Strategies for Monitoring Microbial Life in Beach Sand for Protection of Public Health.

The 2021 revised guidelines of the World Health Organization recommend monitoring the quality of sand in addition to water at recreational beaches. This review provides background information about the types of beaches, the characteristics of sand, and the microbiological parameters that should be measured. Analytical approaches are described for quantifying fungi and fecal indicator bacteria from beach sand. The review addresses strategies to assess beach sand quality, monitoring approaches, sand remediation, and the proposed way forward for beach sand monitoring programs. In the proposed way forward, recommendations are provided for acceptable levels of fungi given their distribution in the environment. Additional recommendations include evaluating FIB distributions at beaches globally to assess acceptable ranges of FIB levels, similar to those proposed for fungi.

Health risk posed by direct ingestion of yeasts from polluted river water.

River water is an essential human resource that may be contaminated with hazardous microorganisms. However, the risk of yeast infection through river water exposure is unclear because it is highly dependant on individual susceptibility and has therefore not been well-studied, to date. To evaluate this undefined risk, we analysed the fungal communities in less polluted (LP) and highly polluted (HP) river water, as determined using principal coordinate analysis of pollution indicators. We enumerated culturable yeasts using a thermally selective isolation procedure (37 °C) and thus promoted the growth of potentially opportunistic species. Yeast species identified as clinically relevant were then tested for antifungal resistance. In addition, we propose a quantitative microbial risk assessment (QMRA) framework to quantitatively assess the potential risk of yeast infection. Our results indicated that pollution levels significantly altered fungal communities (p = 0.007) and that genera representing opportunistic and pathogenic members were significantly more abundant in HP waters (p = 0.038). Additionally, the yeast species Candida glabrata and Clavispora lusitaniae positively correlated with other pollution indicators, demonstrating the species' indicator potential. Our QMRA results further indicate that higher risk of infection is associated with increased water pollution levels (considering both physicochemical and bacterial indicators). Furthermore, yeast species with higher pathogenic potential present an increased risk of infection despite lower observed concentrations in the river water. Interestingly, the bloom of Meyerozyma guilliermondii during the wet season suggests that other environmental factors, such as dissolved oxygen levels and water turbulence, might affect growth characteristics of yeasts in river water, which consequently affects the distribution of annual infection risks. The presence of antifungal resistant yeasts, observed in this study, could further contribute to variation in risk distribution. Research on the ecophysiology of yeasts in these environments is therefore necessary to ameliorate the uncertainty and sensitivity of the proposed QMRA model. In addition to the vital knowledge on opportunistic and pathogenic yeast occurrence in river water and their observed association with pollution, this study provides valuable methods and insights to initiate future QMRAs of yeast infections.

Climate Change Impacts on Microbiota in Beach Sand and Water: Looking Ahead.

Beach sand and water have both shown relevance for human health and their microbiology have been the subjects of study for decades. Recently, the World Health Organization recommended that recreational beach sands be added to the matrices monitored for enterococci and Fungi. Global climate change is affecting beach microbial contamination, via changes to conditions like water temperature, sea level, precipitation, and waves. In addition, the world is changing, and humans travel and relocate, often carrying endemic allochthonous microbiota. Coastal areas are amongst the most frequent relocation choices, especially in regions where desertification is taking place. A warmer future will likely require looking beyond the use of traditional water quality indicators to protect human health, in order to guarantee that waterways are safe to use for bathing and recreation. Finally, since sand is a complex matrix, an alternative set of microbial standards is necessary to guarantee that the health of beach users is protected from both sand and water contaminants. We need to plan for the future safer use of beaches by adapting regulations to a climate-changing world.

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach.

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave-current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria-sediment interactions, and bacteria-sand-sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria-sand-sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Modeling the photoinactivation and transport of somatic and F-specific coliphages at a Great Lakes beach.

Fecal indicator organisms (FIOs), such as Escherichia coli and enterococci, are often used as surrogates of contamination in the context of beach management; however, bacteriophages may be more reliable indicators than FIO due to their similarity to viral pathogens in terms of size and persistence in the environment. In the past, mechanistic modeling of environmental contamination has focused on FIOs, with virus and bacteriophage modeling efforts remaining limited. In this paper, we describe the development and application of a fate and transport model of somatic and F-specific coliphages for the Washington Park beach in Lake Michigan, which is affected by riverine outputs from the nearby Trail Creek. A three-dimensional model of coliphage transport and photoinactivation was tested and compared with a previously reported E. coli fate and transport model. The light-based inactivation of the phages was modeled using organism-specific action spectra. Results indicate that the coliphage models outperformed the E. coli model in terms of reliably predicting observed E. coli/coliphage concentrations at the beach. This is possibly due to the presence of additional E. coli sources that were not accounted for in the modeling. The coliphage models can be used to test hypotheses about potential sources and their behavior and for predictive modeling.

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.

Monitoring E. coli in a changing beachscape.

Increased emphasis on protection of recreational water quality has led to extensive use of fecal indicator bacteria monitoring of coastal swimming waters in recent years, allowing for long-term, widespread retrospective studies. These studies are especially important for tracking environmental changes and perturbations in regional waters. We show that E. coli concentrations (EC) have decreased in Lake Michigan over the last 15years, coincident with the rapid invasion of Eurasian quagga mussels (Dreissenidae). While median water clarity in Lake Michigan increased by 32% from 2000 to 2014, median EC decreased by 34.9%. Of the 45 Lake Michigan beaches studied, 42 (93.3%) showed a relative decrease (76% significantly, p<0.05), in mean log E. coli between pre- and post-2007. As a result, Lake Michigan beach advisory frequency decreased by 40.0% (p<0.001) from 19.9% in 2000-2007 to 11.9% in 2008-2014. Finite Volume Coastal Ocean Model simulations at Ogden Dunes beach confirm that EC would decrease in response to the observed changes in water clarity (predicted=4.3%, actual=2.3%). In contrast, mean EC in western Lake Erie showed the opposite trend, with 17 of 19 (89.5%) beaches increasing in mean EC after 2007 (p<0.001). We explore plausible explanatory influences on lakewide EC and conclude that bacterial photoinactivation due to increased water clarity is an important contributing factor explaining the general decrease of E. coli densities in Lake Michigan. The trends and explanatory factors reported here may have important public health, management and ecological implications.

Geographic coincidence of richness, mass, conservation value, and response to climate of U.S. land birds.

Distributional patterns across the United States of five avian community breeding-season characteristics--community biomass, richness, constituent species' vulnerability to extirpation, percentage of constituent species' global abundance present in the community (conservation index, CI), and the community's position along the ecological gradient underlying species composition (principal curve ordination score, PC--were described, their covariation was analyzed, and projected effects of climate change on the characteristics and their covariation were modeled. Higher values of biomass, richness, and CI were generally preferred from a conservation perspective. However, higher values of these characteristics often did not coincide geographically; thus regions of the United States would differ in their value for conservation depending on which characteristic was chosen for setting conservation priorities. For instance, correlation patterns between characteristics differed among Landscape Conservation Cooperatives. Among the five characteristics, community richness and the ecological gradient underlying community composition (PC) had the highest correlations with longitude, with richness declining from east to west across the contiguous United States. The ecological gradient underlying composition exhibited a demarcation near the 100th meridian, separating the contiguous United States grossly into two similar-sized avian ecological provinces. The combined score (CS), a measure of species' threat of decline or extirpation, exhibited the strongest latitudinal pattern, declining from south to north. Over -75% of the lower United States, projected changes in June temperature and precipitation to year 2080 were associated with decreased averaged values of richness, biomass, and CI, implying decreased conservation value for birds. The two ecological provinces demarcated near the 100th meridian diverged from each other, with projected changes in June temperatures and precipitation from the year 2000 to 2080 suggesting increased ecological dissimilarity between the eastern and western halves of the lower United States with changing climate. Anticipated climate-related changes in the five characteristics by 2080 were more weakly correlated with latitude or longitude then the responses themselves, indicating less distinct geographic patterns of characteristic change than in the characteristics themselves. Climate changes projected for 2080 included geographic shifts in avian biomass, CS, and PC values, a moderate overall decline in CI, and general decline in species richness per site.