Aboveground biomass (AGB) serves as a crucial measure of ecosystem productivity and carbon storage in alpine grasslands, playing a pivotal role in understanding the dynamics of the carbon cycle and the impacts of climate change on the Qinghai-Xizang Plateau. This study utilized Google Earth Engine to amalgamate Landsat 8 and Sentinel-2 satellite imagery and applied the Random Forest algorithm to estimate the spatial distribution of AGB in the alpine grasslands of the Beiliu River Basin in the Qinghai-Xizang Plateau permafrost zone during the 2022 growing season. Additionally, the geodetector technique was employed to identify the primary drivers of AGB distribution. The results indicated that the random forest model, which incorporated the normalized vegetation index (NDVI), the enhanced vegetation index (EVI), the soil-adjusted vegetation index (SAVI), and the normalized burn ratio index (NBR2), demonstrated robust performance in regards to AGB estimation, achieving an average coefficient of determination (R2) of 0.76 and a root mean square error (RMSE) of 70 g/m2. The average AGB for alpine meadows was determined to be 285 g/m2, while for alpine steppes, it was 204 g/m2, both surpassing the regional averages in the Qinghai-Xizang Plateau. The spatial pattern of AGB was primarily driven by grassland type and soil moisture, with q-values of 0.63 and 0.52, and the active layer thickness (ALT) also played a important role in AGB change, with a q-value of 0.38, demonstrating that the influences of ALT should not be neglected in regards to grassland change.

This study tested the hypothesis that soil organic carbon (SOC) and total nitrogen (TN) spatial distributions show clear relationships with soil properties and vegetation composition as well as climatic conditions. Further, this study aimed to find the corresponding controlling parameters of SOC and TN storage in high-altitude ecosystems. The study was based on soil, vegetation and climate data from 42 soil pits taken from 14 plots. The plots were investigated during the summers of 2009 and 2010 at the northeastern margin of the Qinghai-Tibetan Plateau. Relationships of SOC density with soil moisture, soil texture, biomass and climatic variables were analyzed. Further, storage and vertical patterns of SOC and TN of seven representative vegetation types were estimated. The results show that significant relationships of SOC density with belowground biomass (BGB) and soil moisture (SM) can be observed. BGB and SM may be the dominant factors influencing SOC density in the topsoil of the study area. The average densities of SOC and TN at a depth of 1 m were about 7.72 kg C m(2) and 0.93 kg N m 2. Both SOC and TN densities were concentrated in the topsoil (0-20 cm) and fell exponentially as soil depth increased. Additionally, the four typical vegetation types located in the northwest of the study area were selected to examine the relationship between SOC and environmental factors (temperature and precipitation). The results indicate that SOC density has a negative relationship with temperature and a positive relationship with precipitation diminishing with soil depth. It was concluded that SOC was concentrated in the topsoil, and that SOC density correlates well with BGB. SOC was predominantly influenced by SM, and to a much lower extent by temperature and precipitation. This study provided a new insight in understanding the control of SOC and TN density in the northeastern margin of the Qinghai-Tibetan Plateau.