Search Results (78)

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

Artificial reservoirs in arid regions provide unique ecological environments for studying the spatial and functional dynamics of plankton communities under the combined stressors of climate change and anthropogenic activities. This study conducted a systematic investigation of the phytoplankton community structure and its environmental drivers in 17 artificial reservoirs in the Ili region of Xinjiang in August and October 2024. The Ili region is located in the temperate continental arid zone of northwestern China. A total of 209 phytoplankton species were identified, with Bacillariophyta, Chlorophyta, and Cyanobacteria comprising over 92% of the community, indicating an oligarchic dominance pattern. The decoupling between numerical dominance (diatoms) and biomass dominance (cyanobacteria) revealed functional differentiation and ecological complementarity among major taxa. Through multivariate analyses, including Mantel tests, principal component analysis (PCA), and redundancy analysis (RDA), we found that phytoplankton community structures at different ecological levels responded distinctly to environmental gradients. Oxidation-reduction potential (ORP), dissolved oxygen (DO), and mineralization parameters (EC, TDS) were key drivers of morphological operational taxonomic unit (MOTU). In contrast, dominant species (SP) were more responsive to salinity and pH. A seasonal analysis demonstrated significant shifts in correlation structures between summer and autumn, reflecting the regulatory influence of the climate on redox conditions and nutrient solubility. Machine learning using the random forest model effectively identified core taxa (e.g., MOTU1 and SP1) with strong discriminatory power, confirming their potential as bioindicators for water quality assessments and the early warning of ecological shifts. These core taxa exhibited wide spatial distribution and stable dominance, while localized dominant species showed high sensitivity to site-specific environmental conditions. Our findings underscore the need to integrate taxonomic resolution with functional and spatial analyses to reveal ecological response mechanisms in arid-zone reservoirs. This study provides a scientific foundation for environmental monitoring, water resource management, and resilience assessments in climate-sensitive freshwater ecosystems. Full article

Snow cover variations significantly affect the stability of regional water supply and terrestrial ecosystems in arid northwest China. This study comprehensively evaluates snow resource changes since 2000 by integrating multisource remote sensing datasets and analyzing four key indicators: snow cover area (SCA), snow phenology (SP), snow depth (SD), and snow water equivalent (SWE). The results reveal a slight downtrend in SCA over the past two decades, with an annual decline rate of 7.13 × 10³ km². The maximum SCA (1.28 × 10⁶ km²) occurred in 2010, while the minimum (7.25 × 10⁵ km²) was recorded in 2014. Spatially, SCA peaked in December in the north and January in the south, with high-altitude subregions (Ili River Basin (IRB), Tarim River Region (TRR), North Kunlun Mountains (NKM), and Qaidam Basin (QDB)) maintaining stable summer snow cover due to low temperatures and high precipitation. Analysis of snow phenology indicates a significant shortening of snow cover duration (SCD), with 62.40% of the study area showing a declining trend, primarily driven by earlier snowmelt. Both SD and SWE exhibited widespread declines, affecting 75.09% and 84.85% of the study area, respectively. The most pronounced SD reductions occurred in TRR (94.44%), while SWE losses were particularly severe in North Tianshan Mountains (NTM, 94.61%). The total snow mass in northwest China was estimated at 108.95 million tons, with northern Xinjiang accounting for 66.24 million tons (60.8%), followed by southern Xinjiang (37.44 million tons) and the Hexi Inland Region (5.27 million tons). Consistency analysis revealed coherent declines across all indicators in 55.56% of the study area. Significant SD and SCD reductions occurred in TRR and Tuha Basin (THB), while SWE declines were widespread in NTM and IRB, driven by rising temperatures and decreased snowfall. The findings underscore the urgent need for adaptive strategies to address emerging challenges for water security and ecological stability in the region. Full article

Salix alba L. (Linnaeus, 1753; Salicaceae), a widely distributed riparian species, remains understudied regarding its genetic diversity patterns and driving factors in arid zone ecosystems. In this study, 320 Salix alba samples were collected from 10 geographic unit groups in Xinjiang, China, a typical arid zone, and analyzed using a comprehensive approach that incorporated SSR molecular marker technology with multi-dimensional data on geographic and climatic factors. The analysis revealed that: (1) The genetic diversity of Salix alba in the arid zone was found to be relatively rich, with populations in the humid areas of northern Xinjiang (e.g., Shannon’s index of I = 0.45 in Ili) significantly higher than those in the extreme arid regions of southern Xinjiang (e.g., Hotan), with I = 0.0762 in Yili. Further analysis using both STRUCTURE (K = 3) and PCoA methods confirmed the division of Salix alba populations in Xinjiang into three independent genetic clusters, with 65% of the observed genetic variation originating from differences between these populations. (2) Secondly, climatic factors exhibited higher explanatory power than geographic factors in elucidating variations in genetic distances among individuals. Cold season precipitation differences (Bio19, r = 0.621) and the coefficient of variation of annual precipitation (Bio17, r = 0.588) were identified as the primary drivers of these variations. Conversely, the latitudinal difference (r = 0.487) and geographic distance (r = 0.207) exhibited a significant impact on genetic distance, underscoring the importance of geo-graphic factors in shaping genetic variation. Full article

Climate change is leading to an increase in the frequency and intensity of flooding, making it necessary to consider future changes in flood risk management. In regions where ground-based observations are significantly restricted, the implementation of conventional risk assessment methodologies is always challenging. This study proposes an integrated remote sensing and machine learning approach for flood risk assessment in data-scarce regions. We extracted the historical inundation frequency using Sentinel-1 SAR and Landsat imagery from 2001 to 2023 and predicted flood susceptibility and inundation frequency using XGBoost, Random Forest (RF), and LightGBM models. The risk assessment framework systematically integrates hazard components (flood susceptibility and inundation frequency) with vulnerability factors (population, GDP, and land use) in two SSP-RCP scenarios. The results indicate that in the SSP2-RCP4.5 and SSP5-RCP8.5 scenarios, combined high- and very-high-flood-risk areas in the Ili River Basin in China (IRBC) are projected to reach 29.1% and 29.7% of the basin by 2050, respectively. In the short term, the contribution of inundation frequency to risk is predominant, while vulnerability factors, particularly population, contribute increasingly in the long term. This study demonstrates that integrating open geospatial data with machine learning enables actionable flood risk assessment, quantitatively supporting climate-resilient planning. Full article

The Ili River Transboundary Basin is an important area within the Belt and Road Initiative, and its ecological security impacts China–Kazakhstan diplomatic relations and the building of the Belt and Road Initiative. Using the copula method, this study quantifies the vulnerability of vegetation to drought in the Ili River Transboundary Basin based on the Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The vulnerability of vegetation in the Ili River Transboundary Basin is highest in June, with the proportion of highly vulnerable areas reaching 63.29% under extreme drought conditions. As the drought severity increases, the probability of vegetation loss rises, with vegetation being affected the most in June. From May to June, drought-prone areas are mainly located in Almaty Oblast and East Kazakhstan. From July to September, drought-prone areas are mainly found in the Ili River Valley and southeastern Almaty Oblast. Rainfed croplands are most susceptible to drought, while, for irrigated croplands, higher drought severity enhances the mitigating effect of irrigation measures. Vegetation areas are most affected by drought in semi-arid regions, particularly in summer. These findings offer valuable scientific support for drought management and sustainable development in the region. Full article

Drought presents significant challenges in arid regions, influencing local climate and environmental dynamics. While the large-scale climatic phenomena in Xinjiang, northwest China, are well-documented, the finer-scale climatic variability in subregions such as the Ili River Valley (IRV) remains insufficiently studied. This knowledge gap impedes effective regional planning and environmental management in this ecologically sensitive area. In this study, we analyze the spatiotemporal evolution of drought in the IRV from 1961 to 2023, using data from ten meteorological stations. The SPEI drought index, along with Sen’s trend analysis, the Mann–Kendall test, the cumulative departure method, and wavelet analysis, were employed to assess drought patterns. Results show a significant drying trend in the IRV, starting in 1995, with frequent drought events from 2018 onwards, and no notable transition year observed from wet to dry conditions. The overall drought rate was −0.09 per decade, indicating milder drought severity in the IRV compared to broader Xinjiang. Seasonally, the IRV experiences drier summers and wetter winters compared to regional averages, with negligible changes in autumn and milder drought conditions in spring. Abrupt changes in the drying seasons occurred later in the IRV than in Xinjiang, with delays of 21 years for summer, and over 17 and 35 years for spring and autumn, respectively, indicating a lagged response. Spatially, the western plains are more prone to aridification than the central and eastern mountainous regions. The study also reveals significant differences in drought cycles, which are longer than those in Xinjiang, with distinct wet–dry phases observed across multiple time scales and seasons, emphasizing the complexity of drought variability in the IRV. In conclusion, the valley exhibits unique drought characteristics, including milder intensity, pronounced seasonal variation, spatial heterogeneity, and notable resilience to climate change. These findings underscore the need for region-specific drought management strategies, as broader approaches may not be effective at the subregional scale. Full article

Statistical characteristics of atmospheric circulation patterns (ACPs) and associated diurnal variation characteristics (DVCs) of precipitation in summer (June–August) from 2015 to 2019 over the complex terrain in northern Xinjiang (NX), northwestern arid region of China, were investigated based on NCEP FNL reanalysis data and Weather Research and Forecasting model simulation data from Nanjing University (WRF-NJU). The results show that six different ACPs (Type 1–6) were identified based on the Simulated ANealing and Diversified RAndomization (SANDRA), exhibiting significant differences in major-influencing synoptic systems and basic meteorological environments. Types 5, 3, and 2 were the most prevalent three patterns, accounting for 21.6%, 19.7%, and 17.7%, respectively. Type 5 mainly occurred in June and July, while Types 3 and 2 mainly occurred in August and July, respectively. From the perspective of DVCs, Type 1 reached its peak at midnight, while Type 5 was most frequent in the afternoon and morning. The overall DVCs of hourly precipitation intensity and frequency demonstrated a unimodal structure, with a peak occurring at around 16 Local Solar Time (LST). Basic meteorological elements in various terrain regions exhibit significant diurnal variation, with marked differences between mountainous and basin areas under different ACPs. In Types 3 and 6, meteorological elements significantly influence precipitation enhancement by promoting the convergence and uplift of low-level wind fields and maintaining high relative humidity (RH). The Altay Mountains region and Western Mountainous regions experience dominant westerly winds under these conditions, while the Junggar Basin and Ili River Valley regions benefit from counterclockwise water vapor transport associated with the Iranian Subtropical High in Type 6, which increases RH. Collectively, these factors facilitate the formation and development of precipitation. Full article

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a globally significant fungal disease that seriously threatens wheat yield, particularly in China. This study investigates the genetic structure and reproductive patterns of Pst populations in Ili, Xinjiang, using 12 pairs of Simple Sequence Repeat (SSR) molecular markers. Analyses of 79 Pst isolates from either spring or winter wheat areas in Ili revealed three primary genetic clusters, indicating notable differences between populations associated with spring and winter wheat. The STRUCTURE results, complemented by UPGMA and PCoA analyses, highlight significant genetic diversity within these populations, with evidence of genetic recombination and sexual reproduction in certain areas. Pst populations in Ili exhibit a mixed mode of reproduction, predominantly sexual in Qapqal and Xinyuan D and primarily asexual within the spring wheat populations. The gene flow analysis underscores extensive inter-population communication, which facilitates the spread and adaptation of the pathogen across diverse wheat-growing environments. This study marks the first documentation of sexual reproduction in Pst within Xinjiang, providing new insights into its spread and genetic variation. These findings suggest that sexual reproduction may play a role in the regional adaptation and evolution of Pst, impacting future management strategies for wheat stripe rust in Xinjiang and potentially in broader Central Asian contexts. Full article

Exposed to seasonal climate changes, the loess in the Ili region of Xinjiang, which has variable engineering properties, frequently undergoes freezing–thawing (F-T) and wetting–drying (W-D) cycles. In the present research, a series of uniaxial compression tests were conducted to investigate the collapsibility characteristics of the representative loess slope in the Ili region. In parallel, scanning electron microscopy (SEM) and nuclear magnetic resonance (NMR) tests were conducted. The test results obtained from the research indicated that both F-T cycles and W-D cycles exacerbate the deterioration of the loess, with the most severe effects observed after 6–10 cycles. Under the combined physical cycles, the microstructure of the loess progressively evolves from the relatively aggregated state to the dispersed one. Meanwhile, the porosity of the loess exhibited an initial increase with the number of W-D cycles, followed by an obvious decrease. Note that the pattern of the loess experiences fluctuation, which was achieved at the given point with the increased number of F-T cycles. It is suggested that the variability in loess wetting collapse is attributed to the irreversible alteration in the microstructure attributed to the combined cycles. The main reasons for the occurrence of loess collapse are the frost heaving force and the swelling–shrinking action. The impacts of W-D and F-T cycles on the loess obtained from this research can make a contribution to the in-depth understanding about loess collapse in the Ili valley. Full article

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. Full article

Background: Influenza is a contagious respiratory illness responsible for seasonal epidemics and with potential to cause pandemics. The decline in influenza-related studies published since 2018 resulted in data gaps, particularly in emerging markets. Methods: This systematic review searched for studies in six databases and gray literature sources to define the clinical burden of influenza and influenza-like illness (ILIs) and their associated sequelae among humans across emerging markets. Eligible studies were published in English, Spanish, or Chinese between January 2018 and September 2023 and conducted in Asia, the Middle East, Africa, and Latin America. Results: In total, 256 articles were included, mostly on lab-confirmed influenza infections (n = 218). Incidences of lab-confirmed influenza cases in Asia (range 540–1279 cases/100,000 persons) and Sub-Saharan Africa (range 34,100–47,800 cases/100,000 persons) were higher compared to Latin America (range 0.7–112 cases/100,000 persons) and the Middle East and North Africa (range 0.1–10 cases/100,000 persons). Proportions of lab-confirmed influenza cases and influenza-associated outcomes (i.e., hospitalization, ICU admission and death) varied widely across regions. Temporal variation in influenza trend was observed before and during the COVID-19 pandemic. Conclusions: In conclusion, influenza causes significant disease burden in emerging markets. Robust large real-world studies using a similar methodology are needed to have more accurate estimates and compare studies within age groups and regions. Continuous monitoring of influenza epidemiology is important to inform vaccine programs in emerging markets with heavy influenza disease burden. Full article

Rainbow trout, or mykiss (Oncorhynchus mykiss), is one of the most popular species used in aquaculture and has been naturalized worldwide, including in the Central Asian Balkhash basin, which has unique aboriginal fish fauna. Both rainbow trout from European farms and wild mykiss from Kamchatka were introduced to some mountain lakes and rivers of the Balkhash basin about 50 years ago. This study investigates the current distribution and life history traits of the alien species and its possible impact on the local fish fauna. This study showed that the rainbow trout occupies various habitats in the Ili River basin: mountain lakes, fast-flowing mountain rivers, and lowland rivers with slow currents and warm water (up to +27 °C). Rainbow trout from European fish farms dominate the mountain Middle Kolsay Lake, while the wild trout from Kamchatka occupies the small Ulken Kokpak River. Both co-occur in the Chilik River. Contrary to that in other regions, the distribution of rainbow trout in the Balkhash basin remained almost the same after their introduction. Broad intrapopulation variability in terms of size, growth rate, and maturation age was revealed, apparently as a result of adaptation to the new environment and intrapopulation competition. In particular, the growth rate has decreased, but life span, surprisingly, has increased as compared to the originally introduced fish. Intrapopulation variation in growth and maturity patterns was also noted. Differences in skin coloration between highland (cold-water) and lowland (warm-water) populations were discovered. The feeding mode of naturalized trout is insectivorous (insect imago), indicating that it occupies its own niche in the local fish communities. The largest population of rainbow trout was recorded in the Lower Kolsay Lake, lowering the population of native fish species, while in other localities, no negative impact on local fish communities was recorded. Full article

Background: During the 2022–2023 influenza season, the influenza activities in most regions of China were postponed, including Beijing. The unusually delayed influenza epidemic posed a challenge to the effectiveness of the influenza vaccine. Methods: Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022–2023 influenza season against influenza A-associated outpatient and emergency-department-attended influenza-like illness (ILI) in Beijing, China, from 9 January to 30 April 2023. Results: The analysis included 8301 medically attended ILI patients, of which 1342 (46.2%) had influenza A(H1N1)pdm09, 1554 (53.4%) had influenza A(H3N2), and 11 (0.4%) had co-infection of the two viruses. VE against influenza A-associated ILI patients was 23.2% (95% CI: −6.5% to 44.6%) overall, and 23.1%, 9.9%, and 33.8% among children aged 6 months to 17 years, adults aged 18–59 years, and adults aged ≥60 years, respectively. VE against influenza A(H1N1)pdm09 and against influenza A(H3N2) were 36.2% (95% CI: −1.9% to 60.1%) and 9.5% (95% CI: −34.1% to 39.0%), respectively. VE of the group with vaccination intervals of 14–90 days (70.1%, 95% CI: −145.4 to 96.4) was higher than that of the groups with a vaccination interval of 90–149 days (18.7%, 95% CI: −42.4% to 53.6%) and ≥150 days (21.2%, 95% CI: −18.8% to 47.7%). Conclusions: A moderate VE against influenza A(H1N1)pdm09 and a low VE against influenza A(H3N2) were observed in Beijing during the 2022–2023 influenza season, a season characterized with a delayed and high-intensity influenza epidemic. VE appears to be better within three months after vaccination. Our findings indicate a potential need for the optimization of vaccination policies and underscore the importance of continuous monitoring of influenza to enhance vaccines and optimizing vaccination timing. Full article

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. Full article