Spatial variability of CO2 uptake in polygonal tundra: Assessing low-frequency disturbances in eddy covariance flux estimates

Norbert Pirk, Jakob Sievers, Jordan Mertes, Frans Jan W. Parmentier, Mikhail Mastepanov, Torben R. Christensen

Research output: Contribution to journalArticlepeer-review

Abstract

The large spatial variability in Arctic tundra complicates the representative assessment of CO2 budgets. Accurate measurements of these heterogeneous landscapes are, however, essential to understanding their vulnerability to climate change. We surveyed a polygonal tundra lowland on Svalbard with an unmanned aerial vehicle (UAV) that mapped ice-wedge morphology to complement eddy covariance (EC) flux measurements of CO2. The analysis of spectral distributions showed that conventional EC methods do not accurately capture the turbulent CO2 exchange with a spatially heterogeneous surface that typically features small flux magnitudes. Nonlocal (low-frequency) flux contributions were especially pronounced during snowmelt and introduced a large bias of -46 gCm-2 to the annual CO22 budget in conventional methods (the minus sign indicates a higher uptake by the ecosystem). Our improved flux calculations with the ogive optimization method indicated that the site was a strong sink for CO2 in 2015 (82 gCm2). Due to differences in light-use efficiency, wetter areas with lowcentered polygons sequestered 47% more CO2 than drier areas with flat-centered polygons. While Svalbard has experienced a strong increase in mean annual air temperature of more than 2K in the last few decades, historical aerial photographs from the site indicated stable ice-wedge morphology over the last 7 decades. Apparently, warming has thus far not been sufficient to initiate strong ice-wedge degradation, possibly due to the absence of extreme heat episodes in the maritime climate on Svalbard. However, in Arctic regions where ice-wedge degradation has already initiated the associated drying of landscapes, our results suggest a weakening of the CO2 sink in polygonal tundra.

Original languageEnglish
Pages (from-to)3157-3169
Number of pages13
JournalBiogeosciences
Volume14
Issue number12
DOIs
Publication statusPublished - 2017 Jun 29

Subject classification (UKÄ)

  • Physical Geography
  • Climate Research

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