As an important production base for livestock and a unique ecological zone in China, the northeast Tibetan Plateau has experienced dramatic land use/land cover (LULC) changes with increasing human activities and continuous climate change. However, extensive cloud cover limits the ability of optical remote sensing satellites to monitor accurately LULC changes in this area. To overcome this problem in LULC mapping in the Ganan Prefecture, 2000–2018, we used the dense time stacking of multi-temporal Landsat images and random forest algorithm based on the Google Earth Engine (GEE) platform. The dynamic trends of LULC changes were analyzed, and geographical detectors quantitatively evaluated the key driving factors of these changes. The results showed that (1) the overall classification accuracy varied between 89.14% and 91.41%, and the kappa values were greater than 86.55%, indicating that the classification results were reliably accurate. (2) The major LULC types in the study area were grassland and forest, and their area accounted for 50% and 25%, respectively. During the study period, the grassland area decreased, while the area of forest land and construction land increased to varying degrees. The land-use intensity presents multi-level intensity, and it was higher in the northeast than that in the southwest. (3) Elevation and population density were the major driving factors of LULC changes, and economic development has also significantly affected LULC. These findings revealed the main factors driving LULC changes in Gannan Prefecture and provided a reference for assisting in the development of sustainable land management and ecological protection policy decisions.

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Grazing is one of the main human disturbance factors in alpine grassland on the Qinghai-Tibet Plateau (QTP), which can directly or indirectly influence the community structures and ecological functions of grassland ecosystems. However, despite extensive field grazing experiments, there is currently no consensus on how different grazing management approaches affect alpine grassland diversity, soil carbon (C), and nitrogen (N). Here, we conducted a meta-analysis of 70 peer-reviewed publications to evaluate the general response of 11 variables related to alpine grassland ecosystems plant diversity and ecological functions to grazing. Overall, the results showed that grazing significantly increased the species richness, Shannon–Wiener index, and Pielou evenness index values by 9.89% (95% CI: 2.75–17.09%), 7.28% (95% CI: 1.68–13.62%), and 3.74% (95% CI: 1.40–6.52%), respectively. Aboveground biomass (AGB) and belowground biomass (BGB) decreased, respectively, by 41.91% (95% CI: −50.91 to −32.88%) and 17.68% (95% CI: −26.94 to −8.52%). Soil organic carbon (SOC), soil total nitrogen (TN), soil C:N ratio, and soil moisture decreased by 13.06% (95% CI: −15.88 to −10.15%), 12.62% (95% CI: −13.35 to −8.61%), 3.27% (95% CI: −4.25 to −2.09%), and 20.75% (95% CI: −27.89 to −13.61%), respectively, whereas, soil bulk density and soil pH increased by 17.46% (95% CI: 11.88–24.53%) and 2.24% (95% CI: 1.01–3.64%), respectively. Specifically, moderate grazing, long-durations (>5 years), and winter grazing contributed to increases in the species richness, Shannon–Wiener index, and Pielou evenness index. However, AGB, BGB, SOC, TN, and soil C:N ratios showed a decrease with enhanced grazing intensity. The response ratio of SOC was positively associated with AGB and BGB but was negatively related to the Shannon–Wiener index and Pielou evenness index. Furthermore, the effects of grazing on plant diversity, AGB, BGB, SOC, and TN in alpine grassland varied with grazing duration, grazing season, livestock type, and grassland type. The findings suggest that grazing should synthesize other appropriate grazing patterns, such as seasonal and rotation grazing, and, furthermore, additional research on grazing management of alpine grassland on the QTP is needed in the future.