Environmental controls on ecosystem‐scale CH₄ emission from polygonal tundra in the Lena River Delta, Siberia

Abstract

[1] We present the first ecosystem-scale methane flux data from a northern Siberian tundra ecosystem covering the entire snow-free period from spring thaw until initial freeze-back. Eddy covariance measurements of methane emission were carried out from the beginning of June until the end of September in the southern central part of the Lena River Delta (72°22 0 N, 126°30 0 E). The study site is located in the zone of continuous permafrost and is characterized by Arctic continental climate with very low precipitation and a mean annual temperature of À14.7°C. We found relatively low fluxes of on average 18.7 mg m À2 d À1 , which we consider to be because of (1) extremely cold permafrost, (2) substrate limitation of the methanogenic archaea, and (3) a relatively high surface coverage of noninundated, moderately moist areas. Near-surface turbulence as measured by the eddy covariance system in 4 m above the ground surface was identified as the most important control on ecosystem-scale methane emission and explained about 60% of the variance in emissions, while soil temperature explained only 8%. In addition, atmospheric pressure was found to significantly improve an exponential model based on turbulence and soil temperature. Ebullition from waterlogged areas triggered by decreasing atmospheric pressure and near-surface turbulence is thought to be an important pathway that warrants more attention in future studies. The close coupling of methane fluxes and atmospheric parameters demonstrated here raises questions regarding the reliability of enclosure-based measurements, which inherently exclude these parameters.

Intense methane ebullition from open water area of a shallow peatland lake on the eastern Tibetan Plateau

“…This was probably related to the disadvantage of the floating chamber method, i.e. failing to evaluate the influence of turbulence on methane ebullition from shallow sediments (Sachs et al, 2008). Furthermore, methane ebullition from lakes are thought to be highly variable both in spatial and temporal scales (Bastviken et al, 2004(Bastviken et al, , 2008Wik et al, 2013).…”

The surface energy balance of a polygonal tundra site in northern Siberia – Part 1: Spring to fall

“…More detailed descriptions of the vegetation and landscape characteristics are available; cf. Are and Reimnitz (2000), Kutzbach et al (2004Kutzbach et al ( , 2007, Boike et al (2008) and Sachs et al (2008).…”

“…Until now it is unclear whether permafrost regions will turn into massive sources of greenhouse gases, such as methane and carbon dioxide, as the frozen soils begin to thaw (Hobbie et al, 2000;Davidson and Janssens, 2006). Recent measurements taken at wet tundra landscapes demonstrate the importance of the freeze and thaw dynamics for methane emission, which are related in a non-linear manner (Christensen et al, 2003;Sachs et al, 2008;Mastepanov et al, 2008). For this purpose, efforts have been initiated to incorporate permafrost and the annual freeze and thaw dynamics into global climate models (e.g., Stendel and Christensen, 2002;Lawrence and Slater, 2005;Nicolsky et al, 2007;Lawrence et al, 2008).…”

A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams

“…In order to test the model response to drier and wetter conditions, we simulate different configurations by changing the amount of incoming precipitation. We then compare the cumulative precipitation simulated by the model and the one measured in the field in order to have realistic scenarios comparable with data from field campaigns Sachs et al, 2008). Field studies observed in particular the influence of lateral runoff and storage: water table drops in the late summer season since the water table usually lies above thaw depth, and it leads to lateral fluxes of water in the ice-wedge channel network.…”

“…1). Previous works involved closed-chamber and eddy covariance measurements of methane fluxes (see e.g., Sachs et al, 2008Sachs et al, , 2010Wille et al, 2008;Kutzbach et al, 2004), as well as measurements and modeling of hydrological properties , and of surface energy balance (Langer et al, 2011a,b) in this typical periglacial landscape. Recent studies with the help of remote sensing data were able to capture and analyze surface heterogeneity (land cover and surface temperature) and its importance for the landatmosphere water fluxes (Muster et al, 2012;Langer et al, 2010).…”