| dc.description.abstract | Global biodiversity loss and changing disturbance patterns are having significant effects on the composition, function, and productivity of biological communities. Functional diversity, a multifaceted trait-based component of biodiversity, is emerging as an effective metric of community function, resilience, and response to environmental change. Remote sensing techniques can be used to measure the biochemical, physiological, and morphological traits of plants and assess functional diversity across a landscape. In this study, I demonstrated the use of multispectral imagery and light detection and ranging (LiDAR) to determine relationships between physiological and morphological functional diversity metrics - functional richness, functional evenness, and functional divergence - and forest management implemented at Pushmataha Forest Habitat Research Demonstration Area (FHRA). Indices of vegetation biochemistry, physiology, and morphology were affected by forest management, including combinations of prescribed fire, selective thinning, and pine timber harvest, while the effects of management on functional diversity metrics estimated from remote sensing were less defined. Morphological functional evenness and divergence differed between treatments, and fire return interval was determined to play a key role in vegetation community morphology and functional diversity. By expanding the methodology to assess metrics of functional diversity across the larger forest-savanna landscape of Pushmataha Wildlife Management Area, I examined the scale dependency of functional diversity metrics and demonstrated the potential for using multispectral imagery from satellite platforms to fill gaps in global functional diversity knowledge. | |
