Search Results (38)

The Qinghai-Xizang Plateau is among the most ecologically vulnerable and responsive areas worldwide. Studying the characteristics of soil microbial communities along altitudinal gradients on plateaus and revealing the response mechanisms and vertical distribution patterns of microbial communities in alpine ecosystems is of significant academic value for assessing the ecological stability of the Qinghai-Xizang Plateau. This research examines the Lhasa River Basin by employing Illumina NovaSeq high-throughput sequencing to investigate how soil bacterial and fungal communities shift across elevation gradients in the Duilong Qu subbasin. This study also explored the key environmental drivers behind these microbial distribution patterns. The results indicate the following: (1) Key bacterial groups in the Duilong Qu Basin soil include Proteobacteria, Acidobacteria, and Actinobacteria, with Ascomycota, Mortierellomycota, and Basidiomycota as the prevalent fungal phyla. (2) Soil bacterial richness fluctuates with increasing elevation, and diversity exhibits a V-shaped distribution; fungal richness increases monotonically with elevation, whereas diversity shows no altitudinal dependence. (3) Principal coordinate analysis (PCoA) revealed that bacterial community structures exhibit separation trends across different elevations, with high intragroup consistency; fungal community structures at mid-elevations (4000–5000 m) show clustering similarity, whereas those at 3650–5000 m and 5500 m remain highly distinct from those at other elevations. (4) RDA reveals that factors such as accessible phosphorus, potassium, and organic content have a major effect on how bacterial communities are arranged. On the other hand, soil conductivity, along with available and total phosphorus levels, as well as pH, plays a key role in shaping fungal communities. (5) Functional prediction analysis suggests that soil bacteria shift from aerobic and biofilm-forming to facultatively anaerobic, stress-tolerant, and pathogenic traits with increasing elevation. Fungi are predominantly undefined saprotrophs, transitioning from ectomycorrhizal and pathogenic functions to saprotrophic functions at relatively high elevations. Full article

Limited surface energy and mass flux data hinder the understanding of glacier retreat mechanisms on the Qinghai–Tibet Plateau (QTP). Glaciers in the west Nyainqentanglha Range (WNR) supply meltwater to the densely populated Lhasa River basin (LRB) and Nam Co, the QTP’s second-largest endorheic lake. In this study, we used a glacier mass balance model based on the degree-day method (GMB-DDM) to understand the response of glacier changes to climate warming. The spatiotemporal variation in degree-day factors for ice (DDF_ice; plural form: DDFs_ice) was assessed to characterize the sensitivity of glacier melt to warming over 44 years in the WNR. Our results demonstrate that the GMB_DDM effectively captured the accelerated mass loss and regional heterogeneity of WNR glaciers from 2000 to 2020, particularly the intensified negative balance after 2014. Moreover, glacier ablation was more sensitive to warming in the WNR during 2000–2020 than 1976–2000, with DDF_ice increases of 21% ± 8% in the LRB and 31% ± 10% in the Nam Co basin (NCB). Increased precipitation during the ablation season and reduced glacier surface albedo can explain the increased sensitivity to warming during 2000–2020. These findings could support sustainable water resource management in the LRB, NCB, and the surrounding areas of the QTP. Full article

The internal response mechanism of vegetation change in fragile high-altitude ecosystems is pivotal for ecological stability. This study focuses on the Lhasa River Basin (LRB) on the Tibetan Plateau (TP), a typical high-altitude fragile ecosystem where vegetation dynamics are highly sensitive to climate change and human activities. Utilizing MODIS surface reflectance data (MOD09Q1), a general regression neural network (GRNN) was applied to create a 250 m resolution fractional vegetation cover (FVC) dataset from 2001 to 2022, whose accuracy was verified with field survey data. Through methods like the Theil–Sen Median trend analysis, Mann–Kendall significance test, Hurst exponent, and geographical detector, the collaborative mechanism of 14 driving factors was systematically explored. Key conclusions are as follows: (1) The FVC in the LRB evolved in stages, first decreasing and then increasing, with 46.71% of the basin area expected to show an improvement trend in the future. (2) Among natural factors, elevation (q = 0.480), annual mean potential evapotranspiration (q = 0.362), and annual mean temperature (q = 0.361) are the main determinants of FVC spatiotemporal variation. (3) In terms of human activities, land use type has the highest explanatory power (q = 0.365) for FVC. (4) The interaction of two factors on FVC is stronger than that of a single factor, with the elevation–land use interaction being the most significant (q = 0.558). These results deepen our understanding of the interactions among vegetation, climate, and humans in fragile high-altitude ecosystems and provide a scientific basis for formulating zoned restoration strategies on the TP. Full article

Terrestrial ecosystem vegetation are vulnerable to the joint impacts of human activities and climate change, particularly in ecologically fragile areas such as the Tibetan Plateau. Identifying vegetation cover changes and distinguishing their driving factors are crucial for ecological conservation in this region. This study utilized MODIS normalized difference vegetation index (NDVI) data from 2000 to 2019, combined with trend analysis (univariate linear regression and the Mann–Kendall test), partial correlation analysis, and residual analysis methods, to investigate the spatial and temporal dynamics of vegetation cover and its responses to climate change and human activities in the Yarlung Tsangpo River, Lhasa River, and Nianchu River Basin (YLN Basin) on the Tibetan Plateau. The results revealed significant differences in vegetation dynamics both in summer and the growing season: the average summer NDVI showed a significant decreasing trend during the study period, whereas the growing season NDVI exhibited no significant overall temporal trend, which highlighted the necessity of assessing vegetation dynamics seasonally to accurately capture their interannual complexity. Partial correlation analysis indicated that precipitation was the key limiting climatic factor for vegetation growth in this region, with its positive influence covering over 90% of the land area during summer and over 60% during the growing season. The residual analysis further indicated the dual and spatially heterogeneous roles of human activities: on the one hand, positive impacts, primarily from vegetation restoration projects, promoted NDVI increases in some areas; on the other hand, negative impacts, such as continuous grazing pressure, population growth, and associated land use changes, inhibited vegetation development in other areas. This study quantitatively assessed the combined effects of climate variability and complex human activities on the vegetation NDVI in the YLN Basin, emphasizing that the development of adaptive management and effective vegetation restoration strategies must fully consider seasonal differences, the key climatic limiting factor (water availability), and the spatial heterogeneity of human impacts to promote sustainable development in this ecologically fragile region. Full article

The Lhasa River, as one of the major rivers on the Tibetan Plateau, is of great value for the study of climate and environmental changes on the Tibetan Plateau. In this paper, the grain size and the mineralogical and geochemical characteristics of the sediments from the Lhasa River were investigated. The results show the following: (1) The average grain size of the Lhasa River sediments is coarse (65.5% sand, 23.6% silt), and the sorting is overall poor; the skewness is mostly positive, and the kurtosis is wide, which reflects the obvious characteristics of river sand deposition. (2) The mineral composition of the Lhasa River sediments is dominated by quartz (38.4%), feldspar, and plagioclase feldspar, followed by clay minerals, and the content of carbonate minerals is relatively low; the content of clay minerals in the illite content is as high as 83.3%, while the chlorite content is slightly higher than kaolinite, and smectite content is very low. The chemical index of illite is less than 0.4, indicating that illite is mainly iron-rich magnesium illite. (3) The value of the chemical weathering index (CIA) of the sediments is low, implying that the sediments are in a weak–moderate chemical weathering state and dominated by physical weathering. Comprehensive analyses further revealed that the weathering process of the sediments in the Lhasa River was influenced by both climate and lithology, i.e., sediment composition is influenced not only by chemical weathering in a dry, cold climate but also by physical weathering of granites exposed over large areas. The results of this study can provide scientific references for further in-depth research on the environmental and climatic effects of the Tibetan Plateau. Full article

The dynamic changes in plateau river ecosystems and the driving mechanisms of environmental factors have garnered significant attention. Phytoplankton, a core component of aquatic ecosystems, can directly reflect changes in the aquatic environment. This study focuses on the phytoplankton in the Lhasa River Basin, including the riverbed from the source to the river mouth, five largest tributaries, and two adjacent wetlands. We analyzed the spatial and temporal variation characteristics of phytoplankton and explored the environmental driving mechanisms based on four field surveys conducted between September 2019 and March 2021. Results showed that a total of 127 species of phytoplankton from six algal phyla were identified, including Cyanobacteria. Among these, Bacillariophyta was the dominant group, accounting for 41.7% of the identified species. Spatially, phytoplankton diversity showed a decreasing trend from upstream to downstream while temporally peaking in spring and autumn. Redundancy analysis revealed that upstream phytoplankton were driven by total hardness and altitude, midstream by pH and potassium ions, and downstream by nitrate and ammonium nitrogen. Classification and regression tree analysis showed total hardness, magnesium ions, and nitrite were key factors influencing phytoplankton abundance, diversity, and evenness. This study highlights the ecological dynamics and driving mechanisms of phytoplankton communities in the Lhasa River, demonstrating their high sensitivity to environmental factors. These findings could help to establish phytoplankton as critical indicators of aquatic ecosystem health and provide scientific guidance for the conservation and management of the plateau river ecosystems. Full article

Grazing intensity is one of the crucial anthropogenic activities on alpine grasslands. However, how grazing intensity affects soil microorganism diversities and their co-occurrence networks in alpine steppe remains uncertain. We carried out a controlled grazing experiment (null grazing, CK; moderate grazing, MG; and heavy grazing, HG) on a typical alpine steppe in the Lhasa River Basin, Central Tibet, China. We used high-throughput sequencing to find the sequences of bacterial 16S rRNA and fungal ITS gene amplicons. Then, we analyzed their alpha and beta diversities and set up co-occurrence networks that show how often they occur together. MG significantly increased the bacterial Shannon index and changed the bacterial community structure. In contrast, HG decreased the fungal ACE and Chao1 indices and also changed the fungal community structure (p < 0.05). Linear mixed-effect model revealed that available phosphorus in soil significantly impacted on soil bacterial Shannon, ACE, and Chao1 indices across grazing intensities, while total carbon in subsoil significantly affected these indicators of soil fungi. Moreover, MG increased the complexity of the co-occurrence network in the bacterial community, while HG simplified it. However, both MG and HG made the co-occurrence networks in the fungal community less complicated. This shows that the intensity of grazing has different impacts on how microbes interact with each other. Therefore, sustainable grazing intensity necessitates a deeper understanding of biodiversity conservation in alpine grasslands. Full article

The analysis of temporal and spatial variability in risk has garnered significant research attention, particularly regarding flash flood disasters in the context of warming and wetting conditions on the Qinghai–Tibetan Plateau. Focusing on the Lhasa River basin, this study develops a framework that integrates geographic information systems and a combined subjective–objective weighting approach to comprehensively assess flash flood risk despite limited observations. This paper investigates the distribution patterns of hazard, vulnerability, and the integrated risk of pluvial flash floods; demonstrates the reliability of the assessment results; and provides mitigation recommendations for disaster risk management at the county level. The results showed a trend in increasing flash flood risk in recent decades compared to the 1990s. Moreover, very-high- and high-risk areas were concentrated in downstream regions with frequent precipitation extremes and anthropogenic activity. From 1991 to 2020, the high to very high-risk areas gradually expanded from central Lhasa to neighbouring counties. This study contributes valuable insights into flash flood risk assessment cand mapping, which are crucial in terms of the protection of life and property in the plateau basin. Full article

Accurate cropland distribution data are essential for efficiently planning production layouts, optimizing farmland use, and improving crop planting efficiency and yield. Although reliable cropland data are crucial for supporting modern regional agricultural monitoring and management, cropland data extracted directly from existing global land use/cover products present uncertainties in local regions. This study evaluated the area consistency, spatial pattern overlap, and positional accuracy of cropland distribution data from six high-resolution land use/cover products from approximately 2020 in the alpine agricultural regions of the Hehuang Valley and middle basin of the Yarlung Zangbo River (YZR) and its tributaries (Lhasa and Nianchu Rivers) area on the Qinghai-Tibet Plateau. The results indicated that (1) in terms of area consistency analysis, European Space Agency (ESA) WorldCover cropland distribution data exhibited the best performance among the 10 m resolution products, while GlobeLand30 cropland distribution data performed the best among the 30 m resolution products, despite a significant overestimation of the cropland area. (2) In terms of spatial pattern overlap analysis, AI Earth 10-Meter Land Cover Classification Dataset (AIEC) cropland distribution data performed the best among the 10 m resolution products, followed closely by ESA WorldCover, while the China Land Cover Dataset (CLCD) performed the best for the Hehuang Valley and GlobeLand30 performed the best for the YZR area among the 30 m resolution products. (3) In terms of positional accuracy analysis, the ESA WorldCover cropland distribution data performed the best among the 10 m resolution products, while GlobeLand30 data performed the best among the 30 m resolution products. Considering the area consistency, spatial pattern overlap, and positional accuracy, GlobeLand30 and ESA WorldCover cropland distribution data performed best at 30 m and 10 m resolutions, respectively. These findings provide a valuable reference for selecting cropland products and can promote refined cropland mapping of the Hehuang Valley and YZR area. Full article

Runoff simulation is essential for effective water resource management and plays a pivotal role in hydrological forecasting. Improving the quality of runoff simulation and forecasting continues to be a highly relevant research area. The complexity of the terrain and the scarcity of long-term runoff observation data have significantly limited the application of Physically Based Models (PBMs) in the Qinghai–Tibet Plateau (QTP). Recently, the Long Short-Term Memory (LSTM) network has been found to be effective in learning the dynamic hydrological characteristics of watersheds and outperforming some traditional PBMs in runoff simulation. However, the extent to which the LSTM works in data-scarce alpine regions remains unclear. This study aims to evaluate the applicability of LSTM in alpine basins in QTP, as well as the simulation performance of transfer-based LSTM (T-LSTM) in data-scarce alpine regions. The Lhasa River Basin (LRB) and Nyang River Basin (NRB) were the study areas, and the performance of the LSTM model was compared to that of PBMs by relying solely on the meteorological inputs. The results show that the average values of Nash–Sutcliffe efficiency (NSE), Kling–Gupta efficiency (KGE), and Relative Bias (RBias) for B-LSTM were 0.80, 0.85, and 4.21%, respectively, while the corresponding values for G-LSTM were 0.81, 0.84, and 3.19%. In comparison to a PBM- the Block-Wise use of TOPMEDEL (BTOP), LSTM has an average enhancement of 0.23, 0.36, and −18.36%, respectively. In both basins, LSTM significantly outperforms the BTOP model. Furthermore, the transfer learning-based LSTM model (T-LSTM) at the multi-watershed scale demonstrates that, when the input data are somewhat representative, even if the amount of data are limited, T-LSTM can obtain more accurate results than hydrological models specifically calibrated for individual watersheds. This result indicates that LSTM can effectively improve the runoff simulation performance in alpine regions and can be applied to runoff simulation in data-scarce regions. Full article

Alluvial fans have been proven to have great utilisation potential in QTP, but to what extent they are suitable for agricultural development is unknown. Therefore, using the alluvial fan in the Lhasa River Basin (LRB) as a case study, this paper established an evaluation system of land suitability for agriculture (LSA). Principal component analysis (PCA) and the exhaustive method (EM) were used to define the minimum dataset (MDS) and then the LSA of the alluvial fan in the LRB was evaluated using a comprehensive index of LSA. Two scientific approaches were implemented to improve the LSA using a scenario simulation. The results showed that the MDS assessed by the EA was more representative compared to the PCA. Alluvial fans with suitable grades are mainly distributed in the Lhasa River’s middle and lower reaches. Developing facility agriculture and repairing roads accessing the alluvial fans are effective approaches to improve the LSA, which can increase the suitable-grade area from 58.62% to 97.82% and 63.85%, respectively. Therefore, most alluvial fans in the LRB are suitable for developing agriculture, and under the influence of human activities, there will be more alluvial fans suitable for developing agriculture. Our research provides scientific methods for the sustainable development of land in alpine regions. Full article

The quantitative evaluation and prediction of ecosystem service value (ESV) in the Lhasa River Basin can provide a basis for ecological environment assessment and land-use optimization and adjustment in the future. Previous studies on the ESV in the Lhasa River Basin have focused mainly on static assessment and evolution analysis based on historical data, and have not considered future development trends. Moreover, most of the current driving factors selected in land use and ESV prediction studies are homogeneous, and do not reflect the geographical and cultural characteristics of the study area well. With the Lhasa River Basin as the research focus, 20 driving factors were selected according to the characteristics of the plateau alpine area, and the land-use changes under three developmental orientations, namely, natural evolution, ecological protection, and agricultural development, were predicted for the year 2030 with the FLUS-Markov model. Based on these predictions, the values of ecosystem services were calculated, and their spatiotemporal dynamic characteristics were analyzed. The results show that the model has high accuracy in simulating land-use change in the Lhasa River Basin, with a kappa coefficient of 0.989 and an overall accuracy of 99.33%, indicating a high applicability. The types of land use in the Lhasa River basin are dominated by the existence of grassland, unused land, and forest, with a combined proportion of 94.3%. The change trends of each land-use type in the basin under the three scenarios differ significantly, with grassland, cropland, and building land showing the most significant changes. The area of cropland increased only in the agricultural development scenario; the areas of forest and grassland increased only in the ecological protection scenario; and the expansion of building land was most effectively controlled in the ecological protection scenario. The ESV increased in all three scenarios, and the spatial distribution of the ESV per unit area in the middle and lower reaches was greater than that in the upper reaches. The ESV was the greatest in the ecological protection scenario, with grasslands, forests, and water bodies contributing more to the ESV of the basin. This study provides decision-making references for the effective utilization of land resources, ecological environmental protection planning, and urban construction in the Lhasa River Basin in the future. Full article

Quantifying the spatiotemporal patterns of the coordination between ecosystem service supply and demand is vital for regional sustainable development. To reveal the dynamic pattern of the coordination of ecosystem service (ES) supply and demand in the Lhasa River Basin, we quantified the supply of the following four ESs using the InVEST model from 2000 to 2018: carbon sequestration (CS), water conservation (WC), habitat quality (HQ), and soil conservation (SC). Using socio-economic data, including land development degree, GDP, and population density, the ES demand was quantified. The ES supply–demand ratio (ESDR) and coupling coordination degree (CCD) model were used to evaluate the coupling relationship and coordination of ES supply and demand. The spatial autocorrelation analysis was used to determine the spatial correlation and changes in the ES supply–demand coupling coordination degree. The results indicate that the distribution of ESDR exhibited significant spatial heterogeneity. The area with ES supply far greater than demand was always in the upstream area of the Lhasa River, while the ES demand of Chengguan District far exceeded supply. Grasslands and forests were the main contributors to ESDRs, providing positive ESDRs for three services, SC, HQ, and WC, with a total proportion above 80%. From 2000 to 2018, the mismatch between ES supply and demand was gradually spreading upstream, while the upstream areas had a relatively high CCD. The spatial correlations of the CCD in the Lhasa River basin all showed statistically significant differences (p < 0.01). The high–high aggregation areas were concentrated in the northeast of the Lhasa River basin, while the low–low aggregation areas were centered around Chengguan District. This study provides reference values for optimizing the land use spatial patterns in ecologically vulnerable areas with the goal of sustainable development. Full article

The species-area relationship (SAR) is a well-established, globally recognized ecological pattern, and research on SAR has expanded to include the phylogenetic diversity-area relationship (PDAR). However, this research has generally been limited to terrestrial systems. Using data on freshwater macroinvertebrates, the log–log form of the SAR and PDAR power models were compared between the Lhasa River and the Niyang River on the Tibetan Plateau in China. The study reveals that there is a significant difference in the slopes of SAR and PDAR between the two rivers, with the Lhasa River having a considerably higher slope. The beta diversity calculations in these two basins support this pattern, with the Lhasa River exhibiting significantly higher numbers of species and greater total phylogenetic beta diversity than the Niyang River. Regarding species replacement, the turnover component was the primary driver of both species and phylogenetic beta diversity in both rivers. These differences in the beta diversity components were mainly driven by dispersal constraints because spatial distance had a large effect on total beta diversity and turnover fractions. In addition, the nestedness component was more affected by climate and land cover, indicating that highland rivers are subject to the threats of anthropogenic disturbance and climate change. Therefore, spatial factors play a crucial role in determining the distribution of passively dispersed benthic organisms as the scale of change in rivers increases from local to regional effects. Full article

The Yarlung Zangbo River (YZR) is the longest plateau river in China and has famous tributaries, the Lhasa River and the Nianchu River. A total of 75 water samples were collected from the Yarlung Zangbo River Basin (YZRB) in this study to investigate the dissolved concentration, spatial distribution, and source of trace elements (Fe, V, Be, Ti, Mo, Se, Cd, Zn, Cu, Ni, Co, Mn, Cr, Ba, Tl, Pb, Hg, As, and Sb). The results indicate that only Cr and Tl contaminate water, while the other trace elements were in an unpolluted state. In addition, correlation analysis showed that there was a highly significant positive correlation between the concentrations of As, Sb, and Mo; there was also a highly significant positive correlation between the concentrations of Fe, Mn, Ti, Pb, Ni, Co, and Ba. The results of Positive Matrix Factorization (PMF) showed that there were four sources of trace elements in the YZRB, including the resuspension and dissolution of sediments (16.283%), agricultural source (11.436%), lithological source (47.418%), and soil-forming rocks (6.374%). Cluster analysis combined with PMF normalized contribution analysis, which showed that the trace elements found in the YZR’s mainstream were predominantly influenced by the surrounding rocks composition. Meanwhile, both the discharge of mining wastewater and sediments were marked in the Lhasa River. Additionally, agricultural activities were the chief contributors to the trace elements in the Nianchu River. Furthermore, the entire basin was subjected to the influence of soil-forming rocks. This study comprehensively analyzed and evaluated the physicochemical properties of water, the spatial distribution, and the pollution degree, and performed source analysis of trace elements in the YZRB. This research provides a foundational reference for further investigation of the spatial distribution and origins of trace elements in the rivers of the Qinghai–Tibet Plateau (QTP). Full article