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This paper aims to update our understanding of the carbon cycle in the Himalayas, the most intense collisional orogeny globally, by providing new insight into its impact on Cenozoic climate cooling through the use of isotopic variations in both organic and inorganic carbon and an isotopic mass balance model. Our results from 20 selected hot springs show that the relative contributions of dissolved carbon from the mantle, metamorphic decarbonization, aqueous dissolution, and soil organic matter are approximately 2%, 82%, 6%, and 10%, respectively. Approximately 87% ± 5% of CO2 generated in the deep crust precipitates as calcite, while approximately 5.5% ± 1% of this carbon is converted to biomass through microbial chemosynthesis at depths less than 2 km. Our random forests approach yielded a metamorphic carbon flux from the entire Himalayan orogenic belt of approximately 2.7 ∼ 4.5 × 1012 mol/yr. The minor CO2 released into the atmosphere (2.5 ∼ 4.2 × 1011 mol/yr) is comparable to the carbon consumption driven by Himalayan weathering. This paper provides new insights into deep carbon cycling, notably that approximately 93% of deeply sourced carbon is trapped in the shallow crust, rendering orogenic processes carbon neutral and possibly acting as one of the major triggers of long‐term climate cooling in the Cenozoic. Plain Language Summary: Large‐scale deep metamorphic decarbonization and CO2 release into the atmosphere during continental collision orogenesis worldwide have had significant impacts on Cenozoic global climate change. However, the carbon sources and sinks and the mechanisms underlying their impacts on climate change are not fully understood. This paper reports the chemistry of aqueous solutions, carbon isotopic compositions of dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC), and helium and carbon isotopic compositions of free gases from hot springs in southern Tibet. The carbon isotope fractionation model between gas and aqueous solutions revealed that the carbon released from depth underwent six different stages. Based on the random forests machine learning algorithm, we estimated the metamorphic carbon flux across the Himalayan orogenic belt. Furthermore, only a small fraction (7%) of deep carbon is eventually released into the atmosphere, and this volume is the same magnitude as the amount of carbon absorbed by silicate weathering on the Tibetan Plateau. This paper emphasizes that the carbon sequestration process in the upper crust may have resulted in nearly carbon‐neutral geological bodies in the Himalayan orogenic belt, thus playing a critical role in Cenozoic climate cooling. Key Points: Approximately 87% of deeply sourced carbon precipitates as calcite, while approximately 5.5% is sequestered as biomass in the shallow crustThe carbon flux across the Himalayan orogenic belt was estimated by the random forests approachCrustal thickening has attenuated long‐term deep carbon emissions from the Himalayas [ABSTRACT FROM AUTHOR]

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 Tibetan Plateau is a driver and amplifier of global climate change. The increased frequency and scale of landslides in this area are one of the manifestations of extreme climate change. Studying the trigger of landslides is of great value to the research, protection, and management of engineering geology and climatic environmental changes. However, to our knowledge, there is no efficient, convenient and intelligent method to recognize the trigger of landslides in the Tibetan Plateau. Therefore, a new high-efficiency and high-precision deep learning algorithm has been proposed in this study to analyze the landslides triggers. Specifically, this paper proposes a novel lightweight neural network landslide classification method (MNTL) based on MobileNet-V2 and transfer learning. Mobilenet-V2 requires few parameters and few floating-point operations per second. Furthermore, it is integrated with transfer learning to improve the representation learning ability of the model. The proposed method was applied to classify landslides induced by rainfall and thawing effect. The method required only 30 samples of each class, and it converged quickly in just 3 min and achieved a 94% forecast accuracy. Compared with six state-of-the-art deep learning classification methods—specifically, VGG-16, VGG-19, ResNet-50, ResNet-101, Inception, and MobileNet-V2, the proposed method exhibited competitive advantages in terms of convergence speed and generalization capability. MNTL can be embedded into the mobile terminal, which is conducive to the rapid application of landslide-related research results at a small cost. More importantly, the work in this paper could serve as a potential basis for advancing research on the correlation between landslide hazards and climate change in southeast Tibet. [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]

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]

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]

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]

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]

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]

Mountain glaciers are one of the most sensitive indicators of climate change. Reconstructing past glacier extents provides valuable insights into the climate change for specific regions where instrumental records are not enough and even absent. In the paper we mapped the outlines for 691 Little Ice Age (LIA) glaciers in terms of prominent moraines beyond contemporary glaciers in the Tanggula Mountains, central Tibetan Plateau (TP). Based on these glacier outlines, we reconstructed the ice thicknesses and surfaces for the LIA glaciers in the region. Accordingly, we calculated the equilibrium-line altitudes (ELAs) for contemporary and LIA glaciers. By comparing the ELAs between the contemporary and LIA glaciers, we estimated the LIA summer temperature decreases in different subregions of the Tanggula Mountains. Since the LIA, the ELA have risen by 35.6 ± 18.8 m, 26.1 ± 17.6 m, and 63.1 ± 38.6 m in the respective western, central, and eastern subregions of the Tanggula Mountains. Assuming no change in precipitation, the LIA summer temperature would decrease by 0.22 ± 0.12 °C, 0.14 ± 0.09 °C, and 0.34 ± 0.21 °C in the three subregions, respectively. Moreover, glaciers in the western, central, and eastern subregions have lost 13.3%, 23.9%, and 42.8% of their area, 15.4%, 25.3%, and 39.6% of their length, and 20.8%, 39.0%, and 61.0% of their volume, respectively. By compiling the LIA ELA data from previous studies, we also estimated the LIA summer temperature changes for other regions of the TP. The LIA ELA and summer temperature changes relative to the present showed a decreasing trend from the edges towards the interior on the TP. • LIA glaciers and summer climate were reconstructed at the Tanggula Mountains. • LIA summers were 0.22 ± 0.12 °C, 0.14 ± 0.09 °C, and 0.34 ± 0.21 °C cooler than present in three subregions. • Summer temperature change had a decreasing trend from the edges towards the interior on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The implementation of the "Belt and Road" strategy not only promotes the coordinated development of China's regional economy but also generates a large amount of greenhouse gas emissions. The research and policy recommendations on agricultural carbon emissions are of great significance for China toward engendering sustainable agricultural development and appreciably contributing to the alleviation of global climate change. In this paper, agricultural carbon emissions in the Belt and Road region of China from 2003-2018 are calculated, and its spatial-temporal characteristics are analyzed. Then, we modified the logarithmic mean Divisia index model from the original four factors to six to analyze the drivers of agricultural carbon emissions. The research results obtained are as follows: (1) Total carbon emission reached a peak of 26.6326 million tons in 2016, representing a 54.53% increase from the 17.2342 million tons in 2003. Moreover, it indicated a downward trend in 2017 and dropped by approximately 4% to 25.5685 million tons in 2018. (2) Spatially, agricultural carbon emission varies greatly, with the highest value recorded in Heilongjiang and the lowest in Tibet, thereby exhibiting the characteristics of "northwest>northeast>southwest>southeast." (3) Overall, the economic factor was the most important driving factor, whereas the subsidy factor was the strongest inhibiting factor for the growth of agricultural carbon emissions. Notably, the foreign trade factor had both promoting and inhibiting effects on it. [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]

Understanding future dry and wet changes under global climate change is of great regional significance in China. Based on six Global Climate Models (GCM) from the Coupled Model Intercomparison Project phase 6 (CMIP6), we project the changes of dry‐wet climate regions in China in the 21st century under the three SSP‐RCP (shared socioeconomic pathway‐representative concentration pathway) scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), and further identify the key climatic factors that lead to the transition of dry‐wet climate regions. The results show the area of humid and subhumid regions in China will show an upward trend in the future, while the area of semiarid and arid regions will show a downward trend. Especially under the SSP5‐8.5 scenario, the area of the subhumid region has the largest increase trend (0.042% per year), and the area of the arid region has the largest decline trend (−0.048% per year). The three main transfer directions of dry‐wet climate regions are from arid to semiarid regions, from semiarid to subhumid regions, and from subhumid to humid regions in the future. Due to the future extensive wetting trend in the north, the future dry‐wet climate regions will shift to wetter types in Tibet, North China, the Qinling‐Huaihe regions and the northeast. In addition, the key climatic factors for the transition of dry‐wet climate regions are mainly precipitation, maximum temperature and solar radiation. The increase of precipitation plays a dominant role for areas projected to change to wetter types, and the increase of potential evapotranspiration (PET) plays a dominant role for areas projected to change to drier types. The PET changes in changed areas of dry‐wet climate regions are mainly dominated by maximum temperature and solar radiation. Our research has important implications for future water resource management and reconsideration of climate mitigation and adaptation policies. [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 Nyang River is located in an area sensitive to global climate change, the climate warming changes and human activities have impacted the fragile ecosystem of Plateau Rivers, for which we analyzed the bacterial diversity, community structure characteristics and main influencing factors in the surface sediments of 7 sampling sites in the middle and lower of the Nyang River in Tibet which is in China by high-throughput sequencing technology. The study showed that the abundance of bacterial community in the surface sediments of the middle and lower reaches of the Nyang River that is S1 (upstream of the junction of Bahe Town), S2 (Bahe River), S3 (downstream of the junction of Bahe Town), S4 (upstream of Duobu Hydropower Station), S5 (downstream of Duobu Hydropower Station), S6 (upstream of Bayi Town), S7 (downstream of Bayi Town). The abundance of bacterial community and bacterial diversity at S2 site are relatively high, and the bacterial diversity and abundance of the 7 sampling sites are lower than those of other areas. Five dominant bacteria phyla, including Firmicutes, Proteobacteria, Cyanobacteria, Actinobacteria, Bacteroidetes, and seven dominant bacteria genera, including Exiguobacterium, Hymenobacter, Hyphomicrobium, Leptolyngbya_FYG, Phormidesmis_ANT. L52.6, Tychonema_CCAP_1459-11B were extracted from the surface sediments of the middle and lower reaches of the Nyang River in the dry season. There were significant differences in the dominant bacteria among the samples. Further study found that the influencing factors were flow velocity, environmental factors and nutrients in descending order. [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]

Studies of geochemical proxies, such as carbonate δ18O and TEX 86 , show that the Earth's climate has changed significantly during the Cretaceous Period. However, knowledge about the sea surface temperature (SST) history of the eastern Tethys is limited. Based on the calcareous nannofossil record of the Nirang section, Tethys Himalayas, this paper attempts to establish the biostratigraphic framework and SST evolution of the Cretaceous Period in the southern Tibet. A total of 131 species were identified from the studied succession. Twelve bioevents were recognized, allowing for early Albian to the early Campanian (CC8 to CC18 biozones) in the section. Meanwhile, a disconformity within 81–71 Ma was also identified. The SST evolution was analysed by the calcareous nannofossils modified temperature index (mTI), and the results reveal that the long-term SST changes in the Tethys Himalayas of southern Tibet experienced progressive warming from the early Albian to the early Turonian and the warm interval persisted until the early Campanian. Short-term warming and cooling events, e.g., rapid warming in the early and late Albian, subsequent cooling in the latest Albian and peak warmth at the Cenomanian–Turonian transition, are also recorded in the study area. The SST history of the Albian-Cenomanian in the eastern Tethys can be well correlated to the western Tethys (central Italy). However, the compilation of TEX 86 data indicates substantial global cooling during the Coniacian to Campanian. This study suggests that the northward drift of the Indian continent towards the equator is likely to be responsible for the sustained warmth in the Tethys Himalayas from the middle Turonian to the early Campanian. • Calcareous nannofossil biozones of Albian-early Campanian in Tethys Himalaya of southern Tibet is defined. • Based on mTI of nannofossils, long term history of Cretaceous palaeoclimate of eastern Tethys is reconstructed. • The SST history in Tethys Himalaya is controlled by changes of global palaeotemperature and regional palaeolatitude. [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]

• LUE-VPM produced better quality NPP than MODIS products. • PAR produced from high-resolution DEM can be used in regional NPP modelling. • The MODIS NPP is statistical different with the in-situ measurements in Zeku implementation. Accurate estimation of grassland Net Primary Productivity (NPP) is one of the most important steps in monitoring and further analysing the status of the grassland ecosystem. However, the quality of regional or even global grassland NPP estimations are commonly limited by the two most important input datasets: Photosynthetic Active Radiation (PAR) and climatic data, which make the NPP estimate unrepresentative or even inaccurate. This paper uses a Light Use Efficiency with Vegetation Photosynthesis Model (LUE-VPM) to estimate the high-quality grassland NPP in Zeku. By using the PAR data derived from high resolution DEM products and the improved land surface temperature data, the NPP produced by LUE-VPM shows that it is statistically the same as in situ converted NPP with a p-value of t -test equalling 0.90 (the RMSE between the two is 97.77 gC/m2), while MODIS NPP in Zeku is statically different from the all the in-situ sampling results with a p-value of t-text smaller than 0.03. The results of this paper provided a better estimate than MODIS NPP, and LUE-VPM can be used for the high-quality regional grassland NPP estimation when the quality of PAR data and climatic data improved. [ABSTRACT FROM AUTHOR]

The Minamata Convention on Mercury (Hg) calls for global efforts to reduce the release and risk of Hg. A better understanding of the global Hg budget, transformation and transport as well as toxicity of Hg in the environment, and the Hg emission controlling technologies, is important to minimize Hg pollution and exposure risks. Here, we summarized recent findings regarding the Hg cycle, transport, transformation, and controlling technologies, based on publications in Critical Review in Environmental Science and Technology (CREST) during 2017–2021. In terms of CREST publications we first focused on the biogeochemical cycle and impacts of Hg in the sensitive environment of the Tibet Plateau, and technologies being used to control Hg0 emission from thermal power plants. Second, we discussed the roles of forest in the global cycle of Hg. Third, we reviewed the transport of Hg at artisanal and small-scale gold mining sites, and the mobility and transformation of Hg species in the environment. This special issue covers the recent studies on the cycle, transport, and transformation of Hg, enhances our abilities to develop better strategies to minimize its risks. There are emerging concerns with climatic change and natural and human perturbations on the biogeochemical cycle of Hg in the environment and futures studies are warranted in these areas as well as the global Hg cycle, transport, and remediation. [ABSTRACT FROM AUTHOR]

We assess the Asian summer monsoon anticyclone (ASMA) in Coupled Model Intercomparison Project Phase 6 (CMIP6) models for the historical period (1850–2014). The ASMA is a quasi‐stationary warm anticyclone during the boreal summer monsoon season, centred around Tibet. It is a prominent circulation feature that affects trace species transport, stratosphere–troposphere exchange, along with strong feedbacks to weather and climate. The study is a novel attempt to quantify the performance of models participating in the CMIP6 consortium and understand long‐term variability and teleconnections of the ASMA. We note that CMIP6 models capture the mean ASMA features reasonably well, albeit with some differences around the edges. For most of the models, interannual variations are not in phase with the reanalysis and show sharper increasing trend in the ASMA strength. There is about a twofold increase in the trends during the recent period (1980–2014) as compared to the 1950–2014 period. A multimodel mean (MME) chosen based upon the statistical metrics (mean, standard deviation, mean absolute error and root‐mean‐square error), target diagram, and density distributions is further used to examine the prominent modes of variability. Our results suggest that the signals of significant periodicity, particularly the 2–4 years signal, and the SST correlations in MME are inconsistent with observations. In CMIP6 models, we note stronger upper level divergence over the western and eastern Pacific but convergence over the Indian ocean, South Asia and the central Pacific. The streamfunction and rotational winds also show strong highs north of 20°N. Overall, it is seen that basic features such as spatial extent and evolution of ASMA are reasonably captured, but the strength and interannual variations are dissonant across the CMIP6 models. These findings are useful for studies focusing on regional meteorology, transportation of atmospheric tracers and climate change projections over the region involving the ASMA. [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]

As an essential climate variable (ECV), land surface albedo plays an important role in the Earth surface radiation budget and regional or global climate change. The Tibetan Plateau (TP) is a sensitive environment to climate change, and understanding its albedo seasonal and inter-annual variations is thus important to help capture the climate change rules. In this paper, we analyzed the large-scale spatial patterns, temporal trends, and seasonal variability of land surface albedo overall the TP, based on the moderate resolution imaging spectroradiometer (MODIS) MCD43 albedo products from 2001 to 2019. Specifically, we assessed the correlations between the albedo anomaly and the anomalies of normalized difference vegetation index (NDVI), the fraction of snow cover (snow cover), and land surface temperature (LST). The results show that there are larger albedo variations distributed in the mountainous terrain of the TP. Approximately 10.06% of the land surface is identified to have been influenced by the significant albedo variation from the year 2001 to 2019. The yearly averaged albedo was decreased significantly at a rate of 0.0007 (Sen's slope) over the TP. Additionally, the yearly average snow cover was decreased at a rate of 0.0756. However, the yearly average NDVI and LST were increased with slopes of 0.0004 and 0.0253 over the TP, respectively. The relative radiative forcing (RRF) caused by the land cover change (LCC) is larger than that caused by gradual albedo variation in steady land cover types. Overall, the RRF due to gradual albedo variation varied from 0.0005 to 0.0170 W/m2, and the RRF due to LCC variation varied from 0.0037 to 0.0243 W/m2 during the years 2001 to 2019. The positive RRF caused by gradual albedo variation or the LCC can strengthen the warming effects in the TP. The impact of the gradual albedo variations occurring in the steady land cover types was very low between 2001 and 2019 because the time series was short, and it therefore cannot be neglected when examining radiative forcing for a long time series regarding climate change. [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]

Drought poses a significant risk to human life, agriculture, energy, ecosystem, wildlife, and other aspects of the terrestrial system. Climate warming may increase drought hazards around the globe. This study compares the pre- and post-industrial impact of climate change on the spatiotemporal evolution of drought over the Tibet Plateau region. Two standardized drought indices (SDIs), namely Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), are utilized to characterize drought by averaging the time-series data of precipitation and temperature from 23 climate models of Coupled Model Intercomparison Project 6 database. Sen slope estimates and steady-state probabilities of the Markov Chain are used to assess drought characteristics. This study shows that an increasing trend in temperature has led to increased evaporation. Increasing evaporation had caused expansion in water deficiency; the decreasing trend of SPEI index on almost the entire Tibet Plateau reveals the persistence of future drought. A slight increase has been observed in extreme wet classes in higher timescales. However, the long-term probabilities of extreme drought and extreme wet episodes at the one-month timescale of SPI are equivalent and stable in both periods. The chance of occurrences of severe drought episodes has decreased. Comparatively, a significant increase in the likelihood of severe drought has been observed under the SPEI. Furthermore, the spatiotemporal quantitative comparison reveals that the SPI index is consistent in both periods. However, a significant decline ratio of SPEI values has been observed in the post-industrial period. It is because increasing temperature causes more evaporation. Consequently, the increase in water deficiency is the main reason for increasing drought episodes under SPEI. [ABSTRACT FROM AUTHOR]

The tropopause plays an important role in climate change, particularly in Tibet with complex topography and climate change system. In this paper, the temperature and height of the Cold Point Tropopause (CPT) in Tibet are obtained and investigated from COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) GPS Radio Occultation (RO) during June 2006–Feb 2014, which are compared with Lapse Rate Tropopause (LRT) from Atmospheric Infrared Sounder (AIRS/NASA). Furthermore, the impact of Gravity waves (GW) potential energy ( E p ) on the CPT-Temperature, CPT-Height, and the variation of stratospheric water vapor with GW E p variations are presented. Generally the coldest CPT temperature is in June–July–August (JJA) with −76.5 °C, resulting less water vapor into the stratosphere above the cold points. The temperature of the cold point increases up to −69 °C during the winter over the Tibetan Plateau (25–40°N, 70–100°E) that leads to increase in water vapor above the cold points (10 hPa). Mean vertical fluctuations of temperature are calculated as well as the mean gravity wave potential energy E p for each month from June 2006 to Feb 2014. Monthly E p is calculated at 5°×5° grids between 17 km and 24 km in altitude for the Tibetan Plateau. The E p raises from 1.83 J/Kg to 3.4 J/Kg from summer to winter with mean E p of 2.5 J/Kg for the year. The results show that the gravity waves affect the CPT temperature and water vapor concentration in the stratosphere. Water vapor, CPT temperature and gravity wave ( E p ) have good correlation with each other above the cold points, and water vapor increases with increasing E p . [ABSTRACT FROM AUTHOR]

Aboveground net primary productivity (ANPP) and rain-use efficiency (RUE) are important indicators in assessing the response of ecosystems to climate change. In this paper, the Changtang Plateau in the Tibetan Autonomous Region was selected as the study area to analyze the spatial and temporal changes of ANPP and RUE in grassland communities and their response to climate change. The results showed the following:(1) The spatial pattern of ANPP was closely related to rainfall on the Changtang Plateau. The average ANPP over the past 15 years increased gradually from the arid west to the humid east. A consistent pattern was exhibited in different grassland types and climate zones. (2) The RUE was higher at the east and west edges of the Changtang Plateau, especially in the arid west, but was lower in the center. From the perspective of different climatic zones, the average RUE in the southern Tibetan semiarid climate zone and the Ngari arid climate zone was significantly higher than that in other climate zones. However, the average RUE in different grassland types only varied from 0.07 to 0.09 g·m−2·mm−1. The spatial variation in RUE was more distinct in different climatic zones than in different grassland types. (3) Climate change influenced the interannual variation of ANPP and RUE, but the response of ANPP to rainfall showed a significant lag. The interannual change in RUE was negatively correlated with changes in precipitation. (4) In general, a greater area showed a significant increase rather than a decrease in ANPP on the Changtang Plateau, which meant that the grassland condition is improving. The temporal variation patterns of ANPP and RUE in different climate zones were consistent with the overall patterns on the Changtang Plateau, while the variation was not significant in different grassland types. [ABSTRACT FROM AUTHOR]

As the world's Third Pole, the Qinghai‐Tibet Plateau has a large area of marshes, which plays an important role in global carbon cycle. The net primary productivity (NPP) of vegetation is a crucial index for measuring the carbon flux of marsh ecosystems. Understanding the change in marsh NPP and its response to climatic change is important for assessing carbon sequestration of marsh ecosystems. Based on MODIS NPP data and climate data from 2000 to 2020, this study analyzed the spatiotemporal change in marsh NPP and determined its relationship with climate factors on the Qinghai‐Tibet Plateau. The results showed that the average annual NPP of marshes on the Qinghai‐Tibet Plateau increased significantly by 11.70 ± 1.07 g C·m−2/10a during 2000–2020, with an average value of about 184.37 ± 11.12 g C·m−2. Spatially, the annual marsh NPP showed obviously increasing trend in the northeast but decreasing trend in the southwest regions. Daytime maximum and nighttime minimum temperatures had asymmetric effects on marsh NPP, with a larger positive effect of minimum temperature. Warmed minimum temperatures in winter and spring significantly increased the annual marsh NPP on the Qinghai‐Tibet Plateau. The increasing maximum and minimum temperatures in the summer obviously promoted the vegetation growth in marshes. Additionally, the increasing spring precipitation could significantly increase the marsh NPP. Our results highlight that the asymmetric impacts of daytime and nighttime temperatures on marsh vegetation should be adequately considered in predicting marsh carbon sequestration on the Qinghai‐Tibet Plateau, especially in the context of global asymmetric diurnal warming. Plain Language Summary: As the highest plateau in the world, the Qinghai‐Tibet Plateau has large areas of marshes, which has important effects on the biogeochemical cycle and carbon balance. The net primary productivity (NPP) of marsh vegetation is a crucial index for measuring the carbon sequestration of marsh ecosystems. Until recently, the vegetation NPP changes of marsh and its response to climate change in the Qinghai‐Tibet Plateau remain unclear. Using the NPP and climate data, this study analyzed the spatiotemporal variation in marsh NPP and its response to climate change in marshes of the Qinghai‐Tibet Plateau. This study analyzed, for the first time, the influences of daytime and nighttime temperature changes on vegetation NPP of marshes. Results show that the effects of day and night temperatures on the productivity of marsh vegetation are asymmetric on the Qinghai‐Tibet Plateau. Compared with the annual maximum temperature, the annual minimum temperature had a larger positive effect on marsh NPP. Increased minimum temperatures in winter and spring could increase the annual marsh NPP on the Qinghai‐Tibet Plateau. The increasing maximum and minimum temperatures in the summer were beneficial to the vegetation growth in marshes. Additionally, increased spring precipitation could significantly increase the Plateau's annual marsh NPP. Key Points: Daytime and nighttime temperatures had asymmetric effects on the annual net primary productivity (NPP) of marshes on the Qinghai‐Tibet PlateauThe increases in summer daytime and nighttime temperature and nighttime temperature in winter and spring increased marsh NPPIncreased spring precipitation could increase the annual marsh NPP on the Plateau [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]

Fritillariae Cirrhosae Bulbus (FCB) is a famous traditional Chinese medicine, mainly used for relieving cough and resolving phlegm. According to Chinese Pharmacopoeia (2020), the medicine comes from dried bulbs of five species and one variety in Fritillaria. Due to climate change and human disturbance, the wild resources have become critically endangered in recent years. Following three climate change scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) under 2050s and 2070s, geographic information technology (GIS) and maximum entropy model (MaxEnt) were used to simulate the ecological suitability of FCB, a third-grade rare and endangered medicinal plant species. The results showed that the key environmental variables affecting the distribution of FCB were altitude, human activity intensity, and mean temperature of coldest quarter. Under current climate situation, the highly suitable areas were mainly located in the east of Qinghai Tibet Plateau, including Western Sichuan, southeastern Tibet, southern Gansu, Northwestern Yunnan, and Eastern Qinghai, with a total area of 31.47×104 km2, the area within the nature reserve was 7.13×104 km2, indicating that there was a large protection gap. Under the future climate change scenarios, the areas of the highly and poorly suitable areas of FCB showed a decreasing trend, while the areas of the moderately and total suitable areas showed an increasing trend. The geometric center of the total suitable area of the medicine will move to the northwest. The results could provide a strategic guidance for protection,development, and utilization of FCB though its prediction of potential distribution based on the key variables of climate change. [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]

Under global climate change, more frequent and widespread droughts have dramatic impacts on the water and carbon cycles. Water use efficiency (WUE) is a commonly used indicator reflecting the trade‐off relationship between carbon sequestration and water consumption. Therefore, this study aims to clarify the variations in WUE and the effects of drought on WUE in sensitive alpine meadows on the Tibetan Plateau. Based on 6‐year (2013–2018) continuous carbon and water flux data observed by the eddy covariance system, WUE was calculated by gross ecosystem productivity (GEP)/evapotranspiration (ET). WUE followed a unimodal variation with time during growing seasons in the years without droughts. However, drought disrupted this pattern by its effects on the coupled relationship between carbon and water fluxes. Specifically, droughts showed divergent effects on WUE variations in different periods of the growing seasons. In the early‐growing seasons, droughts induced an increase in WUE. During this period, WUE was mainly regulated by temperature and leaf area index (LAI), and the GEP was low due to the smaller LAI. Therefore, the drought‐induced reduction in GEP was less than that in ET; thus, WUE increased. In the mid‐growing seasons, droughts depressed WUE. WUE was dominated by water conditions and the LAI during this period. When drought occurred, GEP decreased faster than ET, and hence, WUE decreased. In the late‐growing season, WUE was mainly driven by temperature and the LAI, but short‐term drought slightly enhanced WUE. These results are helpful in understanding the responses of fragile alpine ecosystems to future climate change. [ABSTRACT FROM AUTHOR]

Based on four reanalyses or gridded data sets (ERA5, 20CR, APHRODITE and REGEN), we provide an overview of 23 Historical and 7 HighResMIP experiments' performance from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (for short, 6-Hist, HighRes) in simulating seven extreme precipitation indices over Asia defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We compare them with 28 Historical experiments in CMIP5 (5-Hist). CMIP5 and CMIP6 models are generally able to reproduce extreme precipitation's spatial distribution and their trend patterns in comparison to the benchmark data set (APHRODITE). The overall performance of individual model is summarized by a "portrait" diagram based on four statistics for each index. We divide all 58 models into three groups (A, the top 20%; B, the median 60% and C group, the last 20%) according to MR rankings (the comprehensive ranking measure). Based on the "portrait" diagram and MR rankings, models that perform relatively well for all seven extreme precipitation indices include HadCM3, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES from 5-Hist, EC-Earth3, EC-Earth3-Veg from 6-Hist and ECMWF-IFS-HR, ECMWF-IFS-LR, ECMWF-IFS-MR from HighRes. The simulated performance of CMIP6 is polarized, for the top four and the last five ranking models are both from CMIP6. Compared with the counterpart models in CMIP6 and CMIP5, the improvement of PCC (pattern correlation coefficient) is more obvious. Furthermore, the dry biases of CMIP6 (both 6-Hist and HighRes) in Southern China and India and the wet biases of CMIP6 in Tibet are reduced compared to CMIP5. This may benefit from the improvement that CMIP6 models can capture the characteristics of meridional moisture flux convergence, and improve the overestimation or underestimation of meridional and zonal specific humidity eddies compared to CMIP5. [ABSTRACT FROM AUTHOR]

Due to various land cover changes, vegetation dynamics, and climate, drought is the most complex climate-related disaster problem in Tibet and Xinjiang, China. The purpose of the present study is to analyze the performance of the AVHRR Normalized Vegetation Index (NDVI) and the temporal and spatial differences of seasonal vegetation dynamics by correlating the results with rainfall and temperature data of NASA's MERRA to examine the vegetation dynamics and droughts in Tibet and the Xinjiang Province of China. Our method is based on the use of AVHRR NDVI data and NASA MERRA temperature and precipitation during 1983–2016. Due to the dryness and low vegetation, NDVI is more useful to describe the drought conditions in Tibet and Xinjiang of China. The NDVI, TCI, VHI, NVSWI, VCI, TVDI, and NAP from April to October increased rapidly. While the NDVI, TCI, VHI, NVSWI, NAP, TVDI, and VCI are stable every month in September, again improve in October, and then confirm downward trend in December. The NDVI, TCI, VHI, NVSWI, NAP, VCI, and TVDI monthly values indicate that Tibet and Xinjiang province of China suffered from severe drought in 2006, 2008, and 2012 which were the most drought years. For monitoring drought in Tibet and Xinjiang province of China, the NDVI, TVDI, NAP, VCI, and NVSWI values were selected as a tool for reporting drought events during different growing seasons. Seasonal values of TVDI, NDVI, NAP, NVSWI, and VCI confirmed that Tibet and Xinjiang province of China suffered from severe drought in 2006, 2008, and 2012 and led the durations of severe drought. The correlation between NDVI, TCI, VHI, NAP, TVDI, and VCI showed a significantly positive correlation, while the significantly negative correlation between NVSWI and NDVI showed a good indication for the assessment of drought, especially for the agricultural regions of Tibet and Xinjiang province of China. This shows that the positive sign to support NAP, NVSWI, and TVDI is good monitoring of the drought indexes in Tibet and the Xinjiang province of China. [ABSTRACT FROM AUTHOR]

In this paper, we review evidence for a major biotic turnover across the Oligocene/Miocene in the Tibetan Plateau region. Based on the recent study of six well-preserved fossil sites from the Cenozoic Lunpola and Nima basins in the central Tibetan Plateau, we report a regional changeover from tropical/subtropical ecosystems in the Late Oligocene ecosystem (26–24 Ma) to a cooler, alpine biota of the Early Miocene (23–18 Ma). The Late Oligocene fossil biota, comprising of fish (climbing perch), insects and plants (palms), shows that the hinterland of the Tibetan Plateau was a warm lowland influenced by tropical humidity from the Indian Ocean. In the Early Miocene, the regional biota became transformed, with the evolution and diversification of the endemic primitive snow carp. Early Miocene vegetation was dominated by temperate broad-leaved forest with abundant conifers and herbs under a cool climate, and mammals included the hornless rhinoceros, Plesiaceratherium , a warm temperate taxon. This dramatic ecosystem change is due to a cooling linked to the uplift of Tibetan region, from a Late Oligocene paleo-elevation of no greater than 2300 m a.s.l. in the sedimentary basin to a paleo-elevation of about 3000 m a.s.l. Another factor was the Cenozoic global climatic deterioration toward to an ice-house world. • The Tibetan uplift had a profound impact on the evolution of terrestrial ecosystems. • The Oligocene subtropical ecosystem was replaced by a Miocene cooler biota in Tibet. • The Late Oligocene biota showed that the Tibetan hinterland was a warm lowland. • The Early Miocene biota eventually culminated in the present ecosystem of Tibet. • This dramatic ecosystem change is due to the cooling effect of the Tibetan Plateau. [ABSTRACT FROM AUTHOR]