In the Hawaiian dry forest, 45% of all tropical dry forest trees and shrubs are on the federal threatened and endangered species list. Research is needed to focus on understanding the current range of these endangered species, the factors that affect their current and future distributions, and ultimately, possible areas for the most successful restoration to be undertaken. This research uses species distribution modeling to predict the potential range of Hibiscus brackenridgei, the state flower of Hawaii and a federally endangered species found on Oahu. We used presence data and the modeling algorithm Maxent to model the current potential distribution of H. brackenridgei, identify climate and environmental variables that influence the species' distribution, and model the species' predicted future distribution based on a range of projected climate change scenarios. Statistical analysis suggests that the Maxent models accurately predict the species' distribution, and therefore, may be useful for conservation management. Comparing the current model with the future models of changes for 2060-2089, changes in the potential niche of H. brackenridgei only range from -4% to 14%. This suggests that the predicted changes in climate, under both low (B2a) and high (A2a) global emissions scenarios, may not significantly impact the future distribution of H. brackenridgei on Oahu. We identified a total of 115 km2 of very highly (≥0.70) and highly (≥ 0.50) suitable habitat which represents potential areas where restoration projects could be implemented. This research suggests that threats like habitat loss, fire, invasive species, and grazing may be more important than climate for the future conservation of Hawaiian dry forest species.

Tropical dry forests in Hawaii are among the most endangered forest types in the world with half of all plant species listed as federally threatened or endangered. Although there have been some efforts to protect remaining dry forest fragments, conservation of this ecosystem has proven difficult due to a poor understanding of the current distribution of native species, environmental factors influencing their distributions, potential sites for species reintroductions, and of how the dry forest has changed over the past 30 years. This dissertation addresses the question: How can field-based methods, habitat suitability modeling (HSM), geographic information systems (GIS), and remote sensing improve conservation and restoration efforts in Hawaii’s dry forest? To answer this question, habitat suitability modeling is used to assess factors influencing species distributions and identify potential sites for endangered species restoration. Secondly, a field-based case study is conducted to evaluate the environmental variables affecting restoration success of an endangered plant. Finally, GIS and remote sensing are used to assess changes in dry forest dynamics over the past decade across the Hawaiian Islands. Results from habitat suitability

modeling suggest that topography and soil variables may be a key driver in the distribution of endangered dry forest species and that current protected areas may not capture the best habitat for reintroductions. Furthermore, results from the restoration study suggest that sites with low soil moisture and high exposure to sunlight may be the most suitable reintroduction sites for endangered dry forest species like, Hibiscus brackenridgei. The methodology and findings from this dissertation will provide a framework for conservation management of endangered dry forest fragments in Hawaii as well as other oceanic islands