Title: Influence of Tundra Polygon Type and Climate Variability on CO2 and CH4 Fluxes Near Utqiagvik, Alaska

Journal Article · · Journal of Geophysical Research. Biogeosciences
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of Nebraska, Lincoln, NE (United States). Inst. of Agriculture
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
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Arctic tundra has the potential to generate significant climate feedbacks, but spatial complexity makes it difficult to quantify the impacts of climate on ecosystem-atmosphere fluxes, particularly in polygonal tundra comprising wetter and drier polygon types on the scale of tens of meters. We measured CO2, CH4, and energy fluxes using eddy covariance for 7 yr (April to November, 2013–2019) in polygonal tundra near Utqiagvik, Alaska. This period saw the earliest snowmelt, latest snow accumulation, and hottest summer on record. To estimate fluxes by polygon type, we combined a polygon classification with a flux-footprint model. Methane fluxes were highest in the summer months but were also large during freeze-up and increased with the warming trend in August–November temperatures. While CO2 respiration had a consistent, exponential relationship with temperature, net ecosystem exchange was more variable among years. CO2 and CH4 exchange (June–September) ranged between -0.83 (Standard error [SE] = 0.03) and -1.32 (SE = 0.04) μmol m-2s-1 and 13.92 (SE = 0.26)—23.42 (SE = 0.45) nmol m-2s-1, respectively, and varied interannually (p ≤ 0.05). The maximum-influence method effectively attributed fluxes to polygon types. Areas dominated by low-centered polygons had higher CO2 fluxes except in 2016–2017. Methane fluxes were highest in low-centered polygons 2013–2015 and in flat-centered polygons in subsequent years, possibly due to increasing temperature and precipitation. Sensible and latent heat fluxes also varied significantly among polygon types. Accurate characterization of Arctic fluxes and their climate dependencies requires spatial disaggregation and long term observations.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1863779
Journal Information:
Journal of Geophysical Research. Biogeosciences, Journal Name: Journal of Geophysical Research. Biogeosciences Journal Issue: 12 Vol. 126; ISSN 2169-8953
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English

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  • 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/10.5440/1126515
dataset January 2017
Airborne Imagery Collections Barrow 2013
  • Cherry, Jessica; Crowder, Kerri
  • 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/10.5440/1167159
dataset January 2016
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  • Sloan, Victoria; Norby, Richard
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dataset January 2014
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dataset January 2017
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dataset January 2019
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54 ENVIRONMENTAL SCIENCES
Alaska
Arctic
eddy covariance
energy balance
greenhouse gases
polygon tundra