Dataset Information

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

ABSTRACT: Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized. Flow composited river samples were collected over low-flow ( n = 89) and rainfall or snowmelt runoff events ( n = 130). Approximately 90% of samples had evidence of human fecal pollution, with highest loads from urban watersheds. Ruminant indicators were found in ?60-100% of runoff-event samples in agricultural watersheds, with concentrations and loads related to cattle density. Rain depth, season, agricultural tile drainage, and human or cattle density explained variability in daily flux of human or ruminant indicators. Mapping host-associated indicator loads to watershed discharge points sheds light on the type, level, and possible health risk from fecal pollution entering the Great Lakes and can inform total maximum daily load implementation and other management practices to target specific fecal pollution sources.

SUBMITTER: Dila DK

PROVIDER: S-EPMC6437017 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

Dila Deborah K DK Corsi Steven R SR Lenaker Peter L PL Baldwin Austin K AK Bootsma Melinda J MJ McLellan Sandra L SL

Environmental science & technology 20180927 20

Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized. Flow composited river samples were collected over l ...[more]

PMID: 30192524

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Project description:Great Lakes tributaries are known to deliver waterborne pathogens from a host of sources. To examine the hydrologic, land cover, and seasonal patterns of waterborne pathogens (i.e. protozoa (2), pathogenic bacteria (4) human viruses, (8) and bovine viruses (8)) eight rivers were monitored in the Great Lakes Basin over 29 months from February 2011 to June 2013. Sampling locations represented a wide variety of land cover classes from urban to agriculture to forest. A custom automated pathogen sampler was deployed at eight sampling locations which provided unattended, flow-weighted, large-volume (120-1630 L) sampling. Human and bovine viruses and pathogenic bacteria were detected by real-time qPCR in 16%, 14%, and 1.4% of 290 samples collected while protozoa were never detected. The most frequently detected pathogens were: bovine polyomavirus (11%), and human adenovirus C, D, F (9%). Human and bovine viruses were present in 16.9% and 14.8% of runoff-event samples (n = 189) resulting from precipitation and snowmelt, and 13.9% and 12.9% of low-flow samples (n = 101), respectively, indicating multiple delivery mechanisms could be influential. Data indicated human and bovine virus prevalence was different depending on land cover within the watershed. Occurrence, concentration, and flux of human viruses were greatest in samples from the three sampling locations with greater than 25% urban influence than those with less than 25% urban influence. Similarly, occurrence, concentration, and flux of bovine viruses were greatest in samples from the two sampling locations with greater than 50 cattle/km2 than those with less than 50 cattle/km2. In seasonal analysis, human and bovine viruses occurred more frequently in spring and winter seasons than during the fall and summer. Concentration, occurrence, and flux in the context of hydrologic condition, seasonality, and land use must be considered for each watershed individually to develop effective watershed management strategies for pathogen reduction.

Project description:This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli, Enterococcus spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; P < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; P < 0.01) compared to traditional FIB (rho = 0.583; P < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; P < 0.05).IMPORTANCE The results of this study may support the hypothesis of using PMMoV as an alternative indicator of human fecal contamination in tropical surface waters from the perspective of land use patterns. The predictive result of the occurrence of human fecal indicators with high accuracy may reflect the source and transportation of human fecal pollution, which are directly related to the risk to human health, and thereafter, steps can be taken to mitigate these risks.

Project description:Colored dissolved organic matter (CDOM), a major component of the dissolved organic carbon (DOC) pool in many lakes, is an important controlling factor in lake ecosystem functioning. Absorption coefficients at 440 nm (a440, m-1), a common measure of CDOM, exhibited strong associations with dissolved iron (Fediss) and DOC in 280 lakes of the Upper Great Lakes States (UGLS: Minnesota, Wisconsin, and Michigan), as has been found in Scandinavia and elsewhere. Linear regressions between the three variables on UGLS lake data typically yielded R2 values of 0.6-0.9, suggesting that some underlying common processes influence organic matter and Fediss. Statistical and experimental evidence, however, supports only a minor role for iron contributions to a440 in UGLS lakes. Although both DOC and Fediss were significant variables in linear and log-log regressions on a440, DOC was the stronger predictor; adding Fediss to the linear a440-DOC model improved the R2 only from 0.90 to 0.93. Furthermore, experimental additions of FeIII to colored lake waters had only small effects on a440 (average increase of 0.242 m-1 per 100 μg/L of added FeIII). For 136 visibly stained waters (with a440 > 3.0 m-1), where allochthonous DOM predominates, DOM accounted for 92.3 ± 5.0% of the measured a440 values, and Fediss accounted for the remainder. In 75% of the lakes, Fediss accounted for < 10% of a440, but contributions of 15-30% were observed for 7 river-influenced lakes. Contributions of Fediss in UGLS lakes to specific UV absorbance at 254 nm (SUVA254) generally were also low. Although Fediss accounted for 5-10% of measured SUVA254 in a few samples, on average, 98.1% of the SUVA254 signal was attributable to DOM and only 1.9% to Fediss. DOC predictions from measured a440 were nearly identical to those from a440 corrected to remove Fediss contributions. Overall, variations in Fediss in most UGLS lakes have very small effects on CDOM optical properties, such as a440 and SUVA254, and negligible effects on the accuracy of DOC estimated from a440, data for which can be obtained at broad regional scales by remote sensing methods.

Dataset Information

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

Publications

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

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