Abstract
Returning organic nutrient sources (for example, straw and manure) to rice fields is inevitable for coupling crop–livestock production. However, an accurate estimate of net carbon (C) emissions and strategies to mitigate the abundant methane (CH4) emission from rice fields supplied with organic sources remain unclear. Here, using machine learning and a global dataset, we scaled the field findings up to worldwide rice fields to reconcile rice yields and net C emissions. An optimal organic nitrogen (N) management was developed considering total N input, type of organic N source and organic N proportion. A combination of optimal organic N management with intermittent flooding achieved a 21% reduction in net global warming potential and a 9% rise in global rice production compared with the business-as-usual scenario. Our study provides a solution for recycling organic N sources towards a more productive, carbon-neutral and sustainable rice–livestock production system on a global scale.
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Data availability
The data used in this study are publicly available: climatic factors from WorldClim 2 (https://www.worldclim.org/), soil properties from Harmonized World Soil Database1.2 (https://www.fao.org/soils-portal/en/) and fertilization conditions from EARTHSTAT (http://www.earthstat.org/). All data in this study are uploaded at https://doi.org/10.6084/m9.figshare.25193996. Source data are provided with this paper.
Code availability
The codes used in this study are available, and all codes in this study are uploaded at https://doi.org/10.6084/m9.figshare.25193996.
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Acknowledgements
This work is funded by the National Key Research and Development Program of China (2023YFE0105000; 2023YFD1900605), National Natural Science Foundation of China (NSFC; grant number U20A2047), Innovation Research 2035 Pilot Plan of Southwest University (SWU-XDZD22001) and the China Postdoctoral Science Foundation (2023M733786).
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Xinping Chen and Z.L. designed the work. B.L., C.G., J.X., and Q.Z. performed the data extraction and analysis. B.L. wrote the first draft of the paper. All co-authors reviewed and revised the paper.
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Extended data
Extended Data Fig. 1 Changes in rice yield (a, e), CH4 emission (b, f), N2O emission (c, g), and SOC (d, h) under SN (a-d) and AN (e-h).
The abbreviation SN stands for substitution of synthetic N with organic N source and AN represents addition of extra organic N source to synthetic N. Short, medium, and long experimental duration refer to the treatment conducted at ≤3 years, 4–10 years, >10 years, respectively. In the forest plots, points stand for mean effect sizes and error bars are 95% calculate confidence intervals. Numbers of observations and literature (in parentheses) are listed on the right side of each individual figure.
Extended Data Fig. 2 Relationships of effect sizes of rice yield (a-h), CH4 emission (i-p) against environmental factors, respectively.
The abbreviation SN (orange) stands for substitution of synthetic N with organic N source and AN (blue) represents addition of extra organic N source to synthetic N. Dot sizes represent weights of effect sizes in individual studies for the meta-analysis. The solid lines or curves are average slopes and shaded bands refer to 95% confidence intervals. Statistical significance was obtained with a two-sided Student’s t-test. n, number of observations.
Extended Data Fig. 3 Relationships of effect sizes of N2O emission (a-h), SOC (i-o) against environmental factors, respectively.
The abbreviation SN (orange) stands for substitution of synthetic N with organic N source and AN (blue) represents addition of extra organic N source to synthetic N. Dot sizes represent weights of effect sizes in individual studies for the meta-analysis. The solid lines or curves are average slopes and shaded bands refer to 95% confidence intervals. Statistical significance was obtained with a two-sided Student’s t-test. n, number of observations.
Extended Data Fig. 4
PRISMA flow diagram to show the publications selection in the meta-analysis.
Extended Data Fig. 5 The distribution of effect sizes for the mean response ratio of rice yield (a, e), CH4 emission (b, f), N2O emission (c, g), and SOC (d, h) in the meta-analysis.
The shaded region refers to P < 0.10 and the white region represents P > 0.10. a-d, AN; e-h, SN. The abbreviation SN stands for substitution of synthetic N with organic N fertilizer and AN represents addition of organic N fertilizer to synthetic N.
Extended Data Fig. 6 Verification of simulated effect sizes of rice yield (a, e), CH4 emission (b, f), N2O emission (c, g), and SOC (d, h) in the Random Forest model against observed data.
a–d, AN; e–h, SN. The abbreviation SN stands for substitution of synthetic N with organic N source and AN represents addition of extra organic N source to synthetic N. Statistical significance was obtained with a two-sided Student’s t-test. The slope of dashed line = 1.
Extended Data Fig. 7 Verification of simulated rice yield (a, e, i), CH4 emission (b, f, j), N2O emission (c, g, k), and SOC sequestration (d, h, l) in the Random Forest model against the observed data.
a–d, BAU management method; e–h, CF; i–l, IF. BAU, business as usual; CF, conventional flooding; IF, intermittent flooding. Statistical significance was obtained with a two-sided Student’s t-test. The slope of dashed line = 1.
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Liu, B., Guo, C., Xu, J. et al. Co-benefits for net carbon emissions and rice yields through improved management of organic nitrogen and water. Nat Food 5, 241–250 (2024). https://doi.org/10.1038/s43016-024-00940-z
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DOI: https://doi.org/10.1038/s43016-024-00940-z
