Impacts of a changing earth on microbial dynamics and human health risks in the continuum between beach water and sand.

Although infectious disease risk from recreational exposure to waterborne pathogens has been an active area of research for decades, beach sand is a relatively unexplored habitat for the persistence of pathogens and fecal indicator bacteria (FIB). Beach sand, biofilms, and water all present unique advantages and challenges to pathogen introduction, growth, and persistence. These dynamics are further complicated by continuous exchange between sand and water habitats. Models of FIB and pathogen fate and transport at beaches can help predict the risk of infectious disease from beach use, but knowledge gaps with respect to decay and growth rates of pathogens in beach habitats impede robust modeling. Climatic variability adds further complexity to predictive modeling because extreme weather events, warming water, and sea level change may increase human exposure to waterborne pathogens and alter relationships between FIB and pathogens. In addition, population growth and urbanization will exacerbate contamination events and increase the potential for human exposure. The cumulative effects of anthropogenic changes will alter microbial population dynamics in beach habitats and the assumptions and relationships used in quantitative microbial risk assessment (QMRA) and process-based models. Here, we review our current understanding of microbial populations and transport dynamics across the sand-water continuum at beaches, how these dynamics can be modeled, and how global change factors (e.g., climate and land use) should be integrated into more accurate beachscape-based models.

Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed-Use Watersheds.

Microbial fate and transport in watersheds should include a microbial source apportionment analysis that estimates the importance of each source, relative to each other and in combination, by capturing their impacts spatially and temporally under various scenarios. A loosely configured software infrastructure was used in microbial source-to-receptor modeling by focusing on animal- and human-impacted mixed-use watersheds. Components include data collection software, a microbial source module that determines loading rates from different sources, a watershed model, an inverse model for calibrating flows and microbial densities, tabular and graphical viewers, software to convert output to different formats, and a model for calculating risk from pathogen exposure. The system automates, as much as possible, the manual process of accessing and retrieving data and completes input data files of the models. The workflow considers land-applied manure from domestic animals on undeveloped areas; direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; pastureland, cropland, forest, and urban or engineered areas; sources that directly release to streams from leaking septic systems; and shedding by domestic animals directly to streams. The infrastructure also considers point sources from regulated discharges. An application is presented on a real-world watershed and helps answer questions such as: What are the major microbial sources? What practices contribute to contamination at the receptor location? What land-use types influence contamination at the receptor location? and Under what conditions do these sources manifest themselves? This research aims to improve our understanding of processes related to pathogen and indicator dynamics in mixed-use watershed systems.

Capturing Microbial Sources Distributed in a Mixed-use Watershed within an Integrated Environmental Modeling Workflow.

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is part of a workflow containing multiple models and databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal- and human-impacted catchments. A hypothetical application - accessing, retrieving, and using real-world data - demonstrates how the infrastructure can automate many of the manual steps associated with a standard watershed assessment, culminating in calibrated flow and microbial densities at the watershed's pour point.

Human and Bovine Viruses and Bacteria at Three Great Lakes Beaches: Environmental Variable Associations and Health Risk.

Waterborne pathogens were measured at three beaches in Lake Michigan, environmental factors for predicting pathogen concentrations were identified, and the risk of swimmer infection and illness was estimated. Waterborne pathogens were detected in 96% of samples collected at three Lake Michigan beaches in summer, 2010. Samples were quantified for 22 pathogens in four microbial categories (human viruses, bovine viruses, protozoa, and pathogenic bacteria). All beaches had detections of human and bovine viruses and pathogenic bacteria indicating influence of multiple contamination sources at these beaches. Occurrence ranged from 40 to 87% for human viruses, 65-87% for pathogenic bacteria, and 13-35% for bovine viruses. Enterovirus, adenovirus A, Salmonella spp., Campylobacter jejuni, bovine polyomavirus, and bovine rotavirus A were present most frequently. Variables selected in multiple regression models used to explore environmental factors that influence pathogens included wave direction, cloud cover, currents, and water temperature. Quantitative Microbial Risk Assessment was done for C. jejuni, Salmonella spp., and enteroviruses to estimate risk of infection and illness. Median infection risks for one-time swimming events were approximately 2 × 10(-5), 8 × 10(-6), and 3 × 10(-7) [corrected] for C. jejuni, Salmonella spp., and enteroviruses, respectively. Results highlight the importance of investigating multiple pathogens within multiple categories to avoid underestimating the prevalence and risk of waterborne pathogens.

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan.

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples.

The green alga, Cladophora, promotes Escherichia coli growth and contamination of recreational waters in Lake Michigan.

A linkage between Cladophora mats and exceedances of recreational water quality criteria has been suggested, but not directly studied. This study investigates the spatial and temporal association between Escherichia coli concentrations within and near Cladophora mats at two northwestern Lake Michigan beaches in Door County, Wisconsin. Escherichia coli concentrations in water underlying mats were significantly greater than surrounding water (p < 0.001). Below mat E. coli increased as the stranded mats persisted at the beach swash zone. Water adjacent to Cladophora mats had lower E. coli concentrations, but surpassed EPA swimming criteria the majority of sampling days. A significant positive association was found between E. coli concentrations attached to Cladophora and in underlying water (p < 0.001). The attached E. coli likely acted as a reservoir for populating water underlying the mat. Fecal bacterial pathogens, however, could not be detected by microbiological culture methods either attached to mat biomass or in underlying water. Removal of Cladophora mats from beach areas may improve aesthetic and microbial water quality at affected beaches. These associations and potential natural growth of E. coli in bathing waters call into question the efficacy of using E. coli as a recreational water quality indicator of fecal contaminations.

Geographic relatedness and predictability of Escherichia coli along a peninsular beach complex of Lake Michigan.

To determine more accurately the real-time concentration of fecal indicator bacteria (FIB) in beach water, predictive modeling has been applied in several locations around the Great Lakes to individual or small groups of similar beaches. Using 24 beaches in Door County, Wisconsin, we attempted to expand predictive models to multiple beaches of complex geography. We examined the importance of geographic location and independent variables and the consequential limitations for potential beach or beach group models. An analysis of Escherichia coli populations over 4 yr revealed a geographic gradient to the beaches, with mean E. coli concentrations decreasing with increasing distance from the city of Sturgeon Bay. Beaches grouped strongly by water type (lake, bay, Sturgeon Bay) and proximity to one another, followed by presence of a storm or creek outfall or amount of shoreline enclosure. Predictive models developed for beach groups commonly included wave height and cumulative 48-h rainfall but generally explained little E. coli variation (adj. R2=0.19-0.36). Generally low concentrations of E. coli at the beaches influenced the effectiveness of model results presumably because of low signal-to-noise ratios and the rarity of elevated concentrations. Our results highlight the importance of the sensitivity of regressors and the need for careful methods evaluation. Despite the attractiveness of predictive models as an alternative beach monitoring approach, it is likely that FIB fluctuations at some beaches defy simple prediction approaches. Regional, multi-beach, and individual beach predictive models should be explored alongside other techniques for improving monitoring reliability at Great Lakes beaches.

Effects of Rainfall on E. coli Concentrations at Door County, Wisconsin Beaches.

Rainfall and its associated storm water runoff have been associated with transport of many pollutants into beach water. Fecal material, from a variety of animals (humans, pets, livestock, and wildlife), can wash into beach water following rainfall and result in microbial contamination of the beach. Many locales around the world issue pre-emptive beach closures associated with rainfall. This study looked at eight beaches located in Door County, Wisconsin, on Lake Michigan to determine the impact of rainfall on E. coli concentrations in beach water. Water samples were collected from beach water and storm water discharge pipes during rainfall events of 5 mm in the previous 24 hours. Six of the eight beaches showed a significant association between rainfall and elevated beach water E. coli concentrations. The duration of the impact of rainfall on beach water E. coli concentrations was variable (immediate to 12 hours). Amount of rainfall in the days previous to the sampling did not have significant impact on the E. coli concentrations measured in beach water. Presence of storm water conveyance pipes adjacent to the beach did not have a uniform impact on beach water E. coli concentrations. This study suggests that each beach needs to be examined on its own with regard to rain impacts on E coli concentrations in beach water.

Effects of the nuisance algae, Cladophora, on Escherichia coli at recreational beaches in Wisconsin.

Recreational beaches constitute a large part of the 12 billion dollar per year tourism industry in Wisconsin. Beach closures due to microbial contamination are costly in terms of lost tourism revenue and adverse publicity for an area. Escherichia coli (E. coli), is used as an indicator of microbial contamination, as high concentrations of this organism should indicate a recent fecal contamination event that may contain other, more pathogenic, bacteria. An additional problem at many beaches in the state is the nuisance algae, Cladophora. It has been hypothesized that mats of Cladophora may harbor high concentrations of E. coli. Three beaches in Door County, WI were selected for study, based on tourist activity and amounts of algae present. Concentrations of E. coli were higher within Cladophora mats than in surrounding water. Beaches displayed an E. coli concentration gradient in water extending away from the Cladophora mats, although this was not statistically significant. Likewise, the amount of Cladophora observed on a beach did not correlate with E. coli concentrations found in routine beach monitoring samples. More work is needed to determine the impact of mats of Cladophora on beach water quality, as well as likely sources of E. coli found within the mats.

Discrimination and characterization of environmental strains of Escherichia coli by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS).

A rapid and reliable bacterial source tracking (BST) method is essential to counter risks to human health posed by fecal contamination of surface waters. Genetic fingerprinting methods, such as repetitive sequence based-PCR (rep-PCR), have shown promise as BST tools but are time-consuming and labor-intensive. In this work, we investigate the ability of MALDI-TOF-MS to characterize and discriminate between closely related environmental strains of Escherichia coli and to classify them according to their respective sources. We compared the performance of a rapid MALDI-TOF-MS-based method to a commonly used rep-PCR-based method that employs the BOX-A1R primer. Among the criteria evaluated were repeatability and the ability of each method to group E. coli isolates according to their respective sources. Our data suggest that the MALDI-TOF-MS-based approach has a lower repeatability level compared to rep-PCR but offers an improved ability to correctly assign E. coli isolates to specific source groups. In addition, we have identified five biomarkers that appear conserved among avian species. We conclude that MALDI-TOF-MS may represent a promising, novel and rapid approach to addressing the problem of fecal contamination of surface waters and warrants further investigation.

Influence of sampling depth on Escherichia coli concentrations in beach monitoring.

While the US Environmental Protection Agency's (EPA) Beaches Environmental Assessment and Coastal Health (BEACH) Act requires coastal and Great Lakes' states to implement plans for monitoring bacterial contamination of recreational beach water, exactly how this monitoring should occur has not been regulated. This study examined differences in concentration of Escherichia coli in water collected from different depths and from different horizontal locations across the beach. E. coli concentrations were significantly different (p<0.05), when water from different depths was compared. Sampling water at depths of 30, 60, and 120 cm resulted in significantly lower E. coli concentrations as depth increased. Had the State of Wisconsin chosen to collect beach water monitoring samples at a shallower or deeper depth, numbers of beach closures and the potential risk to public health would have changed substantially. These data imply that a revised and standardized protocol for monitoring beach water should be adopted by all states of a monitoring region to better compare microbial contamination of beaches and protect public health.