Marvin Browne in front of plants

The Fall 2023 Biology Seminar Series continues with a talk from Marvin Browne, "Prediction and Ecological Consequences of Variation in Leaf Drought Traits." The seminar is on Tuesday, September 19th, at 12:00pm.

Among the many constituents of a plant’s environment, water is critical to the functionality of most of a plant’s physiological processes. Therefore, it is imperative to clarify how plants acquire, retain, utilize, and lose water to understand how these organisms will perform in a changing environment. The most salient metrics of plant responses to drought at leaf scale are pressure volume (PV) curve traits, estimated from the relationship between leaf water potential (Ψleaf), a common measurement of water stress, and relative water content (RWC). These indices are correlated for a given dehydrating leaf and are physically interrelated. However, while PV traits are central in the analysis and prediction of drought tolerance there has been little characterization of the variation of PV parameters across leaves within species. To address this gap, I constructed a physically based model to discern and explain the patterns of changes in water status scaled from terahertz radiation in-situ remote sensing. Then, I estimated the impact of intraspecific variation and inter-relationships of pressure volume curve parameters on prediction and interpretation, establishing a novel baseline variation among sun leaves of 50 species. Lastly, I quantified intraspecific plasticity in the osmotic potential at full turgor (πo), an important drought tolerance trait, among ecotypes of a model species, Arabidopsis thaliana, and tested for associations among osmotic adjustment, drought survival, growth under well-watered conditions, and native climate. My work provides new resolution of the determinants of tissue water status, with applications at both small scales, such as clarifying the mechanistic traits underlying drought tolerance within species, and at larger scales, such as for spectroscopic estimation of plant water status.

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