Methane Emissions from Paludified Boreal Soils in European Russia as Measured and Modelled

Spatial or temporal forest–peatland transition zones were proposed as potential hot spots of methane (CH4) emissions. Consequently, paludified soils are an important component of boreal landscape biogeochemistry. However, their role in the regional carbon cycle remains unclear. This study presents CH4 fluxes from two forest–peatland transition zones, two wet forest sites and two clear-cut sites which were compared to fluxes of open peatlands and dry forest. The median fluxes measured using the closed-chamber technique varied from − 0.04 to 12.6 mg m−2 h−1 during three climatically different years. The annual mean CH4 emissions of the forest–peatland transition zone were significantly lower than the fluxes of the open peatland sites, 7.9 ± 0.5 and 21.9 ± 1.6 g m−2a−1, respectively. The dry forest site was characterized by a small uptake of CH4 (− 2.3 ± 0.2 g m−2a−1). Although clear-cut forest area drastically increased in European Russia during the last two decades, if water level depths in these forests remains below 10 cm they do not act as CH4 sources. Fluxes of CH4 from the transition zone sites showed a higher response to soil temperature than to water table level. Fluxes of CH4 between the atmosphere and the two investigated peatlands were not significantly different, although a significant difference in water table level could be observed. The meteorological conditions of the investigated summers changed from being hot and dry in 2013 to cold and wet in 2014; the summer of 2015 was characterized as warmer and drier in the first half and colder and wetter in the second half. Significant differences in CH4 fluxes were measured only between 2014 and 2013. Significant differences in CH4 fluxes and in nonlinear regressions showed that the CH4 fluxes of the different site types such as dry forests, transition zones and open peatlands need to be modelled separately on a landscape level. Obviously, underlying processes vary with the ecosystem and (along with regional aspects) have to be understood first before large-scale modelling is possible.