Dissolved organic compounds in shale gas extraction flowback water as principal disturbance factors of soil nitrogen dynamics

Carbon availability and microbial activity manipulate the temperature sensitivity of anaerobic degradation in a paddy soil profile

Soil contains a substantial amount of organic carbon, and its feedback to global warming has garnered widespread attention due to its potential to modulate atmospheric carbon (C) storage. Temperature sensitivity (Q10) has been widely utilized as a measure of the temperature-induced enhancement in soil organic carbon (SOC) decomposition. It is currently rare to incorporate Q10 of CO2 and CH4 into the study of waterlogged soil profiles and explore the possibility of artificially reducing Q10 in rice fields. To investigate the key drivers of Q10, we collected 0-1 m paddy soil profiles, and stratified the soil for submerged anaerobic incubation. The relationship between SOC availability, microbial activity, and the Q10 of CO2 and CH4 emissions was examined. Our findings indicate that as the soil layer deepens, soil C availability and microbial activity declined, and the Q10 of anaerobic degradation increased. Warming increased C availability and microbial activity, accompanied by weakened temperature sensitivity. The Q10 of CO2 correlated strongly with soil resistant C components, while the Q10 of CH4 was significantly influenced by labile substrates. The temperature sensitivity of CH4 (Q10 = 3.99) was higher than CO2 emissions (Q10 = 1.78), indicating the need for greater attention of CH4 in predicting warming's impact on anaerobic degradation in rice fields. Comprehensively assessing CO2 and CH4 emissions, the 20-40 cm subsurface soil is the most temperature-sensitive. Despite being a high-risk area for C loss and CH4 emissions, management of this soil layer in agriculture has the potential to reduce the threat of global warming. This study underscores the importance of subsurface soil in paddy fields, advocating greater attention in scientific simulations and predictions of climate change.