Search Results (264)

Tianshanhong (TSH), black tea products originating from the Ningde Tianshan Mountain, has gained significant recognition in the market. However, the chemical characteristics contributing to the flavor of TSH have not yet been reported. To systematically investigate the non-volatile and volatile compounds in TSH, four grades of TSH were evaluated using national standard sensory methods, revealing that overall quality improved with higher grades. Based on the detection of ultra-performance liquid chromatography–mass spectrometry (UPLC-MS), the content of ester-type catechins was relatively high and decreased with lower grades. A total of 19 amino acids (AAs) were clustered, among them, three amino acids, L-Theanine (L-Thea), Arg, and GABA, showed highly significant correlations with the refreshing taste of TSH. Notably, the content of Arg had the highest correlation with TSH grade, with a coefficient of 0.976 (p < 0.01). According to gas chromatography mass spectrometry (GC-MS) analysis, a total of 861 kinds of volatile compounds were detected, with 282 identified and aroma-active compounds across grades selected using the PLS model. Methyl salicylate and geraniol were particularly notable, showing strong correlations with TSH grades at 0.975 and 0.987 (p < 0.01), respectively. Our findings show that non-volatile and volatile compounds can rationally grade TSH and help understand its flavor quality. Full article

The priming effect (PE), a microbially mediated process, critically regulates the balance between carbon sequestration and mineralization. This study used soils from different soil depths (0–20 cm, 20–40 cm, and 40–60 cm) under Picea schrenkiana forest in the Tianshan Mountains as the research object. An indoor incubation experiment was conducted by adding three concentrations (1% SOC, 2% SOC, and 3% SOC) of ¹³C-labelled glucose. We applied ¹³C isotope probe-phospholipid fatty acid (PLFA-SIP) technology to investigate the influence of readily labile organic carbon inputs on soil priming effect (PE), microbial community shifts at various depths, and the mechanisms underlying soil PE. The results indicated that the addition of ¹³C-labeled glucose accelerated the mineralization of soil organic carbon (SOC); CO₂ emissions were highest in the 0–20 cm soil layer and decreased trend with increasing soil depth, with significant differences observed across different soil layers (p < 0.05). Soil depth had a positive direct effect on the cumulative priming effect (CPE); however, it showed negative indirect effects through physico-chemical properties and microbial biomass. The CPE of the 0–20 cm soil layer was significantly positively correlated with ¹³C-Gram-positive bacteria, ¹³C-Gram-negative bacteria, and ¹³C-actinomycetes. The CPE of the 20–40 cm and 40–60 cm soil layers exhibited a significant positive correlation with cumulative mineralization (CM) and microbial biomass carbon (MBC). Glucose addition had the largest and most significant positive effect on the CPE. Glucose addition positively affected PLFAs and particularly microbial biomass. This study provides valuable insights into the dynamics of soil carbon pools at varying depths following glucose application, advancing the understanding of forest soil carbon sequestration. Full article

The M_w7.0 earthquake that occurred on 23 January 2024, in Wushi County, Xinjiang, China, was centered on the Maidan fault, located at the rear edge of the Kalpin reverse-thrust system in the southwestern Tianshan Mountains, at a depth of 13 km. This event caused significant surface deformation and triggered a series of secondary geologic hazards. In this study, data from two satellites, Sentinel-1A and LuTan-1, were combined to obtain the coseismic deformation field of the earthquake. The two-step inversion method was applied to determine the geometrical parameters and slip characteristics of the mainshock fault. The results indicate that the seismicity is primarily driven by reverse faulting, with a contribution from sinistral strike–slip faulting, and the maximum dip–slip displacement is 4.2 m. Additionally, an aftershock of magnitude 5.7 occurring on January 30 was identified in the LT-1 data. This aftershock was controlled by a reverse fault dipping opposite to the mainshock fault, and its maximum slip is 0.65 m. Analysis of the Coulomb stress triggering effect suggests that the Wushi earthquake may have induced the aftershock. Full article

Understanding vegetation responses to atmospheric drought is critical for arid ecosystem management under climate change. However, the threshold of the response mechanism of grassland in arid regions to atmospheric drought remains unclear. This study investigates how vapor pressure deficit (VPD) regulates grassland gross primary productivity (GPP) in Xinjiang, China, using MODIS and other multi-source remote sensing data (2000–2020). The results show intensified atmospheric drought in central Tianshan Mountains and southern Junggar Basin, with VPD exhibiting a widespread increasing trend (significant increase: 15.75%, extremely significant increase: 4.68%). Intensified atmospheric drought occurred in the central Tianshan Mountains and southern Junggar Basin. Integrated analyses demonstrate that VPD has a dominant negative impact on GPP (path coefficient = −0.58, p < 0.05), primarily driven by atmospheric drought stress. A ridge regression-derived threshold was identified at 0.61 kPa, marking the point where VPD transitions from stimulating to suppressing productivity. Spatially, 58.75% of the total area showed a significant increase in GPP. These findings advance the mechanistic understanding of atmospheric drought impacts on arid ecosystems and inform adaptive grassland management strategies. Full article

Reconstructing historical grazing intensity is essential for understanding long-term human–environment interactions in arid and semi-arid regions. However, historical documents often lack continuous, site-specific information on land use and grazing pressure. We present a high-resolution reconstruction of pastoral activity and hydrological evolution since 1560 AD using fungal spore assemblages from a 92 cm lacustrine-peat sequence from the Sichanghu (SCH) peatland on the northern slope of the Tianshan Mountains, Central Asia. Quantitative analysis of coprophilous fungal spores and principal component analysis (PCA) of spore influxes identify three distinct phases of pastoral intensity: gradual intensification from 1560 to 1730 AD, a sharp decline from 1730 to 1770 AD, and rapid intensification from 1770 AD to the present. These transitions are consistent with historical records of land use and human migration in Xinjiang. Additionally, fungal assemblages reveal a long-term drying trend at Sichanghu, broadly consistent with regional aridification in northwestern China. However, centennial-scale discrepancies in humidity between local and regional records—particularly during the late Little Ice Age—indicate that local hydrological responses were strongly influenced by anthropogenic disturbances. This study highlights the value of fungal spores, particularly influx-based interpretations, as robust indicators of both human activities and hydroclimatic variability. It also underscores the importance of integrating local and regional signals when reconstructing past environmental changes in sensitive dryland ecosystems. Full article

Canopy chlorophyll content (CCC) is a key indicator for assessing the carbon sequestration capacity and material cycling efficiency of ecosystems, and its accurate retrieval holds significant importance for analyzing ecosystem functioning. Although numerous destructive and remote sensing methods have been developed to estimate CCC, the accurate estimation of CCC remains a significant challenge in mountainous regions with complex terrain and heterogeneous vegetation types. Through the synergistic analysis of ground hyperspectral and Sentinel-2 data, this study employed Pearson correlation analysis and spectral resampling techniques to identify Sentinel-2 blue band B1 (443 nm) and red band B4 (665 nm) as chlorophyll-sensitive bands through spectral matching with the hyperspectral reflectance of typical grassland vegetation. Based on this, we developed a new four-band vegetation index (VI), the Dual Red-edge and Coastal Aerosol Vegetation Index (DRECAVI), for estimating the CCC of heterogeneous grasslands in the middle section of the Tianshan Mountains. DRECAVI incorporates red-edge anti-saturation modules (bands B4 and B7) and aerosol correction modules (bands B1 and B8). In order to test the performance of the new index, we compared it with eight commonly used indices and a hybrid model, the Sentinel-2 Biophysical Processor (S2BP). The results indicated the following: (1) DRECAVI demonstrated the highest accuracy in CCC retrieval for mountainous vegetation (R² = 0.74, RMSE = 16.79, MAE = 12.50) compared to other VIs and hybrid methods, effectively mitigating saturation effects in high biomass areas and capturing a weak bimodal distribution pattern of CCC in the montane meadow. (2) The blue band B1 enhances atmospheric correction robustness by suppressing aerosol scattering, and the red-edge band B7 overcomes the sensitivity limitations of conventional red-edge indices (such as NDVI705, CIred-edge, and NDRE), demonstrating the potential application of the synergy mechanism between the blue band and the red-edge band. (3) Although the S2BP achieved high accuracy (R² = 0.73, RMSE = 19.83, MAE = 14.71) without saturation effects and detected a bimodal distribution of CCC in the montane meadow of the study area, its algorithmic complexity hindered large-scale operational applications. In contrast, DRECAVI maintained similar precision while reducing algorithmic complexity, making it more suitable for regional-scale grassland dynamic monitoring. This study confirms that the synergistic use of multi-source data effectively overcomes the limitations of the spectral–spatial resolution of a single data source, providing a novel methodology for the precision monitoring of mountain ecosystems. Full article

Ecological network construction has been widely accepted and applied to guide regional ecological conservation and restoration. For arid regions, ecological networks proposed based on ecological risk assessments are better aligned with the sensitive and fragile characteristics of local ecosystems. This study assesses landscape ecological risk in Wensu County, located on the southern slope of the Tianshan Mountains in the arid region of northwestern China, and it further proposes an optimized ecological network. A multidimensional framework composed of the natural environment, human society, and landscape patterns was employed to construct an ecological risk assessment system. Spatial principal component analysis (SPCA) was applied to identify the spatial pattern of ecological risk. Morphological spatial pattern analysis (MSPA) and a minimum cumulative resistance (MCR) model integrated with circuit theory were used to extract the ecological sources and delineate the ecological corridors. The results reveal significant spatial heterogeneity in terms of ecological risk: Low-risk zones (16.26%) are concentrated in the southwestern forest and water areas. In comparison, high-risk zones (28.27%) are mainly distributed in the northern mountainous mining region. A total of 24 ecological source patches (4105.24 km²), 44 ecological corridors (313.6 km), 39 ecological pinch points, and 38 ecological barriers were identified. Following optimization, the Integral Index of Connectivity (IIC) increased by 89.04%, and the Landscape Coherence Probability (LCP) rose by 105.23%, indicating markedly enhanced ecological connectivity. The current ecological network exhibits weak connectivity in the south and fragmentation in the central region. Targeted restoration of critical nodes, optimization of corridor configurations, and expansion of ecological sources are recommended to improve landscape connectivity and promote biodiversity conservation. Full article

Desert plants in arid regions are facing escalating challenges from global warming, underscoring the urgent need to predict shifts in the distribution and habitats of dominant species under future climate scenarios. This study employed the Maximum Entropy (MaxEnt) model to project changes in the potential suitable habitats of three keystone desert species in Xinjiang—Halostachys capsica (M. Bieb.) C. A. Mey (Caryophyllales: Amaranthaceae), Haloxylon ammodendron (C. A. Mey.) Bunge (Caryophyllales: Amaranthaceae), and Karelinia caspia (Pall.) Less (Asterales: Asteraceae)—under varying climatic conditions. The area under the Receiver Operating Characteristic curve (AUC) exceeded 0.9 for all three species training datasets, indicating high predictive accuracy. Currently, Halos. caspica predominantly occupies mid-to-low elevation alluvial plains along the Tarim Basin and Tianshan Mountains, with a suitable area of 145.88 × 10⁴ km², while Halox. ammodendrum is primarily distributed across the Junggar Basin, Tarim Basin, and mid-elevation alluvial plains and aeolian landforms at the convergence zones of the Altai, Tianshan, and Kunlun Mountains, covering 109.55 × 10⁴ km². K. caspia thrives in mid-to-low elevation alluvial plains and low-elevation alluvial fans in the Tarim Basin, western Taklamakan Desert, and Junggar–Tianshan transition regions, with a suitable area of 95.75 × 10⁴ km². Among the key bioclimatic drivers, annual mean temperature was the most critical factor for Halos. caspica, precipitation of the coldest quarter for Halox. ammodendrum, and precipitation of the wettest month for K. caspia. Future projections revealed that under climate warming and increased humidity, suitable habitats for Halos. caspica would expand in all of the 2050s scenarios but decline by the 2070s, whereas Halox. ammodendrum habitats would decrease consistently across all scenarios over the next 40 years. In contrast, the suitable habitat area of K. caspia would remain nearly stable. These projections provide critical insights for formulating climate adaptation strategies to enhance soil–water conservation and sustainable desertification control in Xinjiang. Full article

The China–Mongolia arid region adjacent to the Altai Mountain (CMA) has a sensitive ecosystem that relies heavily on both terrestrial water (TWS) and groundwater storage (GWS). However, during the 2003–2016 period, the CMA experienced significant glacier retreat, lake shrinkage, and grassland degradation. To illuminate the TWS and GWS dynamics in the CMA and the dominant driving factors, we employed high-resolution (0.1°) GRACE (Gravity Recovery and Climate Experiment) data generated through random forest (RF) combined with residual correction. The downscaled data at a 0.1° resolution illustrate the spatial heterogeneity of TWS and GWS depletion. The highest TWS and GWS decline rates were both on the north slope of the Tianshan River Basin (NTRB) of the Junggar Basin of Northwestern China (JBNWC) (27.96 mm/yr and −32.98 mm/yr, respectively). Human impact played a primary role in TWS decreases in the JBNWC, with a relative contribution rate of 62.22% compared to the climatic contribution (37.78%). A notable shift—from climatic (2002–2010) to anthropogenic factors (2011–2020)—was observed as the primary driver of TWS decline in the Great Lakes Depression region of western Mongolia (GLDWM). To maintain ecological stability and promote sustainable regional development, effective action is urgently required to save essential TWS from further depletion. Full article

Against the background of global warming, forests across environmental gradients show distinct responses to climate change, necessitating research on tree growth patterns under specific conditions. Climate and competition are critical factors affecting tree growth, yet their combined effects across altitudinal gradients remain unclear, especially in arid regions such as Central Asia. This study investigated how climate and competition influence radial growth of Picea schrenkiana Fisch. et C.A.Mey. across altitudinal gradients (1500–2670 m) in the Middle Tianshan Mountains. Using dendroclimatology, competition indices, multivariate statistical analyses, and nonlinear models across 12 plots, we examined spatial variability in growth responses. Results revealed significant altitudinal differences in growth responses to climate and competition across altitudes. At low elevations, growth is primarily limited by water availability; drought indices and spring precipitation exert positive effects, while high temperatures inhibit growth. At mid-elevations, climate becomes the dominant driver, particularly spring temperature and precipitation playing key roles, while competition has no significant effect. At high elevations, temperature becomes the primary driver of growth; however, the overall sensitivity to climate is reduced compared to lower elevations. Multiple regression analyses confirm that water-related factors drive growth at lower and middle elevations, whereas temperature is the primary driver at higher elevations. Further model comparison indicates that while nonlinear models performed slightly better at mid-elevations, linear approaches similarly provided interpretable climate–growth relationships. This study demonstrates significant spatial variation in growth determinants, with water-driven controls dominating at lower elevations and competition effects ranging from significant to non-significant as altitude increases. Future warming may further intensify drought stress at lower elevations, and whether or not the weak positive responses currently observed at higher elevations will persist remains uncertain. These findings provide a scientific basis for sustainable management of arid mountain forests under climate change. Full article

Glaciers, often regarded as “frozen reservoirs”, play a crucial role in replenishing numerous rivers in arid regions, contributing to ecological balance and managing river flow. Recently, the rapid shrinkage of the glaciers in the East Tianshan Mountains has affected the water quantity in the Karez system. However, studies on glacier changes in this region are limited, and recent data are scarce. This study utilizes annual Landsat composite images from 1990 to 2022 obtained via the Google Earth Engine (GEE). It utilizes a ratio threshold approach in conjunction with visual analysis to gather the glacier dataset specific to the Turpan–Hami region. The Open Global Glacier Model (OGGM) is used to model the flowlines and mass balance of around 300 glaciers. The study analyzes the glacier change trends, distribution characteristics, and responses to climate factors in the Turpan–Hami region over the past 30 years. Additionally, future glacier changes through the end of the century are projected using CMIP6 climate data. The findings indicate that the following: (1) From 1990 to 2022, glaciers in the research area underwent considerable retreat. The total glacier area decreased from 204.04 ± 0.887 km² to 133.52 ± 0.742 km², a reduction of 70.52 km², representing a retreat rate of 34.56%. The number of glaciers also decreased from 304 in 1990 to 236 in 2022. The glacier length decreased by an average of 7.54 m·a⁻¹, with the average mass balance at −0.34 m w.e.·a⁻¹, indicating a long-term loss of glacier mass. (2) Future projections to 2100 indicate that under three climate scenarios, the area covered by glaciers could diminish by 89%, or 99%, or even vanish entirely. In the SSP585 scenario, glaciers are projected to nearly disappear by 2057. (3) Rising temperatures and solar radiation are the primary factors driving glacier retreat in the Turpan–Hami area. Especially under high emission scenarios, climate warming will accelerate the glacier retreat process. Full article

Water resources are vital for sustainable development in arid regions, where glacial runoff plays a significant role in maintaining water supply. This study quantitatively assesses the sustainability of water resources in the Manas River Basin (MnsRB) and the Muzati River Basin (MztRB), situated on the northern and southern slopes of the Tianshan Mountains, respectively, over the period from 1991 to 2050. Freshwater availability was simulated and projected using the Variable Infiltration Capacity Chinese Academy of Sciences (VIC-CAS) hydrological model. Furthermore, three development modes—traditional development, economic growth, and water-saving—were established to estimate future water consumption. The levels of water stress were also applied to assess water resources sustainability in the MnsRB and MztRB. Results indicate that from 1991 to 2020, the average annual available freshwater resources were 13.94 × 10⁸ m³ in the MnsRB and 14.27 × 10⁸ m³ in the MztRB, with glacial runoff contributing 20.24% and 65.58%, respectively. Under the SSP5-8.5 scenario, available freshwater resources are projected to decline by 10.94% in the MnsRB and 4.37% in the MztRB by 2050. Total water withdrawal has increased significantly over the past 30 years, with agriculture water demand accounting for over 80%. The levels of water stress during this period were 1.14 for the MnsRB and 0.87 for the MztRB. Glacial runoff significantly mitigates water stress in both basins, with average reductions of 21.16% and 69.84% between 1991 and 2050. Consequently, clear policies, regulations, and incentives focused on water conservation are vital for effectively tackling the increasing challenge of water scarcity in glacier-covered arid regions. Full article

This study investigates the spatiotemporal changes in land use within the urban agglomeration on the northern slopes of the Tianshan Mountains (TNUA), aiming to identify the driving factors and provide a scientific basis for regional ecological protection, rational land use planning, and sustainable resource utilization. Using land use data, we analyzed transitions, dynamics, intensity, and gravity shifts in land use, examined driving mechanisms using geographic detectors, and simulated future land use patterns with the Patch-generating Land Use Simulation (PLUS) model. The results indicate that between 2010 and 2020, forest, water body, and unused land areas decreased, while cropland, grassland, and construction land expanded. The rate of land use change accelerated significantly, increasing from 0.0955% during 2010–2015 to 0.3192% during 2015–2020. The comprehensive land use dynamic degree index rose from 157.8371 to 161.1008, with Shayibake District exhibiting the most rapid growth. Precipitation, temperature, economic development, and elevation were the dominant driving factors throughout the study period. Population density had the strongest influence on the expansion of water body, while slope was the most significant factor for cropland expansion. Nighttime light was the primary driver of construction land growth. Projections for 2025, 2030, and 2035 suggest a continued decline in unused land and forest areas, alongside increases in cropland, grassland, water body, and construction land. Full article

The flood–drought severity in arid regions such as Xinjiang is increasingly influenced by climate extremes. While prior studies have explored the relationship between climate extremes and flood–drought dynamics, few have analyzed these interactions at different time and spatial scales using different method combinations. This study addresses that gap by utilizing a gridded dataset (CN05.1) during 1961–2020, examining the China Z index (flood–drought index) and climate extremes. The analysis reveals significant increases in precipitation and heat extremes, while cold extremes have decreased. In addition to overall periodic changes with 2.5 and 8 years in the flood–drought severity, our results demonstrate a significant spatial shift between 1981 and 2000 and between 2001 and 2020. Previously flood-dominant regions, including portions of the Junggar Basin, Eastern Tianshan Mountains, and Tarim River Basin, transitioned to drought-dominant in 2001–2020. Conversely, drought-dominant regions became flood-dominant. Strong positive correlations (0.65–0.84) were found between the Z index and precipitation extremes, while temperature extremes showed weaker correlations. Furthermore, we applied six variable selection regression methods, with Random Forest variable selection + Random Forest regression (RF+RF) performing the best (mean R² = 0.71), highlighting their ability to manage non-linear relationships and multicollinearity between climate indices. RF+RF proved more effective at handling correlated variables, which were crucial in capturing the region’s flood–drought dynamics. The quantified spatial reversals and non-linear climate-flood/drought relationships provide actionable metrics for early warning systems, enabling targeted infrastructure upgrades and water allocation policies in arid regions. These findings establish a transferable framework linking climate extremes to hydrological risks, directly informing adaptive land management and disaster preparedness strategies for Xinjiang and analogous regions under intensifying climate variability. 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