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    Testing environmental DNA sampling and predictive modeling as means to investigate wood frog (Rana sylvatica) distribution in Alaska and Northern Canada

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    Spangler_M_2017.pdf
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    Author
    Spangler, Mark Anthony
    Chair
    Huettmann, Falk
    Committee
    López, J. Andrés
    Barnes, Brian M.
    Keyword
    Wood frog
    Alaska
    Genetics
    Canada, Northern
    Geographical distribution
    Models
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/11122/8142
    Abstract
    Global amphibian declines over the past 30+ years have led to a greater awareness of amphibian conservation issues. Few amphibian species occur in northern landscapes, however, and the species that do occur are widely dispersed and at the northern extent of their range. Accordingly, amphibian research is not prioritized in northern landscapes. Deficient monitoring practices have resulted in incomplete distribution knowledge that impedes the management of wood frogs (Rana sylvatica) in Alaska and northern Canada. I developed an environmental DNA detection assay to complement monitoring practices at the northern extent of the wood frog's range. This assay was tested to be species-specific, allowing it to be implemented in areas where wood frogs may co-occur with other amphibian species. It can detect wood frog DNA in environmental samples to a concentration of 1.83 x 10⁻³ pg/μL. I further demonstrate that environmental DNA occurrence data can be used to predict wood frog distribution in the Fairbanks North Star Borough. I combined environmental DNA occurrence data with environmental GIS data and analyzed the resulting dataset with machine learning algorithms to define an ecological niche for the wood frog. This niche, when extrapolated to the landscape, results in a species distribution model that attains 74% predictive accuracy. Lastly, I conducted an environmental DNA mega-transect survey along the Elliot/Dalton Highway corridor in Alaska. I combined the results of this survey with citizen science occurrence data from past and current monitoring projects to create a set of alternative occurrence data. This alternative data was combined with environmental GIS data and analyzed with machine learning algorithms to create a species distribution model that achieves 92% predictive accuracy across Alaska and the Yukon Territory, Canada. These results improve upon prior species distribution models developed for wood frogs in Alaska. They provide deeper insights into potential wood frog distribution at high latitudes and elevations in Alaska, where anecdotal observations have previously been recorded. Adoption and widespread use of an environmental DNA monitoring protocol in under-sampled regions of Alaska and northern Canada will generate larger datasets with wider geographic coverage, leading to models with even higher predictive accuracy. Alternative data, including that obtained from environmental DNA and citizen science monitoring, can boost efforts to further develop baseline knowledge of wood frog occurrence in these areas. Species distribution models generated in this research can help guide these efforts. Increasing knowledge of wood frog distribution may assist conservation managers to designate critical habitat, study climate impacts, and make more informed decisions regarding amphibians in northern landscapes.
    Description
    Thesis (M.S.) University of Alaska Fairbanks, 2017
    Table of Contents
    Chapter 1 Development, validation, and evaluation of an assay for the detection of wood frogs (Rana sylvatica) in environmental DNA -- Chapter 2 Application of environmental DNA-based occurrence data in modeling wood frog (Rana sylvatica) distribution in Interior Alaska -- Chapter 3 A reassessment of wood frog (Rana sylvatica) distribution in Alaska and northern Canada based on environmental DNA and citizen science -- Conclusion -- References -- Appendices.
    Date
    2017-12
    Type
    Thesis
    Collections
    Biological Sciences

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