Spatial and temporal dynamics in eddy covariance observations of methane fluxes at a tundra site in northeastern Siberia

• Main Authors: Parmentier, F J W, van Huissteden, J, van der Molen, M K, Schaepman-Strub, G, Karsanaev, S A, Maximov, T C, Dolman, A J
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union 2011
• Subjects: Institute of Evolutionary Biology and Environmental Studies; 570 Life sciences; biology; 590 Animals (Zoology); Tundra; Siberia
• Online Access: https://www.zora.uzh.ch/id/eprint/53637/; https://www.zora.uzh.ch/id/eprint/53637/1/Parmentier_etal_GR11.pdf; https://www.zora.uzh.ch/id/eprint/53637/4/Parmentier_et_al_Spatial_and_temporal_dynamics.pdf; https://doi.org/10.5167/uzh-53637; https://doi.org/10.1029/2010JG001637

In the past two decades, the eddy covariance technique has been used for an increasing number of methane flux studies at an ecosystem scale. Previously, most of these studies used a closed path setup with a tunable diode laser spectrometer (TDL). Although this method worked well, the TDL has to be calibrated regularly and cooled with liquid nitrogen or a cryogenic system, which limits its use in remote areas. Recently, a new closed path technique has been introduced that uses off-axis integrated cavity output spectroscopy that does not require regular calibration or liquid nitrogen to operate and can thus be applied in remote areas. In the summer of 2008 and 2009, this eddy covariance technique was used to study methane fluxes from a tundra site in northeastern Siberia. The measured emissions showed to be very dependent on the fetch area, due to a large contrast in dry and wet vegetation in between wind directions. Furthermore, the observed short- and long-term variation of methane fluxes could be readily explained with a nonlinear model that used relationships with atmospheric stability, soil temperature, and water level. This model was subsequently extended to fieldwork periods preceding the eddy covariance setup and applied to evaluate a spatially integrated flux. The model result showed that average fluxes were 56.5, 48.7, and 30.4 nmol CH4 m&8722;2 s&8722;1 for the summers of 2007 to 2009. While previous models of the same type were only applicable to daily averages, the method described can be used on a much higher temporal resolution, making it suitable for gap filling. Furthermore, by partitioning the measured fluxes along wind direction, this model can also be used in areas with nonuniform terrain but nonetheless provide spatially integrated fluxes.