Search Results (78)

This study investigated the distribution patterns of zooplankton species composition and functional groups, their correlations with aquatic environmental factors, and the mechanisms underlying community stability under the influence of regional barriers in arid areas of Xinjiang, China. The aim was to elucidate the ecological processes driving zooplankton communities in artificial aquatic ecosystems in Central Asia. A systematic survey was conducted on water environmental parameters and zooplankton community structures across 10 artificial water bodies, including the southern foot of the Altai Mountains and both northern and southern slopes of the Tianshan Mountains. The survey encompassed physical and nutrient indicators, and the results revealed significant spatial variation among water bodies across regions. Artificial water bodies in the southern Altai Mountains and northern Tianshan Mountains exhibited substantial fluctuations in temperature, dissolved oxygen (DO), total nitrogen (TN), and total phosphorus (TP). In contrast, water bodies in the southern Tianshan Mountains showed less variation in nutrient indicators. Zooplankton identification results indicated marked differences in zooplankton communities across regions, which were further confirmed by cluster analysis and non-metric multidimensional scaling (NMDS). A total of 19 dominant zooplankton species were identified across the three basins, classified into 6 functional groups. The composition of zooplankton functional groups also varied considerably, which may be closely associated with significant fluctuations in nutrient indicators of aquatic environmental factors across regional barriers. Additionally, there were specific differences in zooplankton diversity among the three basins: the SA region ranged from α-mesosaprobic to polysaprobic and β-mesosaprobic; the NT region was classified as β-mesosaprobic; and the ST region ranged between β-mesosaprobic and lightly polluted. These results may be attributed to differences in regional barriers and glacial meltwater conditions. Canonical Correspondence Analysis (CCA) showed that environmental factors collectively explained 71.1% of the variation in species distribution. Exploring the zooplankton species composition and their relationships with aquatic environmental factors under different regional barriers provides a scientific basis for regional water resource management and environmental protection. Full article

Flash drought (FD) is an extreme climate event that intensifies within days and exerts severe socio-environmental impacts. Its onset and evolution remain difficult to predict. Here, we quantify the spatio-temporal dynamics of FD across northern Xinjiang from 1961 to 2023 and identify the dominant driving factors. We apply linear trend detection, wavelet analysis, change-point detection, random forest (RF) modeling, and Pearson correlation. Results show that winter is becoming significantly wetter, whereas the annual signal and the other three seasons exhibit drying trends. After 1980, both FD frequency and FD duration increased; the longest single event lasted 40 days. Spatially, FD is concentrated in the Ili River Valley and the Altay region; the Akdala station recorded the highest count (nine events). Duration, rather than frequency, peaks on the northern slope of the Tianshan Mountains, where the maximum length reaches 40 days. RF importance ranks the Pacific Decadal Oscillation (PDO) as the leading driver (20.9%), followed by air temperature (17.8%); the sunspot index contributes only 6.1%. Full article

Net Primary Productivity (NPP) stands as a crucial metric for evaluating the condition and performance of terrestrial ecosystems. This study focuses on northern Xinjiang, China, as the research site. By employing the Carnegie Ames Stanford Approach (CASA) model alongside meteorological data, we examined the spatiotemporal variations in vegetation NPP from 2001 to 2022. The model utilized monthly NDVI, climate drivers, and vegetation type raster data as inputs, while the Mann–Kendall test, We utilized Theil–Sen trend analysis and residual analysis to investigate how climatic factors and human activities drove NPP changes. Results show that from 2001 to 2022, vegetation NPP in northern Xinjiang generally rose with fluctuations, averaging 127.96 gC·m⁻²·a⁻¹ annually and growing linearly at 0.58 gC·m⁻²·a⁻¹. Spatially, NPP displayed a pattern of “high in the west and low in the east, high in mountainous areas and low in deserts.” High NPP areas are mainly clustered in the Ili River Valley and adjacent mountainous regions, encompassing eastern and southwestern Ili Prefecture, northern Tianshan slopes, Balq Mountains, and southern Borokunu foothills, where hydrothermal conditions are relatively advantageous. In the last 22 years, the mean temperature in northern Xinjiang showed a fluctuating upward trend, precipitation exhibited a fluctuating downward trend, and solar radiation demonstrated a significant declining trend. Partial correlation analysis revealed that, compared with temperature and solar radiation, precipitation had a stronger positive correlation with NPP. Residual analysis showed that in areas where vegetation NPP exhibited recovery, human activities were the dominant driving factor, accounting for 23.58% of the total area, whereas the influence of climate change was relatively minor. Conversely, in regions where vegetation NPP degraded, climate change exerted a greater impact than human activities. This research clarifies the combined impacts of climate and human actions on ecosystem productivity in arid areas, offering a scientific foundation and reference for ecological protection and regional carbon control in such regions. This provides a scientific basis for formulating rational response strategies to restore vegetation and enhance the quality of ecosystems in arid regions. Full article

In the rapidly changing Urban Agglomeration on the Northern Slope of the Tianshan Mountains (UANSTM), urbanization and oasis ecosystem degradation have intensified the need for ecological security planning. However, traditional ecosystem service assessments often struggle to capture the spatial heterogeneity of these fragile landscapes. This study integrates revised ecosystem service value (RESV), ecological sensitivity, and circuit-theory-based connectivity analysis to identify ecological sources and construct an ecological security pattern (ESP). Results indicate: From 2000 to 2020, land conversion among exposed areas, irrigated farmland, and grassland dominated regional change, with 5902 km² of exposed land converting to grassland and 4554 km² to irrigated farmland. RESV declined initially but rose overall from 1104 to 1255 billion yuan, yielding a net increase of about 14%. Ecologically sensitive areas were concentrated in the northeast, covering roughly 19,300 km² and dominated by irrigated farmland. In total, 23 ecological sources, 47 ecological corridors, 28 ecological barrier points, and 61 ecological bottleneck points were identified, forming the basis for a targeted point–line–area protection strategy to guide ecological zoning and restoration. This study provides scientific basis for ecological conservation and territorial spatial planning in arid urban clusters. Nonetheless, limitations related to data resolution and indicator selection remain. Future research should incorporate higher-resolution ecological data and scenario-based simulations to further refine ESP construction. Full article

Understanding the evolutionary dynamics of land use and habitat quality (HQ) under climate change scenarios is pivotal for formulating science-based biodiversity conservation policies and promoting climate-resilient urban development in arid regions. By integrating the SD–PLUS–InVEST framework with SPEI-driven drought scenarios, this study introduces a novel coupling mechanism that links climate variability, land-use transitions, and HQ evolution in the Northern Slope of the Tianshan Mountains (UANSTM) under SSP–RCPs scenarios. The HQ assessment was validated using the Remote Sensing Ecological Index (RSEI). Simultaneously, the Optimal Multivariate-Stratification Geographical Detector (OMGD) was applied to identify scale-optimized drivers of HQ changes. The results indicated the following: (1) From 2000 to 2020, cultivated and construction land in the UANSTM expanded, while forest and water areas declined, with unused land remaining dominant from 2000 to 2020. (2) HQ decreased from 0.36 to 0.33 (2000–2020), significantly correlating with RSEI (Pearson r = 0.329, Spearman ρ = 0.446, p < 0.001), with climatic, vegetation, and coupled natural-social factors remaining the dominant drivers. (3) From 2020 to 2050, under all climate scenarios, the areas of farmland, grassland, and construction land are expected to grow, while HQ is projected to improve through the conversion of low-quality areas into moderate- and high-quality habitats (greatest under SSP119, least under SSP585). The framework advances predictive insights for arid-region ecological planning, supporting practical applications in habitat management and sustainable land-use planning, while providing a methodological paradigm for dryland habitat resilience assessment. Full article

Grazing pressure (GP) was a key factor influencing net primary productivity (NPP) in pasturelands and was characterized by two indicators: grazing intensity (GI) and grazing density (GD). However, current research has not yet clarified whether the mechanisms linking GP to NPP varied by season, or whether seasonal thresholds of grazing pressure existed. This study employed the Carnegie–Ames–Stanford Approach (CASA) model to estimate NPP over eight time periods between 2010 and 2024 for three seasonal pastures (spring–autumn, summer, and winter) in the study area. Estimation accuracy was evaluated by comparing our NPP estimates with existing NPP products. Trends in NPP and their significance were analyzed using the Sen–MK method, followed by further examination of spatiotemporal variations in NPP across the three seasonal pastures. Subsequently, by comparing two grazing pressure indicators (GI and GD), we identified the optimal metric to represent GP and, on this basis, analyzed the spatiotemporal variations and threshold dynamics of pasture NPP across three seasons under the influence of GP. Results indicated that the CASA model achieved R² > 0.90 for multi-year NPP estimation, with RMSE ranging from 27 to 45 g C m⁻² y⁻¹. Spring–autumn and winter pastures exhibited pronounced slope changes and intense spatiotemporal NPP variations, whereas summer pastures showed insignificant slope changes and stable spatiotemporal NPP patterns. Of the two GP indicators, the GD metric developed herein more effectively characterized grazing pressure across the study area. Across the three seasonal pastures, a consistent negative feedback between GD and NPP was evident; however, its strength differed markedly, with spring–autumn and winter pastures exhibiting greater NPP sensitivity to GD. The GD thresholds for spring–autumn, summer, and winter pastures in the study area were approximately 900, 700, and 5000 sheep km⁻², respectively. Exceeding these thresholds led to degradation, while falling below them promoted recovery. The study revealed a threshold-mediated negative feedback between GD and NPP across seasonal pastures, quantified season-specific upper bounds of carrying capacity, and provided an evidence base for zoned rest/rotational grazing and GD regulation along the northern slope of the Tianshan Mountains. Full article

Rapid and uncoordinated urban expansion in arid oasis city clusters intensifies land use conflicts and ecological pressure, threatening regional sustainability. This study investigates the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains (UANSTM) in Xinjiang, northwestern China—an arid region urban cluster. A multi-source spatial data framework was established to delineate urban built-up areas and to construct land use efficiency (LUE) indicators, thereby facilitating an integrated analysis of the spatial coupling between urban expansion intensity (UEI) and LUE from 2000 to 2020. The results indicate that: (1) The urban built-up area expanded from 322 km² to 1096 km², shifting northward and northwestward, producing fragmented and decentralized patterns; (2) LUE improved but exhibited clear spatial disparities. Core cities like Urumqi showed strong synergy between rapid expansion and rising efficiency, whereas peripheral cities such as Wusu expanded quickly without corresponding efficiency gains, reflecting evident trade-offs; (3) The relationship between UEI and LUE exhibited a nonlinear evolution—trade-offs dominated during 2000–2005, synergy strengthened from 2005 to 2015, and trade-offs resurged again after 2015.These findings reveal the cyclical vulnerability of arid region urbanization and highlight the effectiveness of the proposed framework for diagnosing spatial mismatches and guiding compact, efficiency-oriented urban development toward long-term sustainability. Full article

Ecosystem services play a crucial role in sustaining human life, providing numerous benefits that are indispensable for our well-being. However, these vital functions are increasingly compromised by land use changes that have been instigated by human activities. This study aims to evaluate the spatiotemporal variability of ecosystem service value (ESV) within the urban agglomeration located on the northern slope of the Tianshan Mountains over a historical period stretching from 1990 to 2020, utilizing land use data to conduct a thorough analysis. Subsequently, the Future Land Use Simulation (FLUS) model was employed to forecast ESV in 2030 under three developmental pathways: Ecological Protection Scenario (EPS), Cultivated Land Protection Scenario (CLPS), and Natural Development Scenario (NDS). The evaluation incorporated six primary land classes: cultivated land, forest land, grassland, water bodies, construction land, and unused land. The FLUS model was validated with strong accuracy (overall accuracy = 0.97, Kappa = 0.94). ESV was estimated using the value coefficient method based on equivalent factors, adjusted with a local economic coefficient for crop production. All values are expressed in constant 2020 CNY without further price normalization. Our results show that between 1990 and 2020, cultivated land expanded by 27.18% (17,721 to 22,538 km²) and construction land increased by 75.91% (1926 to 3388 km²), while grassland decreased from 63,502 to 59,027 km² and unused land declined from 106,292 to 104,690 km². Minor changes occurred in forest land and water bodies. Total ESV decreased from 679.06 × 10⁸ CNY in 1990 to 657.67 × 10⁸ CNY in 2020, a decline of 3.15%. Regulating, supporting, and cultural services all decreased, while provisioning services increased. Spatially, vegetated areas functioned as ESV hot spots, whereas construction-degraded areas were identified as cold spots. Scenario projections for 2030 show that under the CLPS and NDS, ESV would further decline by 11.49 × 10⁸ CNY (−1.75%) and 10.18 × 10⁸ CNY (−1.55%), respectively. In contrast, the EPS is projected to increase ESV by 4.53 × 10⁸ CNY (+0.69%), reaching 662.20 × 10⁸ CNY. Full article

Cotton is increasingly important in global development. The exploration of drivers of spatiotemporal patterns for cotton planting, considering spatial heterogeneity, is essential for optimizing its distribution and supporting sustainable production. This study combined the locally explained stratified heterogeneity (LESH) model with geographically weighted regression (GWR) to investigate the factors shaping cotton-planting patterns in the northern slope of the Tianshan Mountains (NSTM), China, from 2000 to 2020. Cotton distribution was derived from long-term Landsat image series, and its expansion showed an average annual growth rate of 2.10 × 10³ km², with intensive cultivation primarily distributed across the central and western counties. The dominant drivers of cotton distribution were elevation (ELE), sunshine duration (SD), slope (SLO), temperature (TEM), runoff (RO), and gross domestic product (GDP). ELE explained about 40% of the spatial heterogeneity. SD showed a declining influence, SLO remained stable, TEM increased in importance, and GDP exhibited a progressive upward trend, although weaker. Moreover, nonlinear weakening interactions, especially between ELE and other factors, as well as between socio-economic and climatic variables, substantially enhanced explanatory power. These findings highlight the significance of accounting for spatial heterogeneity and factor interactions in guiding the spatial optimization and sustainable management of cotton cultivation. Full article

Net primary productivity (NPP) reflects the carbon sequestration capacity of terrestrial ecosystems and it is used as an important indicator for measuring ecosystem quality. However, due to the effects of “warming and humidification” and “oasisization”, the spatiotemporal evolution and driving mechanisms of the NPP of vegetation in the northern slope of the Tianshan Mountains (NSTM), a typical arid area in China, are still unclear. Thus, in this study, we used remote sensing data and meteorological data to construct a Carnegie–Ames–Stanford–Approach (CASA) model for estimating the NPP of vegetation in the study area. Trend analysis, partial correlation analysis, and optimal parameter-based geographic detector (OPGD) methods were combined to explore the spatiotemporal evolution and driving mechanisms to changes in the NPP. The results showed that from 2001 to 2020, the annual average NPP on the NSTM exhibited an overall significant upward trend, increasing from 107.33 gC⋅m⁻²⋅yr⁻¹ to 156.77 gC⋅m⁻²⋅yr⁻¹, with an increase of 2.47 gC⋅m⁻² per year and 46.06% year-on-year. Over the past 20 years, climate change and human activities generally positively affected the changes in NPP in the study area. Human activities in the study area are mainly manifested in the large-scale conversion of other land use types into farmland, with a total increase of 16,154 km² in farmland area, resulting in a net increase of 6.01 TgC in NPP. Precipitation has the strongest correlation with NPP in the study area, with a partial correlation coefficient of 0.30, temperature and solar radiation have partial correlation coefficients with NPPs of 0.17 and 0.09, respectively. Therefore, increases in precipitation, temperature, and solar radiation have a promoting effect on the growth of NPP on the NSTM. During the study period, the land use type and soil moisture were the main factors that affected the spatial differentiation of vegetation NPP, and the effects of human interference on natural environmental conditions had significant impacts on vegetation NPP in the area. Therefore, in this study, we accurately determined the spatiotemporal variations in the NPP on the NSTM and comprehensively explored the driving mechanisms to provide a theoretical basis for sustainable development in arid areas and achieving carbon neutrality goals. Full article

Avalanches occur frequently in mountainous areas and pose significant threats to roads and infrastructure. Clarifying how terrain conditions influence avalanche initiation and movement is critical to improving hazard assessment and response strategies. This study focused on a wet-snow slab avalanche that occurred on 26 March 2024, in the Simutas region of the northern Tianshan Mountains, Xinjiang, China. The authors combined remote sensing imagery, high-resolution meteorological station observations, field investigations, and numerical simulations (RAMMS::Avalanche) to analyze the avalanche initiation mechanism, dynamic behavior, and path recurrence characteristics. Results indicated that persistent heavy snowfall, rapid warming, and substantial daily temperature fluctuations triggered this avalanche. The predominant southeasterly (SE) winds and the northwest-facing (NW) shaded slopes created favorable leeward snow deposition conditions, increasing snowpack instability. High-resolution meteorological observations provided detailed wind, temperature, and precipitation data near the avalanche release zone, clearly capturing snowpack evolution and meteorological conditions before avalanche initiation. Numerical simulations showed a maximum avalanche flow velocity of 19.22 m/s, maximum flow depth of 12.42 m, and peak dynamic pressure of 129.3 kPa. The simulated avalanche deposition area and depth closely matched field observations. Multi-temporal remote sensing images indicated that avalanche paths in this area remained spatially consistent over time, with recurrence intervals of approximately 2–3 years. The findings highlight the combined role of local meteorological processes and terrain factors in controlling avalanche initiation and dynamics. This research confirmed the effectiveness of integrating remote sensing data, high-resolution meteorological observations, and dynamic modeling, providing scientific evidence for avalanche risk assessment and disaster mitigation in mountain regions. 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

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

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