2026 Theses Doctoral

Advancing stomatal conductance models for drought and heatwave responses: disentangling stomatal and non-stomatal responses from multi-scale observations

Han, Jisu

Stomatal conductance (gs) represents the degree of coupling between the leaves and the atmosphere. It controls photosynthesis, transpiration, and plant temperatures, thereby fundamentally shaping the land-atmosphere interactions. Advancing gs representation for environmental stressors is an important goal to improve the terrestrial carbon-water cycle in land surface models.

In this work, I focused on the semi-empirical gs models that take photosynthetic carbon uptake as an argument. This widely used formulation inherently complicates disentangling stomatal (i.e., biophysical) and non-stomatal responses (i.e., mixed effect of biochemical and diffusional limitation, from the modulated photosynthetic capacity and mesophyll conductance regulation, respectively) from the observed change in gs. Correct attribution of stomatal and non-stomatal responses will determine successful prediction of carbon assimilation and transpiration in extreme events, especially given recent evidence of stomatal decoupling during heatwaves (suppressed photosynthesis while maintaining positive transpiration).

To address these problems, I developed frameworks to estimate and investigate the biophysical and biochemical parameters that control gs response using multi-scale observations. Firstly, I proposed an ensemble framework to estimate the photosynthetic capacity of the ecosystem at the leaf scale (Vcmax25, maximum rate of carboxylation at 25℃), which is applicable for eddy covariance measurement sites with soil moisture (SWC) and leaf area index measurements (LAI). This method generates weighted ensembles of biochemical (Vcmax25) and biophysical (g1, slope parameter for semi-empirical gs model) parameters for the gs model. Secondly, I performed global analysis on the flux-driven Vcmax25 and g1 responses to SWC as a time-agnostic function vary across the ecological gradients. Thirdly, I developed a differentiable hybrid model for gs using leaf gas-exchange measurements to obtain gradient-based attribution on leaf water potential and leaf temperature. This enables us to quantify gs sensitivity to leaf state variables and further decompose it into the sensitivity of Vcmax-mediated (non-stomatal) response and the rest (stomatal response).

Together, these cross-scale analyses provide a process-based framework to disentangle stomatal and non-stomatal controls on gs, offering an improved parameterization strategy that can enhance the robustness and predictive capacity of terrestrial biosphere models under climate extremes.