Application of SourceTracker for Accurate Identification of Fecal Pollution in Recreational Freshwater: A Double-Blinded Study

Christopher Staley, Thomas Kaiser, Aldo Lobos, Warish Ahmed, Valerie J. Harwood, Clairessa M. Brown, Michael J. Sadowsky

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

The efficacy of SourceTracker software to attribute contamination from a variety of fecal sources spiked into ambient freshwater samples was investigated. Double-blinded samples spiked with ≤5 different sources (0.025-10% vol/vol) were evaluated against fecal taxon libraries characterized by next-generation amplicon sequencing. Three libraries, including an initial library (17 nonlocal sources), a blinded source library (5 local sources), and a composite library (local and nonlocal sources), were used with SourceTracker. SourceTracker's predictions of fecal compositions in samples were made, in part, based on distributions of taxa within abundant genera identified as discriminatory by discriminant analyses but also using a large percentage of low abundance taxa. The initial library showed poor ability to characterize blinded samples, but, using local sources, SourceTracker showed 91% accuracy (31/34) at identifying the presence of source contamination, with two false positives for sewage and one for horse. Furthermore, sink predictions of source contamination were positively correlated (Spearman's ρ ≥ 0.88, P < 0.001) with spiked source volumes. Using the composite library did not significantly affect sink predictions (P > 0.79) compared to those made using the local sources alone. Results of this study indicate that geographically associated fecal samples are required for SourceTracker to assign host sources accurately.

Original languageEnglish (US)
Pages (from-to)4207-4217
Number of pages11
JournalEnvironmental Science and Technology
Volume52
Issue number7
DOIs
StatePublished - Apr 3 2018

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