Vegetation acts as a substantial link between the geosphere and atmosphere, mediating transpiration (E), and carbon assimilation (A). At the center of this process lie stomata, small pores which actively regulate the rate of CO2 and H2O diffusion between vegetation and the environment. This process, known as stomatal conductance (gsw) helps set the upper limit on E, and through stomatal limitation on A, is a strong determinant of net primary productivity. A series of mathematical models have been developed to predict the sensitivity of gsw to environmental factors, which have been incorporated into land surface models (LSMs). Despite the clear importance of accurately representing gsw in LSMs, major uncertainty remains in the factors influencing the model parameters related to gsw (the stomatal slope and stomatal intercept), particularly in how they are estimated from data, their temporal consistency, and their degree of variation within plant functional types (PFTs). In this dissertation, utilizing a combination of experimental manipulation, observational study, and mathematical and statistical modeling, I assess these three main sources of stomatal parameter uncertainty. My findings demonstrate that when unaccounted-for, branch excision combined with prolonged wait time can substantially impact the estimation of stomatal slope, with consequences for modeled transpiration. Further, I show that in a tropical evergreen forest, stomatal parameters exhibit diurnal variation, with water use efficiency (WUE) increasing throughout the day, however among leaves of different age classes, stomatal behavior is similar. In a temperate deciduous forest, where leaf ontogeny is closely match with seasonality, I show that stomatal and photosynthetic parameters display substantial variation across the growing season. I next demonstrate that stomatal parameters measured in the Arctic differ substantially from default LSM assumptions, and when updated parameters are applied to the model, ecosystem-scale WUE decreases significantly. Finally, using Bayesian modeling, I calculate a set of PFT specific stomatal parameters which can be used to parameterize LSMs, or serve as informative priors for future Bayesian model development. Overall, I demonstrate the effects of several biotic and abiotic drivers of variation in stomatal parameters, which contribute to significant uncertainty in LSM representation of instantaneous gsw and evapotranspiration.



Document Type



Stomata, Water Use Efficiency, Photosynthesis, Terrestrial Biosphere Model

Degree Name

Doctor of Philosophy (PhD)


Shawn P. Serbin