Improving Models of Photosynthetic Thermal Acclimation: Which Parameters are Most Important and How Many Should Be Modified?

Photosynthetic temperature acclimation could strongly affect coupled vegetation-atmosphere feedbacks in the global carbon cycle, especially as the climate warms. Thermal acclimation of photosynthesis can be modelled as changes in the parameters describing the direct effect of temperature on photosynthetic capacity (activation energy, Ea; deactivation energy, Hd; entropy parameter, ΔS) or the basal value of photosynthetic capacity (i.e. photosynthetic capacity measured at 25 °C), however the impact of acclimating these parameters (individually or in combination) on vegetative carbon gain is relatively unexplored. Here we compare the ability of 66 photosynthetic temperature acclimation scenarios to improve predictions of a spatially explicit canopy carbon flux model, MAESTRA, for eddy covariance data from a loblolly pine forest. We show that: 1) incorporating seasonal temperature acclimation of basal photosynthetic capacity improves the model's ability to capture seasonal changes in carbon fluxes; 2) multifactor scenarios of photosynthetic temperature acclimation provide minimal (if any) improvement in model performance over single factor acclimation scenarios; 3) acclimation of enzyme activation energies should be restricted to the temperature ranges of the data from which the equations are derived; and 4) model performance is strongly affected by the choice of deactivation energy. We suggest that a renewed effort be made into understanding the thermal acclimation of enzyme activation and deactivation energies across broad temperature ranges to better understand the mechanisms underlying thermal photosynthetic acclimation.