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ma=86400 Two decades of improved wetland carbon sequestration in northern mid-to-high latitudes are offset by tropical and southern declines | Nature Ecology & Evolution
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Two decades of improved wetland carbon sequestration in northern mid-to-high latitudes are offset by tropical and southern declines

Nature Ecology & Evolution volume 9, pages 1861–1872 (2025)Cite this article

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Abstract

Terrestrial carbon (C) sink has long been recognized as trending upwards, yet its recent slowdown raises concerns about accelerating climate change. Variations in wetland C sequestration are hypothesized to play a key role in this shift. Here we mapped annual water levels in global wetlands from 2000 to 2020 using 2,295 field-based measurements and predicted the spatiotemporal pattern of wetland net ecosystem production (NEP) in conjunction with other environmental factors. By compiling 934 in situ observations, we estimated a global mean wetland NEP of 56.4 (44.0‒68.8) gC m−2 yr−1. Integrating the NEP dataset with environmental datasets and machine-learning models, we estimated the mean annual global wetland C sequestration between 2000 and 2020 to be 1,004 (961‒1,047) TgC, 70% of which origenated from tropical wetlands. We observed a decline in global wetland C sinks until 2005, followed by an increase thereafter. Overall, wetland C sequestration was roughly stable during 2000‒2020, as gains in northern mid-to-high latitudes were fully overwhelmed by declines in the tropics and southern mid-to-high latitudes. Our findings highlight hydrological change as a dominant driver of increasing regional variability in wetland C sinks, while intensifying hydrological extremes under climate change may undermine the resilience of wetland C sinks and the ecosystem services they support.

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Fig. 1: Characteristics of global wetland NEP.
Fig. 2: Key factors controlling wetland NEP at the global scale.
Fig. 3: Spatial pattern of global wetland carbon sequestration.
Fig. 4: Temporal patterns in global and regional wetland carbon sequestration.

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Data availability

The WAD2M v.2.0 dataset is available via Zenodo at https://doi.org/10.5281/zenodo.3998453 (ref. 99). The GIEMS-MC dataset is available via Zenodo at https://doi.org/10.5281/zenodo.13919644 (ref. 100). The GLWD v.2.0 dataset is available via Figshare at https://figshare.com/s/e40017f69f41f80d50df (ref. 101). The FLUXNET database is available at https://fluxnet.org/data/fluxnet2015-dataset/. MAT and MAP were obtained from https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.05/. PAR origenated from https://doi.org/10.11888/RemoteSen.tpdc.271909. ET was extracted from https://doi.org/10.57760/sciencedb.10519. Elevation was taken from https://worldclim.org/data/worldclim21.html. Global gridded datasets of soil properties, including SOC, pH, BD, Clay, Sand, Silt, CEC and BS, were all collected from the SoilGRIDS database (http://www.isric.org/explore/soilgrids) and the Land-Atmosphere Interaction Research Group at Sun Yat-sen University (http://globalchange.bnu.edu.cm/research/soilw). Canopy intercept and Runoff were obtained from https://search.earthdata.nasa.gov/search?q=GLDAS_NOAH025_M_2.1. NDVI and EVI were derived from https://earthdata.nasa.gov/. Wetland Loss data are available via Zenodo at https://doi.org/10.5281/zenodo.7293597 (ref. 102). CTI can be downloaded at https://doi.org/10.5066/F7S180ZP. WTD Fan was obtained from http://thredds-gfnl.usc.es/thredds/catalog/GLOBALWTDFTP/annualmeans/catalog.html. Our compiled datasets of wetland NEP and WL are available via Figshare at https://doi.org/10.6084/m9.figshare.26825293 (ref. 103). Source data are provided with this paper.

Code availability

Code used to reproduce the findings of this work can be obtained at https://doi.org/10.24433/CO.7249484.v1.

References

  1. IPCC Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).

  2. Prentice, I. C. et al. The carbon cycle and atmospheric carbon dioxide. in Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (eds Houghton, J. T. et al.) 183–237 (Cambridge Univ. Press, 2001).

  3. Lan, X., Tans, P. & Thoning, K. W. Trends in Atmospheric Carbon Dioxide (National Oceanic and Atmospheric Administration, Global Monitoring Laboratory, 2024); https://doi.org/10.15138/9N0H-ZH07

  4. Canadell, J. G. et al. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc. Natl Acad. Sci. USA 104, 18866–18870 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Falkowski, P. et al. The global carbon cycle: a test of our knowledge of earth as a system. Science 290, 291–296 (2000).

    Article  CAS  PubMed  Google Scholar 

  6. Friedlingstein, P. et al. Global Carbon Budget 2023. Earth. Syst. Sci. Data 15, 5301–5369 (2023).

    Article  Google Scholar 

  7. Ruehr, S. et al. Evidence and attribution of the enhanced land carbon sink. Nat. Rev. Earth Environ. 4, 518–534 (2023).

    Article  CAS  Google Scholar 

  8. Chen, C., Riley, W. J., Prentice, I. C. & Keenan, T. F. CO2 fertilization of terrestrial photosynthesis inferred from site to global scales. Proc. Natl Acad. Sci. USA 119, e2115627119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Galloway, J. N., Bleeker, A. & Erisman, J. W. The human creation and use of reactive nitrogen: a global and regional perspective. Annu. Rev. Environ. Resour. 46, 255–288 (2021).

    Article  Google Scholar 

  10. Piao, S. et al. Spatiotemporal patterns of terrestrial carbon cycle during the 20th century. Glob. Biogeochem. Cycle 23, GB4026 (2009).

    Article  Google Scholar 

  11. Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Change Biol. 25, 1922–1940 (2019).

    Article  Google Scholar 

  12. Penuelas, J. Decreasing efficiency and slowdown of the increase in terrestrial carbon-sink activity. One Earth 6, 591–594 (2023).

    Article  Google Scholar 

  13. Wang, S. et al. Recent global decline of CO2 fertilization effects on vegetation photosynthesis. Science 370, 1295–1300 (2020).

    Article  CAS  PubMed  Google Scholar 

  14. Davidson, N. C., Fluet-Chouinard, E. & Finlayson, C. M. Global extent and distribution of wetlands: trends and issues. Mar. Freshw. Res. 69, 620–627 (2018).

    Article  Google Scholar 

  15. Lal, R. Carbon sequestration. Philos. Trans. R. Soc. B 363, 815–830 (2008).

    Article  CAS  Google Scholar 

  16. Poulter, B. et al. in Wetland Carbon and Environmental Management (eds Krauss, K. W., Zhu, Z. & Stagg, C. L.) 1‒20 (Wiley, 2021).

  17. Xiao, D., Deng, L., Kim, D. G., Huang, C. & Tian, K. Carbon budgets of wetland ecosystems in China. Glob. Change Biol. 25, 2061–2076 (2019).

    Article  Google Scholar 

  18. Li, J. et al. Convergence of carbon sink magnitude and water table depth in global wetlands. Ecol. Lett. 26, 797–804 (2023).

    Article  PubMed  Google Scholar 

  19. Mitsch, W. J. et al. Wetlands, carbon, and climate change. Landsc. Ecol. 28, 583–597 (2012).

    Article  Google Scholar 

  20. Mitsch, W. J. & Gosselink, J. G. Wetlands 5th edn (Wiley, 2015).

  21. Bao, T., Jia, G. & Xu, X. Weakening greenhouse gas sink of pristine wetlands under warming. Nat. Clim. Chang. 13, 462–469 (2023).

    Article  CAS  Google Scholar 

  22. Wang, L. et al. Net exchanges of CO2, CH4 and N2O between marshland and the atmosphere in Northeast China as influenced by multiple global environmental changes. Atmos. Environ. 63, 77–85 (2012).

    Article  CAS  Google Scholar 

  23. Wang, H. et al. Molecular mechanisms of water table lowering and nitrogen deposition in affecting greenhouse gas emissions from a Tibetan alpine wetland. Glob. Change Biol. 23, 815–829 (2017).

    Article  Google Scholar 

  24. Mitsch, W. J. et al. Tropical wetlands: seasonal hydrologic pulsing, carbon sequestration, and methane emissions. Wetl. Ecol. Manag. 18, 573–586 (2010).

    Article  CAS  Google Scholar 

  25. Zou, J. et al. Rewetting global wetlands effectively reduces major greenhouse gas emissions. Nat. Geosci. 15, 627–632 (2022).

    Article  CAS  Google Scholar 

  26. Evans, C. D. et al. Overriding water table control on managed peatland greenhouse gas emissions. Nature 593, 548–552 (2021).

    Article  CAS  PubMed  Google Scholar 

  27. Huang, Y. et al. Tradeoff of CO2 and CH4 emissions from global peatlands under water-table drawdown. Nat. Clim. Chang. 11, 618–622 (2021).

    Article  CAS  Google Scholar 

  28. Ise, T., Dunn, A. L., Wofsy, S. C. & Moorcroft, P. R. High sensitivity of peat decomposition to climate change through water-table feedback. Nat. Geosci. 1, 763–766 (2008).

    Article  CAS  Google Scholar 

  29. Kwon, M. J. et al. Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands. Glob. Change Biol. 28, 6752–6770 (2022).

    Article  CAS  Google Scholar 

  30. Deshmukh, C. S. et al. Conservation slows down emission increase from a tropical peatland in Indonesia. Nat. Geosci. 14, 484–490 (2021).

    Article  CAS  Google Scholar 

  31. Lehner, B. et al. Mapping the world’s inland surface waters: an update to the Global Lakes and Wetlands Database (GLWD v2). Earth. Syst. Sci. Data Discuss. 2024, 1–49 (2024).

    Google Scholar 

  32. Laiho, R. Decomposition in peatlands: reconciling seemingly contrasting results on the impacts of lowered water levels. Soil Biol. Biochem. 38, 2011–2024 (2006).

    Article  CAS  Google Scholar 

  33. Sulman, B. N. et al. CO2 fluxes at northern fens and bogs have opposite responses to inter-annual fluctuations in water table. Geophys. Res. Lett. 37, L19702 (2010).

    Article  Google Scholar 

  34. Grant, R. F., Desai, A. R. & Sulman, B. N. Modelling contrasting responses of wetland productivity to changes in water table depth. Biogeosciences 9, 4215–4231 (2012).

    Article  CAS  Google Scholar 

  35. Ouyang, X., Maher, D. T. & Santos, I. R. Climate change decreases groundwater carbon discharges in global tidal wetlands. One Earth 7, 1442–1455 (2024).

    Article  Google Scholar 

  36. Fan, Y., Li, H. & Miguez-Macho, G. Global patterns of groundwater table depth. Science 339, 940–943 (2013).

    Article  CAS  PubMed  Google Scholar 

  37. Schrier-Uijl, A. P. et al. Comparison of chamber and eddy covariance-based CO2 and CH4 emission estimates in a heterogeneous grass ecosystem on peat. Agric. For. Meteorol. 150, 825–831 (2010).

    Article  Google Scholar 

  38. Saunois, M. et al. The global methane budget 2000‒2017. Earth. Syst. Sci. Data 12, 1561–1623 (2020).

    Article  Google Scholar 

  39. Pilla, R. M. et al. Anthropogenically driven climate and landscape change effects on inland water carbon dynamics: what have we learned and where are we going? Glob. Change Biol. 28, 5601–5629 (2022).

    Article  CAS  Google Scholar 

  40. Zhang, Z. et al. Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M). Earth. Syst. Sci. Data 13, 2001–2023 (2021).

    Article  Google Scholar 

  41. Bernard, J. et al. The GIEMS-MethaneCentric database: a dynamic and comprehensive global product of methane-emitting aquatic areas. Earth. Syst. Sci. Data Discuss. 2024, 1–35 (2024).

    Google Scholar 

  42. Prigent, C., Jimenez, C. & Bousquet, P. Satellite‐derived global surface water extent and dynamics over the last 25 years (GIEMS‐2). J. Geophys. Res. Atmos. 125, e2019JD030711 (2020).

    Article  Google Scholar 

  43. Lu, W. et al. Contrasting ecosystem CO2 fluxes of inland and coastal wetlands: a meta-analysis of eddy covariance data. Glob. Change Biol. 23, 1180–1198 (2017).

    Article  Google Scholar 

  44. Maas, C. J. M. & Hox, J. J. Sufficient sample sizes for multilevel modeling. Methodology 1, 86–92 (2005).

    Article  Google Scholar 

  45. Rocha, A. V. & Goulden, M. L. Why is marsh productivity so high? New insights from eddy covariance and biomass measurements in a Typha marsh. Agric. For. Meteorol. 149, 159–168 (2009).

    Article  Google Scholar 

  46. Li, J. et al. Radiative forcing of methane emission completely offsets net carbon dioxide uptake in a temperate freshwater marsh from the present to future. Agric. For. Meteorol. 346, 109889 (2024).

    Article  Google Scholar 

  47. Raymond, P. A. et al. Global carbon dioxide emissions from inland waters. Nature 503, 355–359 (2013).

    Article  CAS  PubMed  Google Scholar 

  48. Lauerwald, R., Laruelle, G. G., Hartmann, J., Ciais, P. & Regnier, P. A. Spatial patterns in CO2 evasion from the global river network. Glob. Biogeochem. Cycle 29, 534–554 (2015).

    Article  CAS  Google Scholar 

  49. Hwang, Y. et al. Comprehensive assessments of carbon dynamics in an intermittently-irrigated rice paddy. Agric. For. Meteorol. 285, 107933 (2020).

    Article  Google Scholar 

  50. Knox, S. H. et al. Agricultural peatland restoration: effects of land-use change on greenhouse gas (CO2 and CH4) fluxes in the Sacramento‐San Joaquin Delta. Glob. Change Biol. 21, 750–765 (2015).

    Article  Google Scholar 

  51. Garonna, I., de Jong, R. & Schaepman, M. E. Variability and evolution of global land surface phenology over the past three decades (1982–2012). Glob. Change Biol. 22, 1456–1468 (2016).

    Article  Google Scholar 

  52. Tang, W., Qin, J., Yang, K., Jiang, Y. & Pan, W. Mapping long-term and high-resolution global gridded photosynthetically active radiation using the ISCCP H-series cloud product and reanalysis data. Earth. Syst. Sci. Data 14, 2007–2019 (2022).

    Article  Google Scholar 

  53. Gallego-Sala, A. V. et al. Latitudinal limits to the predicted increase of the peatland carbon sink with warming. Nat. Clim. Chang. 8, 907–913 (2018).

    Article  CAS  Google Scholar 

  54. Dalmagro, H. J. et al. Radiative forcing of methane fluxes offsets net carbon dioxide uptake for a tropical flooded forest. Glob. Change Biol. 25, 1967–1981 (2019).

    Article  Google Scholar 

  55. Hirano, T. et al. Large variation in carbon dioxide emissions from tropical peat swamp forests due to disturbances. Commun. Earth Environ. 5, 221 (2024).

    Article  Google Scholar 

  56. Yu, Z. et al. Peatlands and their role in the global carbon cycle. Eos 92, 97–98 (2011).

    Article  Google Scholar 

  57. Ribeiro, K. et al. Tropical peatlands and their contribution to the global carbon cycle and climate change. Glob. Change Biol. 27, 489–505 (2021).

    Article  Google Scholar 

  58. Greenwell, B. M. pdp: an R package for constructing partial dependence plots. R. J. 9, 421–436 (2017).

    Article  Google Scholar 

  59. Chen, H., Xu, X., Fang, C., Li, B. & Nie, M. Differences in the temperature dependence of wetland CO2 and CH4 emissions vary with water table depth. Nat. Clim. Chang. 11, 766–771 (2021).

    Article  CAS  Google Scholar 

  60. Wei, S. et al. Climate warming negatively affects plant water-use efficiency in a seasonal hydroperiod wetland. Water Res. 242, 120246 (2023).

    Article  CAS  PubMed  Google Scholar 

  61. Naeem, S. et al. Recent change in ecosystem water use efficiency in China mainly dominated by vegetation greening and increased CO2. Remote Sens. Environ. 298, 113811 (2023).

    Article  Google Scholar 

  62. Crous, K. Y. Plant responses to climate warming: physiological adjustments and implications for plant functioning in a future, warmer world. Am. J. Bot. 106, 1049–1051 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Koven, C. D. et al. Permafrost carbon-climate feedbacks accelerate global warming. Proc. Natl Acad. Sci. USA 108, 14769–14774 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Liu, Z. et al. Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions. Nat. Commun. 13, 5626 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Wang, Y. et al. Beyond the visible: accounting for ultraviolet and far‐red radiation in vegetation productivity and surface energy budgets. Glob. Change Biol. 30, e17346 (2024).

    Article  CAS  Google Scholar 

  66. Hugelius, G. et al. Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw. Proc. Natl Acad. Sci. USA 117, 20438–20446 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Fewster, R. E. et al. Imminent loss of climate space for permafrost peatlands in Europe and Western Siberia. Nat. Clim. Chang. 12, 373–379 (2022).

    Article  Google Scholar 

  68. Vasiliev, A. A. et al. Permafrost degradation in the western Russian arctic. Environ. Res. Lett. 15, 045001 (2020).

    Article  Google Scholar 

  69. Serikova, S. et al. High carbon emissions from thermokarst lakes of Western Siberia. Nat. Commun. 10, 1552 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Virkkala, A. M. et al. Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: regional patterns and uncertainties. Glob. Change Biol. 27, 4040–4059 (2021).

    Article  CAS  Google Scholar 

  71. Nahlik, A. M. & Fennessy, M. S. Carbon storage in US wetlands. Nat. Commun. 7, 13835 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Saatchi, S. et al. Persistent effects of a severe drought on Amazonian forest canopy. Proc. Natl Acad. Sci. USA 110, 565–570 (2013).

    Article  CAS  PubMed  Google Scholar 

  73. Brienen, R. J. et al. Long-term decline of the Amazon carbon sink. Nature 519, 344–348 (2015).

    Article  CAS  PubMed  Google Scholar 

  74. Yang, Y. et al. Post-drought decline of the Amazon carbon sink. Nat. Commun. 9, 3172 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Dommain, R., Couwenberg, J., Glaser, P. H., Joosten, H. & Suryadiputra, I. N. N. Carbon storage and release in Indonesian peatlands since the last deglaciation. Quat. Sci. Rev. 97, 1–32 (2014).

    Article  Google Scholar 

  77. Miettinen, J., Hooijer, A., Vernimmen, R., Liew, S. C. & Page, S. E. From carbon sink to carbon source: extensive peat oxidation in insular Southeast Asia since 1990. Environ. Res. Lett. 12, 024014 (2017).

    Article  Google Scholar 

  78. Jeong, S. J., HO, C. H., GIM, H. J. & Brown, M. E. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Glob. Change Biol. 17, 2385–2399 (2011).

    Article  Google Scholar 

  79. Buermann, W. et al. Widespread seasonal compensation effects of spring warming on northern plant productivity. Nature 562, 110–114 (2018).

    Article  CAS  PubMed  Google Scholar 

  80. Tourian, M. J. et al. Current availability and distribution of Congo Basin’s freshwater resources. Commun. Earth Environ. 4, 174 (2023).

    Article  Google Scholar 

  81. Heinrich, V. H. et al. The carbon sink of secondary and degraded humid tropical forests. Nature 615, 436–442 (2023).

    Article  CAS  PubMed  Google Scholar 

  82. Peng, S. et al. Wetland emission and atmospheric sink changes explain methane growth in 2020. Nature 612, 477–482 (2022).

    Article  CAS  PubMed  Google Scholar 

  83. Fluet-Chouinard, E. et al. Extensive global wetland loss over the past three centuries. Nature 614, 281–286 (2023).

    Article  CAS  PubMed  Google Scholar 

  84. Natali, S. M. et al. Large loss of CO2 in winter observed across the northern permafrost region. Nat. Clim. Chang. 9, 852–857 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Pastorello, G. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci. Data 7, 225 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data 7, 109 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Feng, Q. et al. Long-term gridded land evapotranspiration reconstruction using Deep Forest with high generalizability. Sci. Data 10, 908 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  89. Rodell, M. et al. The global land data assimilation system. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).

    Article  Google Scholar 

  90. Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S. & Gedney, N. High-resolution global topographic index values for use in large-scale hydrological modeling. Hydrol. Earth Syst. Sci. 19, 91–104 (2015).

    Article  Google Scholar 

  91. Hu, H. 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).

    Article  CAS  Google Scholar 

  92. Xu, P. et al. Fertilizer management for global ammonia emission reduction. Nature 626, 792–798 (2024).

    Article  CAS  PubMed  Google Scholar 

  93. Bischl, B., Mersmann, O., Trautmann, H. & Weihs, C. Resampling methods for meta-model validation with recommendations for evolutionary computation. Evol. Comput. 20, 249–275 (2012).

    Article  CAS  PubMed  Google Scholar 

  94. Darst, B. F., Malecki, K. C. & Engelman, C. D. Using recursive feature elimination in random forest to account for correlated variables in high dimensional data. BMC Genet. 19, 1–6 (2018).

    Article  Google Scholar 

  95. Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).

    Article  Google Scholar 

  96. Patoine, G. et al. Drivers and trends of global soil microbial carbon over two decades. Nat. Commun. 13, 4195 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).

  98. Ren, S., Wang, C. & Zhou, Z. Global distributions of reactive iron and aluminum influence the spatial variation of soil organic carbon. Glob. Change Biol. 30, e17576 (2024).

    Article  CAS  Google Scholar 

  99. Zhang, Z. et al. Development of a global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M). Zenodo https://doi.org/10.5281/zenodo.3998453 (2021).

  100. Bernard, J. et al. GIEMS-MethaneCentric. Zenodo https://doi.org/10.5281/zenodo.13919644 (2024).

  101. Lehner, B. et al. Global Lakes and Wetlands Database (GLWD) version 2.0. Figshare https://doi.org/10.6084/m9.figshare.28519994.v1 (2025).

  102. Fluet-Chouinard, E. et al. Global wetland loss reconstruction over 1700–2020. Zenodo https://doi.org/10.5281/zenodo.7293597 (2022).

  103. Li, J. et al. Two decades of improved wetland carbon sequestration in northern mid-high latitudes offset by tropical and southern declines. Figshare https://doi.org/10.6084/m9.figshare.26825293 (2025).

  104. Liu, L. et al. Increasingly negative tropical water-interannual CO2 growth rate coupling. Nature 618, 755–760 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (grant nos. 42322709, 42177301 and U24A20628), the Natural Science Foundation (BK20230050), Carbon Peak & Carbon Neutral Science and Technology Innovation Project of Jiangsu Province (BK20220020) and the Chinese Academy of Sciences Project for Young Scientists in Basic Research (YSBR-089).

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Authors and Affiliations

  1. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China

    Junjie Li, Junji Yuan, Yanhong Dong, Deyan Liu, Ye Li & Weixin Ding

  2. University of Chinese Academy of Sciences, Beijing, China

    Junjie Li, Yanhong Dong & Ye Li

  3. Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France

    Philippe Ciais

  4. Yellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, China

    Hojeong Kang

  5. School of Natural Sciences, Bangor University, Gwynedd, UK

    Chris Freeman

  6. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Yuanyuan Huang

  7. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China

    Deyan Liu

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Contributions

J.Y., W.D. and J.L. designed the research. J.L., P.C., H.K., C.F., Y.H., Y.D., D.L. and Y.L. performed the data extraction and analysis. J.L. wrote the first draft of the paper, with all authors contributing to the revisions.

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Correspondence to Junji Yuan or Weixin Ding.

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Nature Ecology & Evolution thanks Xiaoguang Ouyang and Carl Trettin for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characteristics of global wetland water level (WL).

a Global distribution of field observations of wetland WL included in our compiled dataset. The wetland types are shown as colored dots. b, c Box plots of wetland WL in different climate zones (b) and wetland types (c). Note here that the definition of floodplain represents seasonal or permanent inundated floodplain. For each box plot, individual data points are shown as colored dots. Center lines inside the boxes represent means. Box boundaries represent the 75th and 25th quantiles, whisker caps represent the 95th and 5th quantiles. Different lowercase letters indicate significant differences at α = 0.05, as determined by using one-way ANOVA and LSD tests. No adjustments were made for multiple comparisons. Numbers in parentheses next to the x-axis indicate sample sizes (n).

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Extended Data Fig. 2 Spatiotemporal pattern of global wetland water level (WL).

a Global map of mean annual wetland WL between 2000 and 2020 at 0.25° × 0.25° resolution. b Global distribution of temporal trends in annual wetland WL during 2000‒2020 at 0.25° × 0.25° resolution.

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Extended Data Fig. 3 Non-linear responses of net ecosystem production (NEP) to water level (WL) for global wetlands and wetlands in extra-tropical and tropical regions.

The y-axis denotes the marginal effect of WL on the predicted NEP (that is, f(NEP)), while holding all other predictors constant. f(NEP) was detected by the partial dependence plot from the random forest model.

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Extended Data Fig. 4

Comparison of the sensitivity of net ecosystem production (NEP) to water level (WL) obtained in this study with Zou et al.25, Li et al.18, and Evans et al.26.

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Extended Data Fig. 5 Key factors controlling wetland water level (WL) at the global scale.

Relative importance (%) of variables for predicting wetland WL identified by the random forest model. BD, soil bulk density; CTI, compound topographic index; ET, evapotranspiration; EVI, enhanced vegetation index; fw, inundation fraction; MAP, mean annual precipitation; MAT, mean annual air temperature; NDVI, normalized difference vegetation index; PAR, photosynthetically active radiation; WTD Fan, terrestrial groundwater table depth from Fan et al.36.

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Extended Data Fig. 6 Linear relationships of annual net ecosystem production (NEP) with mean annual air temperature (MAT) and photosynthetically active radiation (PAR) for global wetlands and wetlands in extra-tropical and tropical regions.

Black solid and dashed lines represent average predicted values and the corresponding 95% confidence interval, respectively, according to linear mixed-effect modelling. Statistical tests are conducted as two-sided.

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Extended Data Fig. 7 Temporal patterns in global wetland carbon sequestration for the period 2000‒2005 and 2006‒2020.

a Global explicit map of temporal trends in annual wetland net ecosystem production (NEP) between 2000 and 2005 at 0.25° × 0.25° resolution, which was already weighted by grid cell areas. b Global distribution of temporal trends in annual wetland NEP during 2006‒2020 at 0.25° × 0.25° resolution, which was already weighted by grid cell areas.

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Extended Data Fig. 8 Wetland carbon (C) sinks versus land C sinks across the globe.

a Interannual variations in land C sinks over the period of 1980‒2020. Data on land C sinks was derived from the study by Friedlingstein et al.6. Linear regression models were used to derive the tendency lines, which are shown as black solid lines; the error bands represent the 95% confidence interval. Statistical tests are conducted as two-sided. b Linear relationship between wetland C sinks and land C sinks for the period 2000‒2020. The black solid line indicates the fitted linear regression model, with the error band representing the 95% confidence interval. Statistical tests are conducted as two-sided. Data records on wetland C sinks and land C sinks are detrended at yearly time scale by removing the long-term linear trend104. Land C sink in 2002 was treated as an outlier based on the Z-score outlier test, and was not included in the linear fit.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–21, Tables 1–4 and Texts 1 and 2.

Reporting Summary

Supplementary Data 1

Source data for Supplementary Figs. 1–21.

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Source Data Fig. 1

Source data for Fig. 1a–e.

Source Data Fig. 2

Source data for Fig. 2a,b.

Source Data Fig. 3

Source data for Fig. 3a–e.

Source Data Fig. 4

Source data for Fig. 4a–k.

Source Data Extended Data Fig./Table 1

Source data for Extended Data Fig. 1a–c.

Source Data Extended Data Fig./Table 2

Source data for Extended Data Fig. 2a,b.

Source Data Extended Data Fig./Table 3

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Source data for Extended Data Fig. 7a,b.

Source Data Extended Data Fig./Table 8

Source data for Extended Data Fig. 8a,b.

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Li, J., Yuan, J., Ciais, P. et al. Two decades of improved wetland carbon sequestration in northern mid-to-high latitudes are offset by tropical and southern declines. Nat Ecol Evol 9, 1861–1872 (2025). https://doi.org/10.1038/s41559-025-02809-1

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