Environmental controls of winter soil carbon dioxide fluxes in boreal and tundra environments

The carbon cycle in Arctic–boreal regions (ABRs) is an important component of the planetary carbon balance, with growing concerns about the consequences of ABR warming for the global climate system. The greatest uncertainty in annual carbon dioxide (inline-formulaCO₂) budgets exists during winter, primarily due to challenges with data availability and limited spatial coverage in measurements. The goal of this study was to determine the main environmental controls of winter inline-formulaCO₂ fluxes in ABRs over a latitudinal gradient (45inline-formula^∘ to 69inline-formula^∘ N) featuring four different ecosystem types: closed-crown coniferous boreal forest, open-crown coniferous boreal forest, erect-shrub tundra, and prostrate-shrub tundra. inline-formulaCO₂ fluxes calculated using a snowpack diffusion gradient method (inline-formulan=560) ranged from 0 to 1.05 inline-formulag C m² d⁻¹. To assess the dominant environmental controls governing inline-formulaCO₂ fluxes, a random forest machine learning approach was used. We identified soil temperature as the main control of winter inline-formulaCO₂ fluxes with 68 % of relative model importance, except when soil liquid water occurred during 0 inline-formula^∘C curtain conditions (i.e., inline-formulaT_soil≈0 inline-formula^∘C and liquid water coexist with ice in soil pores). Under zero-curtain conditions, liquid water content became the main control of inline-formulaCO₂ fluxes with 87 % of relative model importance. We observed exponential regressions between inline-formulaCO₂ fluxes and soil temperature in fully frozen soils (inline-formulaRMSE=0.024 inline-formula $M16inlinescrollmathmlunit\mathrm{normal\; g}\mathrm{normal\; C}{\mathrm{normal\; m}}^{-\mathrm{normal\; 2}}{\mathrm{normal\; d}}^{-\mathrm{normal\; 1}}$ 56pt15ptsvg-formulamathimg846265b129470ed2a785e3fc2495bc89 bg-20-5087-2023-ie00001.svg56pt15ptbg-20-5087-2023-ie00001.png ; 70.3 % of mean inline-formula $M17inlinescrollmathml{F}_{chem{\mathrm{normal\; CO}}_{\mathrm{normal\; 2}}}$ 23pt14ptsvg-formulamathimge6fbe75052c27002d7e521aeffa5e738 bg-20-5087-2023-ie00002.svg23pt14ptbg-20-5087-2023-ie00002.png ) and soils around the freezing point inline-formula(RMSE=0.286 inline-formula $M19inlinescrollmathmlunit\mathrm{normal\; g}\mathrm{normal\; C}{\mathrm{normal\; m}}^{-\mathrm{normal\; 2}}{\mathrm{normal\; d}}^{-\mathrm{normal\; 1}}$ 56pt15ptsvg-formulamathimgf18e355a8de23fb1f308fdd6806f0e55 bg-20-5087-2023-ie00003.svg56pt15ptbg-20-5087-2023-ie00003.png ; 112.4 % of mean inline-formula $M20inlinescrollmathml{F}_{chem{\mathrm{normal\; CO}}_{\mathrm{normal\; 2}}}$ 23pt14ptsvg-formulamathimga04de94a648508ebd0c86500eff6fdc4 bg-20-5087-2023-ie00004.svg23pt14ptbg-20-5087-2023-ie00004.png ). inline-formula $M21inlinescrollmathml{F}_{chem{\mathrm{normal\; CO}}_{\mathrm{normal\; 2}}}$ 23pt14ptsvg-formulamathimg2244228303899c15525382143556d337 bg-20-5087-2023-ie00005.svg23pt14ptbg-20-5087-2023-ie00005.png increases more rapidly with inline-formulaT_soil around the freezing point than at inline-formulaT_soil<5 inline-formula^∘C. In zero-curtain conditions, the strongest regression was found with soil liquid water content (inline-formulaRMSE=0.137 inline-formula $M26inlinescrollmathmlunit\mathrm{normal\; g}\mathrm{normal\; C}{\mathrm{normal\; m}}^{-\mathrm{normal\; 2}}{\mathrm{normal\; d}}^{-\mathrm{normal\; 1}}$ 56pt15ptsvg-formulamathimg59d9b78a4504cfd25729d06cb261adc3 bg-20-5087-2023-ie00006.svg56pt15ptbg-20-5087-2023-ie00006.png ; 49.1 % of mean inline-formula $M27inlinescrollmathml{F}_{chem{\mathrm{normal\; CO}}_{\mathrm{normal\; 2}}}$ 23pt14ptsvg-formulamathimgee2cd42833ae1a20ede6dcdf6a988edc bg-20-5087-2023-ie00007.svg23pt14ptbg-20-5087-2023-ie00007.png ). This study shows the role of several variables in the spatio-temporal variability in inline-formulaCO₂ fluxes in ABRs during winter and highlights that the complex vegetation–snow–soil interactions in northern environments must be considered when studying what drives the spatial variability in soil carbon emissions during winter.