Masters Theses

Keywords and Phrases

eDNA metabarcoding; environmental DNA; fish; freshwater; Ozark streams; survey

Abstract

Environmental DNA (eDNA) sampling provides a method for assessing fish communities that has potential as a supplement to traditional sampling methods due to its ability to save time as well as its non-invasive nature. This is a method in which from just one sample, eDNA from multiple individual species are able to be sequenced in tandem and the resulting reads identified to describe a community. In order to evaluate this technique and its efficacy for monitoring fish community diversity, we collected water samples alongside surveys performed by the Missouri Department of Conservation sampling program in summers 2020-21. DNA were extracted from these samples and amplified via polymerase chain reaction (PCR), using several targeted mitochondrial gene markers, which were then cleaned and sequenced. We investigated the variation in species detection among different gene markers. We also sought to determine environmental factors involved in variation of eDNA results between summer and winter. We compared the species detected by eDNA to traditional survey detection. Using a variety of statistics including NMDS, ANOSIM, UPGMA clustering, and others, we provide support for the implementation of eDNA metabarcoding techniques to supplement traditional sampling as a robust technique able to provide optimal coverage of fish communities in the Ozarks. We found an average detection rate of 2 species identified by eDNA metabarcoding for every 1 identified by traditional methods--Abstract, page iii.

Advisor(s)

Duvernell, David D. (David Douglas), 1970-

Committee Member(s)

Frank, Ronald L.
Niyogi, Dev
Olbricht, Gayla R.

Department(s)

Biological Sciences

Degree Name

M.S. in Applied and Environmental Biology

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2022

Pagination

x, 69 pages

Note about bibliography

Includes bibliographic references (pages 59-68).

Rights

© 2022 Veronica Marian Lee, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12162

Electronic OCLC #

1344518773

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