Browsing by Author "Graves, Alexandria Kristen"

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    Determining Sources of Fecal Pollution in Water for a Rural Virginia Community
    Graves, Alexandria Kristen (Virginia Tech, 2000-08-01)
    This project involves developing and applying bacterial source tracking (BST) methodology to determine sources of fecal pollution in water for a rural community (Millwood, VA). Antibiotic resistance analysis (ARA) is the primary BST method for fecal source identification, followed by randomly amplified polymorphic DNA (RAPD) analysis for confirmation. Millwood consists of 66 homes, all served by individual septic systems, and a stream (Spout Run) passes through the center of the community. Spout Run drains a 5,800 ha karst topography watershed that includes large populations of livestock and wildlife. Stream and well samples were collected monthly and analyzed for fecal coliforms and fecal streptococci, starting in 5/99 and ending in 5/00. Twelve percent of the well samples and 92% of the stream samples were positive for fecal coliforms, and 26% of the stream samples exceeded the recreational water standard (1,000 fecal coliforms/100 ml). ARA of fecal streptococci recovered from the stream samples indicated that isolates of human origin appeared throughout the stream as the stream passed through Millwood with a yearly average of (approx. 10% human, 30% wildlife, and 63% livestock), and the percent human origin isolates declined downstream from Millwood. These results were obtained by comparing the antibiotic resistance profiles of stream isolates against a library of 1,174 known source isolates with correct classification rates of 94.6% for human isolates, 93.7% for livestock isolates, and 87.8% for wildlife isolates. There is a human signature in Spout Run, but it is small compared to the proportion of isolates from livestock and wildlife. The sporadic instances where well water samples were positive appeared primarily during very dry periods. Restricting livestock access to streams can dramatically lower fecal coliform counts during the unusually hot and dry periods. Reducing FC counts to below recreational water standards for Virginia (1000 per 100ml for any one sample) may be achievable, however to maintain streams below standards may prove to be difficult, as Spout Run is in an area where there are large populations of Canada geese, deer, and other wildlife, and will be hard to restrict these animals.
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    Identifying Sources of Fecal Pollution in Water as Function of Sampling Frequency Under Low and High Stream Flow Conditions
    Graves, Alexandria Kristen (Virginia Tech, 2003-04-15)
    Sources of fecal pollution were evaluated as a function of sampling frequency with stream samples from Mill Creek, Montgomery County, VA. Samples were collected monthly for one year, plus weekly for four consecutive weeks during seasonal high flows (March), and seasonal low flows (September-October), plus daily for seven consecutive days within the weekly schedules. Thirty stream samples were collected from each of two sites (60 total) in Mill Creek, and 48 isolates of E. coli per sample (total of 2,880 stream isolates) were classified by source using antibiotic resistance analysis (ARA) and comparing the resulting patterns against a known-source E. coli library (1,158 isolates). The same process was performed with enterococci isolates against an enterococci library (1,182 isolates). The average rate of correct classification (ARCC) for the E. coli library with a three-way split (human, livestock, and wildlife) was 89.0%, and the ARCC of the species-specific E. coli library (cattle, deer, goose, human, misc. wildlife) was 88.9%. The ARCC of the enterococci library with a three-way split was 85.3%, and the ARCC of the species-specific enterococci library was 88.1%. The results did not justify the need for daily or weekly sampling, but indicated that monthly was adequate (quarterly and every-other-month were not). There was a seasonal effect as the human signature was highest during high flow while the livestock signature dominated during low flow. The results also indicated that sampling should be done over a period of time that includes both seasonal wettest and driest periods (at least 8 months).