Abstract

Aquatic fecal contamination poses human health risks by introducing pathogens in water that may be used for recreation, consumption, or agriculture. Identifying fecal contaminant sources, as well as the factors that affect their transport, storage, and decay, is essential for protecting human health. However, identifying these factors is often difficult when using fecal indicator bacteria (FIB) because FIB levels in surface water are often the product of multiple contaminant sources. In contrast, microbial source-tracking (MST) techniques allow not only the identification of predominant contaminant sources but also the quantification of factors affecting the transport, storage, and decay of fecal contaminants from specific hosts. We visited 68 streams in the Finger Lakes region of Upstate New York, United States, between April and October 2018 and collected water quality data (i.e., Escherichia coli, MST markers, and physical–chemical parameters) and weather and land-use data, as well as data on other stream features (e.g., stream bed composition), to identify factors that were associated with fecal contamination at a regional scale. We then applied both generalized linear mixed models and conditional inference trees to identify factors and combinations of factors that were significantly associated with human and ruminant fecal contamination. We found that human contaminants were more likely to be identified when the developed area within the 60 m stream buffer exceeded 3.4%, the total developed area in the watershed exceeded 41%, or if stormwater outfalls were present immediately upstream of the sampling site. When these features were not present, human MST markers were more likely to be found when rainfall during the preceding day exceeded 1.5 cm. The presence of upstream campgrounds was also significantly associated with human MST marker detection. In addition to rainfall and water quality parameters associated with rainfall (e.g., turbidity), the minimum distance to upstream cattle operations, the proportion of the 60 m buffer used for cropland, and the presence of submerged aquatic vegetation at the sampling site were all associated based on univariable regression with elevated levels of ruminant markers. The identification of specific features associated with host-specific fecal contaminants may support the development of broader recommendations or policies aimed at reducing levels of aquatic fecal contamination.

Highlights

  • Escherichia coli was detectable in all streams and samples with a mean value of 212 Most Probable Number (MPN)/100 ml (Standard Deviation [SD] = 637 MPN/100 ml); nine samples were above the range of quantification

  • generalized linear mixed models (GLMMs) indicated that the probability of finding both human (4.520, p < 0.001, 95% CI = 2.012–10.155) and ruminant (6.838, p < 0.001, 95% CI = 2.406–19.433) markers increased with elevated E. coli levels

  • Total rainfall within 0–2 days before sample collection (d BSC) was associated with higher levels of E. coli (0–1 d BSC, 0.375, p < 0.001, 95% CI = 0.252–0.497; 1–2 d BSC, 0.194, p < 0.001, 95% CI = 0.099– 0.289), while total rainfall 5–10 d BSC was somewhat negatively associated with E. coli levels (−0.077, p = 0.007, 95% CI = −0.132 to −0.021)

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Summary

Introduction

Aquatic fecal contamination poses risks to human and environmental health through the introduction of pathogens (Craun et al, 2006; Arnone and Walling, 2007), nutrients (Sharpley et al, 2003), antimicrobials (Chee-Sanford et al, 2009; Karkman et al, 2019), and hormones (Boxall et al, 2003; Hanselman et al, 2003; Combalbert and Hernandez-Raquet, 2010; Bartikova et al, 2016). The identification of the origins of fecal contaminants and the factors that affect their transport, storage, and decay is essential to protecting ambient water quality and human and environmental health. Previous studies have assessed the association between the presence and levels of fecal indicator bacteria (FIB), such as Escherichia coli or fecal coliforms, and various factors thought to affect their distribution. It is well-established that FIB are ubiquitous in mammalian hosts, including some wildlife, and represent the total level of fecal contamination in a water body (Dufour, 1984). It is difficult to gage the importance of the different factors controlling the input of a single fecal type (e.g., human and ruminant) using FIB as a response because measured FIB levels are a composite of FIB from different sources that may have different origins, routes of introduction, and other factors that control their distribution

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