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Due to warm and humid air currents of the Indian Ocean and the southwest monsoon, the Palong Zangbo catchment in southeastern Tibet has developed oceanic glaciers in the valley, and the activity of glacial debris flows has been gradually intensified under neotectonic activity, frequent earthquakes, climate change, and extreme rainfall. In this paper, the topographic and morphological data of the debris flow basin, the dynamic evolution characteristics of glaciers and glacial lakes were analyzed by using multisource long-term series of remote sensing images. Simultaneously, the distribution of moraines and landslide sources were extracted based on satellite image. In addition, climate change in the study area was analysed using temperature and rainfall data from the last 40 years, revealing that the average temperature in the study area from May to October presented a fluctuating tendency as a whole, especially after 2013, when the temperature gradually increased. As these temperature changes led to continuous melting of the glaciers in the study area, the glacier area decreased from 8,300 km[sup 2] in 1988-4,584 km[sup 2] in 2019, which decreased nearly 45%. However, the number and area of glacial lakes in the study area gradually increased under a power-law trend, which further led to a significant increase on the possibility of glacial lake rupture in the study area. Due to the joint effects of earthquakes, glacier melting and glacial lake collapse, the debris flows in the study area were well developed, and a total of 122 debris flows were found with varying channel lengths, areas and material sources. Importantly, the characteristics of the glaciers, glacial lakes and climate change in the study area have indicated that the glaciers have retreated, the number of glacial lakes has increased, and the risk of debris flow in this basin will increase in the future. Therefore, it is necessary to strengthen monitoring and early warnings on floods due to glacial lake collapses and debris flows in the study area to improve the risk management of debris flows and floods and the prevention and mitigation of disasters. [ABSTRACT FROM AUTHOR]

The growth history of the Tibetan Plateau provides a valuable natural laboratory to understand tectonic processes of the India–Asia collision and their impact on and interactions with Asian and global climate change. However, both Tibetan Plateau growth and Asian paleoenvironments are generally poorly documented in pre-Pliocene times and reflect limited temporal coverage for different parts of the plateau. In this paper, the 238 m thick Cenozoic sediments in the Hongzhuang section of the Xunhua Basin were tested and analyzed via paleomagnetic and environmental magnetic methods. The formation age was determined, and the evolution history of the regional climate environment was analyzed. The magnetostratigraphy study shows that the sediments record a continuous sequence of geomagnetic polarity changes from C5ACn to C10r, which spans an interval of approximately 30~14.3 Ma from the early Oligocene to the middle Miocene. The magnetic susceptibility of the Hongzhuang section is basically similar to the deep-sea oxygen isotope fluctuation, indicating that the monsoon climate change indicated by the magnetic susceptibility is affected by global temperature. It is worth noting that at ~27 Ma and ~15 Ma, there is a negative correlation between magnetic susceptibility and deep-sea oxygen isotope, and magnetic susceptibility lags behind the increase in deep-sea oxygen isotope. Combined with the change in the sedimentary rate curve, we explain the asynchrony between the magnetic susceptibility and the deep-sea oxygen isotope around ~27 Ma and ~15 Ma. As the uplift of the plateau leads to the enhancement of the East Asian summer monsoon, the soil formation in the region is strengthened, resulting in an increase in magnetic susceptibility. At the same time, the rapid uplift of the plateau caused the erosion of the surrounding mountains to strengthen, and the input of near-source materials may promote the increase in magnetic susceptibility. [ABSTRACT FROM AUTHOR]

As the main body of the Qinghai–Tibet Plateau, the Tibet Autonomous Region is an important ecological security barrier for the surrounding areas and even for Asia. However, the ecological environment is very fragile, and slight changes in land use may seriously affect the stability of the ecosystem. Therefore, it is necessary to deeply explore the driving factors of change in the various land-use types to stabilize the ecological structure and function of Tibet. In this paper, the transition matrix, land dynamic degree and Geodetector model are introduced to obtain the land-use change in the whole Tibetan region and its four subregions from 1990 to 2020. Based on the elevation, slope, temperature, precipitation, population and GDP, the driving factors of conversions between land-use types are explored. The results showed that during the study period, farmland, grassland and forest all showed a decreasing trend in area size. The grassland is large in the northwest region and is the main land-use type in Tibet, and its conversion to water area is the largest. The area of construction land has increased significantly, and its occupation of farmland is the largest, especially in the southwest region. The Geodetector results show that there are differences in the driving factors of the conversions between the whole region and each subregion. In the whole region, the increase in precipitation and temperature were the main drivers of unutilized land and grassland-to-water area conversions, whereas the growth of GDP and population were the dominant drivers of built-up land expansion; however, at the subregional scale, the driving effects of topographic and climatic factors in the two conversions were enhanced. In addition, under the implementation of different ecological protection measures, the productivity of vegetation has been improved. Based on the study results, ecological protection and restoration projects can be implemented in a targeted manner by guiding human activities and formulating reasonable plans to achieve the purpose of strengthening the sustainability of land use and protecting the ecological environment regionally. [ABSTRACT FROM AUTHOR]

Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau ecosystem is fragile, experiencing rapid changes in land cover driven by both climate change and human activities, leading to habitat fragmentation and loss and resulting in biodiversity decline. Habitat ecological networks (HA-ENs) are considered effective solutions for habitat connectivity and biodiversity conservation in response to these dual drivers. However, HA-EN studies typically rely on current or historical landscape data, which hinders the formulation of future conservation strategies. This study proposes three future scenarios—improvement, deterioration, and baseline scenarios—focused on the southeastern Qinghai–Tibet Plateau (SE-QPT). The habitats of 10 species across three classes are extracted, integrating land use and climate change data into habitat ecological network modeling to assess the long-term dynamics of HA-ENs in the SE-QPT. Finally, conservation management strategies are proposed based on regional heterogeneity. The results show the following: Climate change and human activities are expected to reduce the suitable habitat area for species, intensifying resource competition among multiple species. By 2030, under all scenarios, the forest structure will become more fragmented, and grassland degradation will be primarily concentrated in the southeastern and western parts of the study area. Compared to 1985 (71,891.3 km2), the habitat area by 2030 is projected to decrease by 12.9% (62,629.3 km2). The overlap rate of species habitats increases from 25.4% in 1985 to 30.9% by 2030. Compared to the HA-EN control in 1985, all scenarios show a decrease in connectivity and complexity, with only the improvement scenario showing some signs of recovery towards the control network, albeit limited. Finally, based on regional heterogeneity, a conservation management strategy of "two points, two cores, two corridors, and two regions" is proposed. This strategy aims to provide a framework for future conservation efforts in response to climate change and human activities. [ABSTRACT FROM AUTHOR]

Exploring NDVI variation and what drives it on the Qinghai–Tibet Plateau can strategically inform environmental protection efforts in light of global climate change. For this analysis, we obtained MODIS NDVI data collected during the vegetative growing season, vegetation types for the region, and meteorological data for the same period from 2001 to 2020. We performed Theil–Sen trend analysis, Mann–Kendall significance testing, spatial autocorrelation analysis, and Hurst index calculation to review the spatiotemporal changes in NDVI characteristics on the plateau for various vegetation types. We used the correlation coefficients from these analyses to investigate how the NDVI responds to temperature and precipitation. We found the following: (1) Overall, the Qinghai–Tibet Plateau NDVI increased throughout the multi-year growing season, with a much larger area of improvement (65.68%) than of degradation (8.83%). (2) The four main vegetation types were all characterized by improvement, with meadows (72.13%) comprising the largest portion of the improved area and shrubs (18.17%) comprising the largest portion of the degraded area. (3) The spatial distribution of the NDVI had a strong positive correlation and clustering effect and was stable overall. The local clustering patterns were primarily low–low and high–high clustering. (4) The Hurst index had an average value of 0.46, indicating that the sustainability of vegetation is poor; that is, the trend of vegetation change in the growing season in a large part of the Qinghai–Tibet Plateau in the future is opposite to that in the past. (5) The plateau NDVI correlated positively with air temperature and precipitation. However, the correlations varied geographically: air temperature had a wide influence, whereas precipitation mainly influenced meadows and grassland in the northern arid zone. The overall temperature-driven effect was stronger than that of precipitation. This finding is consistent with the current research conclusion that global warming and humidification promote vegetation growth in high-altitude areas and further emphasizes the uniqueness of the Qinghai–Tibet Plateau as a climate-change-sensitive area. This study also offers a technical foundation for understanding how climate change impacts high-altitude ecosystems, as well as for formulating ecological protection strategies for the plateau. [ABSTRACT FROM AUTHOR]

Glacial lakes are important freshwater resources in southern Tibet. However, glacial lake outburst floods have significantly jeopardized the safety of local residents. To better understand the changes in glacial lakes in response to climate change, it is necessary to conduct a long-term evaluation on the areal dynamics of glacial lakes, assisted with local observations. Here, we propose an innovative method of classification and stacking extraction to accurately delineate glacial lakes in southwestern Tibet from 1990 to 2020. Based on Landsat images and meteorological data, we used geographic detectors to detect correlation factors. Multiple regression models were used to analyze the driving factors of the changes in glacier lake area. We combined bathymetric data of the glacial lakes with the changes in climatic variables and utilized HEC-RAS to determine critical circumstances for glacial lake outbursts. The results show that the area of glacial lakes in Nyalam County increased from 27.95 km2 in 1990 to 52.85 km2 in 2020, and eight more glacial lakes were observed in the study area. The glacial lake area expanded by 89.09%, where we found significant growth from 2015 to 2020. The correlation analysis between the glacial lake area and climate change throughout the period shows that temperature and precipitation dominate the expansion of these lakes from 1990 to 2020. We also discover that the progressive increase in water volume of glacial lakes can be attributed to the constant rise in temperature and freeze–thaw of surrounding glaciers. Finally, the critical conditions for the glacial lake's outburst were predicted by using HEC-RAS combined with the changes in the water volume and climatic factors. It is concluded that GangxiCo endures a maximum water flow of 4.3 × 108 m3, and the glacial lake is in a stable changing stage. This conclusion is consistent with the field investigation and can inform the prediction of glacial lake outbursts in southwestern Tibet in the future. [ABSTRACT FROM AUTHOR]

Permafrost and alpine vegetation are widely distributed in Tibet, which is a sensitive area for global climate change. In this study, we inverted the surface deformation from 22 May 2018 to 9 October 2021 in a rectangular area within the city of Linzhi, Tibet, using the Sentinel1-A data and two time-series interferometric system aperture radar (InSAR) techniques. Then, the significant features of surface deformation were analyzed separately according to different vegetation types. Finally, multiple machine learning methods were used to predict future surface deformation, and the results were compared to obtain the model with the highest prediction accuracy. This study aims to provide a scientific reference and decision basis for global ecological security and sustainable development. The results showed that the surface deformation rate in the study area was basically between ±10 mm/a, and the cumulative surface deformation was basically between ±35 mm. The surface deformation of grassland, meadow, coniferous forest, and alpine vegetation were all significantly correlated with NDVI, and the effect of alpine vegetation, coniferous forest, and grassland on permafrost was stronger than that of the meadow. The prediction accuracy of the Holt–Winters model was higher than that of Holt′s model and the ARIMA model; it was expected that the ground surface would keep rising in the next two months, and the ground surface deformation of alpine vegetation and the coniferous forest was relatively small. The above studies indicated that the surface deformation in the Tibetan permafrost region was relatively stable under the conditions of alpine vegetation and coniferous forest. Future-related ecological construction needs to pay more attention to permafrost areas under grassland and meadow conditions, which are prone to surface deformation and affect the stability of ecosystems. [ABSTRACT FROM AUTHOR]

The alpine grassland ecosystem accounts for 53% of the Qinghai-Tibet Plateau (QTP) area, which is an important ecological protection barrier, but fragile and highly vulnerable to climate change. Therefore, continuous monitoring of the aboveground biomass (AGB) of grassland is necessary. Although many studies have mapped the spatial distribution of AGB over the QTP, the results vary widely due to the limited ground samples and mismatches with satellite pixel scales. This paper proposed a new algorithm using unmanned aerial vehicles (UAVs) as a bridge to re-estimate the grassland AGB over 20 the QTP from 2000 to 2019. The innovations were as follows: 1) In the aspect of ground data collection, the spatial scale matching among the traditional ground quadrat sampling, UAV photos, and MODIS pixels was fully considered. From 2015 to 2019, 906 pairs of ground-UAV sample data at the quadrat scale and 2,602 sets of UAV data matching the MODIS pixel scale were collected. A total of more than 37,000 UAV photos were captured at the height of 20 meters. Therefore, the ground validation samples was sufficient and scale matched. 2) In terms of model construction, the traditional quadrat scale 25 (0.25m2) was successfully upscaled to the MODIS pixel scale (6,2500 m2) based on the random forest method and stepwise upscaling scheme. Compared with previous studies, the scale matching of independent and dependent variables was realized, effectively reducing the impact of scale mismatch. At the pixel scale, the AGB value estimated by UAV had a more linear correlation with the MODIS vegetation indices than the traditional sampling method. The multi-year independent crossvalidation results showed that the constructed pixel scale AGB estimation had good robustness, with an average R2 of 0.83 30 and RMSE of 34.13 g/m2. Our dataset provides an important input parameter for a comprehensive understanding of the QTP in the process of global climate change. [ABSTRACT FROM AUTHOR]

Over the past two decades, due to the combined effects of natural and human factors, the ecological environment and resources of the Qinghai–Tibet Plateau (QTP) have faced serious threats, profoundly impacting its ecosystem and the lives of its residents. Therefore, the establishment of the ecological security pattern (ESP) is crucial to cope with climate change, maintain ecosystem function, and sustainable development. Based on the Pressure–State–Response (PSR) model, this study constructed an evaluation index system for the ecological security (ES) of the QTP, evaluated the ES of the QTP during 2000–2020, and predicted the ES of the QTP during 2025–2035 based on the deep learning model. Combined with the residents' perception of ES, the ES of the QTP was evaluated comprehensively. The results showed that: (1) From 2000 to 2020, the ES value of the QTP continued to rise, the number of dangerous and sensitive counties decreased, and the number of other counties increased. The overall spatial distribution features higher values in the southeast and lower values in the northwest and central regions. (2) From 2000 to 2020, both hot spots and cold spots on the QTP decreased, with the hot spots mainly concentrated in the southeast of the QTP, represented by Yunnan Province, and the cold spots shifting from west to east, mainly concentrated in the central QTP, represented by Qinghai Province. (3) The Long Short-Term Memory (LSTM) model demonstrates high prediction accuracy. Based on the prediction of LSTM, the ES value of the QTP will continue to rise from 2025 to 2035, and the number of safe counties will reach the highest level in history. The spatial distribution is still higher in the southeast and lower in the northwest and central regions. (4) By analyzing residents' perception of 25 potential factors that may affect the ES of the QTP, the results show that residents generally believe that these factors have an important impact on ES, and their evaluation is between "important" and "very important". In addition, there is a significant correlation between these factors and the predicted values of ES. The results of the study will help to improve our understanding of the overall ecological environment of the QTP, provide accurate positioning and reasonable help for the government to formulate relevant protection strategies, and lay a methodological and practical foundation for the sustainable development of the QTP. [ABSTRACT FROM AUTHOR]

Soil water and soil temperature are important ecological factors and driving forces for ecosystem restoration and sustainable development, possessing great significance for climate modeling and prediction. The Hengduan Mountains in southeastern Tibet, China, are located in a climate-change-sensitive area, and the study of soil hydrothermal dynamics in this area is of great significance for local and global climatic change and water resource utilization. This study, based on the soil hydrothermal and meteorological data of the Hengduan Mountain area in Southeast Tibet, analyzes the dynamic change patterns of soil hydrothermal and meteorological factors and explores their influencing relationships. It was found that the dynamic change in soil water content affected by precipitation was "bimodal" type. Among the meteorological factors, soil water content has the strongest correlation with relative humidity. The intra-annual variation curve of soil temperature is similar to that of the atmospheric temperature, showing a "unimodal" type, and has the highest correlation with atmospheric temperature. Specifically, it takes 70 mm and 170 mm of precipitation to change the soil water content and soil temperature at the 150 cm depth. For every 20 °C change in atmospheric temperature, soil temperature above 150 cm changes by an average of 7.2 °C. [ABSTRACT FROM AUTHOR]

Filamentous algae blooms (FABs) have been increasing globally in recent years, and their presence can have both harmful and beneficial effects on aquatic ecosystems. As one of the most common FABs, Cladophora blooms have been reported in the lakes of the Qinghai-Tibet Plateau during the past few years. However, there have been few studies focused on how FABs impact other aquatic organisms, especially in alpine lakes since these are at the forefront of responding to global climate change. In this study, the phytoplankton communities in different regions of Qinghai Lake were profiled in different seasons using meta-barcode sequencing. The phytoplankton assemblages in areas with Cladophora blooms were compared to those without Cladophora. The phytoplankton community structure correlated with physicochemical properties including water temperature, electrical conductivity, nitrate, and the presence or absence of Cladophora blooms. The relative abundance of Bacillariophytes was found to be higher in zones with Cladophora blooms than in other regions. Significant seasonal changes in phytoplankton biomass and β diversity were observed in zones with Cladophora blooms. Growth and microbial degradation of Cladophora can change the pH, dissolved oxygen, secchi depth, and nitrate. Together with seasonal temperature and electrical conductivity changes, Cladophora growth can significantly impact the phytoplankton biomass, community dissimilarity and assembly process. These results showed that Cladophora plays a key role in littoral aquatic ecosystem ecology. [ABSTRACT FROM AUTHOR]

Three-River-Source (TRS) National Park stands as one of China's earliest established national parks, dedicated to significant ecological responsibilities that include conserving soil and water resources in the Tibetan Plateau region. Research on climate change's influence on the TRS region's grasslands is of great significance in our efforts to comprehend and conserve the grassland ecosystem. The most effective random forest (RF) model was chosen to invert the aboveground biomass (AGB) of grassland in the previous 6 years (2015-2020) and predict the grassland AGB in the following 20 years (2021-2040) by comparing linear regression and multivariate nonlinear regression models such as RF, support vector machine, decision tree, and artificial neural network. A Theil-Sen median trend analysis and a Mann-Kendal test were then used to examine the trends of grassland AGB. The results showed that (1) RF outperformed other models in estimating grassland AGB, with a test set decision coefficient of multiple determination (R²) of 0.722, a root mean square error of 42.596 g/m², and a mean absolute error of 35.619 g/m²; (2) over 6 years, the grassland AGB in TRS National Park had a spatial trend of a steady rise from the northwest to the southeast. The average annual grassland AGB was 247.333 g/m², with averages of 44.836 g/m² , 92.601 g/m² , and 120.217 g/m² in the Yangtze River, Yellow River, and Lancang River source parks respectively. The trend of the grassland AGB was primarily stabilized and slightly recovered, with a small portion of the slightly deteriorated areas; (3) climate change significantly affected grassland AGB, and when temperature and precipitation conditions were adequate, grassland AGB values increased with temperature and precipitation. In the scenarios of ssp119, ssp245, and ssp585, grassland AGB is projected to exhibit a dynamic upward trend over the next 20 years. Global warming is expected to boost grassland AGB. Comprehensive measures are essential to maintain grassland health and ensure a positive impact on global carbon and ecological balance. The study's findings hold great importance for the ecological security of the TRS region and contribute to our global understanding of sustainable grassland development. [ABSTRACT FROM AUTHOR]

Partitioning the contributions of climate, economic growth, and policy to a region's carbon flows is an important process for the Chinese government seeking to optimize their regional development policies to achieve carbon neutrality by 2060. A combination of the carbon emission analysis and human appropriation of net primary production (HANPP) framework was applied to a village in the Lhasa river valley, Tibet, to quantify the contributions of these different factors to carbon flows and neutrality. From 2010 to 2019, the average annual net sequestration of CO2 was 374.9 g CO2 m−2 a−1. Changes in climate conditions and the regional policy of Grassland Ecological Protection Subsidy and Reward increased carbon sequestrations by 409.5 and 25.7 g CO2 m−2 a−1, respectively. Socioeconomic development, policies for reducing poverty, and promotion of forage production led to the increase in CO2 emissions by 103.5, 88.8, and 4.3 g CO2 m−2 a−1, respectively. The cumulative CO2 emissions (including HANPP) caused by land use were 298.92 Tg CO2 (2479.63 g CO2 m−2; 1 Tg = 1012 g), while the cumulative CO2 emissions due to energy use were only 11.22 Tg CO2 (93.07 g CO2 m−2), equal to 3.75% of the CO2 emissions driven by land use. Livestock grazing and cropland cultivation were the two main land use factors affecting the carbon balance. We argue that unhooking economic growth from traditional nomadic animal husbandry and lifestyles through policy optimizations would highly contribute the carbon neutrality in Tibet. [ABSTRACT FROM AUTHOR]

Aim: Research on population genetic patterns and potential distribution dynamics can provide insights into the development of pest management strategies. Herein, we integrated population genetic analyses with the climatic niche approach to investigate spatial population genetic variations and potential geographical distribution (PGD) of the herbivorous pest Phytomyza horticola. We also analysed its population response patterns to both late Pleistocene climatic events and future climate change. Location: China. Methods: We analysed the patterns of genetic diversity distribution in 29 populations from 19 regions across China using three mitochondrial (COI, COII and Cytb) genes as markers. We estimated demographic histories using neutrality tests, mismatch distributions and Bayesian skyline plots. Changes in PGD were assessed using an ecological niche model. Results: High genetic diversity was found in most populations, and the northern population exhibited higher haplotype diversity. The population genetic structure included the Tibet lineage and a large lineage comprising the remaining populations. Demographic analyses indicated that rapid population expansion occurred during the cold Last Glacial Maximum. In addition, our projections suggested that P. horticola currently has a vast PGD in China, for which the human influence index was the strongest variable. Large areas of cold northern regions were highly suitable for its survival. Under future global warming, highly suitable habitats will shift towards the higher latitudes. Main conclusions: P. horticola is widely distributed across varied environments, which may be attributed to its high degree of genetic variation. Human activities likely facilitated the current PGD and the frequent gene flow that homogenized differentiation among most populations. In addition, P. horticola exhibits strong adaptability to cold climates and environments from the past to the future. Considering future climatic changes, prevention and control should focus on high‐latitude regions, and vigilance regarding human‐mediated pest dispersals and outbreaks should be maintained. [ABSTRACT FROM AUTHOR]

Soil microorganisms and soil organic carbon (SOC) play important roles in ecosystem cycling, but there is a lack of clarity about the effects of nitrogen addition on soil microorganisms and SOC, as well as the key microbial taxa that influence SOC. This study was conducted in the alpine wetland of Xiaopo Lake in the Qinghai Lake basin, using NH4NO3 as the nitrogen source, three nitrogen addition gradients (N2: 2 g/m2, N5: 5 g/m2, N10: 10 g/m2), and a blank control treatment (N0: 0 g/m2), with three replicate experiments for each treatment. The main findings were as follows: (1) Both increased soil temperature and decreased precipitation reduced SOC content. SOC content gradually decreased with increasing nitrogen concentration; SOC was reduced by 3.36–29.54% and 8.57–26.66% at 0–15 cm and 15–30 cm soil depths, respectively. (2) Proteobacteria, Chloroflexi, Acidobacteria, and Actinobacteria were the main dominant species, and their changes determined the changes in the entire bacterial community. The relative abundance of Proteobacteria and Actinobacteria decreased under nitrogen addition; Acidobacteria increased significantly; and Chloroflexi did not change significantly. The overall abundance and diversity of soil bacteria showed an increasing trend. The number of soil bacteria is a key factor affecting SOC content, and an increase in the number and diversity of soil bacteria enhances their decomposition capacity, and thus, reduces SOC content. (3) Increased soil temperatures and decreased precipitation are associated with decreased SOC and are the main climatic factors affecting SOC. This study provides a reference for the rational utilization and management of wetland ecosystems under climate change. [ABSTRACT FROM AUTHOR]

Evaluation of changes in dry-wet climate is crucial in the context of global climate change to ensure regional water resources, ecosystem stability, and socio-economic development. Long-term daily meteorological data, including temperature, precipitation, relative humidity, wind speed, sunshine duration, and air pressure data from 1680 stations across mainland China from 1971 to 2019, were collected to investigate the temporal and spatial variations in aridity index (AI), precipitation (P), reference evapotranspiration (ET0), and the underlying driving climatic factors. Results indicated that the Northwest, Northeast, and Huang-Huai regions were undergoing significant wetting processes, while the Southwest and Southeast China were undergoing significant drying processes. The changing AI was mainly decided by the changing trends of ET0. For most regions, ET0 has undergone significant increases. The average increasing rate over mainland China was 3.76 mm/10a. Stations with decreasing trends were mainly located in the Tibet Plateau, Huang-Huai, and northern Northeast China. Trends in ET0 were negatively affected by the increasing changes in relative humidity and positively affected by the decreasing changes in wind speed and sunshine duration and the increasing changes in air temperature. Wind speed and relative humidity were found to be the main dominant factors driving the changes in ET0, and their contribution varied with regions. Huang-Huai and northern Northeast China showed a significant downward trend in ET0, mainly driven by the decrease in wind speed, while the increase in relative humidity was the primary contributor to the significant upward trends in ET0 across all other regions in China. [ABSTRACT FROM AUTHOR]

Geothermal systems in Tibet, a crucial geothermal region in China, belong to the Mediterranean-Himalayan geothermal belt and are characterized by a broad distribution of cesium (Cs) bearing geyserite deposits. Targejia, one of the largest Cs-bearing geyserites in southern-western Tibet, contains 1.446 × 104 tons of Cs. The highest ore grade reaches 2.89 wt%, and the ore-forming process can be subdivided into mineralization stages I to V. Cs is heterogeneously distributed in geyserites. Herein, two Cs-bearing ores are investigated, with distinct characteristics of (1) low-Cs-bearing ore (amorphous silica opal-A and opal-CT type) with low Cs (average of ~0.2 wt%), Na, K, Al, and Ca contents, and (2) high-Cs-bearing ore (clay type) with high-Cs (average of ~1.40 wt%), -Na, -K, -Al, and -Ca contents. It is reported for the first time that Cs primarily exists in clay rather than in amorphous silica opal. The Cs-enrichment mechanisms are diferent for the above two Cs-bearing geyserite types: (1) The deprotonated –OH, surrounded by water molecules, controls the amount of Cs absorbed on the geyserite surface (Si–OH) in the low-Cs-bearing ore. (2) The variable Cs content depends on the Al content because Al substitutes Si, yielding more negative charges to absorb Cs in the high-Cs-bearing ore. Geothermal fluid loading-mass elements, such as Cs and SiO2, precipitate as amorphous silica (opal) with clay minerals. Mineral saturation index modeling was used to predict the most applicable physical parameters for ore formation. The results confirm that the ore forms at ~85 °C and a pH of ~8.5 in the Na-Cl system at stage V. The degree of Cs enrichment reduces from the latest stage V (0–4 ka) to the early stage IV (4–17 ka), and is controlled by clay dissolution, which might further relate to the climate change in Tibet's Holocene. Fluid-rock interaction modeling shows that dissolution–reprecipitation induces a higher order of amorphous silica formation and clay dissolution at >40 °C and pH of 5–9 at stages V and III, excluding Cs from the ore. [ABSTRACT FROM AUTHOR]

Whether or not large-scale vegetation restoration will lead to a decrease in regional terrestrial water storage is a controversial topic. This study employed the Geodetector model, in conjunction with observed and satellite hydro-meteorological data, to detect the changes in terrestrial water storage anomaly (TWSA) and to identify the contributions of climate change and vegetation greening across China during the years 1982–2019. The results revealed that: (1) during the period of 1982–2019, TWSA showed a downward trend in about two thirds of the country, with significant declines in North China, southeast Tibet, and northwest Xinjiang, and an upward trend in the remaining third of the country, with significant increases mainly in the Qaidam Basin, the Yangtze River, and the Songhua River; (2) the positive correlation between normalized vegetation index (NDVI) and TWSA accounts for 48.64% of the total vegetation area across China. In addition, the response of vegetation greenness lags behind the TWSA and precipitation, and the lag time was shorter in arid and semi-arid regions dominated by grasslands, and longer in relatively humid regions dominated by forests and savannas; (3) furthermore, TWSAs decreased with the increase in NDVI and evapotranspiration (ET) in arid and semi-arid areas, and increased with the rise in NDVI and ET in the humid regions. The Geodetector model was used to detect the effects of climate, vegetation, and human factors on TWSA. It is worth mentioning that NDVI, precipitation, and ET were some of the main factors affecting TWSA. Therefore, it is essential to implement rational ecological engineering to mitigate climate change's negative effects and maintain water resources' sustainability in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Climate change is a major driver of cyclical and seasonal changes in alpine phenology. This study investigated how climate change affects vegetation phenology's spatial and temporal responses on the Qinghai–Tibet plateau (QTP) from 1981 to 2020. We used the daily two-band enhanced vegetation index (EVI2) at a 0.05° spatial resolution for 1981–2014, 16-day moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index data for 2000–2020 at 250 m spatial resolution, and climate records from 106 meteorological stations from 1981 to 2020 to construct linear regression models and Mann–Kendall point test to understand the changes on QTP vegetation in response to climate change. We found that the temperature in April, July, and September controls vegetation growth, and spring precipitation (p < 0.05) influences the length of the growing period, with a partial correlation coefficient of −0.69. Over the past 40 years, temperature and precipitation changes on the QTP have not shown abrupt shifts despite the increasingly warm and dry spring climate. We observed a meridional distribution trend in the correlation between precipitation and alpine vegetation greening, browning and the length of the growing period. In regions experiencing strong warming, vegetation growth was hindered by a lack of precipitation. We conclude that climatic factors alone cannot fully explain the changing trends in vegetation phenology across the QTP. [ABSTRACT FROM AUTHOR]

Because of its distinct geological history, frigid temperature, and rich biodiversity, the Tibetan Plateau gives an excellent opportunity to assess the effect of climate change on determining species richness. The distribution patterns of fern species richness and their underlying processes have long been a matter of debate in ecology research, with various hypotheses suggested over the years. Here, we explore richness patterns of fern species in Xizang on the southern and western Tibetan Plateau along an elevational gradient (100-5300 m a.s.l.) and evaluate climatic factors causing the spatial decrease and increase of fern species richness. We used regression and correlation analyses to relate the species richness with elevation and climatic variables. Throughout our research, we identified 441 fern species from 97 genera and 30 families. The Dryopteridaceae family (S = 97) has the highest number of species. All energy-temperature and moisture variables except drought index (DI) had a significant correlation with elevation. The altitude has a unimodal relationship with fern species, and the species richness is the largest at an altitude of 2500 m. The horizontal richness pattern of fern species on the Tibetan Plateau also showed that areas of extremely high species richness are mainly distributed in Zayü and Medog County, with an average elevation of 2800 m and 2500 m, respectively. The richness of fern species has a log-linear relationship with moisture-related factors such as moisture index (MI), mean annual precipitation (MAP), and drought index (DI). Because the peak corresponds spatially with the MI index, the unimodal patterns confirm the significance of moisture on fern distributions. Our results showed that mid-altitudes have the highest species richness (high MI), but high elevations have lower richness due to high solar radiation, and low elevations have lower richness due to high temperatures and low precipitation. Twenty-two of the total species are classified as nearly threatened, vulnerable or critically endangered, and varied in elevation from 800 m to 4200 m. Such relationships between the distribution and richness of fern species and climates on the Tibetan Plateau can provide data support for future predictions of the impacts of climate change scenarios on fern species, the ecological protection of representative fern species, and references for the planning and construction of nature reserves in the future. [ABSTRACT FROM AUTHOR]

Accurate understanding of the impacts of climate change on hulless barley and river in the Lhasa River Basin is of great significance to food security and water resources management in the plateau region. It is important to explore the relationship between hulless barley and river under the background of climate change for the comprehensive and coordinated development of agriculture and water conservancy. Based on the Google Earth Engine (GEE) cloud computing platform, the Random Forest algorithm was used to obtain the spatio‐temporal variation of hulless barley and river in the Lhasa River Basin from 2010 to 2020. The overall accuracy and Kappa coefficient of classification results were 89.54% and 85.96%, respectively. The average area and Normalized Difference Vegetation Index (NDVI) of hulless barley from 2010 to 2020 were 178.46 km2 and 0.69, respectively. The increase of accumulated precipitation, number of precipitation days, average dew point temperature (ADPT) and average wind speed (AWS) promoted the growth of hulless barley, with NDVI significant increasing rate of 0.0173 (R2 = 0.764, p < 0.001). The combined effects of human activities (construction of water conservancy facilities and mining activities), ADPT and AWS resulted in a significant decrease (decreasing rate: 10.8682 km2/year, p < 0.01) in river area during 2010–2020. There was a significant negative correlation (R2 = 0.722, p < 0.01) between hulless barley NDVI and river area driven by climate factors. The changes in hulless barley gravity center and river gravity center were consistent, and both shifted in the northeast direction. These results provide a scientific understanding of the impacts of plateau climate change on agriculture and water resource. The land cover maps of the Lhasa River Basin with long time series and high spatial resolution were drawn. Our study verified the relevance between hulless barley gravity center and river gravity center as well as the internal relationship between hulless barley growth and river area. Furthermore, we explored the interrelation relationships among hulless barley, the Lhasa River area and climate factors. [ABSTRACT FROM AUTHOR]

The dominant influencing factors of changes in vegetation NPP and the relative roles of climate–human factors on the Qinghai–Tibet Plateau (QTP) differ between historical periods and are unclear. Therefore, there is an urgent need to systematically and quantitatively analyze the evolution process of the QTP's ecosystem pattern and the driving factors of this process. Based on MOD17A3H and meteorological data, the Miami model, correlation analysis, and the residual coefficient method were used to investigate the spatiotemporal patterns of changes in vegetation NPP on the QTP from 2000 to 2020. We then quantitatively distinguished the relative roles of climate change and human activity in the process of vegetation NPP change during different historical periods. The results show the following: (1) From 2000 to 2020, zones with increasing vegetation NPP (10–30%) were the most widely distributed, and were mainly located in the Three-Rivers Headwater Region and the northern part of the Hengduan Mountains. (2) From 2000 to 2020, zones with a significant positive correlation between vegetation NPP and annual precipitation were mostly distributed in the northeastern QTP and the Three-Rivers Headwater Region, while zones with a positive correlation between vegetation NPP and annual average temperature were mostly located in southern Tibet. Zones with a significant positive correlation between NPP and annual sunshine hours were mainly distributed in the southeastern part of the QTP and the southern part of the Tanggula Mountains. In contrast, zones with a significant positive correlation between NPP and accumulated temperature (>10 °C) were mainly concentrated in the northern and eastern parts of the QTP. (3) During different historical periods, the relative roles of climate–human factors in the process of vegetation NPP change on the QTP had obvious spatiotemporal differences. These results could provide scientific support for the protection and restoration of regional ecosystems on the QTP. [ABSTRACT FROM AUTHOR]

The sequestration of carbon in forests plays a crucial role in mitigating global climate change and achieving carbon neutrality goals. Carbon use efficiency (CUE) is an essential metric used to evaluate the carbon sequestration capacity and efficiency of Vegetation. Previous studies have emphasized the importance of assessing CUE at specific regions and times to better understand its spatiotemporal variations. The southeastern region of Tibet in the Qinghai-Tibet Plateau is recognized as one of the most biodiverse areas in China and globally, characterized by diverse vegetation types ranging from subtropical to temperate. In this study, we focused on Nyingchi, which is the largest virgin forest area in southeast Tibet, to explore the spatial-temporal dynamic characteristics of regional CUE based on MODIS remote sensing products. The following results were obtained: (1) On a monthly scale, regional CUE exhibits significant seasonal variations, with varying patterns among different vegetation types. Specifically, the fluctuation of CUE is the lowest in high-altitude forest areas and the greatest in grasslands and barrens. On an annual scale, forests exhibit higher fluctuations than areas with sparse vegetation and the overall volatility of CUE increased over the past 11 years. (2) There are regional differences in the trend of CUE changes, with a substantial downward trend in the Himalayan region and a significant upward trend in the residual branches of the Gangdise Mountains. More than 75% of the regions exhibit no persistent trend in CUE changes. (3) Vegetation type is the main determinant of the range and characteristics of vegetation CUE changes, while the geographical location and climatic conditions affect the variation pattern. CUE in the southern and northern regions of Nyingchi at 28.5°N exhibits different responses to temperature and precipitation changes, with temperature having a more significant impact on CUE. [ABSTRACT FROM AUTHOR]

Simple Summary: To form a better understanding and benefit future conservation of the apollo and swallowtail butterflies in the Hengduan Mountains in China, the present research projected the 59 Papilionidae species' spatial richness using the Maxent model and predicted the response to climate change. The spatial pattern of apollos concentrated in the subalpine to alpine areas in western Sichuan, northwestern Yunnan, and eastern Tibet, while that of swallowtails is more confined to the tropical and subtropical valleys of western Yunnan and western Sichuan. Both subfamilies would exhibit northward and upward range shifts with climate change but many apollos would experience drastic habitat contraction, resulting in lower species richness, while most swallowtails would experience habitat expansion, and the species richness would increase. Species with habitat contraction, narrow-ranged distribution and endemicity require more conservation measures in the future. The family of Papilionidae (Lepidoptera: Papilionoidea) is a group of butterflies with high ecological and conservation value. The Hengduan Mountains (HMDs) in Southwest China is an important diversity centre for these butterflies. However, the spatial distribution pattern and the climate vulnerability of Papilionidae butterflies in the HDMs remain unknown to date. The lack of such knowledge has already become an obstacle in formulating effective butterfly conservation strategies. The present research compiled a 59-species dataset with 1938 occurrence points. The Maxent model was applied to analyse the spatial pattern of species richness in subfamilies Parnassiinae and Papilioninae, as well as to predict the response under the influence of climate change. The spatial pattern of both subfamilies in the HDMs has obvious elevation prevalence, with Parnassiinae concentrated in the subalpine to alpine areas (2500–5500 m) in western Sichuan, northwestern Yunnan and eastern Tibet, while Papilioninae is concentrated in the low- to medium-elevation areas (1500–3500 m) in the river valleys of western Yunnan and western Sichuan. Under the influence of climate change, both subfamilies would exhibit northward and upward range shifts. The majority of Parnassiinae species would experience drastic habitat contraction, resulting in lower species richness across the HDMs. In contrast, most Papilioninae species would experience habitat expansion, and the species richness would also increase significantly. The findings of this research should provide new insights and a clue for butterfly diversity and climatic vulnerability in southwestern China. Future conservation efforts should be focused on species with habitat contraction, narrow-ranged distribution and endemicity with both in situ and ex situ measures, especially in protected areas. Commercialised collecting targeting these species must also be regulated by future legislation. [ABSTRACT FROM AUTHOR]

Glaciers are an important part of the cryosphere and important reservoirs of fresh water on Earth. Glaciers in the Gongga Mountains, located in the southeastern Tibetan Plateau, have been experiencing dramatic changes and substantially shrinking over the past two decades. We analyzed the glacier change over the Gongga Mountains using the Landsat data from 1994 to 2021 (interval of 4 or 5 years), with Gaofen-1 (GF-1) data to evaluate the uncertainty. The glacier shrinkage under different terrain conditions, including altitudes, slope, and slope direction, was further explored. Finally, we evaluated the response of glacier shrinkage to climate change using precipitation and temperature data for nearly 30 years. Results show that the glaciers in the Gongga Mountains are experiencing an accelerating ablation, with a glacier area of ~240 km2 in 1994 and ~212 km2 in 2021 (an average annual shrinkage rate of 1.04 km2/a). The shrinkage mainly occurs in areas with altitudes of 5000–5300 m and a slope of 30–40°. Moreover, the shrinkage is strongly related to the recent warming of the climate, with the warming rate being 0.19 °C/10a, while precipitation remains almost constant during 1978–2019. The results provide a scientific basis for water resources management, ecological environmental protection, and natural disaster protection in southeast Tibet for decision making. [ABSTRACT FROM AUTHOR]

A change in precipitation can profoundly change the structure of soil microbial communities, especially in arid and semi-arid areas which are limited by moisture conditions. Therefore, it is crucial to explore how soil bacterial community composition and diversity will respond to variation in precipitation. Here we conducted a precipitation control experiment to simulate precipitation change by reducing and increasing rainfall by 25%, 50%, and 75% in the alpine grasslands of northern Tibet. The composition, diversity, and species interaction network of soil microbial community were studied by high-throughput sequencing, and the relationship between microbial community species and soil environmental factors was analyzed. Our results showed that Proteobacteria (45%-52%) and Actinobacteria (37%-45%) were the dominant bacteria in the soil. The alpha diversity index based on Shannon, Chao1, and Simpson indices revealed that precipitation change had no significant effect on richness and evenness of soil microbial communities. Non-metric multidimensional scaling (NMDS) and analysis of similarities (ANOSIM) showed that a clear separation of soil microbial communities between D2(-50%),D3(-75%) and W2(+50%), W3(+75%) treatments. The microbial interaction network indicated that the water-increasing treatment group had closer connections, and Proteobacteria and Actinomycetes were the core species. Furthermore, there was a stronger positive correlation between species in the water-reducing treatment group, the contribution of Proteobacteria decreased significantly, the role of connecting hub decreased, and Actinomycetes became the most important core microbial species. In addition, soil water content (SWC) and available phosphorus (AP) were closely related to the variations in soil microbial compositions. The findings of this study provide a theoretical basis for the driving mechanism of global climate change on soil microbial community and grassland ecosystem in alpine grassland. [ABSTRACT FROM AUTHOR]

Land evaporation (LET) is an important variable in climate change, water cycle and water resources management. Mastering the projected changes in LET is significant for crop water requirements and the energy cycle. The global climate model (GCM) is a vital tool for future climate change research. However, the GCMs have low spatial resolution and relatively high errors. We use a deep learning (DL)-based model to deal with this problem. The DL approach can downscale the model data and merge simultaneously. We applied the DL approach to a suit of models from the Coupled Model Intercomparison Project 6th edition (CMIP6) LET data. From the result of all the evaluation metrics, the DL merged data greatly improved in both spatial and time dimensions. The mean RMSE is 5.85 mm and the correlation is 0.95 between the DL merged data and reference data (historical reliable evaporation data). The future LET evidently increases in four scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5), and the upward intensity rises from the low to high emission scenarios. The highest increasing regions are in the Tibet Plateau and the south of China and the trend is larger than 10 mm/decade in the high scenarios. From the seasonal point of view, the increasing trend in spring and summer is far larger than for autumn and winter. The Tibet Plateau and the northeast of China have the largest upward trend in the spring of SSP5–8.5, higher than 1.6 mm/decade. [ABSTRACT FROM AUTHOR]

The quantum technology absolute gravimeters, gradiometers, and clocks are at the forefront of the instrumentation to be exploited in a future gravity mission (the QSG mission concept). Apart from the quantum payload, the mission design defines the choice of the number of satellites and the satellite orbit constellation, with the goal of optimizing the observation of the earth's gravity field and reducing aliasing phenomena. Our goal is to define the realistic gravity field changes generated by glaciers and lakes and define the sensitivity of the quantum gravity mission for the detection of hydrologic and cryospheric mass changes. The analysis focuses on mass changes in the high mountains of Asia and the South American continent. The mass changes are based on terrestrial and satellite observations and are of a climatic origin. We show that compared to the existing GRACE-FO mission, a quantum gravity mission significantly improves the detection of the climatic mass gain of lakes and mass loss of glaciers, allowing for smaller mass features to be distinguished, and smaller mass losses to be detected. The greater signal is the seasonal signal with a yearly period, which would be detected at the 10 Gt level for areas > 8000 km2. The yearly mass loss of the Patagonian glaciers can be detected at the 5 Gt/yr level, an improvement from the 10 Gt/yr detectable by GRACE-FO. Spatial resolution would also be improved, with an increase of about 50% in spatial frequency for the detection of the mass change rate of lakes and glaciers in Tibet. The improved spatial resolution enables an improved localization of the lakes and glaciers affected by climatic mass change. The results will contribute to defining the user requirements of the future QSG missions. [ABSTRACT FROM AUTHOR]

The uplift of the Tibetan Plateau (TP) during the late Cenozoic is thought to be one of the crucial factors controlling the Asian climate. However, the complex interaction between tectonics and climate change remains unclear. The carbon and oxygen isotopes and elementary geochemistry of rocks from the early Eocene Lulehe Formation to the Miocene Youshashan Formation in the northern margin of Qaidam Basin, shows important variations in the Rb/Sr, MgO/CaO, Sr/Cu, and V/Cr ratios, together with CMI and CIA, which are interpreted as reflecting relevant regional climate and environmental changes. Combining the above mentioned parameters, we reconstructed the evolution of the sedimentary environment in the Qaidam Basin. The climate is roughly divided into four stages: (1) warm and humid; (2) cold and dry; (3) alternations of cold and dry with warm and humid; and (4) cold and arid. At the same time, there are also minor short-term changes of dry, wet, cold, and warm in each stage. The early Eocene to Miocene climate changes in the Qaidam Basin were mainly affected by global climate changes, the uplift of the Qinghai Tibet Plateau, and the long-lasting plate collision, but there was no continuous drought due to the uplift of the Qinghai Tibet Plateau. From the early Eocene to the late Miocene, the climate of the Qaidam Basin became warm and humid. [ABSTRACT FROM AUTHOR]

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The Tibet Autonomous Region of China constitutes a unique and fragile ecosystem that is increasingly influenced by development and global climate change. To protect biodiversity and ecosystem services in Tibet, the Chinese government established a system of nature reserves at a significant cost; however, the effectiveness of nature reserves at protecting both—biodiversity and ecosystem service functions in Tibet is not clear. To determine the success of existing nature reserves, we determined importance areas for the conservation of mammal, plant, bird, amphibian, and reptile species, and for the protection of ecosystem service functions. The results indicated that important conservation areas for endangered plants were mainly distributed in the southern part of Nyingchi City, and for endangered animals, in the southern part of Nyingchi and Shannan Cities. Extremely important conservation areas for ecosystem service functions of carbon sequestration, water and soil protection, and flood regulation were mainly distributed in the southern part of Nyingchi and Shannan Cities, northern and southeastern parts of Nagqu City, and southern part of Ngari area. Based on an analysis of spatial overlap in protection areas, we conclude that existing natural reserves need to be expanded, and new ones need to be established to better protect biodiversity in Tibet Autonomous Region. [ABSTRACT FROM AUTHOR]

Grassland is the vegetation type with the widest coverage on the Qinghai-Tibet Plateau. Under the influence of multiple factors, such as global climate change and human activities, grassland is undergoing temporal and spatially different disturbances and changes, and they have a significant impact on the grassland ecosystem of the Qinghai-Tibet Plateau. Therefore, timely and dynamic monitoring of grassland disturbances and distinguishing the reasons for the changes are essential for ecological understanding and management. The purpose of this research is to propose a knowledge-based strategy to realize grassland dynamic distribution mapping and analysis of grassland disturbance changes in the region that are suitable for the Qinghai-Tibet Plateau. The purpose of this study is to propose an analysis algorithm that uses first annual mapping and then establishes temporal disturbance rules, which is applicable to the integrated exploration of disturbance changes in highland-type grasslands. The characteristic indexes of greenness and disturbance indices in the growing period were constructed and integrated with deep neural network learning to dynamically map the grassland for many years. The overall accuracy of grassland mapping was 94.11% and that of Kappa was 0.845. The results show that the area of grassland increased by 11.18% from 2001 to 2017. Then, the grassland disturbance change analysis method is proposed in monitoring the grassland distribution range, and it is found that the area of grassland with significant disturbance change accounts for 10.86% of the total area of the Qinghai-Tibet Plateau, and the disturbance changes are specifically divided into seven types. Among them, the type of degradation after disturbance mainly occurs in Tibet, whereas the main types of vegetation greenness increase in Qinghai and Gansu. At the same time, the study finds that climate change, altitude, and human grazing activities are the main factors affecting grassland disturbance changes in the Qinghai-Tibet Plateau, and there are spatial differences. [ABSTRACT FROM AUTHOR]

The vegetation of the Qinghai-Tibet Plateau (QTP), China, is diverse and sensitive to climate change. Because of extensive grassland degradation in the QTP, several ecological restoration projects, which affect the livestock population, have been implemented in the QTP. Although many studies have reported the impacts of climate change on vegetation in the QTP, our knowledge on the impacts of both climate change and livestock on vegetation remains very limited. Here, we investigated the impacts of climate change and livestock population on vegetation growth by using the annual maximum normalized difference vegetation index (NDVImax) and growing-season climate data from 1981 to 2019. We analyzed the relationship between NDVImax and climate and livestock population using the modified Mann-Kendall trend Test and Pearson correlation analysis. For the entire QTP, NDVImax had a two-phase trend, with a slow rise during 1981–2000 and a rapid rise during 2000–2019. Overall, NDVImax in the QTP increased and decreased in 63.7% and 6.7% of the area in 2000–2019. In areas with significant changes in NDVImax, it was strongly correlated with relative humidity and vapor pressure. The small positive trend in NDVImax during 1981–2000 was influenced by warmer and wetter climate, and the overgrazing by a large population of livestock slowed down the rate of increase in NDVImax. Livestock population for Qinghai and Tibet in recent years has been lower than in the 1980s.The warmer and wetter climate and substantial drops in the livestock population contributed to large recovery in vegetation during 2001–2019. Vegetation degradation in Qinghai during 1981–2000 and central-northern Tibet during 2000–2019 was driven mainly by drier and hotter climatic. Although 63.7% of the area in the QTP became greener, the vegetation degradation in central-northern Tibet should not be ignored and more measures should be taken to alleviate the impact of warming and drying climate. Our findings provide a better understanding of the factors that drove changes in vegetation in the QTP. [ABSTRACT FROM AUTHOR]

Alpine treelines are projected to shift upslope in response to climate warming, but empirical studies have yielded inconsistent results, with both upshifted and stable alpine treelines. Additionally, treelines on different slope aspects of the same mountain can differ. Thus, for a better understanding of the mechanisms of treeline formation and treeline responses to climate change, we need to elucidate the population dynamics at treelines on different slope aspects. Here, we quantified the population dynamics of Balfour spruce (Picea likiangensis var. rubescens) at treeline ecotones on contrasting north- and east-facing slopes on the eastern Tibetan Plateau based on field surveys. The alpine treeline positions of Balfour spruce have not advanced toward higher altitudes on the contrasting slopes in recent decades. Compared with the east-facing slope, more recruits occurred on the north-facing slope above the present treeline, indicating a more favorable regeneration condition. However, on the north-facing slope, the individual growth rate of Balfour spruce was lower, and the number of adult trees above the present treeline was higher than that on the east-facing slope. Thus, slope aspects mediate a trade-off between the growth and survival of treeline species, explaining the absence of an impact of slope aspects on treeline responses to climate change. Our results highlight the importance of considering the effect of topography on population dynamics in predicting alpine treeline dynamics under the scenario of climate change. [ABSTRACT FROM AUTHOR]