Reduced Net Methane Emissions Due to Microbial Methane Oxidation in a Warmer Arctic

LETTERS https://doi.org/10.1038/s41558-020-0734-z Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic Youmi Oh 1, Qianlai Zhuang 1,2,3 ✉ , Licheng Liu1, Lisa R. Welp 1,2, Maggie C. Y. Lau4,9, Tullis C. Onstott4, David Medvigy 5, Lori Bruhwiler6, Edward J. Dlugokencky6, Gustaf Hugelius 7, Ludovica D’Imperio8 and Bo Elberling 8 Methane emissions from organic-rich soils in the Arctic have bacteria (methanotrophs) and the remainder is mostly emitted into been extensively studied due to their potential to increase the atmosphere (Fig. 1a). The methanotrophs in these wet organic the atmospheric methane burden as permafrost thaws1–3. soils may be low-affinity methanotrophs (LAMs) that require However, this methane source might have been overestimated >600 ppm of methane (by moles) for their growth and mainte- without considering high-affinity methanotrophs (HAMs; nance23. But in dry mineral soils, the dominant methanotrophs are methane-oxidizing bacteria) recently identified in Arctic min- high-affinity methanotrophs (HAMs), which can survive and grow 4–7 eral soils . Herein we find that integrating the dynamics of at a level of atmospheric methane abundance ([CH4]atm) of about HAMs and methanogens into a biogeochemistry model8–10 1.8 ppm (Fig. 1b)24. that includes permafrost soil organic carbon dynamics3 leads Quantification of the previously underestimated HAM-driven −1 to the upland methane sink doubling (~5.5 Tg CH4 yr ) north of methane sink is needed to improve our understanding of Arctic 50 °N in simulations from 2000–2016. The increase is equiva- methane budgets. Process-based methane models have overesti- −1 lent to at least half of the difference in net methane emissions mated Arctic methane emission by 5–10 Tg CH4 yr when com- estimated between process-based models and observation- pared with observation-based atmospheric inversions11,12. Given based inversions11,12, and the revised estimates better match that 87% of the Arctic is dominated by mineral-rich soils, the HAM- site-level and regional observations5,7,13–15. The new model driven methane sink may greatly reduce current area-integrated net projects doubled wetland methane emissions between 2017– methane emissions. Furthermore, the positive feedbacks of meth- 2100 due to more accessible permafrost carbon16–18. However, ane emission that result from additional accessible permafrost soil most of the increase in wetland emissions is offset by a con- organic carbon (PSOC) may be partially suppressed by negative cordant increase in the upland sink, leading to only an 18% feedbacks from the high activities of HAMs at future increased sur- −1 8 increase in net methane emission (from 29 to 35 Tg CH4 yr ). face temperatures and [CH4]atm (ref. ). The projected net methane emissions may decrease further Previous studies show that simulation of explicit microbial due to different physiological responses between HAMs and dynamics of MGs and HAMs improve model estimates of the mag- methanogens in response to increasing temperature19,20. nitude and seasonality of methane sources and sinks8,25. Microbial Arctic soils are considered to be a substantial net emission source dynamics may also cause additional complexity due to different of methane to the atmosphere. Current process-based biogeo- microbial physiology between MGs and HAMs19,26. Recent labora- chemistry models and observation-based atmospheric inversions tory and field studies show that microbial communities adjust their −1 have estimated this source to be between 15 and 50 Tg CH4 yr , active microbial biomass (MICbiomass) in warmer soils depending on 12 19 which accounts for 20–25% of global natural methane emissions . the microbial growth efficiency (ɛ) and maintenance energy (mE) ; Furthermore, process-based models predict that methane emissions ɛ represents the growth efficiency of MICbiomass per unit of substrate will be two to three times greater by 21002,17,18, as warmer tempera- consumed and it is a factor of ten smaller for MGs (ɛ = 0.05) than 20,27 tures will increase both the rate of decomposition and availability of for HAMs (ɛ = 0.5) ; mE (that is, the rate of metabolic energy gen- soil organic carbon (SOC) from permafrost-affected soils in addi- eration needed to maintain MICbiomass) increases exponentially with tion to SOC from recently dead vegetation for decomposition16,21. temperature for all microbes, including MGs and HAMs, reflecting However, methane emissions are mainly confined to the 13% of the fast turnover associated with cell mortality (equation (16))19,28. Arctic landscapes composed of organic-rich soils where anaerobic These processes are important for current and future Arctic meth- processes dominate16. The rest are composed of mineral-rich soils, ane budgets; however, current process-based methane models have from which recent field studies have identified net annual methane not considered such microbial dynamics. sinks during growing seasons4–7. This difference may be controlled First, this study estimates current pan-Arctic soil methane emis- by differences in methanotroph community composition (Fig. 1)22. sions and consumptions while accounting for microbial and PSOC In wet organic soils, a fraction of methane produced by methano- dynamics; second, it evaluates the magnitude and spatial variabil- genic archaea (methanogens, MGs) is oxidized by methanotrophic ity of those estimates; and, third, projects pan-Arctic changes in 1Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA. 2Purdue Climate Change Research Center, West Lafayette, IN, USA. 3Department of Agronomy, Purdue University, West Lafayette, IN, USA. 4Department of Geosciences, Princeton University, Princeton, NJ, USA. 5Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA. 6NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, CO, USA. 7Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden. 8Center for Permafrost (CENPERM), University of Copenhagen, Copenhagen, Denmark. 9Present address: Laboratory of Extraterrestrial Ocean Systems, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, China. ✉e-mail: [email protected] NatURE Climate CHANGE | www.nature.com/natureclimatechange LETTERS NATURE CLIMATE CHANGE a b CH4 CH4 [CH4]atm Table 1 | A summary of the three models used in this study [CH4]atm Model set-up XPTEM- PTEM- TEM ε XHAM HAM PSOC dynamics On On Off mE NPP LAM HAMLAM HAMs On On Off t = 1,2,3… Microbial dynamics of HAMs On Off Off 4 and MGs CH The set-up for XPTEM-XHAM is explained in detail in Fig. 1. For PTEM-HAM, the production of methane in wetlands is dependent on SOC derived from vegetation and thawing permafrost; ε mE SOC MG methane is oxidized by HAMs, but MICbiomass changes are not explicitly simulated. In the set-up of t = 1,2,3… TEM, the production of methane in wetlands is dependent on SOC derived from vegetation only, methane is oxidized by LAMs only, and MICbiomass changes are also not explicitly simulated. Permafrost PSOC Climatic Research Unit (CRU) data were used as meteorological Fig. 1 | A schematic diagram of XPTEM-XHAM. a,b, The model simulates inputs for a contemporary simulation from 2000 to 201631, and CH production by MGs and oxidation of CH by LAMs in wetlands ( ) as 4 4 a inputs from IPCC representative concentration pathways (RCPs) well as the oxidation of [CH4]atm by HAMs in uplands (b). We used static 32 33 2.6, 4.5 and 8.5 were used for projections to 2100 . For PTEM- inundation data to divide the Arctic landscape into wetland and upland HAM and XPTEM-XHAM, we used the Northern Circumpolar regions but later varied the regions on the basis of time-varying inundation Soil Carbon Database v.2 (NCSCDv2) to estimate PSOC at different data34,35. Changes in MIC of MGs and HAMs (grey dashed lines) biomass soil depths16. The simulated methane emission from wetlands and depend on and m , and are tracked as a function of time (t (h)). PSOC ε E consumption from uplands were area-integrated for each grid cell dynamics are added to account for SOC that is accessible from thawing on the basis of static fractional inundation data33. permafrost when soil temperatures at the corresponding depths become For a sensitivity test of the surface area of the wetlands and higher than 1 °C. The dark blue arrow refers to PSOC dynamics, dark red uplands of XPTEM-XHAM, we used time-varying inundation arrows refer to microbial dynamics and grey arrows refer to processes from data from the Satellite-driven Surface Water Microwave Product the original TEM. Series—Gobal Lakes and Wetlands Database (SWAMPS-GLWD) from 2000 to 201234 and transient inundation fraction simulated by Community Land Model v.5.0 from 2017 to 210035. We further soil methane emissions and consumptions through 2100. These conducted XPTEM-XHAM sensitivity tests of wetland emission projections take into account enhanced methane emissions due to and upland consumption to changes in meteorology and substrate increased available PSOC and stimulated HAM methane consump- inputs from 2000 to 2016. For XPTEM-XHAM from 2017–2100, tions, as well as the different physiological responses of MGs and we varied mE of MGs and HAMs to increase with temperature to HAMs at warmer temperatures. model microbial physiological responses (equations (13C), (13D) To address these objectives, we implemented explicit microbial and (16)). Finally, for RCP 8.5 of XPTEM-XHAM, we varied dynamics for MGs and HAMs into a biogeochemistry model; that coenzyme Q10 for methane production and oxidation, and fixed 9,10 is, the terrestrial ecosystem model (TEM) (Fig. 1) . In a wetland [CH4]atm to the contemporary level (1.8 ppm) to test model sen- system, we simulated methane oxidation by LAMs as a function of sitivity to temperature and [CH4]atm changes (see Methods and environmental parameters. We fixed LAM MICbiomass due to its lim- Supplementary Methods).

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