The seasonality of autotrophic activity has large implications for resource cycling. Observing the patterns and studying the underlying processes behind these cycles provides insights into the way autotrophs respond to changing environments.
My work is primarily focused on the development of models which incorporate biological mechanisms. Models are developed in R and are tested against a combination of in situ physiological measurements, flux-derived measures of ecosystem productivity, and remotely sensed products.
Plant ecophysiology provides a way to mediate responses to exogenous factors. Plant functional traits are commonly recorded and used to characterize the responses of individuals based on suites of traits. These functional traits provide a straightforward way to begin incorporating physiological characteristics into modeling frameworks.
I use remote sensing as a tool for both observing and validating patterns in vegetation. The combination of high frequency temporal measurements from near-surface remote sensing platforms and broad spatial coverage provided by satellites is a powerful tool for assessing responses of vegetation to environmental conditions.