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Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic


Methane emissions from organic-rich soils in the Arctic have been extensively studied due to their potential to increase the atmospheric methane burden as permafrost thaws1,2,3. However, this methane source might have been overestimated without considering high-affinity methanotrophs (HAMs; methane-oxidizing bacteria) recently identified in Arctic mineral soils4,5,6,7. Herein we find that integrating the dynamics of HAMs and methanogens into a biogeochemistry model8,9,10 that includes permafrost soil organic carbon dynamics3 leads to the upland methane sink doubling (~5.5 Tg CH4 yr−1) north of 50 °N in simulations from 2000–2016. The increase is equivalent to at least half of the difference in net methane emissions estimated between process-based models and observation-based inversions11,12, and the revised estimates better match site-level and regional observations5,7,13,14,15. The new model projects doubled wetland methane emissions between 2017–2100 due to more accessible permafrost carbon16,17,18. However, most of the increase in wetland emissions is offset by a concordant increase in the upland sink, leading to only an 18% increase in net methane emission (from 29 to 35 Tg CH4 yr−1). The projected net methane emissions may decrease further due to different physiological responses between HAMs and methanogens in response to increasing temperature19,20.

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Fig. 1: A schematic diagram of XPTEM-XHAM.
Fig. 2: Annual estimates of the Arctic methane budget by three models for 2000–2016.
Fig. 3: The spatial variability of annual net methane flux north of 50 °N for XPTEM-XHAM.
Fig. 4: Projected annual net Arctic methane emissions from 2017 to 2100 north of 50 °N.

Data availability

The data are archived and freely available at the Purdue University Research Repository (PURR) at: (

Code availability

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This work was supported by NASA Earth and Space Science Fellowship Program (grant no. 80NSSC17K0368 P00001) and NASA Interdisciplinary Research in Earth Science (grant no. NNX17AK20G). B.E. acknowledges Danish National Research Foundation (grant no. CENPERM DNRF100) for financial support. We also thank W. Wieder for providing model results and valuable discussions.

Author information

Authors and Affiliations



Y.O., Q.Z., M.C.L., T.C.O. and D.M. conceived the study. Y.O., Q.Z. and L.L. built the model. L.D., B.E. and G.H. provided unpublished or raw data. Y.O. conducted the model runs. All authors contributed to data interpretation and preparation of manuscript text.

Corresponding author

Correspondence to Qianlai Zhuang.

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The authors declare no competing interests.

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Peer review information Nature Climate Change thanks Lauren Hale and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Pan-Arctic monthly mean methane fluxes for XPTEM-XHAM and PTEM-HAM from 2000-2016 north of 50°N.

Estimates of pan-arctic (a, c) monthly wetland methane emission and (b, d) monthly upland methane consumption in mg m-2 day-1 for (a, b) XPTEM-XHAM and (c, d) PTEM-HAM model. The blue line is monthly averages over 2000-2016, and grey lines represent values of each year.

Extended Data Fig. 2 Inter-annual variability of methane fluxes from 2000 – 2016 north of 50°N.

(Left) Annual estimates of pan-arctic (a) wetland methane emission, (b) upland methane consumption, and (c) net methane emission for XPTEM-XHAM (blue), PTEM-HAM (yellow), and TEM (red) in TgCH4yr-1 from 2000-2016. The shaded area represents one standard deviation of models determined by varying the optimized parameters. (Right) Mean and one standard deviation averaged over the simulation period for each metric are given by the bars. Panel (c) additionally shows mean and one standard deviation of previous estimates of net methane emission estimated by top-down inversions (times symbol) by the bars.

Extended Data Fig. 3 Spatial variability of soil and vegetation properties north of 50°N.

(a) annual top 10-cm soil temperature in °C, (b) annual top 10-cm soil moisture in % volume, (c) monthly net primary productivity in gC m-2 month-1, and (d) permafrost SOC stored in the top 3-m in kg m-23,16. The soil temperature, moisture, and net primary productivity were averaged over the contemporary period during 2000-2016. The dotted longitudinal lines are at 30° intervals, and the latitudinal line is at 65°N.

Extended Data Fig. 4 Inter-annual variability of methane fluxes using time-varying inundation fraction from 2000 – 2012 north of 50°N.

Annual estimates of pan-arctic (a) net methane emission, (b) wetland methane emission, and (c) upland methane consumption for XPTEM-XHAM model using static inundation fraction33 (blue) and time-varying inundation fraction from SWAMPS-GLWD34 (green) in TgCH4yr-1. The shaded area represents one standard deviation determined by varying the optimized parameters.

Extended Data Fig. 5 Model-data comparison of methane fluxes using site-level data.

Comparison of (a) wetland methane emission and (b) upland methane consumption of data from 46 in situ measurements (supplementary table 5) with simulation results from XPTEM-XHAM (blue), PTEM-HAM (yellow), and TEM (red).

Extended Data Fig. 6 Inter-annual variability of methane fluxes using time-varying inundation fraction from 2017 – 2100 north of 50°N.

Annual estimates of pan-Arctic (a) net methane emission, (b) wetland methane emission, and (c) upland methane consumption for XPTEM-XHAM model using static inundation fraction (blue) and dynamic inundation fraction (green) in TgCH4yr-1 using RCP 2.6 (dotted), RCP 4.5 (dashed), and RCP 8.5 (solid).

Extended Data Fig. 7 Future Arctic methane feedbacks.

Previous studies predicted a positive feedback between temperature increase and methane emission (circles 1–2). However, because high-affinity methanotrophs may respond strongly to temperature and less strongly to soil moisture due to uncertain Arctic hydrology (circles 3–4), this feedback may be partially suppressed. Moreover, explicit modeling of microbial dynamics (circle 5) will facilitate future model developments that include effects of microbial physiology (modified Fig. 5 of Oh et al., 8).

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Supplementary Methods 1–6, Figs. 1–16, Tables 1–8 and references.

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Oh, Y., Zhuang, Q., Liu, L. et al. Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic. Nat. Clim. Chang. 10, 317–321 (2020).

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