Modeling boreal forest’s mineral soil and peat C stock dynamics with Yasso07 model coupled with updated moisture modifier

Abstract. As soil microbial respiration is the major component of land CO₂ emissions, differences in the functional dependence of respiration on soil moisture among the Earth system models (ESM) contributes significantly to the uncertainties in their projections.

Using soil organic C (SOC) stocks and CO₂ data from a boreal forest – mire ecotone in Finland and Bayesian data assimilation, we revised the precipitation-based environmental function of the Yasso07 soil carbon model. We fit this function to the observed microbial respiration response to moisture and compared its performance against the original Yasso07 model and the version used in the JSBACH land surface model with a reduction constant for decomposition rates in wetlands.

The Yasso07 soil C model coupled with the calibrated unimodal moisture function with an optimum in dry soils accurately reconstructed observed SOC stocks and soil CO₂ emissions and clearly outperformed previous model versions on paludified organo-mineral soils in forested peatlands and water-saturated organic soils in mires. The best estimate of the posterior moisture response of decomposition used both measurements of SOC stocks and CO₂ data from the full range of moisture conditions (from dry/xeric to wet/water-saturated soils). We observed unbiased residuals of SOC and CO₂ data modelled with the moisture optimum in well-drained soils, suggesting that this modified function accounts more precisely for the long-term SOC change dependency according to ecosystem properties as well as the contribution of short term CO₂ responses including extreme events.

The optimum moisture for decomposition in boreal forests was in dry well-drained soils instead of the mid-range between dry and water-saturated conditions as is commonly assumed among many soil C and ESM models. Although the unimodal moisture modifier with an optimum in well-drained soils implicitly incorporates robust biogeochemical mechanisms of SOC accumulation and CO₂ emissions, it needs further evaluation with large scale data to determine if its use in land surface models will decrease the uncertainty of projections.