LAUSR

A mechanistic dynamic model predicts CO2 uptake, water release by C4 leaves, simulated stomatal responses and water use optimality in response to light fluctuations over 1 day. C4 plants are major grain (maize [Zea mays] and sorghum [Sorghum bicolor]), sugar (sugarcane [Saccharum officinarum]), and biofuel (Miscanthus spp.) producers and contribute ∼20% to global productivity. Plants lose water through stomatal pores in order to acquire CO2 (assimilation [A]) and control their carbon-for-water balance by regulating stomatal conductance (gS). The ability to mechanistically predict gS and A in response to atmospheric CO2, water availability, and time is critical for simulating stomatal control of plant-atmospheric carbon and water exchange under current, past, or future environmental conditions. Yet, dynamic mechanistic models for gS are lacking, especially for C4 photosynthesis. We developed and coupled a hydromechanical model of stomatal behavior with a biochemical model of C4 photosynthesis, calibrated using gas-exchange measurements in maize, and extended the coupled model with time-explicit functions to predict dynamic responses. We demonstrated the wider applicability of the model with three additional C4 grass species in which interspecific differences in stomatal behavior could be accounted for by fitting a single parameter. The model accurately predicted steady-state responses of gS to light, atmospheric CO2 and oxygen, soil drying, and evaporative demand as well as dynamic responses to light intensity. Further analyses suggest that the effect of variable leaf hydraulic conductance is negligible. Based on the model, we derived a set of equations suitable for incorporation in land surface models. Our model illuminates the processes underpinning stomatal control in C4 plants and suggests that the hydraulic benefits associated with fast stomatal responses of C4 grasses may have supported the evolution of C4 photosynthesis.