Exploring the diversity and formation mechanism of under-ground bud banks is essential for understanding population regeneration and community succession. However, there are few studies on the response of bud bank size and composition to different degradation gradients in alpine meadows. In view of this, we investigated the size and composition of bud bank under four degradation gradients (non-degraded:ND, lightly degraded:LD, moderately degraded:MD, and heavily degraded:HD) on a typical alpine meadow in Tibet, China, and analyzed the influence of soil physical and chemical properties on the correlation of bud bank types. Our results show that in ND meadows, rhizome buds dominate, in LD meadows, tiller buds account for a larger proportion, and in MD meadows, root-sprouting buds dominate. The total bud bank density decreases as the degradation gradient increases. The density of cyperaceae buds decreased with the degree of degradation. The density of leguminosae was insignificant in each degradation gradient. The density of gramineae and weeds were dominant in LD and MD meadows, respectively. Rhizome bud density was significantly positively correlated with soil organic carbon (SOC), total nitrogen (TN), NH+ 4- N, and NO- 3 - N (P < 0.001 for all), soil water content (SWC), total phosphorus (TP) and available phosphorus (AP) (P < 0.01), and negatively correlated with pH (P < 0.001). Tiller bud was significantly positively correlated with SWC and TP(P < 0.05). Root-sprouting buds are only significantly negatively correlated with TP(P < 0.05). Therefore, our research shows that rhizome buds are more important in ND meadow habitats, tiller buds are more important in LD meadow habitats, and root-sprouting buds are more important in MD meadows. In addition, rhizome buds have been proved to be suitable for survival in a weak acid environment.

As an important soil carbon pool in Qinghai-Tibet Plateau (QTP), alpine peatland are extremely sensitive to global change. Duration of drainage and water table drawdown accelerate peatland degradation due to the soil changed from anaerobic condition to aerobic condition, which may even worsen under climate warming. Hence, the objective of our research was to evaluate the effect of drainage on microbial characteristics, greenhouse gas (GHG) emissions and their influencing factors, and further analyze whether the the variability of GHG emissions increases with warming. The results showed that the influence of water table drawdown on microbial communities were greater than that of duration of drainage. Both the fungal and prokaryotic community compositions varied with water table gradient, and soil microbiota may served as a biomarker to analyze the differences in GHG emissions among three different water table treatments. Intriguingly, the GHG emission decreased with the increase of drainage age, while water table drawdown decreased the emissions of CO2 and CH4, and increased the emission of N2O. In addition, high temperature increased CO2 by 75% and N2O by 42%, but not significantly decreased the CH4 emission rates. Structural equation modeling showed that microbe was the primary factor affecting GHG emissions from drained peatlands, especially prokaryotes. In all, this study indicate water table has a greater effect on GHG emissions than duration of drainage, and the variability of GHG emissions increases with warming.

As an important soil carbon pool in Qinghai-Tibet Plateau (QTP), alpine peatland are extremely sensitive to global change. Duration of drainage and water table drawdown accelerate peatland degradation as the soils are no longer protected by anaerobic condition, which may worsen under climate warming. Hence, the purpose of our study was to evaluate the effect of drainage on microbial characteristics, greenhouse gas (GHG) emissions and their influencing factors, and further analyze whether the the variability of GHG emissions increases with warming. The results showed that the influence of water table drawdown on microbial communities were greater than that of duration of drainage. Both the fungal and prokaryotic community compositions varied with water table gradient, and soil microbiota may served as a biomarker to analyze the differences in GHG emissions among three different water table treatments. Intriguingly, the GHG emission decreased with the increase of drainage age, while water table drawdown reduced the CO2 and CH4 emission rates, and increased N2O emission rates. In addition, high temperature increased CO2 by 75% and N2O by 42%, but not significantly decreased the CH4 emission rates. Structural equation modeling showed that microbe was the primary factor affecting GHG emissions from drained peatlands, especially prokaryotes. Overall, our results indicate that water table has a greater impact on GHG emissions than duration of drainage, and the variability of GHG emissions increases with warming.

As an important soil carbon pool in Qinghai-Tibet Plateau (QTP), alpine peatland are extremely sensitive to global change. Duration of drainage and water table drawdown lead to rapid soil degradation and C losses, and this may worsen under warming as the soils are no longer protected by anaerobic conditions. Hence, the objective of this study was to assess the effect of drainage on microbial characteristics, greenhouse gas (GHG) emissions and their influencing factors, and further analyze whether the the variability of GHG emissions increases with warming. The results showed that the influence of water table drawdown on microbial community structure was greater than that of duration of drainage. Both the fungal and prokaryotic community compositions varied with water table gradient, and soil microbiota may served as a biomarker to analyze the differences in GHG emissions among three different water table treatments. Intriguingly, the GHG emission decreased with the increase of drainage age, while water table drawdown reduced the CO2 and CH4 emission rates, and increased N2O emission rates. In addition, high temperature increased CO2 by 75% and N2O by 42%, but not significantly decreased the CH4 emission rates. Structural equation modeling suggested that microbial community composition was the primary factor affecting GHG emissions from drained peatlands, especially prokaryotes. Overall, our results indicate that water table plays a more important role in GHG emissions than duration of drainage, and the variability of GHG emissions increases with warming.