Methane (CH4) emissions from Arctic tundra are an important feedback to global climate. Currently, modelling and predicting CH4 fluxes at broader scales are limited by the challenge of upscaling plot-scale measurements in spatially heterogeneous landscapes, and by uncertainties regarding key controls of CH4 emissions. In this study, CH4 and CO2 fluxes were measured together with a range of environmental variables and detailed vegetation analysis at four sites spanning 300 km latitude from Barrow to Ivotuk (Alaska). We used multiple regression modelling to identify drivers of CH4 flux, and to examine relationships between gross primary productivity (GPP), dissolved organic carbon (DOC) and CH4 fluxes. We found that a highly simplified vegetation classification consisting of just three vegetation types (wet sedge, tussock sedge and other) explained 54% of the variation in CH4 fluxes across the entire transect, performing almost as well as a more complex model including water table, sedge height and soil moisture (explaining 58% of the variation in CH4 fluxes). Substantial CH4 emissions were recorded from tussock sedges in locations even when the water table was lower than 40 cm below the surface, demonstrating the importance of plant-mediated transport. We also found no relationship between instantaneous GPP and CH4 fluxes, suggesting that models should be cautious in assuming a direct relationship between primary production and CH4 emissions. Our findings demonstrate the importance of vegetation as an integrator of processes controlling CH4 emissions in Arctic ecosystems, and provide a simplified framework for upscaling plot scale CH4 flux measurements from Arctic ecosystems.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)