Search Results (257)

The proglacial lakes of the Qinghai-Xizang Plateau serve as natural laboratories for studying microbial adaptation to extreme environments. However, research on the composition and functional characteristics of microorganisms in these settings remains limited. In this study, three typical high-altitude proglacial lakes in southern Xizang (Qudengnima proglacial lake, Gangbugou proglacial lake, and Qiangyong proglacial lake) were selected as research subjects. Bacterial community structure, diversity in the water and sediment of these lakes were analyzed using 16S rRNA sequencing. The results showed that Pseudomonadota, Actinomycetota, and Bacteroidota were highly abundant across all samples. The relative abundances of Cyanobacteriota and Acidobacteriota, however, exhibited distinct habitat preferences: Cyanobacteriota was enriched in the water, whereas Acidobacteriota was predominantly found in sediment. Alpha diversity analysis showed that both species diversity and richness in Qiangyong proglacial lake were significantly higher than those in the other proglacial lakes, and within the same lake, both diversity and richness in sediment were higher than in the water. Beta diversity analysis indicated that the bacterial community structures in sediment were similar across different proglacial lakes, whereas those in water varied considerably among the lakes. LEfSe analysis identified 94 biomarkers that exhibited significant differences among the different proglacial lake environments at an LDA score threshold of 4. Redundancy analysis revealed that pH, total phosphorus, and ammonium nitrogen were the physicochemical factors significantly influencing the bacterial community structure in the water, while total carbon was the key driver for the community in sediments. This study preliminarily characterized the bacterial community structure and diversity in high-altitude proglacial lakes on the southern Qinghai-Xizang Plateau, which lays a theoretical foundation for exploiting microbial resources and understanding their ecological functions in such extreme environments. Full article

Avian influenza remains a major threat to poultry production, wildlife conservation, and public health in Asia, where migratory birds, wetlands, rice paddies, domestic ducks, and live poultry trade often intersect. This Asia-focused review synthesizes ecological, epidemiological, surveillance, tracking, phylogenetic, and environmental evidence from 1996 to 2025, with particular emphasis on China, to clarify how risk develops at the wild bird–domestic poultry interface. The reviewed evidence suggests three broad epidemic phases: early Goose/Guangdong-lineage H5N1 outbreaks before 2014, recurrent clade 2.3.4.4 H5Nx expansions during 2014–2019, and the widespread clade 2.3.4.4b H5N1 period since 2020. Spatial risk is concentrated around major stopover wetlands and rice-paddy–duck landscapes, including Qinghai Lake, Poyang Lake, Sanmenxia, the Sanjiang Plain, and peri-urban market belts. Wetlands and paddies can maintain viruses environmentally, free-grazing ducks and bridge hosts can facilitate introduction, and live poultry markets and trade networks can amplify and export risk. By organizing these processes through an Interface–Amplifier–Conduit evidence-mapping approach, this review highlights setting-specific priorities, including seasonal wetland surveillance, closed farm-water systems, improved market hygiene, and better integration of ecological and genomic data for early warning and control. Full article

The Qinghai Lake Basin, a typical ecologically vulnerable, high-altitude, cold region, requires coordinated ecosystem conservation and socio-economic development to achieve territorial sustainability. Based on the Production–Living–Ecological Space (PLES) framework, this study used land use data from five periods between 2000 and 2020 and integrated the PLUS and InVEST models to examine and simulate the evolution of PLES patterns and carbon stock under four scenarios—natural development, ecological protection, economic development, and sustainable development—in 2035. The results show that the PLES pattern in the Qinghai Lake Basin remained generally stable from 2000 to 2020, with ecological space dominating the landscape, while production and living spaces expanded slowly. Carbon stock increased from 214.73 × 10⁶ Mg to 264.70 × 10⁶ Mg, representing a growth rate of 23.27%. Its spatial distribution is highly consistent with the PLES pattern, with ecological space being the main contributor. By 2035, carbon stock is projected to slightly increase under the natural development scenario; under the ecological protection scenario, the expansion of ecological space leads to an increase in carbon stock; it decreases under the economic development scenario due to the encroachment of ecological space by construction land expansion; and under the sustainable development scenario, which balances economic development and ecological protection, carbon stock increases by 4.87 × 10⁶ Mg, achieving the best overall performance. Therefore, it is essential to properly coordinate the relationships among PLES components to achieve synergistic enhancement of ecosystem services and regional sustainable development. The findings provide methodological references and decision support for sustainable development in the Qinghai–Tibet Plateau and other ecologically vulnerable regions. Full article

Qinghai Lake, the largest endorheic saline lake in China, has undergone a pronounced hydrological regime shift from a multi-decadal decline to a rapid post-2004 recovery, reflecting strong hydroclimatic non-stationarity in the northeastern Tibetan Plateau (TP). This paper supplements the current water level and lake area status of Qinghai Lake to provide basic background for future prediction. Reliable forecasting of such climate sensitive lake systems remains difficult because conventional statistical models often fail to capture non-linear fluctuations, whereas standalone deep learning models may overlook long-term deterministic evolution. To address this challenge, we developed a serial decomposition GeoAI framework that integrates autoregressive integrated moving average (ARIMA), one-dimensional convolutional neural networks (1D-CNNs), and long short-term memory (LSTM) networks for non-stationary water level forecasting. Using annual water level observations from 1960 to 2025, the ARIMA component was first used to extract the low-frequency deterministic trend, after which the CNN-LSTM module reconstructed the nonlinear residual variability. The model was trained on the 1960–2012 period and validated over 2013–2025, which represents the most dynamic expansion stage of Qinghai Lake. The hybrid framework outperformed the benchmark models, achieving a Root Mean Square Error (RMSE) of 0.2033 m, Mean Absolute Error (MAE) of 0.1727 m, and Mean Squared Error (MSE) of 0.0413 m² during validation. The decomposition strategy effectively reduced phase lag and amplitude attenuation, improving both predictive accuracy and process interpretability. Multi-step forecasting for 2026–2056 suggests that Qinghai Lake will continue to rise, reaching approximately 3204.08 m by 2056, although the growth rate is projected to slow as negative hydrological feedback strengthen. By explicitly separating deterministic climate scale signals from nonlinear short-term variability, the proposed framework provides a robust and transferable geoinformation based tool for forecasting water level dynamics and supporting adaptive management in climate sensitive, data scarce lake basins. Full article

The Qinghai Lake Basin represents a critical ecological security barrier in the northeastern Qinghai–Tibet Plateau. Water yield and carbon storage within this basin are closely linked to regional ecological security and sustainable development. To investigate their spatiotemporal patterns, influencing factors, and spatial interrelationships from 1995 to 2020, this study integrated the InVEST model, the Optimal Parameter Geodetector model, and spatial autocorrelation analysis. The results indicate that water yield exhibited a fluctuating yet generally increasing trend over the study period, rising from 1.42 × 10⁹ m³ to 1.97 × 10⁹ m³. High water yield values were predominantly concentrated in high-altitude headwater areas, whereas low values mainly occurred in the lake area and its surroundings. Elevation, annual mean temperature, and precipitation were identified as the primary drivers of water yield. Carbon storage increased from 1.76 × 10⁸ t in 1995 to 2.14 × 10⁸ t in 2020. High carbon storage values were mainly concentrated in grassland and forested areas, while low values were largely distributed in built-up land, unused land, and the lake area. Elevation, NDVI, and water yield emerged as the main influencing factors of carbon storage. A significant positive spatial correlation was observed between water yield and carbon storage. Persistent patterns of high-carbon-storage–high-water-yield clusters and low-carbon-storage–low-water-yield clusters demonstrate a clear spatial synergy. These findings provide scientific support for ecological conservation, water resource management, and carbon sink enhancement in the Qinghai Lake Basin and are of practical significance for sustaining regional ecosystem services and safeguarding sustainability. Full article

This study investigated the interactive effects of warming and inundation on methane (CH₄) fluxes and soil physicochemical mechanisms in the littoral wetland of Qinghai Lake. Soil samples were collected from the Bird Island littoral wetland. Eight treatments were established: natural control (CK), different inundation depths (S0, S10, S20), warming alone (ZWCK), and warming combined with inundation (ZW0, ZW10, ZW20). CH₄ fluxes were measured over one year using an ABB LGR analyzer. Principal component analysis (PCA) and Mantel tests were used to identify environmental drivers. The main findings are as follows: (1) Under different water level treatments, CH₄ fluxes showed a unimodal seasonal pattern, peaking in autumn. Warming and the interactive treatments shifted the emission pattern to bimodal or multimodal and significantly increased emission intensity. The warming-alone group had the highest annual emission, with anomalously high winter emission (47.683 μg·m⁻²·h⁻¹). Under the ZW20 treatment, emissions were synergistically enhanced in summer and autumn but turned to suppression in winter. (2) PCA showed that the carbon nitrogen pool (70.5%) and the salinity pH gradient (14.9%) were the main drivers of soil variation. The interactive effects on carbon-nitrogen dynamics shifted with season: warming promoted accumulation in spring; warming with shallow inundation retained carbon-nitrogen in summer, but deep inundation caused loss; warming with deep inundation formed a nutrient center in autumn; inundation dominated accumulation in winter, while warming increased loss. (3) Mantel tests showed that carbon-nitrogen components were highly correlated across seasons, but were strongly and positively correlated with CH₄ flux only in autumn (Mantel’s r ≥ 0.4, p < 0.05), indicating autumn as the key window. These findings provide important insights into carbon cycling processes and regulatory mechanisms of alpine wetlands under future climate change scenarios. Full article

The reliable identification of productive and nutritionally valuable Bromus inermis Leyss. germplasm requires multi–year evaluation because forage performance is strongly influenced by genotype, stand age, and annual environmental variation. We evaluated four experimental genotypes and the cultivar WUSU as a control over three production years at a fixed alpine site on the Qinghai–Tibet Plateau. Agronomic traits, forage yield, dry matter accumulation, and nutritional quality were measured annually. A multi–criteria TOPSIS model was used to integrate yield and quality traits for genotype ranking, while random forest analysis and piecewise structural equation modeling were applied to identify key traits and potential pathways influencing forage performance. Genotype, year, and their interaction significantly affected most agronomic, yield, and nutritional traits. Most traits reached their highest values in the third production year, indicating that this stage was critical for evaluating full productive potential. Among the tested materials, genotype 4–4 showed consistently high biomass production and favorable nutritional performance, whereas WUSU and genotype 1–10 generally ranked lower. Plant height and grass height were positively associated with fresh and hay yield, while fresh forage yield, crude protein content, and stem diameter contributed strongly to model prediction. The SEM results suggested that genotype–year interaction influenced hay yield mainly through changes in stem diameter and acid detergent fiber content. These findings indicate that combining multi–year field evaluation with multi–criteria ranking and pathway analysis can improve the identification of promising B. inermis germplasm. Genotype 4–4 represents a useful candidate for further multi–site validation and breeding for high–yield, high–quality forage production in alpine regions. These findings provide a theoretical basis and candidate germplasm for the genetic improvement of Bromus inermis Leyss. adapted to the Qinghai–Tibet Plateau. Full article

Under the influence of climate change and human activities, alpine grasslands in the Qinghai Lake basin have undergone a degradation trend over recent decades. In this context, investigating the distribution and stability of soil aggregates across varying degradation degrees of alpine grasslands, along with their driving factors, is critical for formulating sustainable management strategies to maintain grassland health and soil structural resilience in this ecologically sensitive region. In this study, plant and soil samples (0–20 cm) were collected at nine sites in the Qinghai Lake basin, each encompassing a non-degraded (ND), a lightly degraded (LD), and a heavily degraded (HD) grassland plot. The distribution and stability of mechanically stable aggregates and water-stable aggregates were evaluated using the dry-sieving and wet-sieving methods, respectively. The results showed that grassland degradation led to declines in plant above-ground and below-ground biomass, soil carbon, nitrogen, phosphorus, and microbial biomass carbon contents, and β-1,4-nacetylglucosaminidase activity, alongside an increase in soil pH. However, soil β-1,4-glucosidase and alkaline phosphatase activities exhibited no significant changes. The 2–0.25 mm fraction is the primary component of mechanically stable aggregates in alpine grasslands across three degradation levels. After degradation, neither the distribution nor the stability of mechanically stable aggregates exhibited significant changes. In terms of water-stable aggregates, the 2–0.25 mm fraction constituted the primary component in ND and LD, whereas the <0.053 mm fraction predominated in HD. Additionally, the mass proportions of the >2 mm and 2–0.25 mm size fractions were significantly lower in HD compared to ND, while the mass fraction of the <0.053 mm fraction was notably higher. The altered distribution of water-stable aggregates resulted in a significant decrease in mean weight diameter and a notable increase in the percentage of aggregate destruction, suggesting a reduced resistance of the soil to water erosion. Plant below-ground biomass, soil total organic carbon, and total nitrogen were identified as crucial factors modulating the dynamics of aggregate stability during grassland degradation. The findings of this study suggest that alpine grassland degradation in the Qinghai Lake basin reduces the water stability rather than the mechanical stability of soil aggregates. Full article

Desert steppe is a typical ecosystem in arid and semi-arid regions and an important component of the global carbon cycle. Under the background of global climate change, the increasing frequency of extreme precipitation events and changes in precipitation patterns can significantly affect water- and heat-sensitive desert steppe ecosystems, thereby regulating soil CO₂ flux; however, the underlying mechanisms remain unclear. To investigate the effects of precipitation changes on soil CO₂ flux and their roles in carbon cycling and ecological sustainability, this study was conducted in a desert steppe. Seven precipitation treatments were established, including a control (CK) and ±15%, ±30%, and ±45% precipitation gradients. Based on the static chamber-gas chromatography method, combined with principal component analysis (PCA), correlation analysis, random forest modeling, and stepwise regression, the main influencing factors and their diurnal variation patterns of soil CO₂ flux were analyzed over 24 h periods from June to August. The results show that CO₂ flux ranged from −68.33 to 77.59 mg·m⁻²·h⁻¹. During the study period, CO₂ flux exhibited a diurnal pattern characterized by daytime emissions and weak nighttime emissions or uptake, along with clear seasonal variation. The ±30% precipitation treatment showed the largest fluctuation in CO₂ flux. Soil hydrothermal factors were identified as the key drivers of CO₂ flux. With changes in precipitation intensity, the combined effects of multiple factors increased ecosystem complexity, and the controlling factors showed clear seasonal differences. The results from different analytical methods were generally consistent, providing a reference for predicting CO₂ flux, developing carbon sink strategies, and supporting sustainable ecological management in desert steppe regions. Full article

Against the background of a warming and humidifying climate on the Qinghai–Tibet Plateau, increasing attention has been paid to the sustainability of water resources and ecosystems in the Qinghai Lake Basin. Investigating the characteristics of precipitation stable isotopes and moisture sources provides critical insights into the driving mechanisms of the regional hydrological cycle. In this study, precipitation samples collected at the Qinghai Lake Wetland Ecosystem National Observation and Research Station from June 2023 to October 2024 were analyzed for hydrogen (δ²H) and oxygen (δ¹⁸O) stable isotopes. The temporal variations of δ²H, δ¹⁸O, and deuterium excess (d-excess) were characterized, and their relationships with air temperature and precipitation amount were examined. In addition, a backward trajectory model was employed to identify the moisture sources of precipitation during the observation period. The results indicate that: (1) precipitation stable isotopes and d-excess exhibit pronounced seasonal variability, characterized by enrichment in summer and depletion in spring and autumn; (2) the Local Meteoric Water Line (LMWL) for the basin is defined as δ²H = 8.15δ¹⁸O + 38.71 (R² = 0.93), with both slope and intercept exceeding those of the Global Meteoric Water Line (GMWL); (3) precipitation isotopes show a discernible temperature effect but are jointly controlled by multiple moisture sources and meteorological factors; and (4) backward trajectory analysis combined with d-excess values reveals that precipitation moisture is primarily derived from westerly transport, while locally recycled moisture and continental air masses also exert significant influences. Overall, these findings reveal the multi-source driving mechanisms of the regional hydrological cycle and provide critical scientific support for understanding hydrological processes in alpine inland basins and their responses to future climate change, thereby contributing to the sustainable management of regional water resources. Full article

Alpine wetlands in the Qinghai Lake Basin, located on the northeastern Qinghai–Tibetan Plateau, are ecologically important but highly vulnerable to climate change and anthropogenic disturbance. Traditional field-based surveys are labor-intensive and spatially constrained, underscoring the need for automated remote sensing approaches for large-scale wetland mapping. In this study, an object-based image analysis (OBIA) framework was developed by integrating Sentinel-2 optical imagery with Sentinel-1 synthetic aperture radar (SAR) data to classify two representative plateau wetland types: marsh meadows and inland tidal flats. Seven categories of features were evaluated, including spectral features, vegetation indices, water indices, red-edge features, topographic variables, radar backscatter, and geometric-textural metrics. The Separability and Thresholds (SEaTH) algorithm was employed for feature selection and optimization prior to classification using a Random Forest model. The results indicate that the incorporating geometric and textural features significantly improved classification performance, achieving an overall accuracy (OA) of 82.53% and a Kappa coefficient of 0.74. Moreover, the SEaTH-based feature optimization scheme yielded the best performance, with an OA of 86.24% and a Kappa coefficient of 0.79. Compared with the full feature set, this approach improved producer’s accuracy by 3.96–6.11% and increased overall accuracy by 1.48%. The proposed framework provides an effective and computationally efficient approach for mapping ecologically fragile alpine wetlands and offers valuable support for wetland conservation in the Qinghai Lake Basin. Full article

The Qinghai–Tibet Plateau is undergoing rapid warming and humidification, with altered precipitation regimes increasingly affecting soil nitrogen cycling and N₂O emissions. Denitrification—a key nitrogen transformation pathway—is particularly sensitive to these hydrological changes. Here, we investigated the response of nirK-type denitrifying microbial communities to altered precipitation in an alpine wetland on the northern shore of Qinghai Lake. Using a long-term precipitation manipulation platform with five gradients (ambient, ±25%, and ±50%), we integrated high-throughput sequencing with bioinformatics to systematically assess community shifts. Short-term precipitation treatments did not significantly alter alpha diversity, but markedly restructured community composition. Extreme wetting (+50%) increased within-group heterogeneity. At the phylum level, Proteobacteria remained dominant across all treatments, whereas extreme drought (−50%) suppressed Planctomycetes. At the genus level, Ochrobactrum was enriched under reduced precipitation, while Rhodopseudomonas increased under increased precipitation. Functional predictions indicated that reduced precipitation enhanced nitrogen fixation potential, whereas increased precipitation favored nitrate respiration. Soil pH and carbon fractions were the key environmental filters driving community variation. Ecological process analysis revealed that community assembly was entirely governed by deterministic processes, specifically variable selection. Together, these findings elucidate how precipitation shifts reconfigure the structure and functional potential of denitrifying microbial communities in alpine wetlands, primarily via changes in soil pH and moisture under variable selection. This work provides critical insights into microbial regulation of the nitrogen cycle on the Tibetan Plateau under ongoing climate change. Full article

Climate warming is an important driver influencing soil microbial involvement in carbon cycling. To clarify the responses of carbon-fixing microorganisms in alpine lakeshore wetlands, we conducted a warming experiment using open-top chambers (OTCs) in the Qinghai Lake lakeshore wetland and applied high-throughput sequencing of the cbbM gene. The results indicated that warming significantly increased soil temperature and reduced soil moisture, but had no significant effects on soil pH, total carbon, or total nitrogen content. Despite the stability of community α-diversity, warming markedly reshaped the community composition and significantly elevated the relative abundances of dominant taxa including Ensifer and Hydrogenovibrio. In addition, warming significantly strengthened the assembly process of the cbbM-bearing carbon-fixing microbial community, in which heterogeneous selection played a leading role. Redundancy analysis revealed that soil total nitrogen and pH were major drivers influencing the composition of the microbial community. Notably, despite significant fluctuations in taxonomic composition, the functional profile dominated by sulfur oxidation and phototrophy remained unchanged, indicating strong functional redundancy. Overall, cbbM carbon-fixing microorganisms in alpine lakeshore wetlands effectively buffered environmental disturbances through functional redundancy and maintained stable carbon metabolic functions, providing scientific evidence for the short-term resilience of carbon sink functions in alpine wetlands under climate warming. Full article

Understanding the forage resources that sustain endangered herbivores under strong seasonal constraints is essential for effective habitat restoration. Przewalski’s gazelle (Procapra przewalskii), an endemic ungulate restricted to the Qinghai Lake Basin on the Qinghai–Tibet Plateau, persists in fragmented subpopulations facing pronounced seasonal bottlenecks in forage availability. Here, we investigated seasonal dietary strategies and forage selectivity across nine geographically isolated subpopulations by integrating fecal microhistological diet analysis with vegetation surveys and availability-corrected Jacobs’ electivity indices. Gazelle diets were compressed in early spring, dominated by graminoids (Poaceae and Cyperaceae), but expanded substantially during summer, with increased contributions from Fabaceae and Rosaceae and significantly higher richness and niche breadth. Electivity analyses revealed a hierarchical spectrum of preferences structured around core foundation taxa consistently selected across seasons, complemented by season-specific priority resources during spring bottlenecks and summer abundance. Basin-wide pairwise ranking further identified seasonal priority forage taxa with varying spatial consistency across subpopulations. These findings provide a seasonally explicit framework for identifying key forage targets and guiding evidence-based restoration and zoned management within Qinghai Lake National Park, offering transferable insights for conserving endangered plateau herbivores under fragmentation and strong seasonal resource limitation. Full article

Alluvial–proluvial parent-material soils are widely distributed in the Qinghai Lake Basin; however, their timing of development and associated climatic background remain poorly constrained. In this study, two representative alluvial–proluvial fan-covered soil profiles (QRZQ and YXC) from the Qinghai Lake Basin were investigated. Quartz optically stimulated luminescence (OSL) dating was combined with analyses of grain-size composition and soil organic carbon (SOC) to constrain the timing of soil development and its climatic background. The results show that the studied soil profiles are mainly characterized by Ah–As–C and Ah–A–C horizon configurations, with soil development spanning from 15.7 to 1.0 ka. The underlying alluvial–proluvial parent material of the QRZQ profile formed during the Last deglaciation, whereas the oldest OSL ages in the YXC profile occur within a weakly developed A horizon, indicating that this profile had already transitioned from a depositional environment to a pedogenic environment during the Last deglaciation. This contrast reflects staged differences between depositional and pedogenic processes within alluvial–proluvial settings. The soils were formed through upbuilding pedogenesis, in which sediment accumulation and top-down pedogenic modification proceeded concurrently. Grain-size composition and SOC characteristics further indicate that the depositional environment of the YXC profile was relatively stable. Integrating the obtained chronological results with regional climatic changes suggests that climate variability in the Qinghai Lake Basin exerted a primary control on the transformation between sedimentary processes and soil development. In particular, the Late Holocene (0–4 ka), characterized by a generally cold–dry climate accompanied by pronounced humidity fluctuations, represents an important pedogenic stage for alluvial–proluvial parent-material soils in the Qinghai Lake Basin. This study provides a robust chronological framework for further investigating the mechanisms of soil development in alluvial–proluvial environments from a climatic perspective. Full article