Application of Proximal and Remote Sensing Methods for Estimating Important Morphological and Ecophysiological Plant Traits

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 are 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. There are four studies in this dissertation that tackle different ecological questions utilizing proximal and/or remote sensing methods.The first study investigates the use of novel high throughput plant phenomics (HTPP) techniques to quantify Quercus bicolor¬ and Quercus prinoides seedlings responses to drought stress. Results showed that HTPP can detect early onset of drought and differences between species, which has significant implications for forest management and tree improvement programs. The second study investigates the impacts of Juniperus virginiana and Pinus ponderosa expansion on grasslands health in Nebraska Sandhills and examines the use of optical-based approaches as indicators for successful monitoring of grasslands. Results demonstrated that VIs can serve as efficient non-invasive tools that can be part of multi-scale integrative grassland management strategies. The third study investigates the effects of different fertilization treatments on Bromus inermis pastures under rotational grazing, through the synergistic use of proximal sensing and traditional destructive and non-destructive techniques. Results indicated the successful use of VIs in identifying the effect of fertilization and grazing on growth and ecophysiological traits in pastures. Last, the fourth study uses multiscale sensing techniques to identify scalable traits using proximal and remote sensing methods as a way for faster and more efficient monitoring of brome pastures.Results from this dissertation are important for the ability to monitor vegetation shifts across multiple scales, which is important for predicting directional changes of these ecosystems in the face of anthropogenic management and climate change, and the development of effective mitigation plans