Presented within this thesis are three studies on three rare and imperiled Southeastern woody plant species: mountain stewartia (Stewartia ovata), Atlantic white-cedar (Chamaecyparis thyoides), and Miller's witch-alder (Fothergilla milleri). This work contributes to the ecological understanding of these three species allowing for better-informed conservation decision-making. Machine learning habitat suitability models are presented for mountain stewartia and Miller's witch-alder. These models can direct limited conservation dollars and manpower towards areas of the highest habitat suitability. This work also utilizes field-based data to assess the habitat needs, species associations, and regeneration potential of both Atlantic white-cedar and Miller's witch-alder. Understanding the habitat and regeneration potential of these species allows conservationists to make more tailored land management decisions for the species. As plant species continue to be threatened with extinction, more basic and applied research is needed to lessen the impacts of the 6th mass extinction on native flora.