Date of Award

8-2015

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Biology

Thesis Sponsor/Dissertation Chair/Project Chair

Meiyin Wu

Committee Member

Lee Lee

Committee Member

John Gaynor

Subject(s)

Nonpoint source pollution--New Jersey, Microbial contamination--New Jersey

Abstract

The bodies of water of New Jersey serve many different purposes from recreational to agricultural and drinking to waste water treatment. Due to the vast diversity of usage and the many people that rely on these water bodies for everyday life it is essential that the health and quality of the water bodies is monitored and maintained regularly. Sources of pollution that affect the health of rivers, lakes and streams include biological, microbial, physical and chemical contaminants. All of these pollutions can impact the health of the water body, the organisms living in it and those who come into contact with the contaminated water. This research focuses on the microbial contaminants of the bodies of water using microbial source tracking (MST) techniques to determine the presence or absence of fecal matter contamination from different species-specific sources. Primer development and optimization lead to the utilization of a PCR based-assay and a real-time PCR (qPCR) based-assay and species-specific primers, which were used to determine a relation between the land cover and land use by the sources of contaminants that were found in the water bodies tested in specific areas representing different types of land usages (agricultural, urban and forested). We found that nonpoint source pollution is higher during rain events. The results obtained identified that the agricultural land use is a higher contributor to nonpoint source pollution than urban and forested land uses. Also, we were able to identify nonpoint source pollution from Canadian goose, cow, deer, dog, horse and human throughout the sampling areas tested. Using qPCR based-assay and a copy number equation we were able to quantify the most dominant sources of contaminants in the agricultural area. In this study, horse was found to be the most dominant.

File Format

PDF

Included in

Biology Commons

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