Haoyu Qian

Rice paddies account for approximately 9% of human‐induced methane (CH₄) emissions. Nitrogen (N) fertilization affects CH₄ emissions from paddy soils through several mechanisms, leading to conflicting results in field experiments. The primary drivers of these N‐related effects remain unclear and the contribution of N fertilization to CH₄ emissions from the rice paddies has not yet been quantified for global area. This uncertainty contributes to significant challenges in projecting global CH₄ emissions and hinders the development of effective local mitigation strategies. Here, we show through a meta‐analysis and experiments that the impact of N fertilization on CH₄ emissions from rice paddies can be largely predicted by soil pH. Specifically, N fertilization stimulates CH₄ emissions most strongly in acidic soils by accelerating organic matter decomposition and increasing the activities of methanogens. Accounting for the interactions between soil pH and N fertilization, we estimate that N fertilization has raised current area‐scaled and yield‐scaled CH₄ emissions across the total global paddy area by 52% and 8.2%, respectively. Our results emphasize the importance of alleviating soil acidification and sound N management practices to mitigate global warming.

Despite growing interest in controlled-release N fertilizers (CRNFs) because of their potential for enhancing nitrogen use efficiency (NUE) and economic returns, their comprehensive impact on machine-transplanted rice remains to be understudied. To address this gap, here, we present a two-year field experiment that assessed the impact of CRNF using mechanical deep placement fertilization (DPF) on rice cultivation. The study involved three CRNF types (bulk blending fertilizer (BBF), polymer-coated urea (PCU), and sulfur-coated urea (SCU)) and two fertilization methods (DPF and broadcast application), with a high-yield split fertilization of urea as a control (CK). The results showed that DPF, especially with SCU, greatly enhanced soil NH₄⁺-N concentrations, NUE, rice yield, and economic benefits compared to broadcast application. BBF consistently exhibited superior NUE and notable economic benefits, regardless of the application method used. Conversely, single-time application of PCU was less favorable for rice growth. In conclusion, for optimal economic benefits and NUE, DPF combined with single-time application of SCU is recommended. However, if deep application is not feasible and only broadcasting is possible in rice cultivation, BBF emerges as the ideal choice for both high NUE and significant economic returns. This research offers insights for improved nitrogen management in machine-transplanted rice, effectively optimizing yield, NUE, and profitability.

Aquaculture ponds are an important artificial aquatic system for global food fish production but also are a hot spot of greenhouse gas (GHG) emissions. The GHG mitigation strategy and the underlying mechanism for aquaculture ponds are still poorly understood. In this study, we conducted a 2 year field experiment to determine the effects of planting high-stalk rice (an artificially bred emergent plant for ponds) on GHG emissions from aquaculture ponds. Our results showed that planting high-stalk rice reduced CH₄ emission by 64.4% and N₂O emission by 76.2% over 2 years. Planting high-stalk rice significantly increased the content of O₂ and the abundance of pmoA in the sediment, thus prompting CH₄ oxidation in the ponds. The reduction of N₂O emission from ponds was attributed to the decreased inorganic nitrogen, amoA-B and nirS in the sediment induced by rice. Furthermore, high-stalk rice culture in the pond increased shrimp yields and gained rice yields, resulting in a significant reduction of yield-scaled global warming potential. Our findings suggest that breeding appropriate emergent aquatic plants is a potential pathway to mitigate GHG emission from aquaculture ponds with more food yields and economic benefits.

Global warming is expected to affect methane (CH₄) emissions from rice paddies, one of the largest human-induced sources of this potent greenhouse gas. However, the large variability in warming impacts on CH₄ emissions makes it difficult to extrapolate the experimental results over large regions. Here, we show, through meta-analysis and multi-site warming experiments using the free air temperature increase facility, that warming stimulates CH₄ emissions most strongly at background air temperatures during the flooded stage of ∼26 °C, with smaller responses of CH₄ emissions to warming at lower and higher temperatures. This pattern can be explained by divergent warming responses of plant growth, methanogens, and methanotrophs. The effects of warming on rice biomass decreased with the background air temperature. Warming increased the abundance of methanogens more strongly at the medium air temperature site than the low and high air temperature sites. In contrast, the effects of warming on the abundance of methanotrophs were similar across the three temperature sites. We estimate that 1 °C warming will increase CH₄ emissions from paddies in China by 12.6%─substantially higher than the estimates obtained from leading ecosystem models. Our findings challenge model assumptions and suggest that the estimates of future paddy CH₄ emissions need to consider both plant and microbial responses to warming.