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Towards establishing a human fecal contamination index in microbial source tracking
Citation:
Cao, Y., C. Hagedorn, O. C. Shanks, D. Wang, J. Ervin, J. F. Griffith, B. A. Layton, C. D. McGee, T. E. Riedel, AND S. B. Weisberg. Towards establishing a human fecal contamination index in microbial source tracking. International Journal of Environmental Science and Engineering Research. Cogent SciTech, 4(3):46-58, (2013).
Impact/Purpose:
To inform the public on matters relating to methods to identify sources of fecal contamination in environmental waters.
Description:
There have been significant advances in development of PCR-based methods to detect source associated DNA sequences (markers), but method evaluation has focused on performance with individual challenge samples. Little attention has been given to integration of multiple samples from the same site having different marker signal strengths and varying levels of agreement among markers for ranking beaches with respect to their extent of human fecal contamination. Here we present a Delphi exercise in which ten water quality experts ranked 26 beaches from a simulated dataset where Enterococcus counts, frequency of human marker detection, magnitude of human marker signal, and consistency between two human-associated markers were systematically varied,with the goal of determining consensus principles for weighting these different factors to determine relative extent of human contamination. The results from the experts' initial ranking varied widely, due primarily to how experts weighted marker frequency compared to magnitude and how each expert used Enterococcus counts. The Delphi exercise was conducted repeatedly until expert opinions converged, with the resulting consensus that: 1) frequency of samples that are positive for human MST markers is of primary importance in ranking beaches with respect to extent of human fecal contamination; 2) magnitude of and consistency between human-associated markers should be used to weight MST marker frequency for assessing condition at a beach; and 3) general FIB data (e.g. Enterococcus) should receive the least weight. Using the expert’s consensus, a conceptual mathematical algorithm is proposed to consistently and transparently quantify the relative probability of human-source contamination at a beach.
URLs/Downloads:
http://journal-ijeser.com/listing-towards-establishing-a-human-fecal-contamination-index-in-microbial-source-tracking-90.html