Modeling Stomatal Conductance

Abstract

Recent advances have improved our ability to model stomatal conductance using process- or optimality-based models, and continuing research should focus on how stomata sense leaf turgor and on how to quantify the direct carbon costs of low leaf water potential.

Figure 1.

Stomatal responses to leaf turgor integrate effects of several other factors. A, Many stomatal responses arise from the effect of leaf water potential, which integrates the influences of many environmental and plant variables. Recent work has advanced the prospect of modeling these responses on a mechanistic basis by showing that the effect of leaf water potential on stomatal conductance is mediated by de novo leaf-endogeneous biosynthesis of ABA in response to reduced leaf turgor (B; McAdam et al., 2016), and stomatal responses to moderate soil drought can be explained almost entirely by effects mediated by leaf turgor (C; Rodriguez‐Dominguez et al., 2016).

Figure 2.

The presence of mesophyll is essential for normal stomatal responses to light and CO₂ in Tradescantia pallida, and the signal from the mesophyll may be a vapor‐phase ion. A to C, Responses of stomatal aperture to changes in photosynthetic photon flux density and ambient CO₂ concentration observed in intact leaves (A), epidermal peels (B), and epidermal peels placed onto mesophyll tissue (C). D, Responses of stomatal aperture in epidermal peels to activation of a large negative voltage (−860 V) in an electrode placed near the epidermis, with and without a barrier placed between the electrode and epidermal peel to prevent transport of matter without altering the electrical field. Modified from Mott et al. (2008) and Mott et al. (2014).

Figure 3.

Relationships that influence the optimal value of μ_w (∂A/∂E, the marginal carbon revenue of transpiring water—the increase in leaf carbon gain that would result from an infinitesimal increase in water loss). Changes in stomatal conductance and therefore water loss lead to immediate carbon gains (in photosynthesis) and costs (of repairing xylem embolisms resulting from reduced water potential), which directly affect ∂A/∂E. However, optimal carbon partitioning requires coordination between ∂A/∂E and the marginal carbon cost of acquiring water. Optimality‐based prediction of ∂A/∂E and thus, stomatal conductance, should consider these long‐term, amortized costs as well as the direct, immediate costs and benefits of variations in stomatal conductance.