Microtopography Determines How CO2 and CH4 Exchanges Respond to Temperature and Precipitation at an Arctic Polygonal Tundra Site
Collaborating with Prof. Robert Grant of the University of Alberta, we applied a three-dimensional mechanistic ecosystem model (ecosys) to quantify and spatially scale the effects of fine-scale polygonal microtopography on biogeochemistry, hydrology, and surface gas and energy exchanges with the atmosphere (Grant et al. 2017). We first demonstrated excellent agreement between ecosys predictions and NGEE-Arctic observations of soil temperature, soil moisture, and surface energy, CH4, and CO2 fluxes (Figure). We then tested hypotheses for topographic controls on CO2 and CH4 exchange in trough, rim, and center features of low- and flat-centered polygons (LCP and FCP) against chamber and eddy covariance (EC) measurements. Larger CO2 influxes and CH4 effluxes were measured with chambers and modeled with ecosys in LCPs than in FCPs and in troughs than in rims within LCPs and FCPs. Spatially aggregated predicted CO2 and CH4 fluxes were significantly correlated with EC flux measurements. Lower features were modeled as C sinks and CH4 sources, and higher features as near C and CH4 neutral. Much of the spatial and temporal variations in CO2 and CH4 fluxes were modeled from topographic effects on water and snow movement. Interestingly, net primary productivity in higher features and CH4 emissions across the landscape increased from 1981 to 2015, attributed more to precipitation than temperatures increases. Finally, although small-scale variation in surface elevation causes large spatial variation of GHG exchanges, our results demonstrate a potentially useful spatial scaling approach that accurately captured landscape-scale states and exchanges with the atmosphere.
Reference: Grant, R. F., A. A. Mekonnen, W. J. Riley, B. Arora, and M. S. Torn 2017a. Microtopography Determines How CO2 and CH4 Exchange Responds to Changes in Temperature and Precipitation at an Arctic Polygonal Tundra Site: Mathematical Modelling with Ecosys, JGR-Biogeosciences, http://dx.doi.org/10.1002/2017JG004037.