Fine-scale spatial variability of winter CO ₂ and CH ₄ fluxes in Arctic tundra derived from snowpack gradient measurements

Winter carbon dioxide (CO ₂ ) and methane (CH ₄ ) fluxes from soils under seasonal snowpacks make non-negligible, yet poorly constrained contributions to annual carbon budgets across Arctic regions. Quantifying these fluxes and their spatial variance will better constrain uncertainties in simulations of winter carbon fluxes from terrestrial biosphere models. We address this gap by measuring and identifying patterns and spatial variability in CO ₂ and CH ₄ soil-atmosphere fluxes through late winter snowpacks at an upland tundra site in the western Canadian Arctic. Instantaneous fluxes were calculated from CO ₂ and CH ₄ microsite concentration gradients at 10 to 20 cm vertical resolution ( n =119) through the snowpack across five homogeneous surface covers, representing dominant vegetation types. We measured consistent soil-to-atmosphere CO ₂ fluxes but with significantly different rates across surface covers (0.8 to 100 mgC m ⁻²  d ⁻¹ ), which were strongly influenced by snow depth and soil surface temperature, exhibiting higher emissions under deeper snowpacks and warmer soil surfaces. CH ₄ fluxes were also coupled to soil surface temperature and varied between −0.04 and 0.08 mgC m ⁻²  d ⁻¹ . Persistent CH ₄ uptake was observed in warmer soils (−6.0 to −0.5 °C) in a sparsely populated black spruce and shrub dominated area with deep snow, indicating active methane oxidation during winter. Microsite scale CO ₂ and CH ₄ fluxes were statistically independent of vertical snow microstructure, indicating that winter fluxes could be reliably calculated from single gas concentration at the soil-snow interface, negating the need for additional snowpack gas measurements. These results open new avenues for quantifying fine-scale spatial variability of wintertime CO ₂ and CH ₄ fluxes in Arctic tundra, which can constrain biogeochemical process representations in terrestrial biosphere models and inform spatial upscaling methodologies.