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Due to increased concerns regarding fecal pollution at marine recreational beaches, daily relative dog abundance and fecal density were estimated on an intensively managed (Beach 1) and a minimally managed (Beach 2) dog beach in Monterey County, California. Fecal loading and factors predictive of fecal deposition also were assessed. After standardizing for beach area, daily beach use and fecal densities did not differ between beaches and yearly fecal loading estimates revealed that unrecovered dog feces likely contributes significantly to fecal contamination (1.4 and 0.2 metric tonnes/beach). Detection of feces was significantly associated with beach management type, transect position relative to mean low tideline, presence of beach wrack, distance to the nearest beach entrance, and season. Methodologies outlined in this study can augment monitoring programs at coastal beaches to optimize management, assess visitor compliance, and improve coastal water quality. [ABSTRACT FROM AUTHOR]

• Beach water samples were assayed for male-specific and somatic coliphage using the new EPA Method 1642. • The relationships observed between enterococci and coliphage were site-dependent and correlated at 7 out of 11 beach sites. • Fewer public health warnings would have been issued using coliphage compared to Enterococcus. • Coliphage provides complementary site prioritization information to FIB at certain locations. Coliphage have been suggested as an alternative to fecal indicator bacteria for assessing recreational beach water quality, but it is unclear how frequently and at what types of beaches coliphage produces a different management outcome. Here we conducted side-by-side sampling of male-specific and somatic coliphage by the new EPA dead-end hollow fiber ultrafiltration (D-HFUF-SAL) method and Enterococcus at southern California beaches over two years. When samples were combined for all beach sites, somatic and male-specific coliphage both correlated with Enterococcus. When examined categorically, Enterococcus would have resulted in approximately two times the number of health advisories as somatic coliphage and four times that of male-specific coliphage,using recently proposed thresholds of 60 PFU/100 mL for somatic and 30 PFU/100 mL for male-specific coliphage. Overall, only 12% of total exceedances would have been for coliphage alone. Somatic coliphage exceedances that occurred in the absence of an Enterococcus exceedance were limited to a single site during south swell events, when this beach is known to be affected by nearby minimally treated sewage. Thus, somatic coliphage provided additional valuable health protection information, but may be more appropriate as a supplement to FIB measurements rather than as replacement because: (a) EPA-approved PCR methods for Enterococcus allow a more rapid response, (b) coliphage is more challenging owing to its greater sampling volume and laboratory time requirements, and (c) Enterococcus ' long data history has yielded predictive management models that would need to be recreated for coliphage. [ABSTRACT FROM AUTHOR]

• Fecal and wastewater bacterial communities were at low proportions in surf zones. • Recycled water bacterial communities were absent in surf zone waters. • HF183 copies in surf zones were mainly from human feces and treated WWTP effluent. • Bather shedding contributed low levels of human fecal contamination in surf zones. • Sequencing based fecal source proportions appeared uncorrelated to qPCR results. Fecal sources to recreational surf zone waters should be identified to protect public health. While watershed origins of human and other fecal sources are often discoverable by quantitative polymerase chain reaction (qPCR) of fecal markers using spatially stratified samples, similarly assessing wastewater treatment plant (WWTP) outfall and other offshore contributions to surf zones is challenged by individual marker fate and transport. Here, bacterial communities were assessed for relatedness between all hypothesized fecal sources and surf zone waters for two urban California recreational beaches, by sequencing genes encoding 16S rRNA and analyzing data using SourceTracker and FEAST. Ambient marine bacterial communities dominated the surf zone, while fecal (human, dog, or gull) or wastewater (sewage or treated WWTP effluent) bacterial communities were present at low proportions and those from recycled water were absent. Based on the relative abundances of bacterial genera specifically associated with human feces, the abundances of HF183 in bacterial community sequences, and FEAST and SourceTracker results when benchmarked to HF183, the major sources of HF183 to surf zone waters were human feces and treated WWTP effluent. While surf zone sequence proportions from human sources (feces, sewage and treated WWTP effluent) appeared uncorrelated to previously obtained qPCR HF183 results, the proportions of human fecal and potential human pathogen sequences in surf zone waters were elevated when there were more swimmers (i.e. during weekday afternoons, holidays and busy weekends, and race events), thus confirming previously-published qPCR-based conclusions that bather shedding contributed low levels of human fecal contamination. Here, bacterial community sequencing also showed evidence that treated WWTP effluent from an offshore outfall was entering the surf zone, thereby resolving a prior uncertainty. Thus, bacterial community sequencing not only confirms qPCR HF183-based human marker detections, but further allows for confirming fecal sources for which individual marker quantification results can be equivocal. [Display omitted] [ABSTRACT FROM AUTHOR]

Traditional beach management that uses concentrations of cultivatable fecal indicator bacteria (FIB) may lead to delayed notification of unsafe swimming conditions. Predictive, nowcast models of beach water quality may help reduce beach management errors and enhance protection of public health. This study compares performances of five different types of statistical, data-driven predictive models: multiple linear regression model, binary logistic regression model, partial least-squares regression model, artificial neural network, and classification tree, in predicting advisories due to FIB contamination at 25 beaches along the California coastline. Classification tree and the binary logistic regression model with threshold tuning are consistently the best performing model types for California beaches. Beaches with good performing models usually have a rainfall/flow related dominating factor affecting beach water quality, while beaches having a deteriorating water quality trend or low FIB exceedance rates are less likely to have a good performing model. This study identifies circumstances when predictive models are the most effective, and suggests that using predictive models for public notification of unsafe swimming conditions may improve public health protection at California beaches relative to current practices. [ABSTRACT FROM AUTHOR]