction identified intracellular parasites (accounting for 27.44% of bacterial community abundance), chemoheterotrophy (10.12%), and phototrophy (17.41%) as the main functions of epiphytic bacteria on leaves of different life form plants. FUNGuild prediction indicated that phyllosphere epiphytic fungi primarily served as Saprotrophs (81.77%), Pathotrophs (17.41%), and Symbiotrophs (0.82%). Co-occurrence network analysis demonstrated a predominance of positive correlations among different microbial taxa. Raup-Crick dissimilarity index analysis revealed that deterministic processes predominantly influenced phyllosphere bacterial and fungal community assembly. Variance partitioning analysis and random forest modeling suggested that plant leaf functional traits significantly impacted both bacterial and fungal community composition, with fungal community composition showing a closer association with leaf nutrients and physiology compared with bacterial community composition. The distinct responses of bacterial and fungal communities to plant traits were attributed to the differing properties of bacteria and fungi, such as bacteria having higher potential dispersal rates and broader ecological niches than fungi. Overall, the results indicate that phyllosphere bacterial and fungal communities undergo similar community assembly processes, with fungi being more influenced by plant characteristics than bacteria. These findings offer novel insights into the ecology of phyllosphere microbial communities of desert plants.

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.

The isotope composition in precipitation has been widely considered as a tracer of monsoon activity. Compared with the coastal region, the monsoon margin usually has limited precipitation with large fluctuation and is usually sensitive to climate change. The water resource management in the monsoon margin should be better planned by understanding the composition of precipitation isotope and its influencing factors. In this study, the precipitation samples were collected at five sampling sites (Baiyin City, Kongtong District, Maqu County, Wudu District, and Yinchuan City) of the monsoon margin in the northwest of China in 2022 to analyze the characteristics of stable hydrogen (δD) and oxygen (δ¹⁸O) isotopes. We analyzed the impact of meteorological factors (temperature, precipitation, and relative humidity) on the composition of precipitation isotope at daily level by regression analysis, utilized the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT)-based backward trajectory model to simulate the air mass trajectory of precipitation events, and adopted the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) to analyze the water vapor sources. The results showed that compared with the global meteoric water line (GMWL), the slope of the local meteoric water line (LMWL; δD=7.34δ¹⁸O-1.16) was lower, indicating the existence of strong regional evaporation in the study area. Temperature significantly contributed to δ¹⁸O value, while relative humidity had a significant negative effect on δ¹⁸O value. Through the backward trajectory analysis, we found eight primary locations that were responsible for the water vapor sources of precipitation in the study area, of which moisture from the Indian Ocean to South China Sea (ITSC) and the western continental (CW) had the greatest influence on precipitation in the study area. The hydrogen and oxygen isotopes in precipitation are significantly influenced by the sources and transportation paths of air mass. In addition, the results of PSCF and CWT analysis showed that the water vapor source areas were primarily distributed in the south and northwest direction of the study area.

Tree plantation and forest restoration are the major strategies for enhancing terrestrial carbon sequestration and mitigating climate change. The Grain for Green Project in China has positively impacted global carbon sequestration and the trend towards fragmentation of plantation forests. Limited studies have been conducted on changes in plantation biomass and stand structure caused by fragmentation, and the effect of fragmentation on the carbon storage of plantation forests remains unclear. This study evaluated the differences between carbon storage and stand structure in black locust forests in fragmented and continuous landscape in the Ansai District, China and discussed the effects of ecological significance of four landscape indices on carbon storage and tree density. We used structural equation modelling to explore the direct and indirect effects of fragmentation, edge, abiotic factors, and stand structure on above-ground carbon storage. Diameter at breast height (DBH) in fragmented forests was 53.3% thicker, tree density was 40.9% lower, and carbon storage was 49.8% higher than those in continuous forests; for all given DBH>10 cm, the trees in fragmented forests were shorter than those in continuous forests. The patch area had a negative impact on carbon storage, i.e., the higher the degree of fragmentation, the lower the density of the tree; and fragmentation and distance to edge (DTE) directly increased canopy coverage. However, canopy coverage directly decreased carbon storage, and fragmentation directly increased carbon storage and tree density. In non-commercial forests, fragmentation reduces the carbon storage potential of plantation, and the influence of patch area, edge, and patchy connection on plantation should be considered when follow-up trees are planted and for the plantation management. Thus, expanding the area of plantation patches, repairing the edges of complex-shaped patches, enhancing the connectivity of similar patches, and applying nutrients to plantation forests at regular intervals are recommended in fragmented areas of the Loess Plateau.

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

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.

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.

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.

Qilian Mountains in Northwest China is a significant ecological security barrier due to its distinctive geographic setting, which has significant biological resource and gene pool. In order to assess the soil quality and ecosystem health in this area, we identified the structural characteristics and functional groups of soil microbial communities. This study focused on Amidongsuo, a typical watershed of the Qilian Mountains, and researched the vertical distribution and dominant populations of soil microorganisms in different habitats, and the relationship between soil microorganisms and environmental factors. Soil microorganisms from three grassland plots, five shrubland plots, and five forest plots in Amidongsuo were studied using high-throughput sequencing. The Venn diagram showed that the types of bacteria were fewer than those of fungi in Amidongsuo. Soil bacteria Acidobacteriota, Proteobacteria, and Methylomirabilota as well as fungi Basidiomycota, Ascomycota, and Mortierellomycota played dominant roles in Amidongsuo, according to the LEfSe (linear discriminant analysis (LDA) effect size) and community structure analyses. According to the ANOSIM (analysis of similarities) result, for both bacteria and fungi, R values of grassland and shrubland were small (R²=0.045 and R²=0.256, respectively), indicating little difference between these two ecosystems. RDA (redundancy analysis) showed a closer relationship between soil nutrients and fungi, and a gradually decreasing correlation between soil nutrients and microorganisms with increasing soil depth. Bacteria were mainly affected by pH, nitrogen (N), and potassium (K), while fungi were mainly affected by K. Overall, fungi had more effect on soil quality than bacteria. Therefore, adjustment of soil K content might improve the soil environment of Amidongsuo in the Qilian Mountains.

The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role. Based on field wind tunnel experiments using 11 common plant species on the southeastern edge of the Tengger Desert, China, we studied the secondary seed dispersal in the fixed and semi-fixed sand dunes as well as in the mobile dunes in order to understand the limitations of vegetation regeneration and the maintenance of its stability. Our results indicated that there were significant variations among the selected 11 plant species in the threshold of wind speed (TWS). The TWS of Caragana korshinskii was the highest among the 11 plant species, whereas that of Echinops gmelinii was the lowest. Seed morphological traits and underlying surface could generally explain the TWS. During the secondary seed dispersal processes, the proportions of seeds that did not disperse (no dispersal) and only dispersed over short distance (short-distance dispersal within the wind tunnel test section) were significantly higher than those of seeds that were buried (including lost seeds) and dispersed over long distance (long-distance dispersal beyond the wind tunnel test section). Compared with other habitats, the mobile dunes were the most difficult places for secondary seed dispersal. Buried seeds were the easiest to be found in the semi-fixed sand dunes, whereas fixed sand dunes were the best sites for seeds that dispersed over long distance. The results of linear mixed models showed that after controlling the dispersal distance, smaller and rounder seeds dispersed farther. Shape index and wind speed were the two significant influencing factors on the burial of seeds. The explanatory power of wind speed, underlying surface, and seed morphological traits on the seeds that did not disperse and dispersed over short distance was far greater than that on the seeds that were buried and dispersed over long distance, implying that the processes and mechanisms of burial and long-distance dispersal are more complex. In summary, most seeds in the study area either did not move, were buried, or dispersed over short distance, promoting local vegetation regeneration.

Nitrogen (N) deposition is a significant aspect of global change and poses a threat to terrestrial biodiversity. The impact of plant-soil microbe relationships to N deposition has recently attracted considerable attention. Soil microorganisms have been proven to provide nutrients for specific plant growth, especially in nutrient-poor desert steppe ecosystems. However, the effects of N deposition on plant-soil microbial community interactions in such ecosystems remain poorly understood. To investigate these effects, we conducted a 6-year N-addition field experiment in a Stipa breviflora Griseb. desert steppe in Inner Mongolia Autonomous Region, China. Four N treatment levels (N0, N30, N50, and N100, corresponding to 0, 30, 50, and 100 kg N/(hm²•a), respectively) were applied to simulate atmospheric N deposition. The results showed that N deposition did not significantly affect the aboveground biomass of desert steppe plants. N deposition did not significantly reduce the alfa-diversity of plant and microbial communities in the desert steppe, and low and mediate N additions (N30 and N50) had a promoting effect on them. The variation pattern of plant Shannon index was consistent with that of the soil bacterial Chao1 index. N deposition significantly affected the beta-diversity of plants and soil bacteria, but did not significantly affect fungal communities. In conclusion, N deposition led to co-evolution between desert steppe plants and soil bacterial communities, while fungal communities exhibited strong stability and did not undergo significant changes. These findings help clarify atmospheric N deposition effects on the ecological health and function of the desert steppe.

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.

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.

Severe soil erosion and drought are the two main factors affecting the ecological security of the Loess Plateau, China. Investigating the influence of drought on soil conservation service is of great importance to regional environmental protection and sustainable development. However, there is little research on the coupling relationship between them. In this study, focusing on the Jinghe River Basin, China as a case study, we conducted a quantitative evaluation on meteorological, hydrological, and agricultural droughts (represented by the Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Standardized Soil Moisture Index (SSMI), respectively) using the Variable Infiltration Capacity (VIC) model, and quantified the soil conservation service using the Revised Universal Soil Loss Equation (RUSLE) in the historical period (2000-2019) and future period (2026-2060) under two Representative Concentration Pathways (RCPs) (RCP4.5 and RCP8.5). We further examined the influence of the three types of drought on soil conservation service at annual and seasonal scales. The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset was used to predict and model the hydrometeorological elements in the future period under the RCP4.5 and RCP8.5 scenarios. The results showed that in the historical period, annual-scale meteorological drought exhibited the highest intensity, while seasonal-scale drought was generally weakest in autumn and most severe in summer. Drought intensity of all three types of drought will increase over the next 40 years, with a greater increase under the RCP4.5 scenario than under the RCP8.5 scenario. Furthermore, the intra-annual variation in the drought intensity of the three types of drought becomes smaller under the two future scenarios relative to the historical period (2000-2019). Soil conservation service exhibits a distribution pattern characterized by high levels in the southwest and southeast and lower levels in the north, and this pattern has remained consistent both in the historical and future periods. Over the past 20 years, the intra-annual variation indicated peak soil conservation service in summer and lowest level in winter; the total soil conservation of the Jinghe River Basin displayed an upward trend, with the total soil conservation in 2019 being 1.14 times higher than that in 2000. The most substantial impact on soil conservation service arises from annual-scale meteorological drought, which remains consistent both in the historical and future periods. Additionally, at the seasonal scale, meteorological drought exerts the highest influence on soil conservation service in winter and autumn, particularly under the RCP4.5 and RCP8.5 scenarios. Compared to the historical period, the soil conservation service in the Jinghe River Basin will be significantly more affected by drought in the future period in terms of both the affected area and the magnitude of impact. This study conducted beneficial attempts to evaluate and predict the dynamic characteristics of watershed drought and soil conservation service, as well as the response of soil conservation service to different types of drought. Clarifying the interrelationship between the two is the foundation for achieving sustainable development in a relatively arid and severely eroded area such as the Jinghe River Basin.

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.

Surface albedo is a quantitative indicator for land surface processes and climate modeling, and plays an important role in surface radiation balance and climate change. In this study, by means of the MCD43A3 surface albedo product developed on the basis of Moderate Resolution Imaging Spectroradiometer (MODIS), we analyzed the spatiotemporal variation, persistence status, land cover type differences, and annual and seasonal differences of surface albedo, as well as the relationship between surface albedo and various influencing factors (including Normalized Difference Snow Index (NDSI), precipitation, Normalized Difference Vegetation Index (NDVI), land surface temperature, soil moisture, air temperature, and digital elevation model (DEM)) in the north of Xinjiang Uygur Autonomous Region (northern Xinjiang) of Northwest China from 2010 to 2020 based on the unary linear regression, Hurst index, and Pearson's correlation coefficient analyses. Combined with the random forest (RF) model and geographical detector (Geodetector), the importance of the above-mentioned influencing factors as well as their interactions on surface albedo were quantitatively evaluated. The results showed that the seasonal average surface albedo in northern Xinjiang was the highest in winter and the lowest in summer. The annual average surface albedo from 2010 to 2020 was high in the west and north and low in the east and south, showing a weak decreasing trend and a small and stable overall variation. Land cover types had a significant impact on the variation of surface albedo. The annual average surface albedo in most regions of northern Xinjiang was positively correlated with NDSI and precipitation, and negatively correlated with NDVI, land surface temperature, soil moisture, and air temperature. In addition, the correlations between surface albedo and various influencing factors showed significant differences for different land cover types and in different seasons. To be specific, NDSI had the largest influence on surface albedo, followed by precipitation, land surface temperature, and soil moisture; whereas NDVI, air temperature, and DEM showed relatively weak influences. However, the interactions of any two influencing factors on surface albedo were enhanced, especially the interaction of air temperature and DEM. NDVI showed a nonlinear enhancement of influence on surface albedo when interacted with land surface temperature or precipitation, with an explanatory power greater than 92.00%. This study has a guiding significance in correctly understanding the land-atmosphere interactions in northern Xinjiang and improving the regional land-surface process simulation and climate prediction.

Tiger nut is a bioenergy crop planted in arid areas of northern China to supply oil and adjust the planting structure. However, in the western region of Inner Mongolia Autonomous Region, China, less water resources have resulted in a scarcity of available farmland, which has posed a huge obstacle to planting tiger nut. Cultivation of tiger nut on marginal land can effectively solve this problem. To fully unlock the production potential of tiger nut on marginal land, it is crucial for managers to have comprehensive information on the adaptive mechanism and nutrient requirement of tiger nut in different growth periods. This study aims to explore these key information from the perspective of nutrient coordination strategy of tiger nut in different growth periods and their relationship with rhizosphere soil nutrients. Three fertilization treatments including no fertilization (N:P (nitrogen:phosphorous)=0:0), traditional fertilization (N:P=15:15), and additional N fertilizer (N:P=60:15)) were implemented on marginal land in the Dengkou County. Plant and soil samples were collected in three growth periods, including stolon tillering period, tuber expanding period, and tuber mature period. Under no fertilization, there was a significant correlation between N and P contents of tiger nut roots and tubers and the same nutrients in the rhizosphere soil (P<0.05). Carbon (C), N, and P contents of roots were significantly higher than those of leaves (P<0.05), and the C:N ratio of all organs was higher than those under other treatments before tuber maturity (P<0.05). Under traditional fertilization, there was a significant impact on the P content of tiger nut tubers (P<0.05). Under additional N fertilizer, the accumulation rate of N and P was faster in stolons than in tubers (P<0.05) with lower N:P ratio in stolons during the tuber expansion period (P<0.05), but higher N:P ratio in tubers (P<0.05). The limited availability of nutrients in the rhizosphere soil prompts tiger nut to increase the C:N ratio, improving N utilization efficiency, and maintaining N:P ratio in tubers. Elevated N levels in the rhizosphere soil decrease the C:N ratio of tiger nut organs and N:P ratio in stolons, promoting rapid stolon growth and shoot production. Supplementary P is necessary during tuber expansion, while a higher proportion of N in fertilizers is crucial for the aboveground biomass production of tiger nut.

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.

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.

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.

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.