湿地
生物圈
环境科学
甲烷
甲烷排放
全球变暖
气候变化
大气科学
温室气体
全球变化
偏移量(计算机科学)
气候学
全球温度
耦合模型比对项目
约束(计算机辅助设计)
气候模式
生态系统
热带
代表性浓度途径
大气甲烷
陆地生态系统
辐射压力
气候敏感性
作者
Zhen Zhang,Benjamin Poulter,Zhenxuan Wang,Lori Bruhwiler,Josep G. Canadell,Nicola Gedney,Akihiko Ito,Robert B. Jackson,Joe R. Melton,Changhui Peng,William J. Riley,Marielle Saunois,Andy Wiltshire,Qian Zhang,Qing Zhu,Qiuan Zhu,Xin Li
标识
DOI:10.1038/s41561-026-01987-2
摘要
Future methane (CH4) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH4 emissions (eCH4) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH4 yr−1 increase in eCH4. We also identify an emergent relationship between contemporary temperature dependence and projected eCH4. When constrained by 163 site-year eddy-covariance measurements of eCH4, we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic eCH4 at the 2020 level, comparable to the reductions committed under the Global Methane Pledge. However, the constraint is dominated by mid- and high-latitude observations, with limited tropical coverage, and uncertainties in projected wetland inundation contribute substantially to uncertainty in eCH4. Our findings reduce the uncertainty in projected wetland methane–climate feedback and highlight its potential impacts on methane mitigation efforts to slow global warming. Enhanced future methane emissions from global wetlands under warming could substantially offset the emissions reduction goals of the Global Methane Pledge, according to ensemble simulations from terrestrial biosphere models.
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