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Xinjiang is the largest cotton-producing region in China, but it faces a severe shortage of water resources. According to relevant studies, the cotton yield does not significantly decrease under appropriate limited water conditions. Therefore, this paper proposes a water and fertilizer integrated control system to achieve water and fertilizer conservation in the process of cotton field cultivation. This paper designs a fuzzy neural network Proportional–Integral–Derivative controller based on the improved Wild Horse Optimizer to address the water and fertilizer integrated control system's time-varying, lag, and non-linear characteristics. The controller precisely controls fertilizer electrical conductivity (EC) by optimizing parameters through an improved Wild Horse Optimizer for the initial weights from the normalization layer to the output layer, the initial center values of membership functions, and the initial base width of membership functions in the fuzzy neural network. The performance of the controller is validated through MATLAB simulation and experimental tests. The results indicate that, compared with conventional PID controllers and fuzzy PID controllers, this controller exhibits excellent control accuracy and robustness, effectively achieving precise fertilization. [ABSTRACT FROM AUTHOR]

The pivotal role of farmers' cropland conservation behavior (CCB) in advancing green agricultural practices is well-recognized. This paper underscores the critical role of stable land tenure in enhancing farmers' CCB, exemplified by the practice of mulch recycling. Drawing on a survey of 349 cotton farmers in Xinjiang, Northwest China, it offers a systematic examination of how land tenure stability influences CCB and its underlying mechanisms. The findings reveal a significant positive correlation between land tenure stability and CCB. Notably, this relationship is mediated by the facilitation of land mortgages, wherein written contracts and extended land tenure durations enhance farmers' participation in land mortgages, thereby bolstering CCB. Furthermore, the stabilizing effect of land tenure on CCB also mitigates the negative impacts of risk aversion and time preference. The study additionally highlights the differential effects of land tenure stability based on farm size and technical training; its facilitative role in CCB is more pronounced among larger-scale farmers and those engaged in technical training. [ABSTRACT FROM AUTHOR]

The southern Junggar Basin, Xinjiang, has abundant coalbed methane (CBM) resources. Currently, the Baiyang River development pilot test area (BYR block for short) in the Fukang east block has achieved large-scale CBM development, but the productivity characteristics and its controlling factor are still unclear. Based on the field production data of the BYR block and experimental tests, this paper summarizes the gas and water production characteristics and presents the analysis results of the geological and geochemical responses to the productivity of CBM wells. The productivity of CBM wells in the BYR block was generally characterized as medium-to-low yield. The productivity was jointly controlled by the burial depth, structure condition, thickness and number of co-production coal seams, and hydrogeological conditions. The gas production first increased and then decreased with the increase in the burial depth of the coal seam, and a burial depth between 750 and 1000 m was the most beneficial to increasing the gas production due to the good gas preservation conditions and suitable permeability and stress conditions. The total thickness of the co-production coal seams had a positive effect on the productivity of gas wells, but the productivity was also affected by the number of co-production coal seams and interlayer interference. In the BYR block, the co-production of the nos. 41 and 42 coal seams was the most favorable combination form for CBM drainage. The productivity of CBM wells had a good response to the Na+, K+ and HCO3− concentrations but a poor response to δD-H2O and δ18O-H2O. Based on the concentrations of the main ions and TDSs of the coal seam water, a productivity response index δ* was established, and there was a good positive correlation between the productivity and δ*. [ABSTRACT FROM AUTHOR]

Thoroughly investigating the evolution of groundwater circulation and its controlling mechanism in the Aksu River Basin, where human activities are intensifying and the groundwater environment is increasingly deteriorating, is highly urgent and important for promoting the theory, development and implementation of groundwater flow systems (GFSs) and protecting groundwater resources. Based on a detailed analysis of the sediment grain size distribution, chronology, electrofacies, glacial sedimentary sequence, palaeoclimate indicators and existing groundwater age, this paper systematically reconstructs the palaeosedimentary environment of the basin-scale aquifer system in the study area and scientifically reveals the evolutionary pattern and formation mechanism of the GFS. The results showed that the later period of the late Pleistocene experienced a rapid downcutting erosional event caused by tectonic uplift, and the sedimentary environment transitioned from a dry–cold deep downcutting environment in the Last Glacial Maximum (LGM) to a coarse-grained fast-filling fluvial facies sedimentary environment in the Last Glacial Deglaciation (LDP) as the temperature rose; then, it shifted to an environment of fine-grained stable alternating accumulation of fluvial facies and lacustrine facies that was dominated by the warm and arid conditions of the Holocene megathermal period (HMP); this process changed the previous river base level via erosion, glacier elongation or shortening and river level, thus resulting in a complex coupling relationship between the palaeosedimentary environment, palaeoclimate and basin GFS. Furthermore, the existing GFS pattern in the basin exhibits a vertically unconformable groundwater age distribution, which indicates that it is the outcome of the complex superposition of groundwater flow controlled by the palaeosedimentary environment in different periods. Therefore, neotectonic movement and climate fluctuation have jointly acted on the variation in the river level, resulting in the "seesaw" effect, thereby fundamentally controlling the strength of the driving force of groundwater and resulting in the gradual evolution of the GFS from the fully developed regional GFS pattern during the LGM to the current multihierarchy nested GFS pattern. [ABSTRACT FROM AUTHOR]

Hydrogen is receiving unprecedented momentum and is projected to meet a sizable share of the final energy demand in the future. The coupling between the hydrogen and power systems can help integrate volatile renewable energy, reduce curtailment, and realize long-term energy storage. Different coupling modes are being proposed, yet quantitative comparisons are absent. To fill this gap, this paper firstly summarizes the system composition of potential power–hydrogen coupling modes and analyzes their advantages and disadvantages. Then, a model for power–hydrogen coordinated planning optimization is proposed for quantitative analysis. Southern Xinjiang is chosen as a representative of the northwestern area in China, which has plentiful renewable resources and a relatively small local load at present, for a case study. Through result analysis, it is found that the mode of power–hydrogen coupling at the source side, either for in situ utilization or for long-distance transport via pipelines, shows better economic competitiveness. The discussion provides suggestions and a reference to policymakers for formulating infrastructure or industry plans in advance to better accommodate the rapidly developing renewable energy. [ABSTRACT FROM AUTHOR]

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall. [ABSTRACT FROM AUTHOR]

There are large, heavy oil reserves in Block X of the Xinjiang oilfields, China. Due to its large burial depth (1300 m) and low permeability (26.0 mD), the traditional steam-injection technology cannot be used to obtain effective development benefits. This paper conducts experimental and simulation research on the feasibility and mechanism of CO 2 -energized fracturing of horizontal wells and N 2 foam huff-n-puff in deep heavy oil reservoirs with low permeability in order to further explore the appropriate production technology. The foaming volume of the foaming agent at different concentrations and the oil displacement effect of N 2 foam at different gas/liquid ratios were compared by the experiments. The results show that a high concentration of foaming agent mixed with crude oil is more conducive to increasing the foaming volume and extending the half-life, and the best foaming agent concentration is 3.0∼4.0%. The 2D micro-scale visualization experiment results show that N 2 foam has a good selective blocking effect, which increases the sweep area. The number of bubbles per unit area increases as the gas/liquid ratio increases, with 3.0∼5.0 being the optimal gas/liquid ratio. Numerical simulation results show that, when CO 2 -energized fracturing technology takes into account the advantages of fracturing and crude oil viscosity reduction by CO 2 dissolution, the phased oil recovery factor in the primary production period can reach approximately 13.7%. A solvent pre-slug with N 2 foam huff-n-puff technology is applied to improve oil recovery factor following primary production for 5∼6 years, and the final oil recovery factor can reach approximately 35.0%. The methodology formulated in this study is particularly significant for the effective development of this oil reservoir with deeply buried depth and low permeability, and would also guide the recovery of similar oil deposits. [ABSTRACT FROM AUTHOR]

In northwest China, underground mining is frequently conducted in weakly cemented rock environments, including the aquiclude that protects the aquifer from dewatering. In this context, understanding the aquiclude responses to longwall mining is significant for assessing the reliability of water-conserved mining in the weakly cemented rock environment. Taking the Jurassic and Paleogene coal measure geology in Yili Mine in Xinjiang Province, China, as a case study, the paper conducted a laboratorial three-dimensional simulation by configuring a longwall operation and induced groundwater migration. The study analysed the aquiclude depressurisation and revealed the aquiclude stability in response to longwall mining. The results indicated that the aquiclude had a significant plastic strain and self-healing ability in the ground depressurisation condition. The aquiclude experienced tension and then compression, and, accordingly, fracture initiation, propagation, and convergence, during which the aquiclude had significant bending deformation. On the aquiclude horizon, tensile fracturing dominated above the set-up and longwall stop positions. The self-healing behaviour was correlated to the high content of clay minerals and disintegration proneness. The simulation results had a good agreement with field measurements, suggesting that the aquiclude had a satisfactory water-resisting ability and that the simulation results were practically reliable. [ABSTRACT FROM AUTHOR]

Accurate precipitation forecasting is of great significance to social life and economic activities. Due to the influence of various factors such as topography, climate, and altitude, the precipitation in semi-arid and arid areas shows the characteristics of large fluctuation, short duration, and low probability of occurrence. Therefore, it is highly challenging to accurately predict precipitation in the northern Xinjiang area of China, which is located in the semi-arid and arid climate region. In this study, six meteorological stations in the northern Xinjiang area were selected as the research area. Due to the high volatility of rainfall in this area, the rainfall was divided into four levels, namely, "no rain", "light rain", "moderate rain", and "heavy rain and above", for rainfall level prediction. In order to improve the prediction performance, this study proposed a rainfall levels nowcasting model based on Conv1D_Transformer (RLNformer). Firstly, the maximum information coefficient (MIC) method was used for feature selection and sliding the data, that is, the data of the first 24 h were used to predict the rainfall levels in the next 3 h. Then, the Conv1D layer was used to replace the word-embedding layer of the transformer, enabling it to extract the relationships between features of time series data and allowing multi-head attention to better capture contextual information in the input sequence. Additionally, a normalization layer was placed before the multi-head attention layer to ensure that the input data had an appropriate scale and normalization, thereby reducing the sensitivity of the model to the distribution of input data and helping to improve model performance. To verify the effectiveness and generalization of the proposed model, the same experiments were conducted on the Indian public dataset, and seven models were selected as benchmark models. Compared with the benchmark models, RLNformer achieved the highest accuracy on both datasets, which were 96.41% and 88.95%, respectively. It also had higher accuracy in the prediction of each category, especially the minority category, which has certain reference significance and practical value. [ABSTRACT FROM AUTHOR]

The arid region of northwest China (ARNC) is one of the most sensitive areas to global warming. However, the performance of new Global Climate Models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating climate in this region, especially in the subregions, is not clear yet. Based on the temperature dataset from historical runs of CMIP6, this paper analyzed and evaluated the simulation ability of 29 GCMs in reproducing the annual mean temperature (tas), annual mean maximum temperature (tasmax) and annual mean minimum temperature (tasmin) in the ARNC and subregions from 1961 to 2014. The results show that (1) the correlation coefficients (CCs) between simulation and observation time series for the mean of two model ensembles (MME for equal-weight multi-model ensemble and PME for preferred-model ensemble) are generally better than those of 29 individual GCMs, with CCs ranging from 0.38 to 0.87 (p < 0.01). (2) All the models can simulate the significant warming trend of the three temperature elements in the study area well. However, the warming magnitude simulated by most of the models (41%) is smaller than the observations except for tasmax, which is also shown in the MME. (3) The spatial pattern of the three temperature elements can be better reflected by most models. Model simulation ability for the ARNC is better compared to that of the four subregions, with a spatial CC greater than 0.7 (p < 0.01). Among the subregions, the simulation performance of the north of Xinjiang for spatial pattern is superior to that of the other regions. (4) The preferred models for each subregion are various and should be treated differently when used. Overall, the PME outperforms both the MME and the individual models; it can not only simulate the linear trend accurately but also reduce the deviation effectively. [ABSTRACT FROM AUTHOR]

Ecosystem services (ESs) are crucial for sustainable development, as they impact human well-being. However, changes in land use/land cover (LULC) caused by climate change and social development can negatively affect ESs, particularly in arid river basins. This study focuses on current and future changes in LULC in the Kaxghar River Basin (KRB) in Xinjiang, China, to determine how these changes will affect the region's ESs. The integrated PLUS-InVEST model was used to investigate the spatiotemporal distribution and changing patterns of habitat quality (HQ) and carbon storage (CS) under the natural increase scenario (NIS), economic development scenario (EDS), and water protection scenario (WPS). Additionally, the Ecosystem Service Contribution Index (ESCI) was also calculated to evaluate the contribution of LULC changes to ESs. The results show the following: (1) from 2000 to 2020, the average value of HQ in the KRB gradually decreased from 0.54 to 0.49 and CS trended slightly upward, with a total increase of 0.07 × 106 t. Furthermore, the changes in CS were highly consistent with changes in LULC. (2) From 2020 to 2030, the area of low-grade (0–0.2) HQ saw a continuous increase, with the fastest growth occurring in 2030 under the EDS. Meanwhile, under the WPS, HQ significantly improved, expanding by 1238 km2 in area. Total CS under the three test scenarios tended to decline, with the NIS showing the smallest decrease. (3) The expansion of cropland and unused land had a negative impact on ESs, particularly on CS, whereas the conversion to grassland and forestland had a significant positive impact. In conclusion, these insights will enrich our understanding of ESs in the study area and contribute to balancing the relationship between ecological conservation and socioeconomic development in the Kaxghar River Basin, as well as in other parts of China's arid Northwest and similar regions around the world. [ABSTRACT FROM AUTHOR]

Health improvement is an important social development goal for every country. By using a geographical weighted regression (GWR) model on the 5th and 6th censuses data, this paper analyzes the spatially varied influencing factors of the change in life expectancy of residents in Chinses cities. The results indicate that: (1) The initial level of life expectancy may have a negative correlation with its increase, indicating that life expectancy in different areas may eventually converge to a higher level; moreover, the degree of convergence of life expectancy in cities with different economic development levels is variant. (2) Results of geographically weighted regression model demonstrate significant spatial heterogeneity in the effects of the level of economic development, medical conditions, demographic structure, and natural environment on health improvement. Natural conditions, such as topography, dictate the change in life expectancy in most cities in the middle eastern region of China. Change of educational level is the leading factor in the vast western region while the change in birth rate is the most critical in Xinjiang. Thus, local-based strategies are critical for solving health problems, especially with a focus on promoting health conditions in middle-income and low-income areas. [ABSTRACT FROM AUTHOR]

China is an important cotton production area in the world. Since 2014, China has implemented a cotton target price subsidy policy in Xinjiang for 7 years. As the policy implementation time has lengthened, some deep-seated problems have started to emerge. Therefore, it is necessary to summarize and evaluate to clarify the future policy direction of the cotton target price subsidy policy. Based on county-level panel data of Xinjiang and Shandong from 2011 to 2018, this paper used the Propensity Score Matching—Difference in Difference method to analyze the impact of the implementation of cotton target price subsidy policy on cotton planting in Xinjiang. The results showed that: (1) after the implementation of the cotton target price subsidy policy, cotton production was stimulated by the transition, cotton producers' enthusiasm for cotton production was higher, cotton production increased rapidly, and the yield per unit area decreased, indicating that there was a 'bubble' in cotton cultivation. (2) The target price subsidy policy mainly achieves the expansion of the cotton planting scale by reducing the area of competitive crops. In view of the above research conclusions, this paper further explains its policy implications. It is proposed that the future cotton target price level should be formulated to fully consider the comparative benefits between different crops, to restrict the subjects that enjoy subsidies and the upper limit of subsidies, and strictly implement the concept of green development; it is necessary to guide cotton production out of ecologically vulnerable areas. [ABSTRACT FROM AUTHOR]

The Xinjiang Uygur Autonomous Region (Xinjiang) borders eight countries and has a complex geographic environment. There are almost 45.696 million herded sheep in Xinjiang, which occupies 13.80% of China's sheep farming industry. However, there is a scarcity of reports investigating the role of sheep or ticks in Xinjiang in transmitting tick-borne diseases (TBDs). A total of 894 ticks (298 tick pools) were collected from sheep in southern Xinjiang. Out of the 298 tick pools investigated in this study, Rhipicephalus turanicus (Rh. turanicus) and Hyalomma anatolicum (H. anatolicum) were identified through morphological and molecular sequencing. In the southern part of Xinjiang, 142 (47.65%), 86 (28.86%), and 60 (20.13%) tick pools were positive for Rickettsia spp., Theileria spp., and Anaplasma spp., respectively. Interestingly, the infection rate of Rickettsia spp. (73%, 35.10%, and 28.56–41.64%) was higher in Rh. turanicus pools than in H. anatolicum pools (4%, 4.44%, and 0.10–8.79%) in this study. Fifty-one tick pools were found to harbor two pathogens, while nineteen tick pools were detected to have the three pathogens. Our findings indicate the presence of Rickettsia spp., Theileria spp., and Anaplasma spp. potentially transmitted by H. anatolicum and Rh. turanicus in sheep in southern Xinjiang, China. [ABSTRACT FROM AUTHOR]

The LuTan-1 (LT-1) mission, China's first civilian bistatic spaceborne Synthetic Aperture Radar (SAR) mission, comprises two L-band SAR satellites. These satellites operate in bistatic InSAR strip map mode, maintaining a formation flight with an adjustable baseline to generate global digital elevation models (DEMs) with high accuracy and spatial resolution. This research introduces a dedicated interferometric calibration model for LT-1, tackling the unique challenges of the bistatic system, such as interferometric parameter coupling and the π -ambiguity problem caused by synchronization phase errors. This study validates the model using SAR images from LT-1 and Xinjiang corner reflector data, achieving interferometric phase accuracy better than 0.1 rad and baseline accuracy better than 2 mm, thereby producing high-precision DEMs with a height accuracy meeting the 5 m requirement. [ABSTRACT FROM AUTHOR]

Drought, as a widespread natural calamity, leads to the most severe agricultural losses among all such disasters. Alterations in the yield of major global agricultural products are pivotal factors influencing food prices, food security, and land use decisions. China's rapidly expanding demand for sustenance will persist over the forthcoming decades, emphasizing the critical need for an accurate assessment of drought's impact on food production. Consequently, we conducted a comprehensive evaluation of the drought risk in China and its repercussions on agricultural output. Additionally, we delved into the underlying factors driving changes in yield for three primary grain crops (wheat, corn, and rice), which hold particular relevance for shaping effective strategies to mitigate future drought challenges. The findings divulge that both the number of drought months (DM) and the drought magnitude index (DMI) have displayed an upward trajectory over 60 years with a correlation coefficient of 0.96. The overall severity of meteorological drought has escalated across China, and it is particularly evident in regions such as the southwest and central parts of the Huang-Huai-Hai region, the northwestern middle region, and the Xinjiang region. Conversely, there has been some relief from drought conditions in southern China and the Yangtze River Delta. Shifts in the total grain output (TGO) during this period were compared: it underwent three stages, namely "fluctuating growth" (1961–1999), then a "sharp decline" (2000–2003), followed by "stable growth" (2004–2018). Similarly, changes in the grain planting area (GPA) experienced two stages, "continuous reduction" (1961–2003) succeeded by "stable growth" (2004–2018), while maintaining an upward trend for grain yield per unit area (GY) throughout. Furthermore, it was revealed that the drought grade serves as a significant constraint on continuous expansion within China's grain output—where the drought damage rate's influence on the TGO outweighs that from the GY. Our research outcomes play an instrumental role in deepening our comprehension regarding how drought impacts agricultural production within China while furnishing the scientific groundwork to devise efficacious policies addressing these challenges. [ABSTRACT FROM AUTHOR]

The oasis serves as the primary supply of cultivable land, along with the hub for human production and habitation in Xinjiang. Accordingly, predicting the land use of these areas based on various goals is an effective instrument for encouraging the sensible distribution of resource space. The study investigated the creation of a land use-allocation optimization model based on the various objectives of ecological protection, food security, and urban growth using the Weigan–Kuche River oasis as an example. The GMOP-PLUS model's restriction conversion area was adjusted to include the findings of the land suitability evaluation. Additionally, it optimized and simulated the spatial arrangement and quantitative structure of land usage in the Weigan–Kuche River oasis in 2035. The results indicate the following: (1) the model's overall accuracy is 89.36%, and its Kappa coefficient is 0.872, more than 0.8. Thus, the model can be considered for adoption in the future when predicting changes in land use in the districts and counties of the Weigan–Kuche River oasis; (2) based on the results of the land suitability evaluation, the percentage of areas that are most suited for agricultural development, urban development, and ecological protection is 39.32%, 24.21%, and 14.06%, respectively; and (3) the three scenarios satisfy the various demands for growth within the oasis, and the land use structure of the oasis varies considerably in response to the various development objectives, with the construction and cultivated land undergoing the most substantial modifications. The multi-scenario simulation of land usage in the oasis can provide essential support and a range of perspectives for future land spatial planning and socioeconomic development decision-making in the Weigan–Kuche River oasis. This is essential for both the efficient use of land resources and sustainable development. [ABSTRACT FROM AUTHOR]

The nephrite belt in the Altun Mountain–Western Kunlun Mountain region, which extends about 1300 km in Xinjiang, NW China, is the largest nephrite deposit in the world. The Qiemo region in the Altun Mountains is a crucial nephrite-producing area in China, with demonstrated substantial prospects for future exploration. While existing research has extensively investigated secondary nephrite deposits in the Karakash River and native black nephrite deposits in Guangxi Dahua, a comprehensive investigation of black nephrite from original deposits in Xinjiang is lacking. Margou black-toned nephrite was recently found in primary deposits in Qiemo County, Xinjiang; this makes in-depth research on the characteristics of this mine necessary. A number of technical analytical methods such as polarizing microscopy, Ultra-Deep Three-Dimensional Microscope, electron microprobe, back-scattered electron image analysis, X-ray fluorescence, and inductively coupled plasma mass spectrometry were employed for this research. An experimental test was conducted to elucidate the chemical and mineralogical composition, further clarifying the genetic types of the black and black cyan nephrite from the Margou deposit in Qiemo, Xinjiang. The results reveal that the nephrite is mainly composed of tremolite–actinolite, characterized by Mg/(Mg + Fe2+) ratios ranging from 0.86 to 1.0. Minor minerals include diopside, epidote, pargasite, apatite, zircon, pyrite, and magnetite. Bulk-rock rare earth element (REE) patterns exhibit distinctive features, such as negative Eu anomalies (δEu = 0.00–0.17), decreasing light REEs, a relatively flat distribution of heavy REEs, and low total REE concentrations (1.6–38.9 μg/g); furthermore, the Cr (6–21 μg/g) and Ni (2.5–4.5 μg/g) contents are remarkably low. The magmatic influence of granite appears to be a fundamental factor in the genesis of the magnesian skarn hosting Margou nephrite. The distinctive black and black cyan colors are attributed to heightened iron content, mainly associated with FeO (0.08~6.29 wt.%). Analyses of the chemical composition allow Margou nephrite to be classified as typical of magnesian skarn deposits. [ABSTRACT FROM AUTHOR]

Fire blight, a devastating disease caused by Erwinia amylovora, poses a significant threat to pear and apple trees in Xinjiang province, China. In an effort to combat this pathogen, we isolated 10 bacteria from various components of apple and crabapple trees and conducted screenings to assess their ability to inhibit E. amylovora in vitro. Through biochemical tests and partial 16S rRNA gene sequencing, we identified two promising strains, Priestia megaterium strain H1 and Bacillus subtilis strain I2. These strains were then evaluated for their efficacy in biocontrol under controlled laboratory conditions, focusing on immature fruits and leaves. Remarkably, all selected antagonists exhibited the capability to reduce the severity of the disease on both fruit and leaves. P. megaterium strain H1 and B. subtilis strain I2 exhibited significant reductions in disease incidence on both immature fruits and leaves compared to the control. Specifically, on immature fruits, they achieved reductions of 53.39% and 44.76%, respectively, while on leaves, they demonstrated reductions of 59.55% and 55.53%, respectively. Furthermore, during the study, we detected the presence of lipopeptides, including surfactin, iturins, bacillomycin D, and fengycins, in the methanol extract obtained from these two antagonistic bacteria using thin-layer chromatography (TLC). Based on the results obtained, B. subtilis strain I2 and P. megaterium strain H1 exhibit considerable potential for controlling fire blight. However, further evaluation of their efficacy under natural field conditions is essential to validate their practicality as a biocontrol method. [ABSTRACT FROM AUTHOR]

In regions with severe cold and high latitudes, concrete structures are susceptible to cracking and displacement due to uneven temperature stress, which directly impacts their normal utilization. Therefore, to investigate the temperature distribution characteristics of concrete box girders under the combined influence of low temperatures and cold waves, a temperature test was conducted on a model of concrete box girders in Xinjiang Province, China. Based on the measured data, the distribution pattern of the most unfavorable negative temperature differential observed in high-latitude regions was determined. Long-term numerical simulation and extreme value analysis were performed using historical meteorological data, revealing that the vertical negative temperature gradient in the concrete box girder structures follows a composite exponential distribution. The temperature differential at the top complies with Chinese code requirements, while at the bottom, it aligns more closely with British standard BS5400. Statistical analysis of historical meteorological data predicts that the 50-year temperature differential will result in a drop amplitude of 26.42 °C, which is 1.44 times higher than measured values obtained from experiments. The proposed negative temperature gradient pattern for concrete box girders presented in this study can encompass general design codes and provide guidance for designing concrete bridges in severe cold areas. [ABSTRACT FROM AUTHOR]

This study aims to advance the recycling of mercury-containing waste and promote sustainable development within the polyvinyl chloride (PVC) industry. Our innovative system integrates pre-treatment technology (spraying potassium permanganate and demisting and dust removal) with efficient non-thermal plasma oxidation, resulting in excellent treatment efficiency, low cost, and simple operation. With a processing capacity of 3000 m3/h, the concentration of mercury emissions in flue gas can achieve the target of <0.01 mg/m3, boasting a removal efficiency exceeding 98%, which satisfies the standard "Emission standard of air pollutants for industrial kiln and furnace" (GB 9078-1996). Our results can provide technical support for the comprehensive purification of mercury-containing flue gas during the resource recovery process from mercury-containing waste. The application of our system can contribute to reducing mercury emissions in the PVC industry, lowering occupational exposure risks for workers, and promoting China's better compliance with "the Minamata Convention on Mercury". [ABSTRACT FROM AUTHOR]

Simple Summary: Mammalian orthoreovirus (MRV) infects many hosts, including humans and animals, in which it causes gastroenteritis and respiratory disease. In China, it has been found in domestic animals such as pigs, cattle, deer, and minks; however, MRV prevalence in small ruminants is still unknown, and a rapid, specific, quantification assay for clinical detection of animal samples is urgently needed. In this study, we established a TaqMan qRT-PCR method for MRV detection targeting the conserved L1 gene. The method was optimized, and the specificity, sensitivity, and repeatability were used to assess quality. We used this method for MRV detection in goat and sheep samples. The overall MRV prevalence was 8.2% (35/429), and the test showed a significantly higher sensitivity than RT-PCR and virus isolation. MRV clearly showed seasonal prevalence, with a high positive rate of infections in goats and sheep from September to April. Small ruminants under two months of age were susceptible to MRV infection. This study investigated the epidemiological characteristics of MRV infection and provides the first evidence of MRV infection in sheep and goats in China, broadening our knowledge of MRV hosts in this country. Mammalian orthoreovirus (MRV) infections are ubiquitous in multiple mammalian species including humans, and mainly causes gastroenteritis and respiratory disease. In this study, we developed a rapid and sensitive TaqMan qRT-PCR method for MRV detection based on the primers and probe designed within the conserved L1 gene. The qRT-PCR assay was evaluated for its sensitivity, specificity, efficiency and reproducibility. It was found that the detection sensitivity was equivalent to 10 DNA copies/μL, and the standard curves had a linear correlation of R2 = 0.998 with an amplification efficiency of 99.6%. The inter- and intra-assay coefficients of variation (CV%) were in the range of 0.29% to 2.16% and 1.60% to 3.60%, respectively. The primer sets specifically amplified their respective MRV segments and had the highest detection sensitivities of 100.25 TCID50/mL with amplification efficiencies of 99.5% (R2 = 0.999). qRT-PCR was used for MRV detection from samples of sheep, goats, and calves from four regions in China, and the overall MRV prevalence was 8.2% (35/429), whereas 17/429 (4.0%) were detected by RT-PCR and 14/429 (3.3%) by virus isolation. The qRT-PCR assay showed significantly higher sensitivity than RT-PCR and virus isolation. Results from an epidemiological survey indicated that the positive rate of MRV in rectal swabs from sheep and goats tested in Shaanxi, Jiangsu, and Xinjiang were 9/80 (11.3%), 12/93 (12.9%) and 14/128 (10.9%), respectively. In goats and sheep, MRV prevalence was obviously associated with season and age, with a high positive rate of more than 8% during September to April and approximately 13% in small ruminant animals under two months of age. This is the first instance of MRV infection in sheep and goats in China, thus broadening our knowledge of MRV hosts. Consequently, primer optimization for qRT-PCR should not only prioritize amplification efficiency and specificity, but also sensitivity. This assay will contribute to more accurate and rapid MRV monitoring by epidemiological investigation, viral load, and vaccination efficacy. [ABSTRACT FROM AUTHOR]

The evaluation of regional water and energy consumption is of great significance to improving regional resource utilization. This paper analyzed the water and energy footprints in different provinces of China, considering regional economic levels. The results indicate: (1) both the largest water footprint and water footprint per capita were in Xinjiang and agriculture had the largest value; (2) Shandong was the largest energy consumer, Ningxia had the largest energy footprint per capita, and coal occupied the largest proportion for the top five energy footprint provinces; and (3) the resource input–output efficiencies in Beijing and Fujian were high, while water and energy consumption were low and gross regional product was high, compared with the average value of China. The situations in Xinjiang and Inner Mongolia were opposite. The change of consumption pattern for each inhabitant, the adoption of water-saving technology, and an increase to water-saving awareness would be helpful to decrease regional water consumption. An increase of regional energy use efficiency and a change to reduced energy consumption would contribute to the decreasing of regional energy consumption. More attention should be paid to renewable and clean Energies. In addition to solution from the local perspective, the virtual water trade and the energy product trade may relieve regional resource pressure in some extent, and the possible influencing should be considered at the same time. This paper could provide suggestions for regional resource utilization and sustainable development. [ABSTRACT FROM AUTHOR]

Freeze–thaw erosion is one of the three major soil erosions in China, including wind erosion and hydraulic erosion, which leads to the destruction of the natural environment, the imbalance of economic development, a threat to personal safety, and irreversible disaster to the country and people. China's permafrost area accounts for about one-fifth of the country's land area, and the seasonal permafrost area accounts for half of China's land area, mainly concentrated in the Qinghai–Tibet Plateau, Xinjiang Province, Heilongjiang Province, Gansu Province, and other regions. In order to establish an evaluation system for the ecological function reserve of the Greater Hinggan Mountains, nine evaluation indicators were selected from the perspectives of topography, climate, soil, and vegetation conditions. GIS technology, a multiple collinearity test, and principal component analysis were used to comprehensively evaluate the freeze–thaw erosion in the ecological function reserve of the Greater Hinggan Mountains. This study categorized the evaluation results into five intensity levels, from micro to severe. Finally, the degree of influence of different influencing factors on freeze–thaw erosion and the interactions between the factors were analyzed using a geographic detector. The results showed the following: (1) The intensity of freeze–thaw erosion in the study area gradually increased from west to east, and the comprehensive evaluation results were −0.2552 to 0.7581. Overall, moderate, severe, and mild erosion accounted for 29.83%, 25.9%, and 21.54% of the total area of the freeze–thaw zone, respectively. (2) Soil moisture content and the annual range in temperature were the main factors contributing to freeze–thaw erosion. The degree of influence of the two effects on freeze–thaw erosion (q = 0.5997) was better than that of the single-factor effect. [ABSTRACT FROM AUTHOR]

Remote sensing image segmentation with samples imbalance is always one of the most important issues. Typically, a high-resolution remote sensing image has the characteristics of high spatial resolution and low spectral resolution, complex large-scale land covers, small class differences for some land covers, vague foreground, and imbalanced distribution of samples. However, traditional machine learning algorithms have limitations in deep image feature extraction and dealing with sample imbalance issue. In the paper, we proposed an improved full-convolution neural network, called DeepLab V3+, with loss function based solution of samples imbalance. In addition, we select Sentinel-2 remote sensing images covering the Yuli County, Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region, China as data sources, then a typical region image dataset is built by data augmentation. The experimental results show that the improved DeepLab V3+ model can not only utilize the spectral information of high-resolution remote sensing images, but also consider its rich spatial information. The classification accuracy of the proposed method on the test dataset reaches 97.97%. The mean Intersection-over-Union reaches 87.74%, and the Kappa coefficient 0.9587. The work provides methodological guidance to sample imbalance correction, and the established data resource can be a reference to further study in the future. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) are important tools for assessing the historical characteristics and predicting the future characteristics of precipitation, yet the quantitative understanding of how these land–atmospheric coupling models perform in simulating precipitation characteristics remains limited. This study conducts a comprehensive evaluation of precipitation changes simulated by 43 ESMs in CMIP5 and 32 ESMs in CMIP6 in Arid Central Asia (ALL) and its two sub-regions for 1959–2005 with reference to Climate Research Unit (CRU) data, and predicts precipitation changes for 2054–2100. Our analyses suggest the following: (a) no single model consistently outperformed the others in all aspects of simulated precipitation variability (annual averages, long-term trends, and climatological monthly patterns); (b) the CMIP5 and CMIP6 model simulations tended to overestimate average annual precipitation for most of the ALL region, especially in the Xinjiang Uygur Autonomous Region of China (XJ); (c) most model simulations projected a stronger increasing trend in average annual precipitation; (d) although all the model simulations reasonably captured the climatological monthly precipitation, there was an underestimation; (e) compared to CMIP5, most CMIP6 model simulations exhibited an enhanced capacity to simulate precipitation across all aspects, although discrepancies persisted in individual sub-regions; (f) it was confirmed that the multi-model ensemble mean (MME) provides a more accurate representation of the three aspects of precipitation compared to the majority of single-model simulations. Lastly, the values of precipitation predicted by the more efficient models across the ALL region and its sub-regions under the different scenarios showed an increasing trend in most seasons. Notably, the strongest increasing trend in precipitation was seen under the high-emission scenarios. [ABSTRACT FROM AUTHOR]

Irrigation water is the main type of water consumption in the Yanqi Basin irrigation district of Xinjiang, which is an oasis-type irrigation district in the arid region of Northwest China. With the continuous expansion of cultivated areas, there is an increasing demand for irrigation water, resulting in an irrigation efficiency paradox and the phenomenon of "the more water-saving, the more water-scarce". In this study, the water balance method and the improved IWMI (International Water Management Institute) water balance method were used with remote sensing and statistical data from 1980 to 2020 to analyze the changes in the irrigation water supply, consumption, and loss for improvement in irrigation water use efficiency (IWUE) in the Yanqi Basin. The results showed that there was an upward trend in the cultivated land area in the irrigation district of Yanqi Basin, as monitored with remote sensing from 1980 to 2020, and the values from the remote sensing data were higher than those from the yearbooks. According to the remote sensing data, the arable land area in the irrigation district increased from 1672 km2 in 1980 to 2494 km2 in 2020, thus showing a trend of expansion. The traditional water use efficiency in the irrigation district showed an increasing trend. The lowest value for the field water-use coefficient was 0.70 in 1998, and it exceeded to 0.81 from 2009 to 2020. The canal water-use coefficient was as low as 0.50 in 1998 and increased from 0.54 in 2009 to 0.82 in 2020. The irrigation water-use coefficient increased from 0.35 in 1998 to 0.68 in 2020, with a general upward trend. In this study, the water consumption ratio indicator DFg (depleted fraction), determined using the improved water balance method, increased from 0.8390 in 1980 to 0.8562 in 2020, although it showed an overall decreasing trend, and the average was 0.8436. Cultivated land's actual irrigation water consumption per unit area reached the highest value of 8.41 × 106 m3/hm2/a in 2011 and the minimum value of 4.01 × 106 m3/hm2/a in 2020, and from 1980 to 2020 it showed a decreasing trend, while the total water diversion showed an increasing trend due to the continuous expansion of arable land. From 1980 to 2020, water diversion into the irrigation district changed from 1.214 km3 to 1.000 km3, and it reached a maximum of 1.593 km3 in 2000; water diversion into the irrigation district showed an overall upward trend. The positive impact of the post-2000 water conservation phase with the adaptation of water-saving irrigation technology was clear, as the findings showed an increase in IWUE in the Yanqi Basin irrigation district. These results provide a theoretical basis for breaking the paradox of irrigation efficiency, which can be used in the water resource management of irrigation districts. [ABSTRACT FROM AUTHOR]

Groundwater plays an important role in ecological environment protection in arid and semi-arid areas. Therefore, understanding the characteristics of hydrochemical evolution is of great significance for the sustainable use of groundwater in the area of the Tailan River Basin. The Tailan River Basin is located in an arid, ecologically sensitive area in western China. In this study, we collected 42 groups of representative water samples from the Tailan River Basin and analyzed the chemical distribution in the groundwater using mathematical statistics, Piper and Gibbs diagrams, ion ratio analysis, and hydrogeochemical simulation methods. We also discussed the water–rock interactions in the groundwater hydrochemical evolutionary process. The results were as follows: (1) The chemical types of groundwater changed from HCO3·SO4-Ca·Na to SO4·Cl-Na·Ca, Cl·SO4-Na, and Cl-Na, and the total dissolved solids content increased from less than 1 g/L to more than 40 g/L from the gravel plain to the fine soil plain. (2) The Gibbs diagram, the ion ratio analysis, and the saturation index showed that the groundwater chemical characteristics in the study area were mainly controlled by water–rock interactions, as well as evaporation and concentration. Along the runoff of groundwater, halite and gypsum were dissolved. Nevertheless, dolomite and calcite precipitated. The relationship between the chlor-alkali index and [(Na+ + K+)-Cl−] and [(Ca2+ + Mg2+)-(HCO3− + SO42−)] indicated that cation exchange also affects the chemical composition of groundwater in the area. (3) Through reverse hydrogeochemical simulation, the main water–rock effect of the groundwater runoff process revealed by qualitative analysis was quantitatively verified. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an important target in China's efforts to combat the climate crisis. The implementation of carbon neutrality requires high crop yields in farmland ecosystems of arid regions. However, the responses of farmland ecosystems to environmental changes and their effects on the conversion and intensity of carbon sources/sinks within farmlands in arid regions remain unclear, which limits carbon sequestration. In this study, we used a set of eddy covariance systems to observe carbon and water fluxes in cotton and spring maize, two typical crops in arid regions of Northern Xinjiang in China. The carbon and water exchange and water use efficiency (WUE) of cotton and spring maize were evaluated over the entire growth cycle with respect to changes in the environment. Our results show that the carbon sequestration capacity of farmland ecosystems in arid regions is undeniable and is strongly influenced by the growth and development of plants. Spring maize, as a representative of C4 plants, exhibited a 58.4% higher carbon sequestration efficiency than cotton, a C3 plant, and they both reached their carbon sequestration efficiency peak in July. Throughout the growth period, temperature, net surface radiation, and saturated vapor pressure differences (VPD) significantly affected the carbon sequestration capacity and WUE of both crops. Optimal temperatures can maximize the carbon sequestration efficiency of cotton and spring maize; for cotton, they are 20–25 °C, and for spring maize, they are 22–27 °C, respectively. In addition, it is recommended that spring maize be harvested at the end of July when it meets the harvesting standards for silage feed and achieves the maximum carbon sequestration. Afterward, winter crops should be planted to maximize the yield and improve the carbon sequestration capacity of farmlands. [ABSTRACT FROM AUTHOR]

Traditional stress sensitivity experiments are typically conducted under dry conditions, without considering the reservoir's water content. In reality, the presence of water within pores significantly influences the extent of stress sensitivity damage in tight sandstone oil formations, subsequently affecting the determination of stress sensitivity coefficients during experimentation. By investigating sandstone samples from wells in the Mahu Block of China's Xinjiang province, we observed that increasing water saturation reduces the stress sensitivity of tight sandstone. By conducting stress sensitivity experiments under varying water content conditions, we found that the stress sensitivity coefficient is not a constant value but decreases as water saturation increases. Based on experimental comparisons, an optimized power-law model for stress-sensitive damage assessment was refined. By conducting stress-sensitive damage assessment experiments under different water content conditions and integrating the concept of comprehensive compression coefficient, an improved stress-sensitive power-law model was established allowing for the influence of water content. The accuracy of this improved model was increased by 46.98% compared to the original power-law model through experimental validation. The research outcomes can enhance the accuracy of permeability and productivity evaluation, providing valuable guidance for unconventional oil and gas development. [ABSTRACT FROM AUTHOR]

The mountains in northern Xinjiang of China were studied during the snowmelt season. Multi-source fusions of live data of the Chinese Land Data Assimilation System (CLDAS, 0.05° × 0.05°, hourly data) were used as real data, and the Central Meteorological Observatory guidance forecast (SCMOC, 0.05° × 0.05°, forecasting the following 10 days in 3 h intervals) was used as forecast data, both of which were issued by the China Meteorological Administration. The dynamic linear regression and the average filter correction algorithms were selected to revise the original forecast products for SCMOC. Based on the conventional temperature forecast information, we designed four temperature-rise prediction algorithms for essential factors affecting snowmelt. The temperature-rise prediction algorithms included the daily maximum temperature algorithm, daily temperature-rise-range algorithm, snowmelt temperature algorithm, and daily snowmelt duration algorithm. Four temperature-rise prediction values were calculated for each prediction product. The root–mean-squared error algorithm and temperature prediction accuracy algorithm were used to compare and test each prediction algorithm value from the time sequence and spatial distribution. Comprehensive tests showed that the forecast product revised by the average filter algorithm was superior to the revised dynamic linear regression algorithm as well as the original forecast product. Through these algorithms, the more suitable temperature-rise forecast value for each grid point in the study area could be obtained at different prediction times. The comprehensive and accurate temperature forecast value in the mountainous snowmelt season could provide an accurate theoretical basis for the effective prediction of runoff in snowmelt areas and the prevention of snowmelt flooding. [ABSTRACT FROM AUTHOR]

The western Tianshan Mountains region in China has a complex topography where basins, mountains and glaciers co-exist. It is of great significance to study the sensitivity of meteorological factors in this region to different parameterization schemes of climate models. In this paper, the regional climate model RegCM4.5 is used to simulate the meteorological factor (mean temperature, maximum temperature, minimum temperature, precipitation and wind speed) occurring in the western Tianshan Mountains region from 2012 to 2016, so as to investigate the effects of different cumulus convective schemes (Grell, Tiedtke and Emanuel), including land cumulus convective schemes (LCCs) and ocean convective schemes (OCCs) on annual and seasonal simulations of meteorological factor by using the schemes of RUN1 (Grell for LCC and Tiedtke for OCC), RUN2 (Tiedtke for LCC and Emanuel for OCC), RUN3 (Grell for LCC and Emanuel for OCC) and ENS (the ensemble of RUN1, RUN2 and RUN3). The results show that the simulations of annual and seasonal meteorological factors are not significantly sensitive to the combination of LCCs and OCCs. In the annual simulations, RUN2 scheme has the best simulation performance for the maximum, average and minimum temperatures. However, other schemes of precipitation simulation outperform RUN2 scheme, and there is no difference among the four schemes for wind speed simulation. In the seasonal simulations, RUN2 scheme still performs well in the simulation of the average, maximum and minimum temperatures for four seasons, except for the simulation of the average temperature in spring and summer. For the simulation of the maximum temperature in summer, RUN2 scheme performs the same as ENS. For the simulation of other seasons, different meteorological factors have different performances in four seasons. Overall, the results show that different combinations of cumulus convection schemes can improve the simulation performance of meteorological factors in the western Tianshan Mountains of Xinjiang. [ABSTRACT FROM AUTHOR]

Species in the genus Tomentella are distributed throughout the temperate and tropical regions worldwide, but few studies associated with the taxonomy and phylogeny of this genus had been reported from Northwest China. In this paper, molecular phylogenetic analyses of the nuclear ribosomal ITS (internal transcribed spacer: ITS1-5.8S-ITS2) and LSU (large subunit: 28S) sequences combined with morphological characteristics identified three new species from Xinjiang Autonomous Region in Northwest China, which were named T. aurantispora, T. kanasensis, and T. schrenkiana. Similar macromorphological and anatomical characteristics are shared by these new species: arachnoid basidiocarps; byssoid sterile margins; utriform basidia with a clamp connection at the base; the absence of rhizomorphs and cystidia; and slightly thick-walled, subglobose to globose basidiospores. Among these new species, the color of the hymenophoral surface, the size of the basidiospores, and some other features can be used for species delimitation. The new species and closely related species in the phylogenetic tree were discussed, and a key to the identified species of Tomentella from China was provided. [ABSTRACT FROM AUTHOR]

Global drought patterns are substantially impacted by climate change, with far-reaching implications for socioeconomic and ecological systems. Existing global climate models (GCMs) are unable to accurately project precipitation and drought characteristics, particularly in countries or regions with complex topography and significant seasonal variability, such as China. Consequently, the purpose of this study is to assess the efficacy of GCMs, and their multi-model ensemble mean, as well as to investigate the seasonal drought characteristics in China using precipitation data from CMIP6 under various "possible future" scenarios. This study selected five GCMs with historical (1961–2014) and future (2015–2100) periods, namely CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-HR, MPI-ESM1-2-LR, and NorESM2-MM, as well as their ensemble mean ENS-CGMMN. Based on the China Daily Precipitation Analysis Product (CPAP) as the reference precipitation, the performance of these models is evaluated using the DISO index and the quantile mapping (QM) method for calibration, as well as seasonal-scale drought using the standardized precipitation index (SPI) and spatiotemporal variability analysis methods. In comparison to other climate models and the ensemble mean, the calibrated MPI-ESM1-2-HR model can more precisely describe the actual precipitation conditions at the seasonal scale. Under four scenarios, China's climate will shift from arid to moist in the future period (2015–2100) (SSP126, SSP245, SSP370, and SSP585). Autumn and summer will see a considerable increase in China's moisture levels. During the autumn, winter, and spring, the moisture will generally increase in the northern subregions of China, including the Qinghai-Tibet Plateau (QTP), Xinjiang (XJ), Northwest (NW), Northeast (NE), and North China (NC). Dryness will decrease in southern subregions, such as the Southwest (SW) and South China (SC). In contrast to these three seasons, summer in XJ exhibits a distinct trend of aridity, especially in the SSP245 scenario, whereas the NE, NC, and SC exhibit a distinct trend of moisture. To be more specific, the aridity changes in subregions during various seasons under different future climate scenarios vary significantly. This study's findings can provide significant support for future research on climate change and drought, which can help improve the accuracy of future climate projections and serve as a reference for drought risk management and policy formulation. [ABSTRACT FROM AUTHOR]

Developing effective regulatory strategies to enhance irrigation water and fertilizer efficiency in the southern Xinjiang region of China, while simultaneously combatting desertification, is of paramount significance. This study focuses on Chinese jujube in Xinjiang and presents findings from a two-year field experiment aimed at investigating the optimal application strategy of microbial organic fertilizer (MOF). The research aims to provide a scientific foundation for achieving high-quality jujube production. The experiment involved a control group (utilizing only freshwater, referred to as CK) and various combinations of MOF treatments. In 2021, these treatments included M1 (0.6 t/ha), M2 (1.2 t/ha), M3 (1.8 t/ha), and M4 (2.4 t/ha), while in 2022, they encompassed M1 (0.6 t/ha), M2 (1.2 t/ha), M4 (2.4 t/ha), and M5 (4.8 t/ha). Over the two-year trial period, we assessed various indices, including the soil's physical properties, hydraulic characteristics, soil enzyme activities, and relative chlorophyll content. Additionally, we evaluated jujube yield, quality, and economic benefits. The results indicate that MOF application led to significant improvements in soil conditions. Specifically, the average moisture content and profile water storage of the 0–50 cm soil layer increased by 10.98% to 36.42% and 1.8% to 26.8%, respectively. Moreover, in both the 2021 and 2022 experiments, soil saturated water content (SSWC) and water-holding capacity (WHC) increased by 6.25% to 15.98%, while soil hydraulic conductivity (Ks) and bulk density (BD) decreased by 2.91% to 9.88% and 0.63% to 8.08%, respectively. In 2021, MOF application resulted in significant enhancements in soil enzyme activities, with urease activity increasing by approximately 22.5% to 100.5%, peroxidase activity rising by around 24.2% to 148.5%, and invertase activity augmenting by about 5.4% to 32.9%. Notably, the M4 treatment in 2021 demonstrated a substantial jujube yield increase of approximately 19.22%, elevating from 7.65 t/ha to 9.12 t/ha. Based on comprehensive analysis, this study recommends an optimal MOF application rate of approximately 2.4 t/ha. This approach not only provides robust support for the sustainable development of the jujube industry but also serves as a valuable reference for enhancing local soil resilience against desertification. [ABSTRACT FROM AUTHOR]

Surface fine particulate matter (PM) with a diameter of less than 2.5 microns (PM2.5) negatively impacts human health and the economy. However, due to data and model limitations, obtaining high-quality, high-spatial-resolution surface PM2.5 concentration data is a challenging task, and it is difficult to accurately assess the temporal and spatial changes in PM2.5 levels at a small regional scale. Here, we combined multi-angle implementation of atmospheric correction (MAIAC) aerosol products, ERA5 reanalysis data, etc., to construct an STW-LightGBM model that considers the spatiotemporal characteristics of air pollution and estimate the PM2.5 concentration of China's surface at 1 km resolution from 2015 to 2020. Our model performed well, and the fitting accuracy of the 10-fold cross-validation between years was 0.877–0.917. The fitting accuracy of the model was >0.85 at different time scales (month, season, and year). The average slope of the regression prediction was 0.9 annually. The results showed that PM2.5 pollution improved from 2015 to 2020. The average PM2.5 concentration decreased by 4.55 μg/m3, and the maximum decrease reached 90.51 μg/m3. The areas with high PM2.5 concentrations were predominantly in the North China Plain, Sichuan Basin, and Xinjiang in the west, and the levels in areas with elevated PM2.5 levels were consistent across most study years. The standard deviation ellipse for PM2.5 in China showed a 'northeast–southwest' spatial distribution. From an interannual perspective, the average values of the four seasonal stations in the country showed a downward trend from 2015 to 2020, with the most obvious decline in winter, from 70.67 μg/m3 in 2015 to 46.75 μg/m3 in 2020. Compared to earlier inversion studies, this work provides a more stable and accurate method for obtaining high-resolution PM2.5 data, which is necessary for local air governance and environmental ecological construction at a fine scale. [ABSTRACT FROM AUTHOR]

Grassland ecosystems are an important component of global terrestrial ecosystems and play a crucial role in the global carbon cycle. Therefore, it is important to study the carbon dioxide (CO2) process in the Middle Tien Shan grassland ecosystem, which can be regarded as a typical representative of the mountain grasslands in Xinjiang. Eddy covariance (EC) and the global carbon fluxes dataset (GCFD) were utilized to continuously monitor the Middle Tien Shan grassland ecosystem in Xinjiang throughout the 2018 growing season. The findings revealed notable daily and monthly fluctuations in net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco). On a daily basis, there was net absorption of CO2 during the day and net emission during the night. The grassland acted as a carbon sink from 6:00 to 18:00 and as a carbon source for the remaining hours of the day. On a monthly scale, June and July served as carbon sinks, whereas the other months acted as carbon sources. The accumulated NEE, GPP, and Reco during the growing season were −329.49 g C m−2, 779.04 g C m−2, and 449.55 g C m−2, respectively. On the half-hourly and daily scales, soil temperature (Ts) was the main contributor to CO2 fluxes and had the greatest influence on the variations in CO2 fluxes. Additionally, air temperature (Ta) showed a strong correlation with CO2 fluxes. The grassland ecosystems exhibited the strongest CO2 uptake, reaching its peak at soil temperatures of 25 °C. Moreover, as the air temperatures rose above 15 °C, there was a gradual decrease in NEE, while CO2 uptake increased. The applicability of GCFD data is good in the grassland ecosystem of the Middle Tien Shan Mountains, with correlations of 0.59, 0.81, and 0.73 for NEE, GPP, and Reco, respectively, compared to field observations. In terms of remote sensing spatial distribution, the Middle Tien Shan grassland ecosystem exhibits a carbon sink phenomenon. [ABSTRACT FROM AUTHOR]

Soil salinization is a major obstacle to land productivity, crop yield and crop quality in arid areas and directly affects food security. Soil profile salt data are key for accurately determining irrigation volumes. To explore the potential for using Landsat 8 time-series data to monitor soil salinization, 172 Landsat 8 images from 2013 to 2019 were obtained from the Alar Reclamation Area of Xinjiang, northwest China. The multiyear extreme dataset was synthesized from the annual maximum or minimum values of 16 vegetation indices, which were combined with the soil conductivity of 540 samples from soil profiles at 0~0.375 m, 0~0.75 m and 0~1.00 m depths in 30 cotton fields with varying degrees of salinization as investigated by EM38-MK2. Three remote sensing monitoring models for soil conductivity at different depths were constructed using the Cubist method, and digital mapping was carried out. The results showed that the Cubist model of soil profile electrical conductivity from 0 to 0.375 m, 0 to 0.75 m and 0 to 1.00 m showed high prediction accuracy, and the determination coefficients of the prediction set were 0.80, 0.74 and 0.72, respectively. Therefore, it is feasible to use a multiyear extreme value for the vegetation index combined with a Cubist modeling method to monitor soil profile salinization at a regional scale. [ABSTRACT FROM AUTHOR]

The recent development in remote sensing imagery and the use of remote sensing detection feature spectrum information together with the geochemical data is very useful for the surface element quantitative remote sensing inversion study. This aim of this article is to select appropriate methods that would make it possible to have rapid economic prospecting. The Qishitan gold polymetallic deposit in the Xinjiang Uygur Autonomous Region, Northwest China has been selected for this study. This paper establishes inversion maps based on the contents of metallic elements by integrating geochemical exploration data with ASTER and WorldView-2 remote sensing data. Inversion modelling maps for As, Cu, Hg, Mo, Pb, and Zn are consistent with the corresponding geochemical anomaly maps, which provide a reference for metallic ore prospecting in the study area. ASTER spectrum covers short-wave infrared and has better accuracy than WorldView-2 data for the inversion of some elements (e.g., Au, Hg, Pb, and As). However, the high spatial resolution of WorldView-2 drives the final content inversion map to be more precise and to better localize the anomaly centers of the inversion results. After scale conversion by re-sampling and kriging interpolation, the modeled and predicted accuracy of the models with square interpolation is much closer compare with the ground resolution of the used remote sensing data. This means our results are much satisfactory as compared to other interpolation methods. This study proves that quantitative remote sensing has great potential in ore prospecting and can be applied to replace traditional geochemical exploration to some extent. [ABSTRACT FROM AUTHOR]

Whether or not large-scale vegetation restoration will lead to a decrease in regional terrestrial water storage is a controversial topic. This study employed the Geodetector model, in conjunction with observed and satellite hydro-meteorological data, to detect the changes in terrestrial water storage anomaly (TWSA) and to identify the contributions of climate change and vegetation greening across China during the years 1982–2019. The results revealed that: (1) during the period of 1982–2019, TWSA showed a downward trend in about two thirds of the country, with significant declines in North China, southeast Tibet, and northwest Xinjiang, and an upward trend in the remaining third of the country, with significant increases mainly in the Qaidam Basin, the Yangtze River, and the Songhua River; (2) the positive correlation between normalized vegetation index (NDVI) and TWSA accounts for 48.64% of the total vegetation area across China. In addition, the response of vegetation greenness lags behind the TWSA and precipitation, and the lag time was shorter in arid and semi-arid regions dominated by grasslands, and longer in relatively humid regions dominated by forests and savannas; (3) furthermore, TWSAs decreased with the increase in NDVI and evapotranspiration (ET) in arid and semi-arid areas, and increased with the rise in NDVI and ET in the humid regions. The Geodetector model was used to detect the effects of climate, vegetation, and human factors on TWSA. It is worth mentioning that NDVI, precipitation, and ET were some of the main factors affecting TWSA. Therefore, it is essential to implement rational ecological engineering to mitigate climate change's negative effects and maintain water resources' sustainability in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Snowstorms frequently hit large parts of the Northern Hemisphere, and their causative factors have been drawing increasing attention in recent years. As the first in-depth study on the mechanisms of a snowstorm associated with a low-level cold front (LLCF) and low-level westerly jet (LLWJ) in the western mountainous region of the Junggar Basin, Xinjiang, based on both observations and numerical simulation, the major findings of this work are as follows: At the early stage, instabilities were mainly dominated by inertial instability (II) occurring near the core region of the LLWJ, while the lower level was mainly controlled by the baroclinic component of moist potential vorticity (MPV2), which was mainly contributed by the vertical shear of the horizontal wind, which is also located near the LLWJ. At the later stage, II was released significantly, whereas the MPV2 still supported snowfall clouds. Further analysis based on the decomposition of the frontogenetical forcing required for the release of the instabilities indicated that the slantwise term was the major contributor, whereas convergence and deformation also played significant roles at low levels above the windward slope. The slantwise term resulted from the combined effects of baroclinicity due to the LLCF and the inhomogeneity of the momentum due to the LLWJ. [ABSTRACT FROM AUTHOR]

Xinjiang is an important arid region in the northwest of China and plays an important role in the field of ecological security protection in China. Because of its aridity, the identification of critical areas for ecological protection and the optimization of ecological space structure in Xinjiang are of great significance for promoting the harmonious development of the oasis economy, enhancing the ecological environment, and improving human well-being. This study applied an ecological security evaluation from the three dimensions of habitat quality, ecosystem service value, and soil-water conservation to identify the basic situation of the ecological security pattern. The core "source" area of ecological protection was extracted using the morphological spatial pattern analysis (MSPA) method, while the ecological corridor and important ecological nodes were identified using the minimum cumulative resistance model (MCR). The "point-line-plane" three-dimensional ecological network structure was then constructed, providing a case for the development of the ecological security and construction in the oasis. The results showed that in the arid regions of Xinjiang, the ecological land is extremely fragmented and is mainly distributed in the mountains and waters distant from human activities. Overall, there is a substantial geographical disparity with a low level of ecological security, particularly in the ecological marginal areas. The ecological network framework of Xinjiang is characterized by an uneven distribution of "sources", broken corridor structure, and a low degree of networking. Therefore, this study proposed an ecological space layout system consisting of "7 ecological subsystems, 51 source areas, 87 ecological corridors, and 33 ecological nodes" by combining the regional physical and geographical characteristics with the overall development plan. [ABSTRACT FROM AUTHOR]

In this study, the spatiotemporal variations in CH4 concentrations in China from 2003 to 2021 are investigated, and their trends are forecasted over the next decade. Based on the seventh edition standard product retrieved by the atmospheric infrared detector (AIRS) at an altitude of 500 hPa, we verified monthly CH4 products using observational data provided by the World Data Center for Greenhouse Gases (WDCGG) from six ground stations in and around China. The correlation coefficients (R values) between the two data sets ranged from 0.68 to 0.92, signifying the ability of AIRS inversion data to represent temporal and spatial changes in surface CH4 concentrations. Additionally, China was classified into three regions (steps) based on terrain, and the changes in CH4 concentrations were assessed from three perspectives: spatial distribution, interannual variation, and seasonal variation. The results revealed that the CH4 concentration decreased with elevation along a topographic gradient, with high-value areas located in the first and second steps, corresponding to the eastern Qinghai–Tibet Plateau, northern Xinjiang Uygur Autonomous Region, and Inner Mongolia Autonomous Region. Over 19 years, the average increase in CH4 concentration has ranged from 65 to 175 ppb. In addition, the CH4 concentrations were higher during summer and autumn and lower during spring and winter. Finally, a SARIMA model was used to predict the near-surface CH4 concentration trend in China over the next ten years, which indicated a continued seasonal increase. [ABSTRACT FROM AUTHOR]

Simple Summary: Tomato leafminer (Tuta absoluta), an important quarantine pest in China, was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. Its damage has grown in recent years, severely harming Solanaceae plants in China and causing enormous economic losses. Here, tomato leafminer's potential distributions in China under the current climate and four future climate models (SSP1–26, SSP2–45, SSP3–70, and SSP5–85) were predicted using the maximum entropy (MaxEnt) model with ArcGIS software, and the accuracy of the prediction results was tested. Under the four models, the area increased in the suitable region of China, with the smallest increase in SSP1–26 and the greatest increase in SSP5–85. Combined with the prediction results of this study, we can clearly see the future diffusion trend of the tomato leaf moth in China, which has important theoretical significance for the control of the tomato leaf moth in China. Tomato leafminer (Tuta absoluta), an important quarantine pest in China, was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. Its damage has grown in recent years, severely harming Solanaceae plants in China and causing enormous economic losses. The study and prediction of the current and future suitable habitats for tomato leafminer in China can provide an important reference for the monitoring, early warning, and prevention and control of the pest. Here, tomato leafminer's potential distributions in China under the current climate and four future climate models (SSP1–26, SSP2–45, SSP3–70, and SSP5–85) were predicted using the maximum entropy (MaxEnt) model with ArcGIS software, and the accuracy of the prediction results was tested. The areas under the receiver operating characteristic curves of the models were all greater than 0.8, and the test omission rate of the model simulation results basically agreed with the theoretical omission rate, suggesting that the prediction results had satisfactory accuracy and reliability. Under the current climatic conditions, the highly suitable habitats for tomato leafminer in China are mainly distributed in most of North China, most of East China, most of South China, most of Central China, most of Southwest China, some parts of Northeast China, and only a few parts of Northwest China. Annual mean temperature is the main environmental factor limiting the distribution. The suitable habitats for tomato leafminer will shift under different future climate models: Under SSP1–26, the highly suitable habitats will spread to the north and northeast and to the southeast coastal areas; under SSP2–45, the size of highly suitable habitats will grow from the present to 2080 and shrink from 2081 to 2100; under SSP3–70, the highly suitable habitats will spread northeastwards, but the highly suitable habitats in southeast coastal areas will shrink from 2081 to 2100 and turn into moderately suitable habitats. Under SSP5–85, the highly suitable habitats will spread northeastwards and northwestwards, with the size of highly suitable habitats gradually decreasing and the size of moderately suitable habitats increasing. Different climates will lead to different distributions of suitable habitats for tomato leafminer, with annual mean temperature, isothermality, and mean diurnal range as the main environmental influences. [ABSTRACT FROM AUTHOR]

Xinjiang is in northwest China and has abundant desert sand. Replacing natural sand with sand from deserts is an urgent need and could be used in making polyethylene fiber−engineered cementitious composite (PE−ECC). The interfacial bonding properties of desert sand PE−ECC (DSPE−ECC) were made using the optimal mix proportion (30% desert sand content, 2% fiber volume) and the laboratory's previous research results. Normal sand PE−ECC (NSPE−ECC) and DSPE−ECC at different test ages (3, 7, 14, and 28 days) were subjected to uniaxial tensile tests, and a method for determining bonding properties is proposed. Scanning electron microscopy and X-ray diffraction were used to analyze the development of PE−ECC fiber and matrix and the formation of hydration products. The results indicated that the cracking loads of the DSPE−ECC at 3, 7, 14, and 28 days increased by 16.72%, 28%, 23.23%, and 10.05%, respectively. Desert sand had low water content and high water absorption, which slowed down the rate of C2S, C3S combining with water molecules to form C−S−H, and had a great influence on the bonding properties of ECC at 3 days. However, the bonding properties of DSPE−ECC were only slightly less than those of NSPE−ECC at 28 days, and the bonding properties had gradually stabilized. Therefore, the addition of desert sand enhanced the fiber/matrix's bonding properties, and the bonding properties stablized with the increase in curing ages. [ABSTRACT FROM AUTHOR]

The Tarim Basin in Xinjiang is located in the northwest inland arid region of China, but research shows that the region is rich in groundwater resources. To understand the hydrochemical characteristics and water quality of shallow groundwater in the desert area of the southern margin of the Tarim Basin, the groundwater was systematically sampled and tested. The ion characteristics and evolution mechanism of groundwater were analyzed by mathematical statistics, Schukarev classification, Piper three-line diagram, Gibbs model and ion ratio. Water quality was evaluated by the water quality index method (WQI) and irrigation water suitability-related parameters. The results indicated that the dominant cation in the study area is Na+, and the main dominant anions are SO42− and Cl−. According to total dissolved solids (TDS), the groundwater mainly belongs to brackish water and semi-saline water. The hydrochemical chemistry types are mainly Cl·SO4-Na·Mg type, followed by Cl-Na type, and the ion source is mainly the weathering and dissolution of evaporation rock, silicate and sulphate. The hydrochemical process is primarily controlled by evaporation concentration and rock weathering, and the cation exchange is weak. Furthermore, the WQI spatial distribution map shows that the groundwater in the middle of the study area is unsuitable for drinking and there are two areas with high WQI values greater than 500. In contrast, the good-excellent groundwater is scattered in the East. The groundwater generally has high to very high salinity, with significant changes in alkalinity. In addition, 54% of the water samples exceed the magnesium hazard (MH) limit. Therefore, certain measures should be taken before irrigation. This study has important implications for the rational development and reasonable utilization of local groundwater. [ABSTRACT FROM AUTHOR]

Dehydration response element binding factor (DREB) is a family of plant-specific transcription factors, whose members participate in the regulation of plant responses to various abiotic stresses. Prunus nana, also known as the wild almond, is a member of the Rosaceae family that is rare and found to grow in the wild in China. These wild almond trees are found in hilly regions in northern Xinjiang, and exhibit greater drought and cold stress resistance than cultivated almond varieties. However, the response of P. nana DREBs (PnaDREBs) under low temperature stress is still unclear. In this study, 46 DREB genes were identified in the wild almond genome, with this number being slightly lower than that in the sweet almond (Prunus dulcis cultivar 'Nonpareil'). These DREB genes in wild almond were separated into two classes. All PnaDREB genes were located on six chromosomes. PnaDREB proteins that were classified in the same groups contained specific shared motifs, and promoter analyses revealed that PnaDREB genes harbored a range of stress-responsive elements associated with drought, low-temperature stress, light responsivity, and hormone-responsive cis-regulatory elements within their promoter regions. MicroRNA target site prediction analyses also suggested that 79 miRNAs may regulate the expression of 40 of these PnaDREB genes, with PnaDREB2. To examine if these identified PnaDREB genes responded to low temperature stress, 15 of these genes were selected including seven homologous to Arabidopsis C-repeat binding factor (CBFs), and their expression was assessed following incubation for 2 h at 25 °C, 5 °C, 0 °C, −5 °C, or −10 °C. In summary, this analysis provides an overview of the P. nana PnaDREB gene family and provides a foundation for further studies of the ability of different PnaDREB genes to regulate cold stress responses in almond plants. [ABSTRACT FROM AUTHOR]

In maize (Zea mays L.), rational root structure promotes high grain yield under dense sowing conditions. This study was conducted at Qitai Farm in Xinjiang, China, in 2019 and 2021. A traditional wide and narrow row planting method was adopted, with wide rows of 0.7 m and narrow rows of 0.4 m. The cultivars DH618 and SC704, which have grain yield potentials of 22.5 and 15 Mg ha−1, respectively, were selected for study of the root structure and distribution characteristics under high-yield and high-density planting conditions. The highest yield (20.24 Mg ha−1) was achieved by DH618 under a planting density of 12 × 104 plants ha−1. The root structure of DH618 was well developed at that planting density, and the root dry weight (RDW) was 17.49 g plant−1 and 14.65 g plant−1 at the silking and maturity stages, respectively; these values were 7.56% and 11.86% higher, respectively, than those of SC704. At the silking stage, the proportions of RDW at soil depths of 0–10, 10–20, 20–40, and 40–60 cm were 66.29%, 11.83%, 16.51%, and 5.38%, respectively, for DH618; over the 20–60 cm soil layer, this was an average of 4.04% higher than the RDW of SC704. At maturity, the proportions of RDW at soil depths of 0–10, 10–20, 20–40, and 40–60 cm were 61.40%, 11.19%, 17.19%, and 10.21%, respectively, for DH618, which was an average of 9.59% higher than that of SC704 over the 20–60 cm soil layer. At maturity, DH618 roots were mainly distributed in the narrow rows, accounting for 72.03% of the root structure; this was 9.53% higher than the roots of SC704. At silking and maturity, the root weight densities of DH618 were 471.98 g m−3 and 382.98 g m−3, respectively (5.18% and 5.97% higher, respectively, than the root weight densities of SC704). The root lengths of DH618 were 239.72 m plant−1 and 199.04 m plant−1 at the silking and maturity stages, respectively; these were 16.45% and 25.39% higher, respectively, than the root lengths of SC704. The root length densities were 0.58 cm cm−3 and 0.46 cm cm−3 at the silking and maturity stages, respectively, and these were 16.86% and 17.08% higher, respectively, than the root length densities of SC704. This study indicated that the maize hybrid DH618 had a more developed root structure with increased root distribution in the deep soil and narrow rows under high-density planting compared to cultivar SC704, contributing to high grain yield under dense planting. [ABSTRACT FROM AUTHOR]

Wheat stripe rust caused by Puccinia striiformis f. sp. tritici is a destructive disease. Its pathogen frequently adapts to newly invaded regions and overcomes resistance in wheat cultivars. This disease is especially important in China due to its favorable conditions for the stripe rust epidemic and the recombination population structure of pathogens. Xinjiang is a vast epidemic region in China, but very limited research on this disease has been performed in this region. In this study, we identified 25 races from 129 isolates collected from winter wheat fields from five different regions (Nileke, Xinyuan, Gongliu, Huocheng, and Qapqal) of Yili, Xinjiang, using the Chinese set of 19 differential wheat lines. All isolates were virulent on the differentials Fulhad and Early Premium, but no isolates were virulent on Yr5. Among the 25 races, Suwon11-1 was the most prevalent, followed by CYR34. Both races were found in four out of the five locations. It is important to continue monitoring stripe rust and its pathogen races in this region, as it forms a pathway between China and Central Asia. Collaborative research is essential for controlling stripe rust in this region, other regions in China, and neighboring countries. [ABSTRACT FROM AUTHOR]

Snow on the Tibetan Plateau (TP) is an important signal for the prediction of East Asian climate. In this study, the relationship between the TP spring snowmelt and spring and summer precipitation in Northwest China (NWC) was investigated, along with the possible mechanisms linked to the impacts of snowmelt on precipitation. The results showed that the TP spring snowmelt had significant impacts on spring and summer precipitation in NWC. For example, when there was a large spring snowmelt in the central- eastern TP, the spring and summer precipitation in the Hexi Corridor and southeast NWC was excessive, especially in summer; when there was a large spring snowmelt in the northern TP, the spring and summer precipitation was deficient across the whole of NWC, while a large spring snowmelt in the western TP led to deficient spring and summer precipitation in eastern NWC but excessive precipitation in western NWC. The possible mechanisms for this included the fact that more spring snowmelt over the TP led to higher soil moisture contents, which further resulted in weakened subtropical westerly and enhanced ridge over Xinjiang. By changing the TP thermal forcing, these anomalous atmospheric circulation conditions transported water vapor into NWC, thus creating excessive summer precipitation in that region. [ABSTRACT FROM AUTHOR]