Date of Award

Fall 12-20-2024

Level of Access Assigned by Author

Open-Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Ecology and Environmental Sciences

Advisor

Matthew Chatfield

Second Committee Member

Michael Kinnison

Third Committee Member

Tanya Lama

Additional Committee Members

Erin Grey

Joseph Zydlewski

Abstract

Species threatened with extinction require careful and informed management strategies to ensure stability and recovery. Unfortunately, many threatened species are subject to conservation measures that operate with relatively little information and major confidence gaps. Among the contributing factors to this issue is the challenge in locating species of conservation interest; many are cryptic by nature, and only become more difficult to detect as their abundance decreases. Traditional methods can require significant quantities of time and money to acquire relatively little information. Additionally, traditional methods of monitoring may be harmful or disruptive to species that are declining, which may frequently be more sensitive to human contact than common species. Biologists are thus faced with a wicked problem; with limited time, money, and ability to detect threatened species, they must somehow acquire data and develop management plans with methods that are often costly, time-consuming, and offer little data. Environmental DNA (eDNA) methodology has come to light in the previous decade as a potentially highly sensitive monitoring tool for detecting species that are otherwise challenging to monitor. By filtering organismal DNA from environmental samples, one can infer presence of an organism at higher sensitivity than many other previous methods, and often at a fraction of the time and cost. Additionally, biologists are learning how to leverage this information to gather details on individuals and population dynamics—all without having to necessarily see or directly interact with the organism. However, being a relatively new methodology, much is to be understood about the variability in eDNA in the environment, and the contexts in which eDNA technology can be best deployed. Here, I conducted three separate projects to begin the process of validating eDNA as a tool for threatened species monitoring in three different contexts; 1) I evaluated eDNA behavior in streams to determine a sampling scheme for threatened turtles, 2) I validated eDNA as a tool to detect illegal wildlife trade, using threatened turtles as an example, and 3) I demonstrated the potential of eDNA in the monitoring of a federally threatened felid by collecting genomic data from snow tracks.

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