Effects of rising CO2 concentrations on photosynthetic traits and leaf morphology to test optimality framework

The eco-evolutionary optimality principle, which states that natural selection rapidly eliminates uncompetitive combinations of traits, has proven to be a powerful source of testable hypotheses and predicting patterns in vegetation structure and composition. In this context, Prentice et al. (2014) proposed an optimality framework for plant functional ecology, which predicts relationships between parameters of photosynthetic biochemistry and stomatal conductance (g_s). Leaf morphology plays an essential role herein, as shown by the conservative g_s/g_smax ratio (McElwain et al., 2016) and the strong correlation between maximum photosynthesis rate and leaf hydraulic traits (Brodribb et al., 2007). The aim of this research is to determine how such leaf morphological adaptations relate to adaptations of photosynthetic traits, mainly  g_s/g_smax and V_cmax, over different timescales. Here we present empirical data to test predicted effects of changing CO₂ concentrations on V_cmax, C_i/C_a, J_max, g_s, and leaf morphology, according to the optimality framework.

The effects were tested in two genotypes of Solanum dulcamara (bittersweet) that were grown from seeds to maturity under 200, 400 and 800 ppm CO₂ in walk-in growth chambers with tight control on light, temperature and humidity. The genotypes were grown from two distinct natural populations; one adapted to well-drained sandy soil (the 'dry' genotype) and one adapted to poorly-drained clayey soil (the 'wet' genotype). Measurements of photosynthetic traits were obtained with a portable photosynthesis system. Morphological and developmental leaf traits were measured on microscopy images, after plant maturation.

The results show that the optimality framework is suitable to predict changes in the photosynthetic traits under changing atmospheric CO₂ concentrations. With higher concentrations, the V_cmax decreased in both S. dulcamara genotypes. Also, at each CO₂ growth level, the dry genotype showed a higher Huber value and a lower V_cmax than the wet genotype, indicating that the ‘dry’ genotype combines a relatively high cost of transpiration with a low cost of photosynthesis, and the ‘wet’ genotype vice versa. The down-regulation of V_cmax under high CO₂ was strongest in the dry genotype, and the downregulation of g_s the strongest in the wet genotype, in line with the predicted trade-off between the costs of transpiration and photosynthesis.

The two leaf morphological traits with the clearest CO₂ response were leaf vein density and guard cell length, which were also strongly correlated. Interestingly, stomatal density showed no CO₂ response in this species, but is correlated to the guard cell length. Overall, our empirical data support the optimality responses in photosynthetic traits and g_s, however, leaf morphological responses appear less consistent with the theory. More research, including experiments over a longer timescale will provide more insight in these relationships.