The soil carbon storage in the Qinghai–Tibet Plateau wetlands is affected by microbiota and wetland types, but the response mechanisms of carbon sequestration microorganisms on the Qinghai–Tibet Plateau to different wetland types are still poorly described. To explore the differences in carbon sequestration microbial communities in different wetlands and the main influencing factors, this study took a marsh wetland, river source wetland and lakeside wetland of Qinghai Lake as the research objects and used high-throughput sequencing to study the functional gene, cbbL, of carbon sequestration microorganisms. The results showed that the dominant bacterial group of carbon sequestration microorganisms in marsh and river source wetlands was Proteobacteria, and the dominant bacterial group in the lakeside wetland was Cyanobacteria. The alpha diversity, relative abundance of Proteobacteria and total carbon content were the highest in the marsh wetland, followed by the river source wetland, and they were the lowest in the lakeside wetland. In addition, the physical and chemical characteristics of the three wetland types were significantly different, and the soil temperature and moisture and total carbon content were the most important factors affecting the community structures of carbon-sequestering microorganisms. There was little difference in the total nitrogen contents between the marsh wetland and river source wetland. However, the total nitrogen content was also an important factor affecting the diversity of the carbon sequestration microbial community. In summary, the wetland type significantly affects the process of soil carbon sequestration. Compared with the riverhead and lakeside wetlands, the marsh wetland has the highest carbon storage.

The use of geostatistics to explore the spatial distribution and variability of soil properties has become an important tool to recognize soil properties. In this paper, we combined actual field sampling data with geostatistics to study the characteristic and spatial variability of soil organic matter and organic carbon content around Qinghai Lake. The results showed that the mean content of soil organic carbon is 5.95 ± 3.40%, and organic matter is 3.45 ± 1.97%, both are low. The variogram model of semi-variance function graph showed the models of soil organic carbon and matter are the exponential model. Isotropic ratio of nugget to sill of soil organic carbon and organic matter are 82.9% and 83%, both variable range are 9300m, all are in the range, here exists a correlation between organic carbon and organic matter content in the space. Fractal dimension can exhibit the higher spatial heterogeneity of soil organic carbon and organic matter content around Qinghai Lake. Anisotropy semi-variance analysis reveals that there does not exist any anisotropy structural characteristics of soil organic carbon and organic matter content in different directions in the study area; but there is spatial variability in the east - west as for organic matter content, while variability is very small in the other directions.

The present study aims to quantitatively assess soil erosion intensity (SEI) and amounts in the Qinghai Lake Basin (QLB) over the 1990–2020 period using the Integrated Valuation Ecosystem Services and Tradeoffs (InVEST) model based on multi-source data. In addition, the changing trends and driving factors of soil erosion (SE) in the study area were systematically analyzed. The result showed: (1) An increasing-decreasing trend in the total soil erosion amount (SEA) in the QLB over the 1990–2020 period, with an average SEI of 579.52 t/km². In addition, very low and low erosion classes covered 94.49% of the total surface area, while areas with high SEI were mainly distributed in alpine areas with low vegetation coverage (VC). (2) The highest average SEI was observed in bare land, while grassland and unused land were the main land use (LU) types where SE mainly occurred, with the ratio of the two being 95.78%. (3) The average value of SEI was positively correlated with altitude values below 4800 m. In addition, areas with altitude ranges of 4000–4400 m, 3600–4000 m, and 4400–4800 m were the main areas where SE occurred, with an average total soil erosion ratio (SER) value of 88.73%. (4) The average SEI was directly proportional to the slope degrees. SE occurred mainly in the areas with slope degree ranges of 15–25°, 25–35°, 8–15°, and >35°, accounting for 93.16% of the average total SER value. (5) The q value of the two-factor interaction was greater than that of the single-factor interaction. In addition, the areas with a high SE risk were mainly those with 1220–2510 m rainfall, 35°. The interaction between rainfall, VC, LULC, elevation, and slope had a significant impact on the spatial distribution of SEI.

The Qinghai Lake Basin (QLB), located in the northeastern part of the Qinghai–Tibet Plateau, has a fragile ecological environment and is sensitive to global climate change. With the progress of societal and economic development, the tourism industry in the QLB has also developed rapidly, which is bound to result in great changes in landscape patterns. In this study, we first analyzed the change characteristics of landscape patterns in the QLB from 1990 to 2018, and we then used the Markov model and the future land use simulation (FLUS) model, combined with natural, social, and ecological factors, to predict the changes in the number and spatial distribution of landscape patterns in the period between 2026 and 2034. The results of the study show that desert areas have been greatly reduced and transformed into grasslands. The grassland area expanded from 49.22% in 1990 to 59.45% in 2018, corresponding to an increase of 10.23%. The direct cause of this result is the combined effects of natural and man-made factors, with the latter playing a leading role. As such, government decision-making is crucial. Lastly, we simulated the landscape patterns in the period from 2018 to 2034. The results show that in the next 16 years, the proportion of various landscapes will change little, and the spatial distribution will be stable. This research provides a reference for the formulation of ecological environment management and protection policies in the QLB.

The impact of climate change on the global hydrological cycle is becoming increasingly significant, with changes in precipitation patterns emerging as a key factor influencing the carbon and nitrogen cycling processes in alpine wetland ecosystems. However, the response of the nosZ-type denitrifying microbial community and its metabolic characteristics in the source wetland to precipitation changes remains unclear. In this study, high-throughput sequencing of the nosZ gene and LC-MS-based metabolomics were used to investigate the response of the nosZ-type denitrifying microbial community and its metabolic characteristics to precipitation changes (4 years) in the source wetland of Qinghai Lake. The results showed that Microvirga was the key bacterial group in the source wetland of Qinghai Lake, and Azospirillum was sensitive to changes in precipitation (P < 0.05). The 50% rainfall enhancement treatment significantly increased soil moisture, and the total carbon content showed an increasing trend with the increase in precipitation (P < 0.05). pH was the most important explanatory factor for community structure, while total nitrogen content was the key explanatory factor for community diversity. Deterministic processes dominated the assemblage of the nosZ-type denitrifying microbial community in the source wetland of Qinghai Lake. Soil metabolomics analysis showed that the differential metabolites in the Source Wetland mostly exhibited significant positive correlations. Precipitation changes significantly affected the relative abundance of N-Acetylaspartic acid. In summary, lower precipitation is more favorable for maintaining carbon storage in the source wetlands of Qinghai Lake. Precipitation variation disrupted the existing nitrogen balance within the ecosystem and altered the structure of the nosZ-type denitrifying microbial community and soil metabolic characteristics. These findings imply that climate change-driven shifts in precipitation patterns may impact carbon and nitrogen dynamics in alpine wetlands, alter ecosystem stability, and have profound effects on microbial communities and biogeochemical cycles.