Harnessing the power of data-driven models to improve management and detection of emerald ash borer
2022-05
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Harnessing the power of data-driven models to improve management and detection of emerald ash borer
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2022-05
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The emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), is an invasive beetle in North America. All North American species of ash (Fraxinus spp.) are susceptible to this beetle such that widespread mortality to ash is occurring as the beetle spreads. Since the discovery of emerald ash borer in North America in the early 2000s, much research has been devoted to improving management efforts that target this species. Here, I study the cold tolerance of Spathius galinae Belokobylskij & Strazanac (Hymenoptera: Braconidae), a classical biological control agent against emerald ash borer. I forecast the ability of this parasitoid to survive winters in the northern range of ash in North America. To improve monitoring and early detection of emerald ash borer, I also evaluate the range of attraction of baited green prism traps using a novel quantitative method. The traps were baited with the host volatile (3Z)-hexenol and the sex pheromone (3Z)-lactone. Lastly, I model the spread rate of emerald ash borer from its first detection in Michigan to present across North America to quantify anisotropy (i.e., directionality) in the rate of spread. I then determine how environmental factors known to affect the spread and demographics of insects are associated with these variable rates of spread. Collectively, my dissertation furthers improvements in monitoring and management efforts for this devastating invasive species.
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University of Minnesota Ph.D. dissertation. May 2022. Major: Entomology. Advisors: Brian Aukema, Robert Venette. 1 computer file (PDF); x, 116 pages.
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Wittman, Jacob. (2022). Harnessing the power of data-driven models to improve management and detection of emerald ash borer. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/241348.
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