Search

Xinjiang is a key area for implementing the Belt and Road Initiative, as well as an ecological security barrier in Northwest China. In this study, the remote sensing ecological index (RSEI) was constructed on the basis of the Google Earth Engine (GEE) platform combined with multiperiod (MODIS) remote sensing imagery to analyze the land use changes in Xinjiang and their impacts on the ecological and environmental quality from 2000 to 2023. The results are as follows. (1) The areas of land use changes in Xinjiang are concentrated mainly in the oasis areas around the mountain ranges and the Tarim Basin. (2) The quality of the overall ecological environment of Xinjiang showed an insignificant linear decreasing trend, with an annual rate of change of −0.0009 a−1 (p > 0.05). (3) The spatial distribution of the RSEI in Xinjiang revealed a significant positive spatial correlation and clustering pattern, which was high in the west and low in the east. (4) The increase in the cultivated land area had a positive effect on improving the quality of the ecological environment in Xinjiang. When the cultivated land area increased by 10%, the area of improvement in the quality of the ecological environment increased by 8.8%. [ABSTRACT FROM AUTHOR]

This study presents a one-step multiplex reverse transcription polymerase chain reaction (RT-PCR) method for the simultaneous detection of multiple viruses affecting melon crops. Viruses such as Watermelon mosaic virus (WMV), Cucumber mosaic virus (CMV), Zucchini yellow mosaic virus (ZYMV), Squash mosaic virus (SqMV), Tobacco mosaic virus (TMV), Papaya ring spot virus (PRSV), and Melon yellow spot virus (MYSV) pose a great threat to melons. The mixed infection of these viruses is the most common observation in the melon-growing fields. In this study, we surveyed northern Xingjiang (Altay, Changji, Wujiaqu, Urumqi, Turpan, and Hami) and southern Xingjiang (Aksu, Bayingolin, Kashgar, and Hotan) locations in Xinjiang province and developed a one-step multiplex RT-PCR to detect these melon viruses. The detection limits of this multiplex PCR were 103 copies/μL for ZYMV and MYSV and 102 copies/μL for WMV, SqMV, PRSV, CMV, and TMV. The detection results in the field showed 242 samples were infected by one or more viruses. The multiplex RT-PCR protocol demonstrated rapid, simultaneous, and relatively effective detection of viruses such as WMV, CMV, ZYMV, SqMV, TMV, PRSV, and MYSV. The technique is designed to identify these melon viruses in a single reaction, enhancing diagnostic efficiency and reducing costs, thus serving as a reference for muskmelon anti-virus breeding in Xinjiang. [ABSTRACT FROM AUTHOR]

Traditional villages are one of the basic types of rural revitalisation and one of the important carriers of cultural inheritance. This research is based on the data of 53 traditional villages in the Xinjiang Uyghur Autonomous Region with the aid of the ArcGIS10.8.1 spatial analysis platform. The study identifies the spatial evolution characteristics from the spatial distribution type, distribution direction, distribution density, distribution balance, etc., and explores their influence mechanisms. The study shows that 1. the spatial structure of traditional villages in Xinjiang was analysed as a cohesive structure type by using the nearest neighbour index method, which shows the evolutionary characteristics of the agglomerative tendency to increase gradually. Among them, Changji Hui Autonomous Prefecture and Turpan City have the highest degree of concentration. 2. The establishment and development of traditional villages in Xinjiang is mainly influenced by natural factors such as geographical features and hydrography. Social factors such as population distribution, transport conditions and economic progression have very important implications for the preservation and continuation of traditional villages. [ABSTRACT FROM AUTHOR]

Agricultural water resources in Xinjiang, China, face significant supply and demand contradictions. Agricultural water demand risk is a key factor impacting water resource management. This study employs the copula function (CF) and Monte Carlo (MC) methods to evaluate agricultural water demand risk at 66 stations in Xinjiang. The evaluation is based on the marginal distributions of precipitation (PR) and reference evapotranspiration (RET). The findings classify Xinjiang's precipitation–evapotranspiration relationship into three types: evapotranspiration, precipitation, and transition. Regions south of the Tianshan Mountains (TMs) primarily exhibit evapotranspiration characteristics. The Ili River Valley and areas north of the TMs display precipitation characteristics. Other areas north of the TMs have transitional characteristics. Both annual precipitation and RET in Xinjiang follow the Generalized Extreme Value (GEV) distribution. The Frank CF effectively describes the coupling relationship between precipitation and RET, revealing a negative correlation. This negative correlation is stronger north of the TMs and weaker to the south. The agricultural water demand risk in Xinjiang varies significantly across regions, with the precipitation–RET relationship being a crucial influencing factor. The demand index (DI) for agricultural water decreases as the risk probability (RP) increases. The stability of the DI is greatest in evapotranspiration-type regions, followed by transition-type, and weakest in precipitation-type regions. When the RP is constant, the DI decreases in the order of evapotranspiration, transition, and precipitation types. This study quantifies the spatial pattern of agricultural water demand risk in Xinjiang. The advantage of the CF–MC method lies in its ability to assess this risk without needing crop planting structures and its ability to evaluate spatial variations. However, it is less effective in areas with few meteorological stations or short monitoring periods. Future efforts should focus on accurately assessing water demand risk in data-deficient areas. The findings are crucial for guiding the regulation and efficient use of agricultural water resources in Xinjiang. [ABSTRACT FROM AUTHOR]

Lake ice phenology directly reflects local climate changes, serving as a key indicator of climate change. In today's rapidly evolving climate, utilizing advanced remote sensing techniques to quickly extract long-term lake ice phenology features and studying their correlation with other climate factors is crucial. This study focuses on lakes in Xinjiang, China, with a mountainous area greater than 100 km2, including Sayram Lake, Ayahkum Lake, Achihkul Lake, Jingyu Lake, and Ahsaykan Lake. The Bayesian ensemble change detection algorithm was employed to extract lake ice phenology information, and the Mann–Kendall (MK) non-parametric test was used to analyze trends. The visual interpretation method was used to interpret the spatial evolution characteristics of lake ice, and the Pearson correlation coefficient was used to explore the driving factors of lake ice phenology. Results indicate the following: (1) Jingyu Lake exhibited the most significant delay in both freezing and complete freezing days, while Ayahkum Lake showed the most stable pattern. Ahsaykan Lake demonstrated the least delay in both starting and complete melting days. (2) Sayram Lake's ice evolution was unstable, with wind causing variability in the locations where freezing begins and melting spreading from the west shore. Ayahkum Lake, Ahsaykan Lake, and Jingyu Lake exhibited similar seasonal variations, while Achihkul Lake's ice spatial changes spread from the east to the center during freezing and from the center to the shore during melting. (3) The study found that the freeze–thaw process is influenced by a combination of factors including lake area, precipitation, wind speed, and temperature. [ABSTRACT FROM AUTHOR]

With the advancement of modernization, traditional bazaars have encountered challenges, such as diminished vitality. Concurrently, the trend of integrating cultural spaces into bazaars has become increasingly evident. Understanding the relationship between bazaars and cultural spaces, as well as the preferences of users of these spaces, is crucial for enhancing bazaar vitality. Employing field research, questionnaire surveys, cross-analysis, and the narrative preference method, this paper compares the bazaar cultural spaces of Central Asia and Chinese from four perspectives: the current state of the bazaar, development overview, user preferences, and cultural space type preferences. This aims to deepen the understanding of the commonalities and differences between the two regions, and to explore the development trends of bazaars and their cultural spaces. The study reveals that (1) Spaces with diversified functions, high accessibility, and openness can enhance the vitality of the bazaar; (2) There exists a synergistic, mutually beneficial relationship between the bazaar and the cultural spaces; (3) Central Asian residents place greater emphasis on the environmental quality of the bazaar and the engaging content of its cultural spaces. In contrast, Chinese residents are more focused on the accessibility of the bazaar and the openness of the cultural spaces; (4) The function of art and culture is the preferred type of cultural space in the bazaar among residents of both regions. This study significantly contributes to the planning, design, and optimization of bazaars and their cultural spaces. [ABSTRACT FROM AUTHOR]

Vegetation net primary productivity (NPP) is a key indicator for assessing vegetation dynamics and carbon cycle balance. Xinjiang is located in an arid and ecologically fragile region in northwest China, but the current understanding of vegetation dynamics in the region is still limited. This study aims to analyze Xinjiang's NPP spatial and temporal trends, using random forest regression to quantify the extent to which climate change and human activities affect vegetation productivity. CMIP6 (Coupled Model Intercomparison Project Phase 6) climate scenario data help assess vegetation restoration potential and future risks. Our findings indicate that (1) Xinjiang's NPP exhibits a significant increasing trend from 2001 to 2020, with three-quarters of the region experiencing an increase, 2.64% of the area showing significant decrease (p < 0.05), and the Ili River Basin showing a nonsignificant decreasing trend; (2) precipitation and radiation are major drivers of NPP variations, with contribution ratios of 35.13% and 30.17%, respectively; (3) noteworthy restoration potential exists on the Tian Shan northern slope and the Irtysh River Basin, where average restoration potentials surpass 80% relative to 2020, while the Ili River Basin has the highest future risk. This study explores the factors influencing the current vegetation dynamics in Xinjiang, aiming to provide references for vegetation restoration and future risk mitigation, thereby promoting sustainable ecological development in Xinjiang. [ABSTRACT FROM AUTHOR]

The Northern Slope of the Tianshan Mountains (NSTM) is characterized by complex and diverse terrain, which represents a fragile ecological environment. Soil wind erosion is a key factor affecting the natural ecosystem and the social development of the region, but it has not been well understood until now. In this study, the revised wind erosion equation (RWEQ) was employed to display the spatial and temporal characteristics of soil wind erosion in the NSTM from 2000 to 2018. In addition, the main driving factors of wind erosion were analyzed. The results showed that approximately 94.25% of the NSTM experienced soil wind erosion, with a multi-year average actual soil wind erosion modulus of 6556.40 t·km−2·a−1. From 2000 to 2018, the actual soil wind erosion modulus in the NSTM showed a trend of fluctuational increase, with an increase rate of 44.65 t·km−2·a−2, but the area affected by soil wind erosion exhibited a downward trend. The wind erosion rate decreased in 76.38% of the total area, except for some areas such as Hami, with an increasing trend of soil wind erosion. The wind factor in RWEQ showed a significant linear relationship with the soil wind erosion modulus (r = 0.62, p < 0.01). Land use changes also have a critical impact on the soil wind erosion. The results of geographical detectors show that the combined effect of weather factor and vegetation factor can explain more than 60% of the changes in soil wind erosion. [ABSTRACT FROM AUTHOR]

Simple Summary: Camels are one of the important economic animals in China; however, their health is often threatened by helminth. This study investigated the prevalence of helminth in camels by collecting 435 samples from five regions in Xinjiang using two methods. The results showed that 18.2% of the camels were infected with helminths, with the highest prevalence observed in Urumqi. Camels under three years old were found to be more susceptible. This study identified three major parasites (Trichostrongylus spp., Chabertia ovina, and Haemonchus contortus) in camels, and most camels were found to be simultaneously infected with multiple parasites. This research is crucial for formulating effective strategies to prevent and control camel parasites, and it contributes to improving the health and production efficiency of camels. Camels, vital to economies in Asia, Africa, and the Arabian Peninsula, have been domesticated for over 4000 years. They thrive in arid regions like Xinjiang, China, but face challenges from internal and external parasites, particularly gastrointestinal parasites, which impact health, meat and milk quality, and production efficiency. This study investigates the prevalence of gastrointestinal helminth infections in camels from five major regions in Xinjiang. We collected 435 fresh fecal samples and used the saturated saline flotation method and McMaster's method for detection. Molecular examination followed. The overall prevalence was 18.2% (95% confidence interval [CI]: 14.7–22.2%), with Urumqi showing the highest prevalence (29%, 95% CI: 23.4–35.1%) compared to other regions (odds ratio [OR]: 4.62, 95% CI: 2.63–8.41%). Younger camels (≤3 years old) were more likely infected by the parasites after adjusting for the region differences (OR: 10.53, 5.12–24.65%). However, we found no evidence that the prevalence was different between male and female camels. PCR analysis identified Trichostrongylus spp., Chabertia ovina, and Haemonchus contortus as predominant parasites, with observed co-infections indicating a complex parasitic landscape. The findings provide essential epidemiological data for effective parasite control strategies. [ABSTRACT FROM AUTHOR]

The ecological and environmental problems of arid zones have become an urgent global concern. Current research on ecological risk is based mainly on the dominant functions of land use, with a primary focus on land use landscape projections and less consideration of potential risks to ecosystems, system resilience and interactions between nature and future sustainable development. In this study, a potential–connectivity–resilience ecological risk assessment model based on the SDGs was constructed using multisource data to spatially quantify indicators at the grid scale in the Turpan and Hami regions of Xinjiang, China. This model was used as a basis for studying ecological risk in arid zones from a production–living–ecological space (PLES) perspective. The results revealed that, during the period 2000–2020, PLESs in the Turpan and Hami regions presented significant spatial similarity, with an increasing trend in overall risk. The production space in the Turpan and Hami regions showed a parabolic trend of increasing and then decreasing, whereas the living space and ecological space in the Hami region showed continuous linear upward trends. The state of ecological security in the Turpan and Hami regions is gradually deteriorating, and comprehensive ecological protection and restoration measures are urgently needed to rationally allocate the structure and layout of the production-–living-–ecological space. The study of ecological risk from a PLES perspective not only helps in fully understanding the development trend of the arid zone; it also provides new ideas and methods for evaluating regional ecological environmental safety and scientific references for formulating regional sustainable development, ecological risk prevention and control and the rational allocation of resources. [ABSTRACT FROM AUTHOR]

The coupling and coordination of humans and natural systems, as the core of geographical research, is an important issue that social development needs to confront and explore. The study of the coupling and coordination of the human–natural system in Xinjiang, as well as the obstacles, is of great significance for its ecological environment and social development. This study establishes a multidimensional index system for the coupling of the human–natural system in Xinjiang. The comprehensive evaluation index and coupling coordination degree of the human–natural system from 2013 to 2020 were calculated, using weighted methods and a coupling coordination evaluation model. The main obstacles to the development of coupling and coordination in Xinjiang were identified, with the aid of a barrier model. The study indicates: (1) the human–natural system composed of ecological environment, urban–rural livability, cultural characteristics, civil harmony, and green development reflects the comprehensive development level of Xinjiang; (2) from 2013 to 2020, the sustainable development of the human–natural system in Xinjiang was good, with an upward trend in the evaluation index; (3) from 2013 to 2020, the level of coupling and coordination of the human–natural system in Xinjiang improved, transitioning from low to high levels; (4) from 2013 to 2020, the main factors impeding the coordinated development of the human–natural system changed. In addition to urban–rural differences and water resource conditions, medical conditions and carbon emissions also became major influencing factors on the coupling and coordination degree of the human–natural system in arid regions. Therefore, the research on the coupling and coordination relationship of the human–natural system and the analysis of obstacles in Xinjiang can provide scientific basis for the high-quality sustainable development and the construction of a beautiful Xinjiang. [ABSTRACT FROM AUTHOR]

The increase in atmospheric CO2 leads to global warming and ecological environment deterioration. Carbon storage modeling and assessment can promote the sustainable development of the ecological environment. This paper took Xinjiang as the study area, analyzed the spatial and temporal evolution of land use in four periods from 1990 to 2020, explored the spatial relationship of carbon stocks using the InVEST model, and coupled the GMOP model with the PLUS model to carry out multiple scenarios for the future simulation of land use in the study area. We found (1) Over time, the types with an increasing area were mainly impervious and cropland, and the types with a decreasing area were grassland, snow/ice, and barren; spatially, the types were predominantly barren and grassland, with the conversion of grassland to cropland being more evident in the south of Northern Xinjiang and north of Southern Xinjiang. (2) The evolutionary pattern of terrestrial carbon stocks is increasing and then decreasing in time, and the carbon sink areas are concentrated in the Tarim River Basin and the vicinity of the Ili River; spatially, there are differences in the aggregation between the northern, southern, and eastern borders. By analyzing the transfer in and out of various categories in Xinjiang over the past 30 years, it was obtained that the transfer out of grassland reduced the carbon stock by 5757.84 × 104 t, and the transfer out of Barren increased the carbon stock by 8586.12 × 104 t. (3) The land use layout of the sustainable development scenario is optimal under the conditions of satisfying economic and ecological development. The reduction in terrestrial carbon stocks under the 2020–2030 sustainable development scenario is 209.79 × 104 t, which is smaller than the reduction of 830.79 × 104 t in 2010–2020. Land optimization resulted in a lower loss of carbon stocks and a more rational land-use layout. Future planning in Xinjiang should be based on sustainable development scenarios, integrating land resources, and achieving sustainable economic and ecological development. [ABSTRACT FROM AUTHOR]

In an arid climate with minimal rainfall, plant growth is constrained by water scarcity and soil salinity. Ecological Water Conveyance (EWC) can mitigate degradation risks faced by riparian plant communities in these regions. However, its effects on long-term dynamics of root zone soil water content, salt levels, and root water uptake remain unclear. This study examined how groundwater affects salt and water dynamics, in addition to root water uptake, under different scenarios involving Tamarix ramosissima Ledeb. The research was conducted in the lower reaches of the Tarim River in northwestern China. The Hydrus-1D model was used, following the EWC strategy. The results show that the distribution of T. ramosissima roots was significantly influenced by soil water and salt distributions, with 56.8% of roots concentrated in the 60–100 cm soil layer. Under water stress conditions, root water uptake reached 91.0% of the potential maximum when considering water stress alone, and 41.0% when accounting for both water and salt stresses. Root water uptake was highly sensitive to changes in Depth-to-Water Table (DWT), notably decreasing with lower or higher DWT at 40% of the reference level. EWC effectively enhances root water uptake by using water to leach salts from the root zone soil, with optimal results observed at 500–600 mm. This study advocates for sustainable EWC practices to support vegetation and combat desertification in the lower reaches of arid inland rivers. [ABSTRACT FROM AUTHOR]

Climatic comfortability serves as a crucial factor in tourism decision making; however, there remains a gap in evaluating the climate comfort conditions specifically for forest therapy. We developed a new index—Forest Therapy Climate Comfort Index (FTCCI)—to evaluate the climate comfort conditions for forest therapy by integrating the Temperature (T), Temperature and Humidity Index (THI), and Wind Efficiency Index (WEI). A total of 26 potential forest therapy bases were selected from the protected areas in Xinjiang and divided into five clusters: Aksu cluster, Hami cluster, Altai cluster, Ili and its surrounding cluster, and Urumqi and its surrounding cluster. Based on the monthly observation data from 25 surface meteorological stations in Xinjiang, spanning from 1994 to 2023, employing the Co-Kriging interpolation method, we explored the spatial–temporal variation in FTCCI from June to September and made clear the climate comfort duration across 26 bases in Xinjiang. The results indicated that (1) The variation in T, THI, and WEI in 26 bases demonstrated a consistent pattern of temporal variation. July emerged as the optimal month, followed closely by August, with most indices in both months falling within the comfort level. Conversely, September proved to be the least favorable month due to frigid conditions and discomfort for the human body, whereas June's sensation was slightly more tolerable. (2) The distribution of T, THI, and WEI showed regional heterogeneity. The Urumqi and its surrounding cluster displayed the most favorable conditions for forest therapy, whereas the Aksu cluster showed the poorest performance. (3) There were differences in both FTCCI and climate comfort duration among various clusters in Xinjiang. Overall, excluding Tomur Peak and Nalati (July and August), the remaining 24 bases offered ideal climate comfort conditions for forest therapy from mid to late June through August. Notably, the bases in Urumqi and its surrounding cluster had the longest climate comfort duration, ranging from 3.5 to 4 months. Therefore, reliance on the unique climate, resource, and geographical condition of each base is crucial in creating special forest therapy products that cater to the diverse health needs of tourists. [ABSTRACT FROM AUTHOR]

The Sentinel-2 Multi-Spectral Instrument (MSI) is characterized by short revisit times (5 days), red-edge spectral bands (665 nm and 705 nm), and a high spatial resolution (10 m), making it highly suitable for monitoring water quality in both inland and coastal waters. Unlike SeaWiFS, which can adjust its viewing angles to minimize sunglint, the Sentinel-2 MSI operates with fixed near-nadir angles, which makes it more susceptible to sunglint. Additionally, the complex optical properties of water pose challenges in accurately determining its water-leaving reflectance. Therefore, we compared the effectiveness of six atmospheric correction (AC) algorithms (POLYMER, MUMM, DSF, C2RCC, BP, and GRS) in correcting sunglint using two typical lakes in Xinjiang, China, as examples. The results indicated that POLYMER achieved the highest overall evaluation score (1.61), followed by MUMM (1.21), while BP exhibited the lowest performance (0.62). Specifically, POLYMER showed robust performance at the 665 nm band with RMSE = 0.0012 sr−1, R2 = 0.74, and MAPE = 30.68%, as well as at the 705 nm band with RMSE = 0.0014 sr−1, R2 = 0.42, and MAPE = 38.44%. At the 443, 490, and 560 nm bands, MUMM showed better performance (RMSE ≤ 0.0026 sr−1, R2 ≥ 0.86, MAPE ≤ 28.20%). In terms of band ratios, POLYMER exhibited the highest accuracy (RMSE ≤ 0.093 and MAPE ≤ 22.2%), particularly for the ratio Rrs(490)/Rrs(560) (R2 = 0.71). In general, POLYMER is the best choice for the sunglint correction of Xinjiang's clean lakes. This study assessed the capability of different AC algorithms for sunglint correction and enhanced the monitoring capability of MSI data in clean waters. [ABSTRACT FROM AUTHOR]

In order to deepen the knowledge of the seasonal variation in total cloud cover (TCC) in Xinjiang, China (XJ), a typical arid region, and to broaden the understanding of the seasonal variation in cloud type (CLT) in the region, we used TCC and CLT datasets from the latest generation of the geostationary satellite Fengyun 4A (FY-4A) from 2018 to 2022 to investigate the seasonal variation characteristics of TCC and CLT in XJ. Meanwhile, to verify the accuracy of TCC from FY-4A, ground observation (GROB) TCC datasets from 105 national meteorological stations (NMSs) in XJ and TCC datasets from ERA5 during the same period were used. In addition, the correlation between TCC from FY-4A and meteorological factors from ERA5 was also analyzed in this study. The TCC from FY-4A, GROB, and ERA5 can all well reflect the significant seasonal variation in TCC in XJ, with the highest (lowest) mean TCC and a distribution pattern of high in the southwest (northwest) and low in the northeast (southeast) in spring (fall) in XJ. Although the mean TCC from FY-4A in all four seasons was lower than that from GROB, the two were comparable in spring (44.09% and 47.32%) and summer (42.88% and 43.17%), while there was a significant difference between the two in fall (27.86% and 40.19%) and winter (30.58% and 46.93%) for 105 NMSs in XJ. The TCC from FY-4A was lower (higher) than that from GROB in spring and summer at most NMSs in northern (southern) XJ, while the TCC from FY-4A was lower than that from GROB for the vast majority of NMSs in fall and winter, especially in northern XJ. The seasonal variation in the spatial distribution of different CLTs (clear, water-type, supercooled-type, mixed-type, ice-type, cirrus-type, and overlap-type) from FY-4A exhibited diverse variation characteristics. Water-type (supercooled-water-type) had a high-frequency center of over 30% in the Tarim Basin (Kunlun Mountains) during summer. Mixed-type (ice-type and cirrus-type) had the highest frequency in winter (spring), while overlap-type had the highest frequency in summer. The correlation between TCC and water vapor conditions (total column vertically integrated water vapor, specific humidity at 250 hPa, 500 hPa, and 700 hPa) was positive in XJ. [ABSTRACT FROM AUTHOR]

The Xinjiang region is prone to frequent and complex wind and sand disasters, which present a significant challenge to the sustainable development of local areas. This research uses multi-source data to analyze the spatial distribution of the aeolian environment in Xinjiang, establishes a four-level zoning scheme, and proposes recommendations for ecological management and engineering and control. Results indicate that (1) Xinjiang's aeolian environment and its types exhibit spatial heterogeneity. The aeolian environment types display a high concentration in the eastern region and a low concentration in the western region. Furthermore, the aeolian environment types are concentrated in the basin region. Moreover, the aeolian environment types exhibit a meridional distribution pattern. (2) A four-level zoning system for aeolian environments in Xinjiang was developed, comprising two first-level zones, seven s-level subzones, 22 third-level wind zones, and 31 fourth-level subdivisions. (3) A structural model for a highway sand control system is proposed for aeolian environment types of subdivisions, including fixing-based, combined blocking and fixing, wind-blocking and sand-transferring, and combined blocking and fixing–transferring. The aeolian environment regionalization program proposed in this study can be a scientific reference for relevant departments in formulating and implementing sand prevention and control planning. [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 Dalaku'an mafic–ultramafic intrusion, located in the western segment of the East Kunlun, presents conducive conditions for the magmatic Cu-Ni sulfide deposits. According to the detailed petrographic observation, the amphiboles within distinct rock types were analyzed by EPMA analysis. The crystallization conditions, such as temperature, pressure, oxygen fugacity, and water content of the magma, were calculated to explore the genesis of the intrusion. The amphiboles were divided into three types: Amp-I, characterized by low silicon content but enrichment of aluminum, titanium, and alkali, predominantly comprising Tschermakitic hornblende and Magnesio-hornblende with mantle-derived traits; Amp-II, exhibiting elevated silicon content but diminished levels of aluminum, titanium, and alkali, primarily constituted of Magnesio-hornblende; whereas Amp-III manifests as Actinolitic hornblende, indicative of crustal origins. The calculated temperatures of amphiboles ranged between Amp-I (955–880) °C, Amp-II (852–774) °C, and Amp-III (761–760) °C; the pressures ranged between Amp-I (454–274) MPa, Amp-II (194–93) MPa, and Amp-III (101–84) MPa; the oxygen fugacities (△NNO) ranged between Amp-I (0.93–2.17), Amp-II (1.55–2.52), and Amp-III (1.89); and the water contents (H2Omelt) ranged from (6.69–8.67) to (5.90–7.32). The magma experienced multiple stages of crystallization and underwent complex magma evolution at different depths. The high oxygen fugacity and water content could be attributed to the subduction of the oceanic crust. The magma source of the Dalaku'an intrusion was metasomatized by fluids from subducting plates, thereby originating within a post-collision extension. [ABSTRACT FROM AUTHOR]

Soil pH is crucial for the quality of the farmland and crop growth. The objective of this study is to analyze the spatial and temporal variations of farmland soil pH in Xinjiang (XJ), and to provide a scientific basis for soil improvement and agricultural production optimization. Based on soil pH data from XJ farmland in two periods, 2008~2010 and 2019~2021, geostatistical methods and kriging spatial interpolation techniques were employed to analyze the spatiotemporal changes in soil pH and to investigate the relationship between relevant influencing factors and pH over more than a decade. The results indicate that the spatiotemporal distribution of soil pH in XJ farmlands is uneven. Between 2019 and 2021, the average soil pH was 8.11, generally being on the higher side, with a coefficient of variation (CV) of 3.85%, indicating minimal spatial variability. In the farmland soil of Southern Xinjiang (S-XJ), the average pH value was 8.17, significantly higher than that of Northern Xinjiang (N-XJ), which was 8.10, demonstrating a spatial pattern of "higher in the south, lower in the north". Over the past decade, soil pH in XJ has significantly increased from 8.11 to 8.13, with a 0.05 unit increase in the north and a 0.01 unit increase in the south (p < 0.05). Regionally, Altay saw the largest increase of 0.22 units, while Bortala Mongol Autonomous Prefecture (Bortala) experienced the most significant decrease, dropping by 0.59 units. Furthermore, this study found that factors such as topography, nutrients, and irrigation methods all have certain influences on the spatial distribution of soil pH in XJ farmland, while variations in climate factors and fertilization levels may affect its long-term temporal changes. These research findings will provide new insights for adjusting and updating agricultural management measures related to soil pH regulation in XJ. [ABSTRACT FROM AUTHOR]

Human activities and climate change have profound impacts on the ecological environment of oases in Xinjiang, and it is of great significance to explore the spatial and temporal evolution patterns of ecological environment quality in this region for the sustainable development of Xinjiang. The remote sensing ecological index (RSEI) was extracted from the Google Earth Engine (GEE) platform from 2000 to 2020, and the coefficient of variation and Hurst index were used to reveal the spatial and temporal characteristics and stability of the ecological environment quality of the artificial oasis and natural oasis in Xinjiang. The key factors affecting the ecological environment quality are explored through correlation analysis and geoprobes. The results show that the distribution of the ecological environment in Xinjiang oases is high in the north and low in the south, and the overall quality shows a fluctuating downward trend from 0.210 to 0.189. Artificial oases have higher RSEI values, stability, and sustainability than natural oases. The RSEI in the study area was mainly influenced by humidity, followed by greenness and heat, and dryness had the least influence on the RSEI model. Based on the geodetector, the top three highest contributors were found to be precipitation (PRE) (0.83) > relative humidity (RHU) (0.82) > evapotranspiration (ET) (0.57). Climate is the main factor affecting the ecological quality of oases, and the RSEI can be improved by increasing the proportion of artificial oases. The study aims to provide a scientific basis for the sustainable development of oases in arid zones. [ABSTRACT FROM AUTHOR]

Xinjiang cotton is characterized by high-density planting, which easily leads to competition between the source and sink, the shading of leaves and reproductive organs, and yield reduction. Balancing the relationship between source and sink can promote high and stable cotton yield. In this study, field experiments were conducted by combining the exogenous application of brassinosteroid with a reduction in leaf source to study their effects on the physiological and yield attributes of cotton. The results indicate that brassinosteroid application increased the yield, with a maximum yield increase of 6.3%. The number of bolls per plant increased by 1.3 nos. The photosynthetic rate and dry matter accumulation were enhanced, and the proportion of reproductive organs in the dry matter increased by >4%. Under the reduced leaf source, brassinosteroid application increased the number of new leaves by 20%, delayed the shedding of reproductive organs by 5–10 days, and reduced the average shedding rate by 8.9%. Additionally, the number of bolls increased in the middle and upper parts and at the edge of the plant. The number of bolls increased by 19.4% on the 4th–8th fruiting branches and 60.7% at the edge. Under leaf reduction treatment, brassinosteroid application could generally increase yield. After brassinosteroid application and removing half the leaves of fruiting branches and all leaves of the vegetive branches, the yield was higher than that of the control. Thus, brassinosteroid application could improve the efficiency of the leaf source and promote dry matter accumulation in sinks. Moreover, it could optimize boll distribution and increase yield by reducing reproductive organ shedding. Under the high-density planting of cotton in Xinjiang, leaf source is a slight surplus, and a moderate reduction in plant density is conducive to increasing yield. [ABSTRACT FROM AUTHOR]

As the medium of geological information, groundwater provides an indirect method to solve the secondary disasters of mining activities. Identifying the groundwater regime of overburden aquifers induced by the mining disturbance is significant in mining safety and geological environment protection. This study proposes the novel data-driven algorithm based on the combination of machine learning methods and hydrochemical analyses to predict anomalous changes in groundwater levels within the mine and its neighboring areas induced after mining activities accurately. The hydrochemistry analysis reveals that the dissolution of carbonate and evaporite and the cation exchange function are the main hydrochemical process for controlling the groundwater environment. The anomalous change in the hydrochemistry characteristic in different aquifers reveals that the hydraulic connection between different aquifers is enhanced by mining activities. The continuous wavelet coherence is used to reveal the nonlinear relationship between the groundwater level change and external influencing factors. Based on the above analysis, the groundwater level, precipitation, mine water inflow, and unit goal area could be considered as the input variables of the hydrological model. Two different data-driven algorithms, the Decision Tree and the Long Short-Term Memory (LSTM) neural network, are introduced to construct the hydrological prediction model. Four error metrics (MAPE, RMSE, NSE and R2) are applied for evaluating the performance of hydrological model. For the NSE value, the predictive accuracy of the hydrological model constructed using LSTM is 8% higher than that of Decision Tree algorithm. Accurately predicting the anomalous change in groundwater level caused by the mining activities could ensure the safety of coal mining and prevent the secondary disaster of mining activities. [ABSTRACT FROM AUTHOR]

To address residual plastic film in fields in which mulched drip irrigation technology is applied, a sprayable degradable film (consisting of 1–5% clay, 5–20% humic acid, 0.5–5% crosslinker, and 0.5–5% auxiliary and water) can be used as a superior alternative to the plastic film applied in drip-irrigated fields. A field experiment was conducted in Xinjiang, Northwest China, to test the impacts of five different mulching treatments (SF1, sprayable degradable film applied at 1900 kg ha−1; SF2, sprayable degradable film applied at 1900 kg ha−1; SF3, sprayable degradable film applied at 2500 kg ha−1; PF, plastic film; and NF, no film mulching) on cotton growth and development, yield, and water use efficiency. The results showed that, compared to the NF treatment, sprayable degradable film mulching (SF1, SF2, and SF3) positively impacted the soil hydrothermal environment, promoted root growth, significantly increased plant height and leaf area, and enhanced physiological characteristics, which, in turn, increased yield and water use efficiency by 11.79–15.00% and 21.88–30.21%, respectively. The maximum yield and water use efficiency were observed in the PF treatment, amounting to 5345 kg ha−1 and 1.28 kg m−3, respectively, and they had no significant differences from those in the SF3 treatment. In general, applying moderate amounts of sprayable degradable film at a rate of 2500 kg ha−1 represents an effective agronomic strategy for managing residual film contamination while maintaining stable cotton yields. [ABSTRACT FROM AUTHOR]

Influenced by climate change, significant alterations in vegetation phenology have been observed globally. Grassland phenology is highly sensitive to climate change. However, research on the variations in grassland phenology and its responses to seasonal climatic changes in arid and semi-arid regions remains scarce. This study, utilizing Solar-Induced Chlorophyll Fluorescence (SIF) data, meteorological station data, and grassland type data, employs trend analysis and time series analysis to explore the trends of seasonal climatic variability and the sensitivity response of grassland phenology in Xinjiang to seasonal climates. The findings reveal the following: (1) The region experiences more pronounced warming in winter and spring than in summer and autumn, with ground temperature increments outpacing those of air temperatures. The summer season registers the peak in precipitation volume and rate of increase, where mountainous zones accrue more rainfall compared to basins and plains. The distribution of sunshine duration is characterized by higher values in eastern areas than in the west and more in the plains than in mountainous regions, potentially due to escalating cloudiness, which has contributed to a diminishing trend in sunshine hours across Xinjiang over the past 20 years. (2) Over the past two decades, the perennial greening phase of Xinjiang grasslands has predominantly occurred in early May, showing an overall trend of occurring earlier by approximately 5.47 days per decade, while the yellowing phase mainly occurs at the end of September and the beginning of October, demonstrating a delaying trend (6.61 days/decade). The average length of the growing season is 145 days, generally showing a slightly increasing trend (11.97 days/decade). (3) In spring, the rise in air and ground temperatures, along with increased sunshine duration, all promote grassland growth, leading to an earlier greening phase. Conversely, in autumn, increases in air temperature, ground temperature, and sunshine duration can inhibit grassland growth, resulting in an earlier yellowing phase. Increased precipitation in summer and autumn can delay the yellowing phase and extend the length of the grassland growing season. This research provides new insights into the factors influencing large-scale grassland phenology and offers references for grassland adaptation to future climate changes. [ABSTRACT FROM AUTHOR]

The accelerated urbanization taking place across Xinjiang in recent years has vastly improved the quality of life for people living in the region. However, to achieve rational urban growth and sustainable regional development, a deeper understanding of the spatial and temporal patterns, spatial morphology, and driving factors of urban sprawl is crucial. Nighttime light (NTL) data provide a novel approach for studying the spatial and temporal changes in urban expansion. In this study, based on DMSP-OLS and NPP-VIIRS data, we analyze the spatiotemporal characteristics of urban changes using the standard deviation ellipse and employ the geographical detector to analyze the impact of natural environmental and socioeconomic factors on the dynamic rate of urban expansion. The results reveal the following. (1) The overall accuracy of urban area extraction is above 80%, and the urban area of Xinjiang has expanded about 9.1 times over the past 30 years. Further, the growth rate from 2007 to 2017 exceeds the growth rate from 1992 to 1997, with the center of gravity of urban development shifting to the southwest. (2) The 5a sliding average temperature and average annual precipitation in the study area in 1992–2022 are 6.08 °C and 169.72 mm, respectively, showing a decrease in the urbanization rate followed by an increase, due to a rise in temperature and precipitation levels. (3) By combining the results of geographical detector factor detection and interaction detection, precipitation is determined to be the main controlling factor, while air temperature and GDP are secondary factors. This study presents new findings on the correlation between urban spatial and temporal changes and climate in Xinjiang, thus providing a scientific reference for future research on urban expansion and natural environment evolution. [ABSTRACT FROM AUTHOR]

Prediction of fine particulate matter with particle size less than 2.5 µm (PM2.5) is an important component of atmospheric pollution warning and control management. In this study, we propose a deep learning model, namely, a spatiotemporal weighted neural network (STWNN), to address the challenge of poor long-term PM2.5 prediction in areas with sparse and uneven stations. The model, which is based on convolutional neural network–bidirectional long short-term memory (CNN–Bi-LSTM) and attention mechanisms and uses a geospatial data-driven approach, considers the spatiotemporal heterogeneity effec It is correct.ts of PM2.5. This approach effectively overcomes instability caused by sparse station data in forecasting daily average PM2.5 concentrations over the next week. The effectiveness of the STWNN model was evaluated using the Xinjiang Uygur Autonomous Region as the study area. Experimental results demonstrate that the STWNN exhibits higher performance (RMSE = 10.29, MAE = 6.4, R2 = 0.96, and IA = 0.81) than other models in overall prediction and seasonal clustering. Furthermore, the SHapley Additive exPlanations (SHAP) method was introduced to calculate the contribution and spatiotemporal variation of feature variables after the STWNN prediction model. The SHAP results indicate that the STWNN has significant potential in improving the performance of long-term PM2.5 prediction at the regional station level. Analyzing spatiotemporal differences in key feature variables that influence PM2.5 provides a scientific foundation for long-term pollution control and supports emergency response planning for heavy pollution events. [ABSTRACT FROM AUTHOR]

The fundamental component of the ecological compensation system, as well as the crucial basis for its efficient functioning, is calculating the ecological compensation amount and establishing the ecological compensation standard. This study integrates the ecological footprint with natural capital monetization and other methods by introducing a natural capital accounting system. From the standpoint of natural capital supply and demand, it also builds an accounting framework for ecological compensation standards that is standardized, dynamic, and regionally differentiated while taking local socioeconomic aspects into account. We determined the amount of ecological compensation by using Xinjiang as the research object and calculating and analyzing the features of regional and temporal changes in the monetary and physical quantities of natural capital in Xinjiang from 2010 to 2020. The findings show that from 2010 to 2020, Xinjiang's ecological footprint increased by 1.26 times in physical terms and 1.21 times in monetary terms and that its ecological carrying capacity increased by 4.13% in physical terms and 9.42% in monetary terms. The ecological deficit continues to grow in physical and monetary terms, with a per capita ecological deficit in 2020 of 19.92 s-nha/cap and 70,100 CNY/cap in physical and monetary terms, respectively. The amount of ecological compensation required to be paid in Xinjiang increased from CNY 5659 million to CNY 10,259 million, and the per capita ecological compensation payment standard increased from 259.42 CNY/cap/yr to 396.11 CNY/cap/yr. In summary, Xinjiang's natural capital supply is insufficient to meet the demand for consumption, and the ecological deficit is growing with time, necessitating the payment of ecological compensation. The study's results lay the foundation for formulating and implementing ecological compensation policies in Xinjiang and provide theoretical support for constructing ecological civilization in Xinjiang. In addition, the ecological compensation accounting framework constructed in this study organically integrates natural capital theory, ecosystem services, and socioeconomic influencing factors, which enriches the methodology of accounting for ecological compensation standards, and, at the same time, can be used as a paradigm of a dynamic and equitable ecological compensation accounting framework to further promote its use at different scales and regions. [ABSTRACT FROM AUTHOR]

As the core area of human activities and economic development in the Xinjiang Autonomous Region, the hilly oasis zone of Xinjiang directly affects the regional sustainable development and stability of the ecosystem. Understanding the effects of different geomorphic types on vegetation distribution is crucial for maintaining vegetation growth and development, especially the improvement in the terrestrial ecological environment in arid areas under the background of climate change. However, there are few studies on the effect of spatial differences in detailed geomorphic types on vegetation distribution patterns. Therefore, this paper divides the Xinjiang hilly oasis zone into six geomorphologic level zones and innovatively investigates the influence of detailed geomorphologic types on the spatial distribution of vegetation and vegetation cover. Further, the area proportion of detailed landform types corresponding to different vegetation coverage in each geomorphic area was quantitatively calculated. Finally, the Geodetector method was used to detect the drivers of interactions between vegetation and the environment. The findings are shown as follows: (1) In the same climate zone, the spatial differentiation of landforms has a great influence on the vegetation distribution, manifesting as the significantly different vegetation distribution in different landform types. Grassland is the main vegetation type in the erosion and denudation of Nakayama; cultivated vegetation and meadows have a larger coverage in the alluvial flood plain and alluvial plain; and the distribution of vegetation in the Tianshan economic zone is characterized by obvious vertical zoning with the geomorphology. (2) The landform type and morphological types are the strongest driving factors for vegetation coverage with q values of 0.433 and 0.295, respectively, which effectually fill the gap caused by only using two terrain indicators, slope and elevation, to study the relationship between landforms and vegetation. (3) In addition, the improved nonlinear interaction resulting from the double factor of landform type and slope is 0.486, which has a stronger control on vegetation coverage than the single factor of landform type. These findings are conducive to enhancing the supply services of vegetation to the ecosystem in arid areas as well as providing important scientific guidance for the construction of ecological civilization and sustainable development in Xinjiang. [ABSTRACT FROM AUTHOR]

Soil diversity plays an important role in maintaining ecological balance and ensuring the sustainability of the land. Xinjiang is a typical arid and semi-arid region of China, and the study of Xinjiang soils is significant for understanding soil properties in all such environments. This study applied the moving window technique and the species–area curve model from ecology to establish optimal analysis windows, calculate landscape pattern indices, and reveal soil distribution characteristics in Southern Xinjiang. Additionally, we used geographic detectors to identify the primary influencing factors in different geomorphic regions. The results indicate a positive correlation between soil richness and area in the Southern Xinjiang region. The Tarim Basin, despite being the largest area, shows the lowest diversity and evenness indices. Overall, mountainous areas have higher soil evenness when compared to basins. In terms of natural factors, temperature, precipitation, and topography play a crucial role in the variation of soil diversity in mountainous areas, while parent material has a greater influence in the basin regions. The characteristics of soil diversity vary by region and are influenced by the interactive effects of various natural factors. However, the impact of human activities also requires consideration. The low evenness poses a greater challenge for soil restoration in the basin regions. Soil conservation efforts in arid regions are of paramount importance. The research findings can provide valuable insights for the development of sustainable agriculture, soil conservation, and for addressing climate change challenges in arid regions. [ABSTRACT FROM AUTHOR]

Situated in China's arid and semi-arid zones, the Xinjiang region heavily relies on groundwater for its freshwater supply. This study utilizes data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, covering the years 2003 to 2021, to quantitatively evaluate the temporal and spatial changes in groundwater storage anomalies (GWSA) in the Xinjiang region. Furthermore, we incorporate the HydroSHEDS dataset to examine the spatial variations in groundwater storage anomalies across watersheds of varying scales. Based on our findings, the GWSA decreased during the study period at a mean rate of −0.381 mm/month, marked by a consistent trend and notable interannual variability. In addition, significant regional disparities are observed; while groundwater storage in the southeastern watersheds is on an upward trend, a general decline is noted in the northern and central regions. The most pronounced depletion is detected in the northwest, especially in the Ili River basin and along the western slopes of the Tianshan Mountains. These changes are intricately linked to anthropogenic factors, including population growth and escalating water demands. In response, the study advocates for the development and enforcement of more rigorous and scientifically informed groundwater management strategies to promote sustainable water use in Xinjiang. [ABSTRACT FROM AUTHOR]

China has implemented a series of ecological protection and restoration projects in Tianshan Mountain and Yili Valley in Xinjiang, which have significantly improved regional vegetation coverage. Vegetation improves soil structure through roots, especially increasing non-capillary porosity, which enhances the precipitation infiltration performance, thus reducing surface runoff, increasing the interception and infiltration of groundwater resources, and enhancing regional water retention capacity of soil. In order to quantitatively study the impact of ecological conservation and restoration (represented by fraction of natural vegetation coverage, FVC) on groundwater storage (GWS), we investigated GWS changes in this region, identified the main factors, and quantified their relative impacts. Here, we combined data from the Gravity Recovery and Climate Experiment (GRACE) satellite, GRACE Follow-On (GRACE-FO), and Global Land Data Assimilation System (GLDAS) hydrological model from January 2003 to December 2020 and evaluated GWS changes. We used the variable importance in projection and partial least squares regression methods to determine the main influencing factors. We found that (1) before and after 2012, GWS decreased at a rate of 0.80 cm/yr and 0.75 cm/yr (with statistical significance p < 0.01), respectively. (2) Before 2012, the main factors affecting the decrease in GWS were agricultural planting areas, and after 2012, they were temperature, evaporation, and FVC, with relative contributions of 54.72%, 34.59%, and 10.69%, respectively. FVC has a positive regulating effect on the increase in regional GWS. [ABSTRACT FROM AUTHOR]

Based on the NDVI and climate data from 2000 to 2022, this study systematically investigated the spatial and temporal patterns, trend characteristics, and stability of the NDVI in Xinjiang using the one-way linear regression method, Theil–Sen Median trend analysis, the Mann–Kendall significance test, and the coefficient of variation. Meanwhile, the persistence of the NDVI distribution was analyzed by combining the trend results and Hurst index. Finally, partial correlation analysis was used to deeply explore the response mechanisms of interannual and seasonal-scale NDVI and climatic factors in Xinjiang, and the characteristics of multi-year vegetation distribution were comprehensively analyzed with the help of human footprint data. The findings indicate the following: (1) The NDVI of interannual and seasonal vegetation in Xinjiang showed a significant increasing trend during the 23-year period, but the spatial distribution was heterogeneous, and the improvement of the vegetation condition in the southern part of the region was remarkable. (2) The NDVI is relatively stable across the region. Unlike in other regions, in general, it is difficult to maintain the existing trend in NDVI in the study area for a long period of time, and the reverse trend is more persistent. (3) On the interannual scale, both precipitation and temperature are positively correlated with the NDVI, and the influence of temperature (80.94%) is greater than that of precipitation (63.82%). Precipitation was dominantly positively correlated with the NDVI in spring, summer, and the growing season, while it was negatively correlated with it in autumn. Temperature and NDVI were positively correlated, with the greatest influence in the spring. (4) Human activities had the greatest impact on the areas with low vegetation cover and areas with medium–low vegetation cover, and there was a high degree of overlap between the areas where the interannual human footprints and NDVI showed an increasing trend. The percentage of human footprints that significantly correlated with interannual NDVI was 34.79%. In the future, the protection and management of ecologically fragile areas should be increased to increase desert-vegetation cover. [ABSTRACT FROM AUTHOR]

Reservoirs are essential hydraulic facilities for water resource allocation in Xinjiang. Since the 1950s, many reservoirs have been constructed for oasis water resource utilization in Xinjiang, enhancing the storage capacity of water resources. There are a few intact and open reservoir archives containing both geolocations and hydraulic attributes, such as the reservoir completion year, which can facilitate our understanding of the correlation between hydraulic engineering and oasis expansion. This paper mapped all the reservoirs of Xinjiang using Sentinel-2 MSI images from 2022. It associated their attributes with the reservoir's extent, such as the capacity, area, complete year, altitude, etc., by consulting historical almanac data to establish a full elemental dataset with both geographic and attribute information. Furthermore, the spatial variability and historical process of the reservoirs were discussed against geomorphic information and oasis evolution. The results showed that 804 reservoirs were mapped cumulatively in Xinjiang up to 2022, and 1960–1980 and 2005–2010 are the rapidly developed periods. The construction history of the reservoirs indicates that reservoirs' locations have the spatial tendency to shift from being in oasis plain areas to mountainous areas, and the newly built reservoirs showed a trend of miniaturization in area and maximization in volume. [ABSTRACT FROM AUTHOR]

Ecosystem water use efficiency (WUE) is an important measure of the degree of water–hydrogen coupling and an important indicator for assessing ecosystem responses to climate change. Drought adversely affects ecosystem security, particularly in irrigated agricultural areas; therefore, understanding the relationship between WUE and drought is important. This study revealed the spatial and temporal characteristics of drought in the Manas River Basin, Xinjiang, China, from 2001 to 2020 through multi-source data using standardised anomaly indices and mutation detection. It also quantitatively analysed the hysteresis effect and resilience characteristics of drought for different vegetation types in the study area. The results showed that droughts at a severe level occurred less frequently in most of the study area on average from 2001 to 2020, and that droughts in the vegetation growing season occurred more frequently, particularly in grasslands; the frequency of droughts in woodlands was low. Furthermore, the lag in WUE to drought occurred on a 3-month scale and accounted for 64.0% of the total watershed area. Finally, 38.16% of the regional vegetation ecosystems in the Manas River Basin exhibited drought resistance. In conclusion, our results provide novel insights into the water-use strategies of plants in the study area and will help facilitate WUE optimisation. [ABSTRACT FROM AUTHOR]

Cultivating cotton and sustaining its productivity are challenging in temperate arid regions around the globe. Exploring suitable cotton cultivation areas to improve productivity in such climatic regions is essential. Thus, this study explores the ecologically suitable areas for cotton cultivation using the MaxEnt model, having 375 distribution points of long-staple cotton and various factors, including 19 climatic factors, 2 terrain factors, and 6 soil factors in Xinjiang. The area under the curve (AUC) of the predicted results was greater than 0.9, indicating that the model's predictions had fairly high accuracy. However, the main environmental factors that affected the cotton's growth were the lowest temperature in the coldest month, the hottest month, the precipitation in the driest season, and the monthly average temperature difference. Further, the temperature factors contributed 71%, while the contribution ratio of terrain and soil factors was only 22%. The research indicated that the current planting area was consistent with the predicted area in many areas of the study. Still, some areas, such as the Turpan region northwest of Bayingolin Mongol Autonomous Prefecture, are supposed to be suitable for planting cotton, but it is not planted. The current potential distribution area of long-staple cotton is mainly located in Aksu Prefecture and the northern part of the Kashgar Prefecture region. The climatic prediction shows that the growing area of long-staple cotton may expand to southern Altay, central Aksu, and Bortala Mongol Autonomous Prefecture. This study will be helpful for cotton cultivation suitability areas in Xinjiang and other regions with similar environments. [ABSTRACT FROM AUTHOR]

Heavy metal pollution has been a problem of concern in soil ecology in recent decades. This study investigated the spatial distribution of heavy metals and their pollution levels in the soil of Xinjiang, based on the data of heavy metals published in the literature in the past five years, by using a geostatistical method, pollution index method, and geographic information system (GIS)-based spatial analysis. Additionally, the effects of five economic development indicators, such as population and industrial activities on the accumulation of heavy metals in soil, were explored by correlation analysis. The results showed that the average contents of Cd, Cr, Cu, Ni, Pb, and Zn in the soils were 2.858, 1.062, 1.194, 1.159, 1.192, and 1.086 times higher than the background values in Xinjiang, respectively. The semi-variance functions indicated that the Cd and Pb block gold coefficients of soils were greater than 25% and less than 50%, with an obvious spatial correlation. The spatial patterns showed that the high values of Cd, Cr, Cu, Ni, Pb, and Zn were mainly distributed in Karamay, Changji, Tacheng, and Kashi areas, with an overall decreasing trend from north to south, and the pollution index showed that the pollution of heavy metal Cd in soil was the most serious. Furthermore, Karamay, Changji, and Kashi areas were at heavy pollution levels. Correlation analysis showed that heavy metal Pb in the soil was significantly positively correlated with the agricultural GDP in Xinjiang, while Cd was correlated significantly and positively with comprehensive energy consumption and more significantly with industrial GDP. Thus, this study could provide a scientific basis for local evaluation of soil environmental quality and prevention and control of soil heavy metal pollution, which is of great significance for understanding the impact of human activities. [ABSTRACT FROM AUTHOR]

Arid and semi-arid areas are facing severe land degradation and desertification due to water scarcity. To alleviate these environmental issues, the Chinese government has launched a "water conveyance" project for environmental protection along the Tarim River. While previous studies have mainly focused on environmental conditions, the influence of these policies on land use conditions remains less explored. Therefore, this study first simulated the land use and land cover (LULC) changes in a major city (Korla) around the Tarim River. We found that the water conveyance routes have exerted notable influences on surrounding LULC changes. Next, we primarily focused on the LULC changes among different reaches of the Tarim River. We found that water and forest areas in the lower reaches have increased at the expense of a slight decrease in such areas in the upper and middle reaches, which suggests that the water conveyance policy may also have unintended consequences. These findings could attract the attention of decision makers in many other arid and semi-arid areas, and they could provide practical policy implications for other similar inter-basin water conveyance projects. The benefits and risks of these man-made projects should be carefully balanced. [ABSTRACT FROM AUTHOR]

Xinjiang is located in arid northwest China, which is a key area for promoting the high-quality development of the regional ecological environment. In recent years, against a background of increasing human activities and rapid natural changes, Xinjiang has faced enormous ecological challenges. This paper utilizes land-use data from 2000 to 2020 to verify the region's current state of the ecosystem. Additionally, it uses the value equivalent factor per unit area, ecosystem service value (ESV) loss and gain matrix, and double-factor spatial autocorrelation analysis to study the spatial and temporal variabilities of ESV in Xinjiang and its attribution to spatial correlation. The results show that (1) the ESV in Xinjiang exhibits an overall increasing trend during 2000–2020, with a total increase of about CNY 18.202 billion. Regulation-service ESV takes the main position in the single-service function, accounting for about 67.18% of the total ESV. In northern Xinjiang, the ESV demonstrates a decreasing trend, dropping by about CNY 16.885 billion, while in southern Xinjiang, the ESV shows an increasing trend, rising by CNY 35.086 billion. (2) For the study period, the main loss of ESV in Xinjiang is the conversion of ecological land with a high ESV into cropland or barren land with a low ESV. The conversion of bare land to grassland led to the largest increase in ESV (about CNY 209.308 billion), whereas the conversion of grassland to barren land led to the largest loss (about CNY 183.046 billion). (3) There are positive correlations among ESV, net primary productivity (NPP), and human activity intensity (HAI). However, all of the relationships weaken year by year. The spatial agglomeration of ESV ∩ NPP is significantly greater than that of ESV ∩ HAI, so NPP is the dominant factor in the spatial correlation of ESV in Xinjiang. The findings of this study provide a scientific basis for promoting high-quality regional ecological development in China's arid northwest. [ABSTRACT FROM AUTHOR]

The convection initiation (CI) mechanisms of severe storms have received increasing attention because severe storms have been occurring more frequently around the globe in recent years. In this work, the CI mechanisms of severe convective weather associated with a gust front (GF) which occurred on 9 July 2016, near the Korla at the northern edge of the Tarim Basin, Xinjiang, is investigated using observational data including Doppler weather radar data and automatic weather stations data, and high-resolution numerical simulation data. The results showed that, during the eastward movement of the GF, a number of convective cells were successively triggered in the vicinity of the GF, which developed rapidly and continuously merged with the convective system from behind, resulting in the further development and maintenance of this convective system. According to the diagnostic analysis of vertical acceleration which can be decomposed into dynamic acceleration ( a d ) and buoyant acceleration ( a b ), it was found that both a d (up to ~4 × 10−3 m s−2) and a b (up to ~7 × 10−3 m s−2) made positive contributions to the CI. Further analyses based on the decompositions of the a d and a b revealed that the extension term was the main contributor for the a d , while the warming of the dry air due to the release of latent heat from the precipitation condensate made the major contribution to the a b . The extension term indicates the elevated convergence jointly induced by the airflow of mid-level horizontal convective rolls (MHCRs) and updraft flow near the leading edge of the GF. The jointly induced elevated convergent updraft can be considered to be an important contributor for the CI mechanisms. [ABSTRACT FROM AUTHOR]

In the context of climate warming, flash drought has become increasingly frequent, posing significant threats to agriculture, ecosystems, and the environment. Xinjiang, located in an arid and semi-arid region, necessitates a thorough investigation into the distinctions between flash drought and traditional drought, as well as an exploration of the driving forces behind both types of drought. In this study, soil moisture data from ERA5-Land were utilized to construct a framework for the identification of flash drought and traditional drought based on historical events. The Geodetector was employed to explore the factors that influence the spatial heterogeneity of these two drought forms. The findings illuminate that (1) in terms of spatial distribution, traditional drought predominated in southern Xinjiang, while flash drought exhibited greater prominence in northern Xinjiang. (2) Regarding changes in trends, both flash drought and traditional drought exhibited an increasing trend in frequency since the 1990s, with the frequency trend of flash drought passing the significance test (α ≤ 0.05). Additionally, the severity of both flash drought and traditional drought displayed a noteworthy and statistically significant increase within sliding windows ranging from 46 to 62 years. (3) Concerning the driving forces, precipitation emerged as the principal driving force behind both flash drought and traditional drought. Furthermore, human activities exerted a more substantial influence on traditional drought, and the interactions involving human activities had the potential to significantly amplify the explanatory power of the spatial heterogeneity for both drought types. (4) In terms of the drought risk, a notable variation in the risk of flash drought was observed across various ecological zones, with the highest risk occurring in mildly fragile ecological zones. Furthermore, when comparing the results from 1995 to 2019, the flash drought risk exhibited a marked increase in severely fragile ecological zones. This study enriches the understanding of the dynamics of flash drought and traditional drought in Xinjiang and carries important implications for enhancing the precision of drought monitoring and early warning systems. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing emphasis on combining intelligent prospecting algorithms, such as random forest, with extensive geological and mineral data for the purpose of quantitatively predicting exploration geochemistry. This approach holds significant importance for enhancing the accuracy of target delineation. The central Kunlun area in Xinjiang possesses highly favorable ore-forming geological conditions, offering excellent prospects for mineral exploration. However, the depletion of shallow deposits coupled with a decade-long gap in geological exploration have presented increasing challenges in the quest to discover substantial metal resources. Consequently, there is now a severe shortage of reserve assets in the region, prompting an urgent need for the implementation of new theories, methods, and technologies in mineral resource investigation and evaluation efforts. The researchers used geological and regional geochemical data to construct a random forest metallogenic discriminant model for predicting the mineralization of gold polymetallic minerals in the central Kunlun area of Xinjiang and delineating the metallogenic target area. Two different sampling methods were compared to quantitatively predict gold polymetallic mineral resources. The results indicate that the selected training samples offer higher prediction accuracy and reliability by fully capturing the complex information of the original data. The random forest model using select training samples has valuable applications in metallogenic prospect prediction and potential division due to its ability to consider the actual exploration cost and identify small areas with high potential and a high proportion of ore. This study significantly improves prediction accuracy, reduces exploration risk, and expands the use of machine learning algorithms in mathematical geology in the central Kunlun area of Xinjiang. [ABSTRACT FROM AUTHOR]

Xinjiang is one of the world's most sensitive and vulnerable regions to climate change. However, little is known about the current status and changes in thermal comfort conditions in this area. Using the Universal Thermal Climate Index (UTCI) derived from the newly available high-resolution dataset HiTiSEA, the spatial–temporal pattern and changes thereof over annual and seasonal scales across Xinjiang from 1981 to 2019 were evaluated. The results reveal that the distribution and change of thermal comfort in Xinjiang have apparent regional heterogeneity and seasonal characteristics. Across all scales, 7 of 10 UTCI thermal stress categories were observed, from slight cold stress to strong heat stress. Annually, the mean UTCI is 3 °C and has significantly increased at 0.37 °C decade−1. The mean number of comfortable days (CDs) is 114 days, with a range from 0 to 189 days. On the space scale, the Tarim Basin experiences the highest UTCI value, while the Ili River Valley, the north side of the Tianshan Mountains, and the peripheral areas of the Tarim Basin have a higher number of CDs. Seasonally, summer has the highest UTCI value, while winter is the lowest. The trend for all seasons is upward, and spring increases fastest. Results also indicate that air temperature has a positive correlation with climate comfort, and the influence of air temperature on climate comfort is most significant. Further research indicates that the range and intensity of population exposure to uncomfortable climates in Xinjiang have increased. The distribution and expansion of population exposure are similar to the population density. These findings contribute to a systematic understanding of the local climate environment and can be helpful for the assessment of the impact of climate change and optimize tourism development. [ABSTRACT FROM AUTHOR]

Extreme precipitation events have been occurring frequently worldwide, and their causative factors and convection initiation (CI) mechanisms have been attracting more and more attention in recent years. As a comprehensive study on the CI mechanisms of extreme rainstorms over the northern slope of the Kunlun Mountains (KLM), Xinjiang, based on both observational and high tempo-spatial numerical simulation, the major findings of this work are as follows: A cold pool (CP) was formed in the northwestern Tarim Basin under the influence of early precipitation evaporation, and it moved towards the northern slope of the KLM several hours before the CI. With the movement of the CP, a significant vertical temperature gradient was formed close to the leading edge of the CP, thereby enhancing local convective instability (up to ~10 PVU). In addition, the vertical shear of the horizontal winds at the leading edge of the CP led to a notable increase in the baroclinic component of moist potential vorticity, thus reinforcing the local conditional symmetric instability (up to ~8 PVU), providing another important unstable energy for the CI. In addition, the combined effect of the convergent lifting of a boundary layer jet (BLJ, the maximum wind speed below 1 km exceeding 10 m s−1) and the significant frontogenetical forcing (up to ~100 × 10−8 K m−1 s−1) at the leading edge of the CP were the causes of the release of the unstable energies. Further analysis of the frontogenetical forcing associated with the CP indicates that the convergence (up to ~2 × 10−3 s−1), diabatic heating and slantwise terms (indicates the baroclinicity and inhomogeneity of the vertical momentum in horizontal direction) were the major contributors, whereas the deformation term at the leading edge of the CP provided a relatively weaker contribution. [ABSTRACT FROM AUTHOR]

Current digital soil mapping of soil properties (soil organic carbon, SOC; electrical conductivity, EC; and pH) is mainly based on transfer learning, which is inadequate in terms of accuracy for the northern plain area of Xinjiang. To address this issue, establishing a new model is urgently required that can improve our understanding of the soil properties in this region. To this end, based on the global bioclimatic variables and surface dry–wet and wet–dry transitions, The study developed a spectral–water–heat database (SWHD). The study then incorporated this database and background data into machine learning algorithms (XGBoost, LightGBM, and random forest) to establish models applicable to the study area and draw spatial changes in the key soil properties. Our findings revealed that the organic carbon content was the highest in grasslands, whereas shrublands had high soil salinity. The pH value indicated overall alkalinity in the study area. Additionally, the SWHD-based predictions outperformed the mean or maximum value datasets, with LightGBM showing superior performance among all models. Furthermore, the validation accuracy obtained through our optimal algorithm was significantly higher than that obtained by other products, such as Harmonized World Soil Database (HWSD) and SoilGrid250, likely because of the limitations of these datasets, which may represent historical soil properties rather than current variations in the soil properties in the region. The study also observed that the mean SOC and EC values significantly decreased compared to the historical data, while the decrease in pH was smaller but not significant. Structural equation modeling and variable importance analysis revealed that the variables with the greatest influence on modeling SOC, EC, and pH were BIO10, DTW2021_406-426_B3 (Surface reflectance acquired in spring), and land use type. Our improved model developed based on the SWHD dataset offers important scientific evidence and decision support for land use management and provides a solid foundation for future research in this field. [ABSTRACT FROM AUTHOR]

Irregular tourism seasons and insufficient momentum in the development of new tourism modes disrupt the supply and demand balance between the development of self-driving tourism and the number of corresponding service facilities in Xinjiang. This constrains the growth of regional comprehensive benefits. This paper constructs an index system for evaluating the location suitability of self-driving camps in Xinjiang by the Delphi method; obtains DEM data, GIS data, POI data, and statistical data; and uses a combination of subjective and objective evaluation to calculate index weights. ArcGIS raster analysis and the P-median model were used to study the location suitability and spatial optimization strategies for self-driving tourism camps in Xinjiang. The results of this study are as follows: (1) An evaluation system for the suitability of self-driving camp locations in Xinjiang is constructed from the supply side and the demand side. (2) Self-driving camps in Xinjiang have a large supply capacity gap between counties and cities. (3) The overall suitability of the demand for self-driving camps in Xinjiang is low to moderate. (4) There exists a spatial imbalance in the suitability of the supply and demand for self-driving tourism camps in Xinjiang. (5) A total of 65 campsites were proposed for self-driving tours in Xinjiang considering spatial optimization. (6) Xinjiang should strengthen the matching of self-driving camps with tourism resources and traffic routes, and produce self-driving tour business maps with complete self-driving tour supporting facilities and services. [ABSTRACT FROM AUTHOR]

Xinjiang, in Northwestern China, was a key point in the prehistoric trans-Eurasian network of exchange and played an important role in facilitating the dispersal of crops across Eurasia. Millet crops were first cultivated and used ca. 10,000 years ago in Northern China, from where they spread via different routes, leaving intriguing traces in various sites across Xinjiang. This paper presents the latest data on millet in Xinjiang. By employing a multidisciplinary approach, including radiocarbon dating, archaeobotanical evidence, and carbon isotope datasets, this study explores potential routes by which millet entered Xinjiang and traces its expansion from the third millennium BC to the 10th century AD. The research highlights the significant role of millet in shaping the ancient economies and cultures of Xinjiang and Central Asia, while also underscoring the importance of further investigation to uncover the complex pathways of its dispersal across Eurasia. [ABSTRACT FROM AUTHOR]

Detailed snow cover maps are essential for estimating the earth's energy balance and hydrological cycle. Mapping the snow cover across spatially extensive and topographically complex areas with less or no cloud obscuration is challenging, but the SNPP-VIIRS Day/Night Band (DNB) nighttime light data offers a potential solution. This paper aims to map snow cover distribution at 750 m resolution across the diverse 1,664,900 km2 of Xinjiang, China, based on SNPP-VIIRS DNB radiance. We implemented a swarm intelligent optimization technique Krill Herd algorithm, which finds the optimal threshold value by taking Otsu's method as the objective function. We derived SNPP-VIIRS DNB snow maps of 14 consecutive scenes in December 2021, compared our snow-covered area estimations with those from MODIS and AMSR2 standard snow cover products, and generated composite snow maps by merging MODIS and SNPP-VIIRS DNB data. Results show that SNPP-VIIRS DNB snow maps are capable of providing reliable snow cover maps superior to MODIS and AMSR2, with an overall accuracy level of 84.66%. The composite snow maps at 500 m spatial resolution provided 55.85% more information on snow cover distribution than standard MODIS products and achieved an overall accuracy of 84.69%. Our study demonstrated the feasibility of snow cover detection in Xinjiang based on SNPP-VIIRS DNB, which can serve as a supplementary dataset for MODIS estimations where clouded pixels are present. [ABSTRACT FROM AUTHOR]

Intangible cultural heritage (ICH) is the essence of excellent traditional culture and the treasure of human civilization. At present, major countries pay more and more attention to the study of ICH. Therefore, it is of great significance to study the spatial distribution characteristics of ICH and to understand the factors affecting the development of ICH. Systematically studying the spatial distribution patterns, influencing factors, differentiation characteristics, and formation mechanisms of ICH is essential for effectively promoting its protection and development, guiding the planning of cultural tourism, and implementing cultural power strategies. There are clear differences between municipal and county-level ICH in Xinjiang. The overall distribution trend shows a spatial aggregation structure with more ICH in the north and fewer in the south. ICH resources are concentrated mainly in Kashgar, Yili, Tacheng, Bazhou, and Urumqi, where the Urumqi-Turpan-Korla region is the high-density core area for all types of ICH. Meanwhile, the Yining and Kashgar areas have a large number of non-relics. Ethnic distributions, cultural environments, policy supports, and other social and cultural factors have greater impacts on the spatial distribution of ICH in Xinjiang, while natural geographical environment factors such as runoff water systems and average precipitation have less influence. Interaction studies revealed that the synergistic effects of natural, economic, and social and cultural factors had a more profound influence on the spatial distribution of ICH. Lastly, to promote sustainable development, suggestions were made to optimize the spatial layout, protection, and development of Xinjiang ICH. [ABSTRACT FROM AUTHOR]

Based on the daily observations from 83 meteorological stations in Xinjiang between 1961 and 2020, urban snow disasters were divided into four grades: extremely severe, severe, medium and light. The patterns in the spatiotemporal variability of snow disasters and the relationship between snow disasters and the Northern Hemisphere circulation indices are discussed. The results show that snow disasters were more frequent in the north than in the south, and severe and extremely severe snow disasters mainly occurred in the north. Over the past 60 years, the frequency of medium and above snow disasters has been increasing significantly, while the frequency of light disasters has been decreasing significantly. The areas with significant changes are mainly located in the snow-rich area of Northern Xinjiang. The above changes were more evident during 1991–2020 and occurred in more than 70% of the whole area. Compared to the previous 30 years, the annual average, the maximum and minimum frequency of snow disasters classified as medium and above increased. This is especially true for severe and extremely severe disasters, which increased by more than 70%. Severe and extremely severe snow disasters in the north are significantly and positively correlated with the Northern Hemisphere Polar Vortex Central Intensity Index (NHPVCI), the India-Burma Trough Intensity Index (IBTI) and negatively correlated with AO during the cold season and the winter. Severe snow disasters in the south are positively correlated with the IBTI during winter and autumn. [ABSTRACT FROM AUTHOR]