Monitoring vegetation dynamics in an efficient and non-invasive way has become increasingly more important for assessing and modeling their responses to the environment and mitigating for climate change. Vegetation optical properties can be used to derive vegetation indices (VIs) which can be used as proxy measures for plants’ biophysical traits. The goal of this dissertation is to use proximal and remote sensing techniques to identify scalable indices and indicators that can be used efficiently to assess vegetation health and performance. The dissertation consists of four studies, each of which tackles different ecological questions utilizing proximal and/or remote sensing methods.

Results from this study are important for the ability to monitor vegetation shifts across multiple scales, important for predicting directional changes of these ecosystems in the face of anthropogenic management and climate change, and the development of effective mitigation plans.