Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P. & Zhuang, Q. The global methane budget 2000–2017. Earth Syst. Sci. Data 12, 1561–1623 (2020).
Tian, H. et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 586, 248–256 (2020).
Qian, H. et al. Greenhouse gas emissions and mitigation in rice agriculture. Nat. Rev. Earth Environ. 4, 716–732 (2023).
United Nations Environment Programme & Climate and Clean Air Coalition Global Methane Assessment: Benefits and Costs of Mitigating Methane Emissions (United Nations Environment Programme, 2021).
Lessmann, M., Ros, G. H., Young, M. D. & de Vries, W. Global variation in soil carbon sequestration potential through improved cropland management. Glob. Change Biol. 28, 1162–1177 (2022).
Tian, H. et al. The terrestrial biosphere at a net source of greenhouse gases to the atmosphere. Nature 531, 225–228 (2016).
Carlson, K. M. et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Change 7, 63–68 (2017).
Zhang, B. et al. Methane emissions from global rice fields: magnitude, spatiotemporal patterns, and environmental controls. Glob. Biogeochem. Cycles 30, 1246–1263 (2016).
Bo, Y. et al. Global benefits of non-continuous flooding to reduce greenhouse gases and irrigation water use without rice yield penalty. Glob. Change Biol. 28, 3636–3650 (2022).
Liu, Y. et al. Rice paddy soils are a quantitatively important carbon store according to a global synthesis. Commun. Earth Environ. 2, 154 (2021).
Zhang, J. et al. Balancing non-CO2 GHG emissions and soil carbon change in U.S. rice paddies: a retrospective meta-analysis and agricultural modeling study. AGU Adv. 5, e2023AV001052 (2024).
Liu, B. 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).
Cai, S. et al. Optimal nitrogen rate strategy for sustainable rice production in China. Nature 615, 73–79 (2023).
Bondeau, A. et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob. Change Biol. 13, 679–706 (2007).
McDermid, S. S., Mearns, L. O. & Ruane, A. C. Representing agriculture in Earth system models: approaches and priorities for development. J. Adv. Model. Earth Syst. 9, 2230–2265 (2017).
Prasad, A. M., Iverson, L. R. & Liaw, A. Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9, 181–199 (2006).
Cutler, D. R. et al. Random forests for classification in ecology. Ecology 88, 2783–2792 (2007).
Climate Change 2023: Synthesis Report (eds Lee, H. et al.) 35–115 (IPCC, 2023).
Chen, Z., Balasus, N., Lin, H., Nesser, H. & Jacob, D. J. African rice cultivation linked to rising methane. Nat. Clim. Change 14, 148–151 (2024).
Zhang, Q. et al. Spatiotemporal patterns of paddy rice production change in China during 1980–2018. Resour. Sci. 44, 687–700 (2022).
Song, H. J. et al. Dilemma of organic matter input to mitigate climate impact of rice paddies. Soil Biol. Biochem. 209, 109873 (2025).
Gao, B. et al. Chinese cropping systems are a net source of greenhouse gases despite soil carbon sequestration. Glob. Change Biol. https://doi.org/10.1111/gcb.14425 (2018).
Liu, L. L. & Greaver, T. L. A review of nitrogen enrichment effects on three biogenic GHGs: the CO2 sink may be largely offset by stimulated N2O and CH4 emission. Ecol. Lett. 12, 1103–1117 (2009).
Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).
Tian, H. et al. History of anthropogenic nitrogen inputs (HaNi) to the terrestrial biosphere: a 5 arcmin resolution annual dataset from 1860 to 2019. Earth Syst. Sci. Data 14, 4551–4568 (2022).
Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedback to climate change. Nature 440, 165–173 (2006).
Runkle, B. R. et al. Methane emission reductions from the alternate wetting and drying of rice fields detected using the eddy covariance method. Environ. Sci. Technol. 53, 671–681 (2018).
Smith, P. Soil carbon sequestration and biochar as negative emission technologies. Glob. Change Biol. 22, 1315–1324 (2016).
Xia, L. et al. Integrated biochar solutions can achieve carbon-neutral staple crop production. Nat. Food 4, 236–246 (2023).
Grohs, M. et al. Seasonal and annual methane and nitrous oxide emissions affected by tillage and cover crops in flood-irrigated rice. Agric. Ecosyst. Environ. 359, 108747 (2024).
Guo, F., Dai, F., Gong, P. & Zhou, Y. CHN-CH4: a gridded (0.1° × 0.1°) anthropogenic methane emission inventory of China from 1990 to 2020. Earth Syst. Sci. Data 17, 4799–4819 (2025).
Tian, H. Q. et al. The Dynamic Land Ecosystem Model (DLEM) for simulating terrestrial processes and interactions in the context of multifactor global change. Acta Geogr. Sci. 65, 1027–1047 (2010).
Zhang, J. T., Tian, H. Q., Yang, J. & Pan, S. Improving representation of crop growth and yield in the Dynamic Land Ecosystem Model and its application to China. J. Adv. Model. Earth Syst. 10, 1680–1707 (2018).
You, Y. et al. Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: toward a unified modeling framework. Agric. For. Meteorol. 325, 109144 (2022).
Portmann, F. T., Siebert, S. & Doll, P. MIRCA2000—global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling. Glob. Biogeochem. Cycles 24, GB1011 (2010).
Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).
Li, X., Tian, H., Lu, C. & Pan, S. Four-century history of land transformation by humans in the United States (1630–2020): annual and 1 km grid data for the HIStory of LAND changes (HISLAND-US). Earth Syst. Sci. Data 15, 1005–1035 (2023).
Lu, C. Q. & Tian, H. Q. Half-degree gridded nitrogen and phosphorus fertilizer use for global agriculture production during 1900-2013. PANGAEA https://doi.org/10.1594/PANGAEA.863323 (2016).
Thomas, D., Iris, J., Fernando, S. C. & Steven, M. Fertilizer application rate maps per crop and year. figshare https://doi.org/10.6084/m9.figshare.25435432.v3 (2024).
Zhang, B. W. et al. Manure nitrogen production and application in cropland and rangeland during 1860 – 2014: a 5-minute gridded global data set for Earth system modeling. PANGAEA https://doi.org/10.1594/PANGAEA.871980 (2017).
Porwollik, V., Rolinski, S. & Müller, C. A global gridded data set on tillage (V. 1.1). GFZ Data Services https://doi.org/10.5880/PIK.2019.009 (2019).
Brown, J. F. & Pervez, M. S. Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture. Agric. Syst. 127, 28–40 (2014).
Pervez, M. S. & Brown, J. F. Mapping irrigated lands at 250-m scale by merging MODIS data and national agricultural statistics. Remote Sens. 2, 2388–2412 (2010).
Batjes, N. H. ISRIC-WISE Harmonized Global Soil Profile Dataset (ISRIC-World Soil Information, 2008).
Iizumi, T. Global dataset of historical yields v1.2 and v1.3 aligned version. PANGAEA https://doi.org/10.1594/PANGAEA.909132 (2019).
Eyring, V. et al. Overview of IGAC/SPARC Chemistry-Climate Model Initiative (CCMI) community simulations in support of upcoming ozone and climate assessments. SPARC Newsl. 40, 48–66 (2013).
Sheffield, J., Goteti, G. & Wood, E. F. Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J. Climate 19, 3088–3111 (2006).
Le Quéré, C. et al. Global carbon budget 2018. Earth Syst. Sci. Data 10, 2141–2194 (2018).
Lamarque, J. F. et al. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): overview and description of models, simulations and climate diagnostics. Geosci. Model Dev. 6, 179–206 (2013).
ESRI. ARCMAP. ArcGIS. 10.2 (Environmental Systems Research Institute, 2013).
Zhang, J. T. CH4 emission dataset for the manuscript “Rising greenhouse gas emissions from global rice paddies and mitigation strategies”. figshare https://doi.org/10.6084/m9.figshare.28180565.v2 (2025).
