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Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity

Journal Article · · Biogeosciences (Online)

Methane (CH4) emissions from wetlands are likely increasing and important in global climate change assessments. However, contemporary terrestrial biogeochemical model predictions of CH4 emissions are very uncertain, at least in part due to prescribed temperature sensitivity of CH4 production and emission. While statistically consistent apparent CH4 emission temperature dependencies have been inferred from meta-analyses across microbial to ecosystem scales, year-round ecosystem-scale observations have contradicted that finding. Here, we show that apparent CH4 emission temperature dependencies inferred from year-round chamber measurements exhibit substantial intra-seasonal variability, suggesting that using static temperature relations to predict CH4 emissions is mechanistically flawed. Our model results indicate that such intra-seasonal variability is driven by substrate-mediated microbial and abiotic interactions: seasonal cycles in substrate availability favors CH4 production later in the season, leading to hysteretic temperature sensitivity of CH4 production and emission. Our findings demonstrate the uncertainty of inferring CH4 emission or production rates from temperature alone and highlight the need to represent microbial and abiotic interactions in wetland biogeochemical models.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)
Grant/Contract Number:
AC02-05CH11231; SC0016440
OSTI ID:
1763692
Journal Information:
Biogeosciences (Online), Journal Name: Biogeosciences (Online) Journal Issue: 22 Vol. 17; ISSN 1726-4189
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English

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  • Chang, Kuang-Yu; Riley, William
  • Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); NGEE Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) https://doi.org/10.5440/1635534
dataset January 2020