Connecting methane fluxes to vegetation cover and water table fluctuations at microsite level: A modeling study
Peatland Ecology and Forestry, Department of Forest Ecology,
P.O. Box 24, FIN-00014 Helsinki University, FINLAND
Systems Analysis Laboratory Research Reports E10 November 2002
The paper presents a process-based model describing methane flux dynamics in different microsites of boreal peatlands. The simulated fluxes matched well to measurements in all microsites without any parameter adjustment. The model emphasizes the importance of microsite characteristics, water table and vegetation cover for methane fluxes. Water level determines the moisture and oxygen profile in peat matrix and therefore affects methane production and oxidation rates in peat profile. Vascular plants provide methanogenesis with substrates, form a pathway for methane to liberate from peat to the atmosphere and enhance methane oxidation by transporting oxygen to water saturated peat. The model connects methane fluxes to the seasonal photosynthetic cycle of plants at the microsite level and hence dynamically combines the microbial processes in peat to changing environmental factors in the level of peatland ecosystem. Sensitivity analysis of the model reveals the importance of substrate supply to methane fluxes. In addition, the capability of the vascular plants to transport oxygen downwards has a large effect on model outcome. Lack of oxygen and methane keep methane oxidation at a low level in the model simulations and changes that compensate for these lacks have a remarkable decreasing effect on simulated flux. Dry periods decrease the simulated methane flux considerably, especially if the drought prevails long, threshold for a dramatic decrease lying between 4 and 6 weeks of drought. Increase in air temperature enchances methane flux especially if the effect of increased temperature on gross primary production is taken into account.
boreal peatlands, microsites, vegetation cover, water table, photosynthetic carbon cycle, methane flux dynamics, process-based models