Novel Experimental Designs and Mathematical Models to Study Fecal Indicator Bacteria Persistence in Surface Water Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/qn59q7103

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  • High counts of fecal indicators, used to signal the potential presence of pathogens associated with untreated waste, result in the classification of water bodies throughout the United States as impaired. Nonpoint sources of unknown origin that contribute to fecal contamination make management of impaired waters challenging, as they are difficult to distinguish, and it is thus problematic to correctly target mitigation efforts. Genetic markers used for microbial source tracking provide valuable information by identifying hosts that contribute to fecal loading, but do not provide a method to detect specific sources that contribute to impairment of water bodies. Spatial modelling efforts have been proposed for use in conjunction with fecal indicators and host-specific markers, but have been limited by a lack of adequate modeling for the complex processes that cause indicator decay. We conducted a quantitative meta-analysis of published decay rate estimates for several common indicators using Bayesian hierarchical linear modeling. The meta-analysis revealed a large amount of variability across studies, including in findings of significance for environmental parameters that impact persistence. Additionally, the meta-analysis revealed gaps in the data for genetic markers, while sufficient data was available for the traditional, culture-based indicators. We determined that temperature was consistently a significant predictor of decay rate estimates for all indicators, but light was only significant for culture-based indicators. We provided synthesized estimates for the selected indicators, but recommend caution in their application for source tracking or quantitative risk assessment due to high variability in parameter estimates and uncertainty in their extension beyond artificial settings. We compared the decay profiles for general fecal indicators and markers associated with ruminants and cattle. We determined best fitting non-linear models based on information theory and used global model fitting to test for differences in curves for each combination of indicators. Additionally, we investigated the potential of the selected ruminant markers for use in source allocation using the ratio method, based on difference in the observed decay profiles. We found statistical differences between the decay curves of E. coli and all but one genetic marker. The differences across decay profiles suggest caution is necessary when interpreting microbial source tracking results using these markers, as differential decay may result in different findings depending on the marker selected. We assessed the possibility of studying fecal indicator persistence in a truly open system using simulations. Using the concept of a Continuous-flow Stirred Tank Reactor, we developed an adjustment that can be applied to observed fecal indicator concentrations from an open system so that only loss due to decay is considered. The simulations showed that this adjustment is an effective way to account for loss for this system. However, implementation of this system has limitations, as the removal of indicators through flow contributes to a decreased period of observations before a given indicator drops below the limits of detection. We used the results from the simulations to design and implement an open system for decay studies. We compared decay profiles generated for several indicators from two open systems with different flow rates to those of closed and partially closed systems that have been previously used in decay studies. We used the results of these comparisons to investigate the effects of artificial settings used to study decay for fecal indicators. We found that the systems used in decay studies significantly influence the results for all indicators used.
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  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2016-09-08T15:22:41Z (GMT) No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) BrooksLaurenE2016.pdf: 3011556 bytes, checksum: 156adff4d9b0c30fb2d9e8ccf597730c (MD5)
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  • description.provenance : Made available in DSpace on 2016-09-08T15:22:41Z (GMT). No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) BrooksLaurenE2016.pdf: 3011556 bytes, checksum: 156adff4d9b0c30fb2d9e8ccf597730c (MD5) Previous issue date: 2016-08-03

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