Relationships among Microbial Indicators of Fecal Pollution, Microbial Source Tracking Markers, and Pathogens in Costa Rican Coastal Waters

Abstract Tropical coastal waters are understudied, despite their ecological and economic importance. They also reflect projected climate change scenarios, e.g., increased rainfall and water temperatures. We conducted an exploratory microbial water quality study at a tropical beach influenced by sewage-contaminated rivers, and tested the hypothesis that fecal microorganisms (fecal coliforms, enterococci, Clostridium perfringens, somatic and male-specific coliphages, pepper mild mottle virus (PMMoV), Bacteroides HF183, norovirus genogroup I (NoVGI), Salmonella, Cryptosporidium and Giardia) would vary by season and tidal stage. The environmental variable that best predicted microbial concentrations in a multivariate analysis was rainfall. Most microorganisms’ concentrations were greater in the rainy season; however, NoVGI was only detected in the dry season and Cryptosporidium was the only pathogen most frequently detected in rainy season. Fecal indicator bacteria (FIB) levels exceeded recreational water quality criteria standards in >85% of river samples and in 89% of ocean samples. Giardia, Cryptosporidium, Salmonella, and NoVGI were frequently detected in rivers (39%, 39%, 26%, and 39% of samples, respectively), but infrequently in ocean water, particularly during the dry season. Multivariate analysis showed that C. perfringens, somatic coliphage, male-specific coliphage, and PMMoV were the subset of indicators that maximized the correlation of indicators with pathogens in the rivers. In the ocean, the best subset of indicators was enterococci, male-specific coliphage, and PMMoV. The seasonal interplay of rainfall and pathogen prevalence undoubtedly influences beach users’ health risks. Relationships are likely to be complex, with some risk factors increasing and others decreasing each season. Future use of multivariate approaches to better understand linkages among environmental conditions, microbial predictors (fecal indicators and MST markers) and pathogens will improve prediction of high-risk scenarios at recreational beaches.