CAREER: A cross-scale, data-efficient approach to understanding plant hydraulic regulation using optimization and maximum entropy

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Plants affect water, carbon, and energy cycles by using water and carbon dioxide (CO2) to photosynthesize and grow. CO2 enters plants through small openings on leaves, called stomata, while water is taken up by roots in the ground and transported to the leaves by plants’ vascular systems. How efficiently the plant stomata and vascular systems work to supply water and CO2 to the plant – through a process called plant hydraulic regulation – depends on a range of environmental conditions (e.g., dryness in the soil and in the air) and plant characteristics. This project will use the mathematical optimization of plant performance to understand how hydraulic regulation impacts stomatal openings (at the leaf scale), carbon use and storage (at the whole-plant scale), and the spatial distribution of plant types (at the ecosystem scale) over different timescales of environmental variation. New insight into how plants cope with variation in environmental conditions can be used to more accurately incorporate plant hydraulic regulation into modeling frameworks, which would allow more accurate predictions of global water, carbon, and energy cycles. Additionally, this project aims to promote systems thinking in the general public and in middle school, undergraduate, and graduate students. The project plans to develop and implement interactive exhibits at the Bell Museum and classes at the University of Minnesota that integrate Earth system science and environmental engineering, both using the context of plant water use in variable environments.This project uses optimization and maximum entropy to improve the understanding and prediction of plant hydraulic regulation at the leaf, plant, and ecosystem scales. At the leaf level, optimal stomatal conductance will be derived such that it maximizes cumulative carbon assimilation over a season, subject to competition and carryover costs. At the whole-plant level, optimal plant carbon allocation will be derived such that it maximizes cumulative net carbon gain over multiple years, subject to legacy effects of drought. At the ecosystem level, the composition of plant hydraulic traits will be derived such that it maximizes the information entropy of the resulting trait distribution, representing the most likely trait configuration under environmental constraints. The educational products from this project will include an interactive makerspace exhibit and summer camp module for middle school students at the Bell Museum, as well as new course modules for undergraduate and graduate students to adopt interdisciplinary practices for environmental engineering and complex environmental systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.