
doi: 10.1029/2024ef005698
AbstractGreen manure (GM) enhances the ecological services in agricultural ecosystems, including soil health and carbon sequestration. However, its effect on regional methane (CH4) emissions from paddy fields is unclear. Here we clarify the impacts of GM rotation by combining process‐based modeling with microbial gene abundance information and coordinated distributed observations at 14 sites in southern China. We found that GM management, including application rate and rotation year, mainly affects CH4 emissions in GM‐rice systems by impacting soil biotic factors, which explain 78.4% of the variation (p < 0.001). The most influential factor is the ratio of soil CH4 production to oxidation gene abundances (R2 = 0.510; p < 0.001), which decreases with GM rotation year due to increased activity of methane‐oxidizing soil microbes (p < 0.001), indicating that CH4 emissions from GM‐rice systems decrease with increased GM rotation year. By incorporating these microbial mechanisms as quantitative parameters in process‐based model, we project that approximately 76% of the paddy rice areas in southern China, which have relatively low GM biomass and baseline CH4 emissions, can achieve reductions in CH4 emissions through nearly 15 years of GM crop rotation. This study indicates that CH4 emissions from GM‐rice rotations with appropriate GM application rate over the long term will not significantly increase, resolving the contradictions in previous research.
[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy, [SDE] Environmental Sciences, [SDE.MCG] Environmental Sciences/Global Changes, rotation year, paddy soil, green manure, methane, process-based modeling
[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy, [SDE] Environmental Sciences, [SDE.MCG] Environmental Sciences/Global Changes, rotation year, paddy soil, green manure, methane, process-based modeling
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
