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Graduate Defense: Stephanie Hudon

April 16 @ 10:00 am - 12:00 pm MDT

Dissertation Information

Title: Molecular Approaches for Analyzing Organismal and Environmental Interactions

Program: Doctor of Philosophy in Biomolecular Sciences

Advisor: Dr. Eric J. Hayden, Biological Sciences

Committee Members: Dr. Jennifer Forbey, Biological Sciences, and Dr. Matthew Ferguson, Physics

Abstract

Our planet is undergoing rapid change due to the expanding human population and climate change, which leads to extreme weather events and habitat loss. It is more important than ever to develop methods which can monitor the impact we are having on the biodiversity of our planet. In order to influence policy changes in wildlife and resource management practices, we need to provide measurable evidence of how we are affecting animal health and fitness and the ecosystems needed for their survival. We also need to pool our resources and work in interdisciplinary teams to find the common threads which can help preserve biodiversity and vital habitats. This dissertation provides advancements to two approaches to monitor the health and well-being of animal populations within changing ecosystems.

Chapter 1 details the development of a universal telomere assay for vertebrates. Recent work has shown the utility of telomere assays in tracking animal health and well-being. This has included predictions of extinction events in animal populations, estimates of life span and the effects of anthropogenic activity on animal fitness. Telomere length assays are an improvement over other methods of measuring animal stress, such as cortisol levels, since they are stable during capture and sampling of animals. This dissertation provides a telomere length assay which can be used for any vertebrate. The assay was developed using a quantitative polymerase chain reaction platform which requires low DNA input and is rapid. It demonstrates how this assay improves on current telomere assays developed for mice and can be used in a vertebrate not previously assayed for telomere lengths, the American kestrel. This work has the potential to propel research in vertebrate systems forward as it alleviates the need to develop new reference primers for each model system. This assay has been well received by the scientific community and has already been utilized in mouse cell line studies, American kestrels, golden eagles, five species of passerine birds, bighorn sheep, osprey and northern goshawks.

Chapter 2 presents a machine learning analysis, utilizing a topic model approach, to integrate big data from remote sensing, leaf area index surveys, sagebrush metabolomics and sagebrush herbivore metagenomics. The sagebrush steppe is home to several threatened species including the pygmy rabbit and sage grouse. It covers vast swaths of the western United States and is subject to habitat fragmentation and land use conversion for both farming and rangeland use. It also is threatened by increases in fire events which can dramatically alter the landscape. Restoration efforts have been hampered by a lack of resources and often by inadequate collaboration between stake holders and scientists. This work brought together scientists from four disciplines to provide a framework for how studies can be designed and analyzed which integrate patterns of biodiversity from multiple scales, from the molecular scale to the landscape scale. A topic model approach was utilized which groups features (chemicals, bacterial and plant taxa, and remote sensing spectra) into communities, which in turn can be analyzed for their presence within individual samples and time points. Within the landscape I found communities which contain encroaching plant species, such as juniper and cheat grass, and within plants I found chemicals which are known toxins to herbivores. Additionally, I identified differences in bacterial taxonomical communities when a sagebrush herbivore is transitioned from a sagebrush-containing diet to a commercial diet. This work will help to inform restoration efforts and provide a road map for designing interdisciplinary studies.