Influences of vegetation structure and elevation on CO₂ uptake in a mature jack pine forest in Saskatchewan, Canada

Eddy covariance (EC) is often used to measure the movement and direction of energy and trace gas concentrations in ecosystems. Data from EC networks are often combined with remote sensing data and ecosystem models in order to assess the spatial and temporal variability of carbon dioxide (CO₂) exchanges within specific areas of interest. This study presented a new method of determining changes in the structural characteristics of biomass and elevation. Lidar was used within the contours of half-hourly flux footprint areas to characterize vegetation structure and elevation. The influences of vegetation structure and elevation on CO₂ concentrations were measured by EC and Lidar measurements for 3 mature growing periods at a mature jack pine site in Saskatchewan. Mensuration data were collected over 2 periods. Meteorological, CO₂, and H2O flux measurements were collected for 30 minute periods each day. Statistical analyses were conducted to determine the influence of meteorological variables on vegetation structure. Footprint contour lines were then layered onto the canopy height models derived by the lidar data. Multiple regression equations were used to determine net ecosystem productivity (NEP) and gross ecosystem productivity (GEP) using meteorological variables, canopy fractional cover; and elevation, as well as the results obtained from a Landsberg equation. The study showed that differences in NEP variability were influenced by differences in canopy and ground surface characteristics within the site. EC measurements underestimated gross CO₂ fluxes by 5 per cent as the biomass was lower within the immediate vicinity of the EC network. It was concluded that canopy structures and elevation are important factors for determining annual carbon balances. 36 refs., 8 tabs., 9 figs