Spatial heterogeneity in soil hydrological and thermal regimes forms microtopography and has been identified as the key control on CH4 and CO2 fluxes in Arctic tundra ecosystems. By taking advantage of incorporating the key microbial processes, a mechanistic ecosystem model, CLM-Microbe, was applied to investigate the microtopographic effects on CH4 and CO2dynamics across seven primary landscape types in Barrow, Alaska: troughs, low-center-polygon (LCP) center, LCP transition, LCP rim, high-center-polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe against static-chamber measured CH4 and CO2 fluxes in 2013 for three landscape types: troughs, LCP center and LCP rim. Sensitivity analysis was conducted to examine the most important processes and parameters for CH4 and CO2 fluxes across seven landscape types. Then modeled CH4 and CO2 fluxes were up-scaled to the eddy covariance (EC) domain using an area-weighted approach for validating against EC fluxes.
Results/Conclusions
Model application indicated that larger CH4 emission and CO2uptake with greater seasonal variation during growing seasons were modeled in wet low-elevation landscape types (troughs, transitions and LCP center) than dry high-elevation types (rims and HCP center). Sensitivity analysis implied that substrate (acetate, CO2+H2) availability for methanogenesis is the most important factor determining CH4 emission in Arctic tundra ecosystems, and Rubisco enzyme activity and plant respiration largely affect the net ecosystem carbon exchange (NEE) and ecosystem respiration (ER). CLM-Microbe underestimated CH4 flux by 20.1% and 25.0% and NEE by 21.4% and -30.0% against EC measurements at daily and hourly time steps, respectively, that emphasize the importance of time scales in reporting CH4 and CO2 fluxes. The substantial differences of CH4 and CO2 fluxes regarding microtopography require a model-data integration framework to better understand and predict C flux across the highly heterogeneous Arctic landscape.