Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants

doi:10.1071/PP9920519

Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C₄ Plants

GJ Collatz, M Ribas-Carbo and JA Berry

Australian Journal of Plant Physiology 19(5) 519 - 538

Abstract

Leaf based models of net photosynthesis (A_n) and stomatal conductance (g) are often components of whole plant, canopy and regional models of net primary productivity and surface energy balance. Since C₄ metabolism shows unique responses to environmental conditions and C₄ species are important agriculturally and ecologically, a realistic and accurate leaf model specific to C₄ plants is needed. In this paper we develop a simple model for predicting A_n and g from leaves of C₄ plants that is easily parameterised and that predicts many of the important environmental responses.

We derive the leaf model from a simple biochemical-intercellular transport model of C₄ photosynthesis that includes inorganic carbon fixation by PEP carboxylase, light dependent generation of PEP and RuBP, rubisco reaction kinetics, and the diffusion of inorganic carbon and O₂ between the bundle sheath and mesophyll. We argue that under most conditions these processes can be described simply as three potentially limiting steps. The leaf photosynthesis model treats A_n as first order with respect to either light, CO₂ or the amount of rubisco present and produces a continuous transition between limitations. The independent variables of the leaf photosynthesis model are leaf temperature (T_I), intercellular CO₂ levels and the absorbed quantum flux.

A simple linear model of g in terms of A_n and leaf surface CO₂ level (p_s) and relative humidity (h_s) is combined with the photosynthesis model to give leaf photosynthesis as a function of absorbed quantum flux, T₁ and p_s and h_s levels.

Gas exchange measurements from corn leaves exposed to varied light, CO₂ and temperature levels are used to parameterise and test the models. Model parameters are determined by fitting the models to a set of 21 measurements. The behaviour of the models is compared with an independent set of 71 measurements, and the predictions are shown to be highly correlated with the data.

Under most conditions the leaf model can be parameterised simply by determining the level of rubisco in the leaves. The effects of light environment, nutritional status and water stress levels on A_n and g can be accounted for by appropriate adjustment of the capacity for rubisco to fix CO₂. We estimate rubsico capacity from CO₂ and light saturated photosynthesis although leaf nitrogen content or rubisco assays from leaf extracts could also be used for this purpose.