Determining Invasive Plant Hot Spots in Sleeping Bear Dunes National Lakeshore to Inform Early Detection and Rapid Response Initiatives

Management of invasive plant species can be a high continual cost in terms of treatment, therefor prevention and early detection efforts are key to protecting natural areas. A tool in the arsenal of natural resource management: modeling, for invasive species in regions of lessened human impact i.e. in parks and wilderness areas creates opportunities to find trends in dispersal and increased density of invasive species to then pre-emptively assess and promote restoration efforts in order to keep out invaders. In this study “hotspots” were evaluated using the loglikelihood calculated for invasive plant diversity per square meter of trail surveyed in Sleeping Bear Dunes National Lakeshore, and significant environmental variables were assessed. The effort of this project was to determine the utility of invasive plant data collected from an Early Detection and Rapid Response program and subsequent survey during May 2018 - August 2018 for the development of a hot spot detection tool using most common species present on North and South Manitou Island in the National Lakeshore. Model results are limited in their use due to the limits of the data collected which contains high variability due to environmental variables and potential outside confounding factors since no ground-truthing has been evaluated. However, data provided from this project helps indicate regions that may have high potential for invasion and confirms some anecdotal observations of species occurrences. Additionally, recommendations from this project can be utilized to design data collection in future programs that is both rapid and can be utilized more effectively to model, evaluate, and manage invasive species hotspots with more accuracy in the future.Master of Science (MS)School for Environment and SustainabilityUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/150629/1/Canniff_Patrick_Practicum.pd