Asymmetric responses of terrestrial C:N:P stoichiometry to precipitation change. Issue 8 (7th June 2021) - Sun, Yuan; Wang, Cuiting; Chen, Han Y. H.; Luo, Xuesong; Qiu, Nianwei; Ruan, Honghua
Abstract: Aim: The aim was to test whether the responses of C:N:P stoichiometry in plant–soil–microorganism systems to precipitation changes support the prediction of the double asymmetry model, which predicts ecological processes (i.e. aboveground productivity, soil microbial community, and soil respiration) are more sensitive to increased precipitation (R+) than decreased precipitation (R−) under normal precipitation changes, whereas more sensitive to R− than R+ under extreme precipitation changes. Location: Global. Time period: 1999–2020. Major taxa studied: Plants, soils, and soil microorganisms. Methods: We performed a global meta‐analysis of 848 observations (587 R− and 261 R+ manipulations) from 160 studies, which tested the effects of precipitation changes on C:N:P across plants, soils, and soil microorganisms. The data encompassed broad variations in ecosystems, climate, precipitation intensity, and experimental duration. Results: We revealed that the C:N and C:P ratios of different ecosystem compartments were more sensitive to moderate R+ rather than moderate R−, whereas they exhibited a higher response to extreme R− rather than extreme R+, which supported the prediction of the double asymmetry model. Moreover, such responses were more pronounced under higher precipitation intensities and longer experimental duration. The effects of precipitation changes on the C:N:P stoichiometry of plants, soils, and soil microorganisms were consistent across ecosystem types (i.e. forests and grasslands) and associated background climates (i.e. mean annual temperature and precipitation). Main conclusions: Our findings provide the first evidence of the asymmetric responses of C:N:P stoichiometry in above‐ and belowground systems to precipitation change. These results extend the double asymmetric model and improve our understanding of C and N cycling, as well as facilitate the prediction of ecosystem responses to precipitation changes.