Leaf size, shape, and internal anatomy are extremely diverse but strongly constrained by functions such as light interception, CO$_2$ diffusion, and managing scarce resources like water and nitrogen. Two common assumptions are that plants i) cannot build tougher leaves without sacrificing photosynthesis and ii) cannot increase photosynthesis without decreasing water-use efficiency. In collaboration with physiologist Jeroni Galmés (UIB, Spain), I have shown that in contrast to (i) increased leaf toughness (higher leaf mass per area) weakly constrains the evolution of photosynthetic function among closely related species (Muir et al. 2014, 2017). Instead we find that faster CO$_2$ diffusion through the mesophyll can simultaneously increase water-use efficiency and photosynthetic rate, contra (ii). This may be important in arid-adapted tomato species that are water-wise yet grow fast during brief periods of water availability (Conesa et al. 2017).
Harnessing natural variation to improve plant growth without evaporating more water has vast potential for sustainable agriculture. To do this, I will use recently developed high-throughput physiological phenotyping methods, phylogenetics, and quantitative genetics to identify the traits and loci that allow desert tomatoes to break tradeoffs between photosynthesis and water-use efficiency. To that end, I am working with computational biologist Matthew Pennell (UBC) to develop
bayCi, an R package for studying the evolution of C$_3$ photosynthesis using Stan, a probabilistic programming language for Bayesian data analysis. My aim is to understand physiological mechanisms while generalizing across many closely related species.