Prove our models wrong: the differences between C4 and C3 photosynthesis

Background

So called C4 species, such as maize and sorghum have a higher photosynthetic capacity than C3 species like rice and wheat. The reason behind that is the fact that C4 crops maintain a higher CO₂ concentration at the site of Rubisco – the enzyme binding CO₂ during photosynthesis. However, this comes at a cost of extra ATP; photosynthetic light use efficiency under limiting lights may not be higher in C4 than in C3 species.

Our theoretical models predict that C4 photosynthesis has a more linear light response curve than C3 photosynthesis, and that such a difference in shape has a direct consequence on the optimum vertical light and nitrogen distribution in canopies for a maximized canopy photosynthesis. For instance, compared with C4 species, C3 plants would benefit more from a more uniform light distribution and from the optimum nitrogen distribution in canopy.

Challenge

In this project, you will be challenged to prove whether or not our models are wrong by addressing questions in both theory and reality:

• Theory: what are the consequences of the theoretical model predictions for the canopy photosynthesis of C3 and C4 species?
• Reality: are these theoretical predictions found in comparable C3, C4 and C3-C4 intermediate species (e.g. Panicum, Moricandia, Flaveria and Alloteropsis semialata) in actual experiments and measurements of photosynthesis?

Methods

You will design and conduct a set of simultaneous photosynthesis measurements (gas exchange and chlorophyll fluorescence) under various temperature, CO₂ and light conditions on leaves of these plants. At canopy levels, you will measure light and nitrogen profiles once canopy is established. The collected data will be combined with biochemical leaf-photosynthesis models for quantifying critical model parameters and sub-processes. These parameters will be incorporated into a canopy photosynthesis model considering light and N profiles.

Expectations

In the end, you will be able to use these models as a research tool, for example to:

• predict leaf photosynthesis for different environment scenarios
• conduct a sensitivity analysis for identifying options with which leaf and canopy photosynthesis can be further enhanced.

The obtained quantitative understanding of photosynthesis in general may have strong implications for crop production of both sustainable food and bio-energy supply.