Bacterial contamination due to excessive levels of bacteria is a confounding problem and remediation of impaired watersheds relies on the detection of fecal indicator bacteria and then assessing the source of said bacteria. Bacterial source tracking (BST) is an approach for assessing potential sources of this contamination. The purpose of this study was to utilize both cultivation-independent and –dependent methods to improve the ability to track sources of fecal contamination. First, E. coli community composition was assessed across three standard water quality assessments including USEPA Methods 1603 and 1604, and Colilert®, to determine their impact on BST library-based performance. Results indicate that the three assessed methods of enumeration and isolation may select for different populations of E. coli and standardized methods may be warranted if library-dependent BST is part of a research plan. Next, BST techniques were used to enumerate and characterize E. coli communities across various dairy manure management techniques used in the Leon River watershed in central Texas to determine effectiveness of BST efforts in tracking contamination from dairy manure. Results of this study indicated that manure and effluent management strategies which employed means to remove solids from the manure tended to decrease the levels of E. coli in the effluent. Some E. coli genotypes were found across the managerial treatments even though there were no clear seasonal trends or site groupings among the dataset. The vast majority of the isolates classified using the Texas E. coli BST library were correctly classified back to their major source class, thus increasing confidence in the methods currently being utilized to track dairy fecal contributions in this Central Texas watershed. Finally, deer bacterial fecal communities from south and central Texas were analyzed using 454-pyrosequencing to assess the potential for the development of a deer-specific BST marker. Microbial communities did not cluster by site or year suggesting that deer fecal communities in these Texas regions are stable over time and could be amenable to marker development.

The goal of monitoring the water quality of shellfish beds is to provide protection against transmission of water-borne infectious diseases. The Coan River and the Little Wicomico River contain shellfish beds that are closed to harvest due to contamination with fecal bacteria. These two rivers are located in Northumberland County, Virginia, and empty into the lower Potomac River and the Chesapeake Bay. Bacterial source tracking (antibiotic resistance analysis of Eschericia coli) was used to determine the sources of fecal contamination that have caused shellfish harvest closures in these two rivers. A total of 1,248 Eschericia coli isolates were collected from known sources to build a regional library for the rivers. The Virginia Department of Shellfish Sanitation (DSS) and project cooperators collected known source samples from August 2001 to September 2002. The Average Rate of Correct Classification for the known source library was 71.9%, with a total of 930 isolates correctly classified. The categories (and rates of correct classification) were Birds (84.7%), Humans (74.8%), Livestock (72.4%), Pets (62.0%), and Wildlife (65.7%). The library was used to identify the sources of Eschericia coli isolated from DSS sampling stations along the Coan and Little Wicomico Rivers from August 2001 to September 2002. Some stations contained a substantial human signature, while wildlife and birds are also major contributors. The results will be used to decide the necessary changes that need to be addressed if the shellfish harvesting beds are to be reopened. / Master of Science

Sources of E. coli were determined from impaired waterways in the Appomattox River watershed (in the lower Piedmont and South-Central Virginia) for the development of bacterial Total Maximum Daily Loads (TMDLs). The Appomattox River watershed is primarily undeveloped with 70.8% of the land forested, 17.0% used for agriculture (mainly livestock production), and 7.7% classified as water, wetland or barren land. The remaining 4.5% is developed for residential, commercial, and industrial land uses (mainly within the city of Petersburg). Using Antibiotic Resistance Analysis, a known source library of 1,280 E. coli isolates (320 isolates per source) was constructed. Water samples were collected monthly for between eleven and fourteen months (11/02-12/03) from 40 locations throughout the Appomattox watershed and analyzed for fecal coliforms, E. coli, and resistance to 7 antibiotics of varying concentrations. A total of 486 water samples (9,907 isolates) were analyzed during the study. The objectives of this study were verify that each sampling site exceeded state bacterial count standards (using fecal coliform data), to compare the Discriminate Analysis and Logistic Regression statistical models for use in the classification of isolates, and finally to determine the source of contamination at each site. The fecal coliform and E.coli data was used to determine if each site exceeded state standards during the assessment period. Thirty-eight of the sites exceeded the fecal coliform standard at least 10% of the time, and thirty-three exceeded the E.coli standard at least 10% of the time. Discriminate Analysis (DA) is typically used to classify isolates, but the results obtained from the DA model were unrealistic based on the watershed land uses. By statistically analyzing the original 1,280 E.coli isolates six different ways, a more appropriate classification of isolates was determined. The six analyzing methods were Regular DA and Logistic Regression (LR); DA and LR where each isolate whose probability fell below 80% was deleted; DA and LR where each isolate whose probability fell below 80% was used to create an Unknown category. The Logistic Regression model with an Unknown category proved to be the most appropriate. By using the Logistic Regression model, with Unknown category, to classify isolates, twenty five of the forty sites were discovered to be contaminated predominately with Livestock and fourteen of the sites predominately by Wildlife. One site was equally divided between these two categories. Human and Pet contamination were not dominant at any of the forty sites. This comparison of the DA and LR statistical methods could change the analysis standard for Bacterial Source Tracking and suggests that the model required to classify isolates depends on the watershed characteristics. / Master of Science

No description available.

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). / Ph. D.

Antibiotic resistance analysis (ARA) of Enterococci was used to determine sources of fecal contamination in three District of Columbia waterways: Rock Creek, the Anacostia River, and the Potomac River. These three waterways were identified as exceeding water quality standards set for fecal coliform levels and were designated by the District of Columbia to the Environmental Protection Agency's 303 (d) impaired waters list. A library profile of 1,806 enterococcus isolates from known sources was built based on antibiotic resistance patterns from thirty concentrations of nine antibiotics. These sources included human, cattle, chicken, horse, goat, sheep, deer, raccoon, muskrat, goose, seagull, coyote, duck, wild turkey, dog, and cat. Antibiotic profiles were characterized for 24 unknown enterococci isolates on each of 198 samples (38 samples from the Potomac River, 79 samples from the Anacostia River, and 81 samples from Rock Creek) collected periodically from July 2002 through April 2003. Two major storm events were also sampled during this period. These isolate profiles were compared to the known source library using logistic regression. Three dominant sources of fecal pollution were detected in the Potomac River: livestock (30%), human (29%), and wildlife (22%). Three dominant signatures were also detected in Rock Creek: horse (26%), human (26%), and wildlife (24%). Human was the only dominant source detected in the Anacostia River, averaging 43% over the sampling period. The results of this study indicate that human is a substantial contributor to the fecal contamination problems, especially in the Anacostia River, but there are significant agricultural and wildlife contributions as well. Significant and predictable seasonal variations were also detected, indicating the influence of precipitation on source distributions. The results of this study will aid the Metropolitan Washington D.C. Council of Governments in making important management decisions to help improve the water quality in and around the Washington D.C. area. Expanding the limits of ARA was also an integral part of this research. Three new and even controversial analytical techniques were run on the data collected from this project in an attempt to improve confidence and provide direction to the results of this study. The first was a comparison of the more commonly used statistical analysis model discriminate analysis (DA) with logistic regression (LR). No significant difference was found between the output of the two models for the known source libraries, therefore no suggestion could be made in favor of one model over the other. Another analytical test of the data was the introduction of a standard requiring isolates to meet a minimum of 80% similarity to the known source profiles where it was classified. With the 80% cutoff, between 41% and 44% of the isolates could not be classified to any source and were placed in an unknown category. Based on the remaining isolates, source distributions were recalculated and were not statistically different than those calculated with no restriction for isolate similarity for matching. The last major test of the data was the analysis of the library for representativeness via pulled sample cross validation and the exclusion of all duplicate patterns from the known source library. These analyses did not confirm the representativeness of the databases, but results were further analyzed based on the implications these analyses have on library based methods. / Master of Science

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. / Master of Science

Antibiotic resistance analysis (ARA) was used to determine sources of fecal pollution in the Blackwater River in South-central Virginia. The Department of Environmental Quality designated six segments as impaired due to high fecal coliform concentrations with non-point source (NPS) agriculture the suspected source of impairment. The Blackwater River watershed encompasses 72,000 ha of dairy, beef, and intensive production agriculture, abundant wildlife populations and many homes with onsite septic systems. A library of antibiotic resistance profiles based on 30 concentrations of 9 antibiotics was developed for 1,451 enterococci isolates from human, cattle, chicken, horse, goat, sheep, deer, raccoon, muskrat, goose, duck, coyote, and wild turkey fecal samples. Each isolate was classified as human, wildlife or livestock. Correct classification rates were 82.3% for human, 86.2% for livestock and 87.4% for wildlife isolates when profiles were analyzed with discriminant analysis. Profiles were also determined for 48 isolates from 128 stream samples collected periodically from August 1999 thru April 2001 and compared to the known sources using discriminate analysis. A human signature was found at each site at least once during the year, ranging from 0.0% to 85.0% of the sample isolates. The livestock signature varied from 2.3% to 100% over sites and months, and the wildlife signature varied from 0.0% to 79.5%. The results indicate that both humans and wildlife contribute to fecal pollution in addition to the suspected source, livestock, and reducing fecal pollution will require consideration of all three sources. The results from this research are being used to develop a total maximum daily load (TMDL) project allocations for fecal coliforms in the Blackwater River. Isolates identified by ARA were also profiled using the Biolog metabolic identification system. A library of metabolic profiles was constructed from known source isolates. Stream isolates were identified by Biolog and the metabolic profile was compared to the Biolog library. Of ten stream isolates identified by ARA as human, the Biolog library identified one as human, four as livestock, and five as wildlife. Of ten isolates identified by ARA as livestock, the Biolog library identified seven as livestock and three as wildlife. Of ten isolates identified by ARA as wildlife, one was identified as human, three as livestock and six as wildlife. The overall correct classification of Blackwater isolates in the Biolog library was 14 of 30 isolates, or 47%. Although the Biolog library was constructed with some isolates from the Blackwater basin, there may not be enough isolates in the Biolog library to adequately represent the variability shown by the Blackwater isolates, resulting in lower than expected correct classifications. In spite of these results, Biolog remains promising as one of several tools with potential as a bacterial source tracking method. / Master of Science

No description available.

Surface water is used for drinking by many people around the world. E. coli is the most frequently used bacterial indicator used for assessing water quality. The survival, sources, and concentrations of E. coli were examined through a series of experiments that investigated the survival of beef cattle E. coli on land and in water, and used bacterial source tracking (BST) to determine the sources of fecal contamination diurnally and annually in multiple watersheds in British Columbia. A fecal pat experiment was conducted to examine the survival of E. coli under 4 levels of solar exposure. E. coli survived longer with increasing shade. Age of fecal pats, as well as exposure to solar radiation negatively influenced the survival of E. coli. The survival of E. coli in stream water was examined in filtered and unfiltered stream water at 3 different temperatures (6, 20 and 26 ºC). There was no significant difference in the survival of E. coli in filtered versus non-filtered stream water. Lower water temperatures (6 ºC) increased the survival of E. coli. The addition of manure to the water substantially increased the nutrient concentrations and organics. BST is a rapidly growing area of research and technology development and many methods are being developed and tested. The choice of method used for BST depends on: question(s) to be answered, scale of identification needed, available expertise, cost of analysis, turnaround time, and access to facilities. The spatial, diurnal, and annual sources and concentrations of E. coli were investigated in several watersheds in British Columbia. Fecal coliforms and E. coli concentrations varied throughout the day, as well as by site, month and year. Ribotyping identified many different sources of E. coli within the watersheds. The majority of E. coli isolates classified were from wildlife sources in each watershed even though they had different land-use.