Doctoral Dissertation Research: Predicting the spread of Rapid Ohia Death and detecting resistant varieties of Metrosideros polymorpha

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This project develops mitigation strategies to lessen the ecological, economic, and social consequences of forest pathogens. Tools that allow forest managers to accurately monitor disease spread across large spatial scales and identify hosts resistant to forest pathogens are critical to controlling disease outbreaks. This project uses remote sensing to develop a monitoring system for Rapid Ohia Death, a problematic pathogen affecting native forest areas, and a means of identifying resistant hosts to assist in the design of conservation strategies. Discovered in 2010, Rapid Ohia Death has led to widespread declines of the keystone species, Metrosideros polymorpha, though the extent of its effect is unknown due to the lack of precise monitoring systems. M. polymorpha accounts for over eighty percent of the biomass across forests, provides habitat to many endemic plants and animals, is vital for groundwater recharge, and is culturally and economically significant to local communities. As a result, many conservation agencies seek to understand and mitigate the threat of Rapid Ohia Death. This project contributes to efforts to conserve native forests by spatially mapping M. polymorpha, its four genetic varieties, and Rapid Ohia Death spread across using state-of-the-art remote sensing technologies. Existing forest species maps are over 20 years old and rely on remote sensing instruments with coarse spatial and spectral resolution. Not only does this award update these M. polymorpha spatial maps, but it also improves upon their accuracy and precision by using high resolution remote sensing data from an airborne imaging spectrometer. This award goes further than species mapping by developing novel landscape-scale spatial data of the four described M. polymorpha subspecies. By fusing maps and data from multispectral satellites, this project tracks Rapid Ohia Death spread through time. These datasets provide the foundation for understanding disease spread and host resistance. Combined, these data products and resulting information will expedite the process of restoring forests with Rapid Ohia Death-resistant M. polymorpha individuals. This research focuses on the needs of federal, State, and private organizations, and resulting data products will be integrated into their mitigation strategies. This project contributes to forest conservation by developing novel methods and datasets to understand the spatial ecology of disease spread regarding host resistance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.