09 Jul 2021

09 Jul 2021

Review status: a revised version of this preprint is currently under review for the journal BG.

Representativeness assessment of the pan-Arctic eddy-covariance site network, and optimized future enhancements

Martijn Pallandt1, Jitendra Kumar2, Marguerite Mauritz3, Edward Schuur4, Anna-Maria Virkkala5, Gerardo Celis6, Forrest Hoffman7, and Mathias Göckede1 Martijn Pallandt et al.
  • 1Department of Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, 07745, GER
  • 2Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  • 3Department of Biological Sciences, The University of Texas at El Paso, El Paso, TX 79902, USA
  • 4Center for Ecosystem Science and Society, and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ 86011, USA
  • 5Woodwell Climate Research Center, Falmouth, MA 02540, USA
  • 6Agronomy Department, University of Florida, Gainesville, FL 32601, USA
  • 7Computer Science and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA

Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens to destabilize ancient permafrost carbon stocks. The eddy covariance (EC) method is an established technique to quantify net losses and gains of carbon between the biosphere and atmosphere at high spatio-temporal resolution. Over the past decades, a growing network of terrestrial EC tower sites has been established across the Arctic, but a comprehensive assessment of the network’s representativeness within the heterogeneous Arctic region is still lacking. This creates additional uncertainties when integrating flux data across sites, for example when upscaling fluxes to constrain pan-Arctic carbon budgets, and changes therein.

This study provides an inventory of Arctic (here >= 60° N) EC sites, which has also been made available online ( Our database currently comprises 120 EC sites, but only 83 are listed as active, and just 25 of these active sites remain operational throughout the winter. To map the representativeness of this EC network, based on 18 bioclimatic and edaphic variables, we evaluated the similarity between environmental conditions observed at the tower locations and those within the larger Arctic study domain. With the majority of sites located in Fennoscandia and Alaska, these regions were assigned the highest level of network representativeness, while large parts of Siberia and patches of Canada were classified as under-represented. This division between regions is further emphasized for wintertime and methane flux data coverage. Across the Arctic, particularly mountainous regions were poorly represented by the current EC observation network.

We tested three different strategies to identify new site locations, or upgrades of existing sites, that optimally enhance the representativeness of the current EC network. While 15 new sites can improve the representativeness of the pan-Arctic network by 20 percent, upgrading as few as 10 existing sites to capture methane fluxes, or remain active during wintertime, can improve their respective network coverage by 28 to 33 percent. This targeted network improvement could be shown to be clearly superior to an unguided selection of new sites, therefore leading to substantial improvements in network coverage based on relatively small investments.

Martijn Pallandt et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2021-133', Dan Metcalfe, 19 Jul 2021
    • AC1: 'Reply on RC1', Martijn Pallandt, 03 Dec 2021
  • EC1: 'Comment on bg-2021-133', Andreas Ibrom, 17 Oct 2021
    • AC2: 'Reply on EC1', Martijn Pallandt, 03 Dec 2021

Martijn Pallandt et al.

Martijn Pallandt et al.


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Short summary
Thawing of Arctic permafrost soils could trigger the release of vast amounts of carbon to the atmosphere, thus enhance climate change. Our study investigated how well the current network of eddy-covariance sites, a technique to monitor greenhouse gas exchange at local scales, captures pan-Arctic flux patterns. We identified large coverage gaps, e.g. in Siberia, but also demonstrated that a targeted addition of relatively few sites can significantly improve network performance.