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Climate is an important factor that affects livability, but the climate comfort model used for low altitudes is not applicable to high altitudes, and further study on climate suitability in high-altitude areas is needed. In response to the absence of high-altitude characteristics in the current climate comfort assessment methods, this study adds oxygen content and solar radiation as plateau characteristic indicators. We use the consulting graded method (CGM), least squares method (LSM) and questionnaire survey method (QSM) to obtain comprehensive weights for oxygen content, solar radiation and comfort index to build the Climate Suitability Index of Plateau (CSIP) and assess climate suitability on the Qinghai-Tibet Plateau. The CSIP decreases obviously as elevation increases from southeast to northwest on the Qinghai-Tibet Plateau, which means that the climate becomes increasingly unsuitable from southeast to northwest. The Qinghai-Tibet Plateau is divided into four regions-"very unsuitable" (83.8 × 10 4  km 2 , 32.4%), "unsuitable" (81.5 × 10 4  km 2 , 31.6%), "suitable" (67.9 × 10 4  km 2 , 26.3%), and "very suitable" (24.9 × 10 4  km 2 , 9.6%)-by the natural break method according to the CSIP. According to the different degrees of response of population density to CSIP, we plot the climate suitability line of the Qinghai-Tibet Plateau to provide basic theoretical support for regional planning in the Qinghai-Tibet region. The CSIP developed in this study provides a new climate suitability assessment method for high-altitude regions and a method for planning human activities on the Qinghai-Tibet Plateau from a climate-focused perspective., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In recent years, there has been growing concern that vegetation changes on the Tibetan Plateau are associated with climate change (temperature and precipitation) and human activities. This study used six types of remote sensing vegetation data, including GIMMS (Global Inventory Modelling and Mapping Studies) NDVI (Normalized Difference Vegetation Index), MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI, MODIS EVI (Enhanced Vegetation Index), SPOT Vegetation (Spot-VGT) NDVI, LAI (Leaf Area Index) and NPP (Net Primary Productivity), and applied the maximum synthesis method, trend analysis, correlation analysis, and multivariate statistical analysis to investigate vegetation change processes since the 1980s. The study showed that the amount of vegetation on the TP had increased significantly since 2000 (p <.01), especially in the northeastern part of the TP. There was no significant change prior to 2000. The different vegetation data sources varied greatly. Four remote sensing indices, MODIS EVI, Spot-VGT NDVI, LAI, and NPP, showed a significant increase in vegetation from 2000, accounting for 16.18%, 44.55%, 30.44% and 8.94% of the total area, respectively (p <.05). Multiple data sources provided a more comprehensive understanding, whereas a single data source had substantial uncertainty. Human activities, such as the implementation of large-scale ecological projects, played a dominant role in increasing vegetation, while climate change played a subsidiary role. The MODIS EVI, Spot-VGT NDVI, LAI, and NPP data showed that the area of increased vegetation caused by human activities accounted for 53.51%, 45.68%, 37.52%, and 31.79% of the total area of the TP, respectively. The relative increase from climate change was 10.28%, 17.49%, 13.15%, and 8.82%, respectively. The current study applied multi-source remotely sensed vegetation data, which effectively reduced the uncertainty caused by individual data sources and provided more rigorous and scientific research conclusions. [ABSTRACT FROM AUTHOR]

High altitude areas play an essential role in the global climate system, and their fragile ecosystems sensitively respond to climate change and human activities. An improved understanding of the influences of multiple factors on the spatiotemporal dynamics of vegetation is needed. This study aimed to understand further the impacts of climate, geography, and human on vegetation and disentangle the contributions of climate and humans to vegetation changes using the MOD13Q1 enhanced vegetation index (EVI, 2000–2019). Greening was detected for 70% of the Tibetan Plateau under increased warming and wetting in the 21st century. A rise in temperature of up to 0.66 ± 0.49°C decade−1 occurred over 2/3 of the Tibetan Plateau, while precipitation increased slightly. In particular, significant greening covered 1/4 of the Tibetan Plateau and occurred within the steppe and desert on the northern due to wetting and ecological protection. Browning depended on urbanization, overgrazing, and lake expansion in 1.9% of the total area. Orbicular browning around lakes accounted for 18.4% of significant browning, and significant browning trends were also detected in densely populated cities situated at low‐altitude and flat areas. The EVI was more strongly positively correlated with the annual mean minimum temperature than the annual mean temperature and maximum temperature and was sensitive to extreme low precipitation events. Residual analysis showed that the relative contribution of climate change was 34%, and that of human activities was 66%. A comprehensive description of the vegetation changes on the Tibetan Plateau will help humans to cope with climate change and ecosystem evolution in high altitude. [ABSTRACT FROM AUTHOR]

• The Universal Soil Loss Equation ensemble model was used to simulate soil erosion credibly. • Soil erosion and soil organic carbon erosion have significantly increased over the past 40 years. • The growth rates of soil erosion and soil organic carbon erosion have decelerated after 1999. • Rainfall change and slope were crucial factors controlling variations in erosion related to land use. Soil erosion by water and loss of soil organic carbon (SOC) are two major contributors to global land degradation. However, the impact of soil erosion and its effect on SOC in the fragile, sensitive alpine ecosystem of the Tibetan Plateau, where climate change is amplified, is not well understood. We used the Universal Soil Loss Equation (USLE) ensemble model to analyse soil erosion, SOC loss, and their dynamics over the past 40 years (1981–2018) on the Tibetan Plateau. The mean soil erosion and SOC erosion rates were 5.91 ± 2.29 t ha−1 yr−1 and 0.374 ± 0.113 t C ha−1 yr−1, respectively, with significant increasing trends because of increased rainfall. Spatially, we identified areas prone to soil and SOC erosion across the plateau. SOC erosion rates rose by 19.0 %, from 0.34 ± 0.03 t C ha−1 yr−1 in the 1980s to 0.40 ± 0.02 t C ha−1 yr−1 in the 2010s. The increasing erosion rates after 1999 were weakened because of the slow increase in rainfall and rapid vegetation greening. Two distinct erosion mechanisms emerged concerning land use: rainfall-dominated and slope-dominated. Our findings underscore the extreme vulnerability of soil erosion and SOC loss on the Tibetan Plateau to climate change, providing helpful insights for sustainable land resource management in this ecologically fragile environment and enhancing our understanding of the incipient impact of soil erosion on the carbon cycle. [ABSTRACT FROM AUTHOR]