Abstract
Compelling evidence has shown that wetland methane emissions are more temperature dependent than carbon dioxide emissions across diverse hydrologic conditions. However, the availability of carbon substrates, which ultimately determines microbial carbon metabolism, has not been adequately accounted for. By combining a global database and a continental-scale experimental study, we showed that differences in the temperature dependence of global wetland methane and carbon dioxide emissions (EM/C) were dependent on soil carbon-to-nitrogen stoichiometry. This can be explained mainly by the positive relationship between soil organic matter decomposability and EM/C. Our study indicates that only 23% of global wetlands will decrease methane relative to carbon dioxide emissions under future warming scenarios when soil organic matter decomposability is considered. Our findings highlight the importance of incorporating soil organic matter biodegradability into model predictions of wetland carbon–climate feedback.
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Data availability
All data needed to evaluate the conclusions are available at Zenodo (https://zenodo.org/records/10044208). The GeoChip data are available in the repository Figshare (https://doi.org/10.6084/m9.figshare.9746303). Source data are provided with this paper.
Code availability
The code used in this study is archived in Supplementary Code 1 and is available at Zenodo (https://zenodo.org/records/10044208).
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Acknowledgements
The authors received funding from Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28030102 to Y.L.), National Natural Scientific Foundation of China (92251305 to M.N., 41622104 to Y.L.), Innovation Program of the Institute of Soil Science (ISSASIP2201 to Y.L.) and Youth Innovation Promotion Association of the Chinese Academy of Sciences (2016284 to Y.L.).
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Y.L., H.H., M.N., J.C. and J. Zhang conceptualized the research project. H.H., M.N., M.D.-B., H.N., F.Z., J. Zhou and Y.L. developed the methodology. H.H., J.C., M.D.-B., H.N., W.H., X.S., H.L. and Y.L. were responsible for data collection and analysis. Y.L., J. Zhang, X.C. and B.S. provided supervision throughout the project. Y.L., H.H., J.C., M.N., D.H. and T.W.C. wrote the original draft. H.H., J.C., F.Z., M.N., D.H., H.L., M.D.-B., H.N., W.H., J. Zhou, X.S., X.C., B.S., J. Zhang, T.W.C. and Y.L. contributed to the review and editing process.
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Extended data
Extended Data Fig. 1 Geographical distribution of the sites in the global database (a) and frequency distribution of carbon emission observations at the site level (b).
In panel a, there might be overlaps among these sites. The size of the circle indicates the number of observations.
Extended Data Fig. 2 Temperature dependence of CO2 (EC) and CH4 (EM) emissions on a global scale.
a, The temperature dependence of the greenhouse gas (GHG) emissions was characterized using the linear mixed effects (LME) model after fitting the Boltzmann-Arrhenius function to the data of the GHG emissions and the standardized temperature (Methods). b, The dashed lines show the average.
Extended Data Fig. 3 Temperature dependence of the CH4:CO2 emission ratio (EM:C) at different water table depth intervals and soil C:N intervals.
The temperature dependence was characterized using the linear mixed effects (LME) model after fitting the Boltzmann-Arrhenius function to the data of the CH4:CO2 emission ratio and the standardized temperature (Methods). Different soil C:N intervals were classified using the results of the sliding window-LME model. Different water table depth intervals are classified according to the results of Chen et al. (ref. 3, 10.1038/s41558-021-01108-4).
Extended Data Fig. 4 Geographical distribution of the sites (a) and sampling strategy (b) in the incubation experiment.
Samples were taken from 39 paddy soil sites located in 13 regions of China. The numbers in parentheses represent the mean annual air temperature (°C) in the sampling region. At each site, 11 nested samples were collected at distances of 1, 6, 16, 36 and 76 m. CC = Changchun; CT = Changting; FQ = Fengqiu; HK = Haikou; HL = Hailun; HY = Hengyang; JO = Jian’ou; LA = Lin’an; OM = organic matter; QX = Qingxin; QZ = Quzhou; SY = Shenyang; TN = total nitrogen; YY = Yuanyang; ZX = Zixi.
Extended Data Fig. 5 Linear regression analysis between the temperature dependences of CH4 emissions (EM) and CO2 emissions (EC) with soil organic matter decomposability in incubation experiments.
The Ea of SOM decomposition represents the apparent activation energy of soil organic matter decomposition. DOC, dissolved organic carbon; SOC, soil organic carbon. Error bands are 95% confidence intervals of the regression lines.
Extended Data Fig. 6 The distribution of the difference in the temperature dependence of CH4 and CO2 emissions (EM:C), soil C:N, water table depth, and mean annual temperature in different climate zones.
a, EM:C distribution in different climate zones. The climatic zones are classified by the Köppen climate classification. A, B, C, D, and E represent tropical, arid, temperate, cold, and polar climates, respectively. Centre lines are medians, and diamonds represent the averages. Box limits are upper and lower quartiles. whiskers are 1.5× the interquartile ranges. The numbers in brackets represent wetland area (km2). b, Relative area of wetlands with positive and negative EM:C values. C, The distribution of soil, water table depth, and mean annual temperature of wetlands in different climate zones. The red dotted lines are the global mean values.
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Including (1) the dataset of meta-analysis, (2) the detail information of the soil samples and (3) the exact value of each point in the global map.
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Including code for the machine-learning and the linear mixed-effects models.
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Hu, H., Chen, J., Zhou, F. et al. Relative increases in CH4 and CO2 emissions from wetlands under global warming dependent on soil carbon substrates. Nat. Geosci. 17, 26–31 (2024). https://doi.org/10.1038/s41561-023-01345-6
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DOI: https://doi.org/10.1038/s41561-023-01345-6
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