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Evaluation of conventional and alternative monitoring methods for a recreational marine beach with nonpoint source of fecal contamination
Authors:Shibata Tomoyuki  Solo-Gabriele Helena M  Sinigalliano Christopher D  Gidley Maribeth L  Plano Lisa R W  Fleisher Jay M  Wang John D  Elmir Samir M  He Guoqing  Wright Mary E  Abdelzaher Amir M  Ortega Cristina  Wanless David  Garza Anna C  Kish Jonathan  Scott Troy  Hollenbeck Julie  Backer Lorraine C  Fleming Lora E
Affiliation:NSF NIEHS Oceans and Human Health Center, Rosenstiel School, University of Miami, Miami, Florida, USA. tshibata@niu.edu
Abstract:The objectives of this work were to compare enterococci (ENT) measurements based on the membrane filter, ENT(MF) with alternatives that can provide faster results including alternative enterococci methods (e.g., chromogenic substrate (CS), and quantitative polymerase chain reaction (qPCR)), and results from regression models based upon environmental parameters that can be measured in real-time. ENT(MF) were also compared to source tracking markers (Staphylococcus aureus, Bacteroidales human and dog markers, and Catellicoccus gull marker) in an effort to interpret the variability of the signal. Results showed that concentrations of enterococci based upon MF (<2 to 3320 CFU/100 mL) were significantly different from the CS and qPCR methods (p < 0.01). The correlations between MF and CS (r = 0.58, p < 0.01) were stronger than between MF and qPCR (r ≤ 0.36, p < 0.01). Enterococci levels by MF, CS, and qPCR methods were positively correlated with turbidity and tidal height. Enterococci by MF and CS were also inversely correlated with solar radiation but enterococci by qPCR was not. The regression model based on environmental variables provided fair qualitative predictions of enterococci by MF in real-time, for daily geometric mean levels, but not for individual samples. Overall, ENT(MF) was not significantly correlated with source tracking markers with the exception of samples collected during one storm event. The inability of the regression model to predict ENT(MF) levels for individual samples is likely due to the different sources of ENT impacting the beach at any given time, making it particularly difficult to to predict short-term variability of ENT(MF) for environmental parameters.
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