Beyond the Big Leaf: Quantifying Interactions between Canopy Structure and Canopy Photosynthesis Using Isotopic Partitioning of Net Ecosystem-Atmosphere Exchange of CO2 in a Temperate Forest

Abstract:

Measurements of the forest-atmosphere exchange of carbon isotopes can be used to partition the net total carbon exchange (measured by standard eddy covariance) into its photosynthetic and respiratory components. This partitioning requires an estimate of the isotopic signature of canopy-scale photosynthesis, which has been obtained to date by assuming that the canopy behaves like a single ‘big leaf’. This assumption neglects the heterogeneity of the canopy both vertically and with respect to leaf angles: leaves at various heights and angles experience different sunlight, temperature, and wind, and are physiologically different as well. In order to explore errors associated with the big leaf assumption, we applied a big leaf isotopic partitioning algorithm to canopy-scale net fluxes of ¹³CO₂, ¹²CO₂, heat, and water generated by a multi-leaf isotopic canopy simulation. The simulation included micro-environmental heterogeneity produced by the canopy geometry (leaf angles and arrangement) as well as physiological variation among leaves, invoking leaf-level energy balance to determine leaf temperatures. Leaf behavior in the simulation was parameterized by leaf-level gas-exchange measurements of the relevant characteristics of a range of leaves in the canopy (e.g. limiting photosynthetic rates, stomatal conductance, daytime respiration). These measurements indicated that photosynthetic capacity increased with height in the canopy, but that within a given canopy layer, leaf behavior showed surprisingly little variability. They also indicated that stomatal conductance did not relate quasi-linearly to light or photosynthetic rate, but was instead roughly constant with light at all photosynthetic photon flux densities above 100 μE m^-2 s^-1. The multi-leaf simulation incorporating these leaf behaviors suggested that the big leaf assumption is valid under diffuse light conditions but can lead to significant errors under clear sky conditions.