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Title: Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Journal Article · · Journal of Advances in Modeling Earth Systems
DOI:https://doi.org/10.1029/2019MS001771· OSTI ID:1579403
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  1. Department of BiologySan Diego State University San Diego CA USA
  2. Environmental Sciences DivisionOak Ridge National Laboratory Oak Ridge TN USA
  3. Department of BiologySan Diego State University San Diego CA USA, Institute of Applied EcologyChinese Academy of Sciences Shenyang City China
  4. Civil and Environmental EngineeringUniversity of California, Berkeley Berkeley CA USA
  5. Earth Sciences DivisionLawrence Berkeley National Laboratory Berkeley CA USA
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Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)
Grant/Contract Number:
AC05-00OR22725; AC02-05CH11231; 1702797
OSTI ID:
1579403
Alternate ID(s):
OSTI ID: 1579405; OSTI ID: 1582360; OSTI ID: 1615822
Journal Information:
Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Vol. 11 Journal Issue: 12; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 23 works
Citation information provided by
Web of Science

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Related Subjects

54 ENVIRONMENTAL SCIENCES
Arctic tundra
CH4 flux
microtopographic
sensitivity analysis
net carbon exchange