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Land degradation has become a catastrophic global environmental issue. The current status of land degradation and changing trends of land remain unclear on the Qinghai-Tibet Plateau (QTP). This study integrated an Optimal Land Degradation Index (OLDI) and spatial footprints of three land degradation pathways (i.e., salinization, desertification and soil erosion) to investigate changing trends and degradation risks from 2001 to 2021 on the QTP. The results showed that land improvements were the dominant changing trends on the QTP compared to land degradation, accounting for 18.83% of the whole plateau. The regions with land improvements were mainly distributed in the northeastern QTP. High-risk degraded land covered an area of 0.55 million km2, and low-risk degraded land covered 0.78 million km2. The spatial distribution of high-risk degraded land varied gradually from scattered small areas to increasingly frequent connected patches from southeast to northwest. Potential driving factor analysis illustrated that land degradation resulted from multidimensional driving forcings, including topography, climatic factors, and human activities. The findings in this study can provide great insight for alpine ecosystem development and make adaption to achieve carbon neutrality with global warming.

Grazing plays a critical role in the sustainable development of grassland. It has been convinced that grazing affects grassland productivity, however, researches on the relationship between grazing intensity and grassland soil quality remain inadequate in the alpine environment. This study compared ten soil quality indexes (SQIs) to quantitative assess the effect of different grazing intensities [no grazing (NG); light grazing (LG); moderate grazing (MG); heavy grazing (HG)] on the soil quality of alpine meadow in the 0–10 cm and 10–20 cm soil layers. Principal component analysis (PCA) and minimum data set (MDS) were applied to indicator selection and weight assignment. The fitting relationship and correlation between SQI-TDS and SQI-MDSs and the sensitivity index (SI) of ten SQIs were used to select the optimal SQI method. Our results showed that compared with NG and LG, HG and MG significantly decreased soil organic matter (SOM), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), and cation exchange capacity (CEC) (p