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Methane (CH) emissions from Arctic tundra are an important feedback to global climate. Currently, modelling and predicting CH 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 CH emissions. In this study, CH and CO 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 CH flux, and to examine relationships between gross primary productivity (GPP), dissolved organic carbon (DOC) and CH 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 CH 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 CH fluxes). Substantial CH 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 CH fluxes, suggesting that models should be cautious in assuming a direct relationship between primary production and CH emissions. Our findings demonstrate the importance of vegetation as an integrator of processes controlling CH emissions in Arctic ecosystems, and provide a simplified framework for upscaling plot scale CH flux measurements from Arctic ecosystems.

Vegetation Type Dominates the Spatial Variability in CH4 Emissions Across Multiple Arctic Tundra Landscapes