Divergent responses of wetland methane emissions to elevated atmospheric CO2 dependent on water table

Yongxin Lin, Junji Yuan, Deyan Liu, Hojeong Kang, Chris Freeman, Hang Wei Hu, Guiping Ye, Weixin Ding

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Elevated atmospheric CO2 may have consequences for methane (CH4) emissions from wetlands, yet the magnitude and direction remain unpredictable, because the associated mechanisms have not been fully investigated. Here, we established an in situ macrocosm experiment to compare the effects of elevated CO2 (700 ppm) on the CH4 emissions from two wetlands: an intermittently inundated Calamagrostis angustifolia marsh and a permanently inundated Carex lasiocarpa marsh. The elevated CO2 increased CH4 emissions by 27.6–57.6% in the C. angustifolia marsh, compared to a reduction of 18.7–23.5% in the C. lasiocarpa marsh. The CO2-induced increase in CH4 emissions from the C. angustifolia marsh was paralleled with (1) increased dissolved organic carbon (DOC) released from plant photosynthesis and (2) reduced (rate of) CH4 oxidation due to a putative shift in methanotrophic community composition. In contrast, the CO2-induced decrease in CH4 emissions from the C. lasiocarpa marsh was associated with the increases in soil redox potential and pmoA gene abundance. We synthesized data from worldwide wetland ecosystems, and found that the responses of CH4 emissions to elevated CO2 was determined by the wetland water table levels and associated plant oxygen secretion capacity. In conditions with elevated CO2, plants with a high oxygen secretion capacity suppress CH4 emissions while plants with low oxygen secretion capacity stimulate CH4 emissions; both effects are mediated via a feedback loop involving shifts in activities of methanogens and methanotrophs.

Original languageEnglish
Article number117682
JournalWater Research
Volume205
DOIs
Publication statusPublished - 2021 Oct 15

Bibliographical note

Funding Information:
This work was supported by grants from the National Natural Science Foundation of China ( U1906220, 41877039, 42177301 ) and Jiangsu Province ( BK20190109 ). HK is grateful to KRF ( 2019K1A3A1A7410742411 ).

Funding Information:
This work was supported by grants from the National Natural Science Foundation of China (U1906220, 41877039, 42177301) and Jiangsu Province (BK20190109). HK is grateful to KRF (2019K1A3A1A7410742411).

Publisher Copyright:
© 2021

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Civil and Structural Engineering
  • Ecological Modelling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution

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