Analyzing the Correlation Between Environmental Variables and Enterococcus Bacteria Contamination Across Boston’s Metropolitan Beaches

Abstract

Enterococcus is a genus of bacteria found worldwide, most abundantly residing in human and animal gastrointestinal tracts. They are historically recognized as fecal indicator bacteria (FIB) and are ill-reputed for their link to millions of infections each year (Byappanahalli et al., 2012). Fecal pollution sources can significantly engender enterococci contamination in marine water (EPA, 2012). Some environmental variables have been correlated with enterococci contamination of beaches, though these relationships have been difficult to determine. In the US, recreational beach water quality is regulated by each state’s Department of Public Health alongside local boards of health (Town of Nahant, 2021). In Massachusetts, beach monitoring is often performed by the Department of Conservation and Recreation (DCR). In a 2021 report on water quality, Nahant Bay boasted adjacent beaches with both the best and worst water quality scores (Save the Harbor, 2021). This makes Nahant Bay, located in the northern region of Boston’s metropolitan beaches, an ideal candidate for analyzing environmental variables and enterococci contamination. For this project, I analyzed fecal pollution sources and environmental variables that potentially correlated with enterococci contamination across Boston’s metropolitan beaches from 2005-2022. I also conducted field samples for a regional case study in Nahant Bay in 2022. I hypothesized that: 1) proximity to fecal pollution sources will have a positive correlation with enterococci contamination as measured by #CFU/100mL per single sample; 2) precipitation, sunlight, and tide were increasingly strong predictors of enterococci contamination from 2005-2022, due to climate change implications; 3) the statistical power of predicting variation in Enterococcus bacteria counts would be enhanced in the 2022 study by increasing the number of environmental predictor variables in regression analysis; and 4) measurement of the variables precipitation, sunlight and tide taken concurrently when sampling at Nahant Bay in 2022 will further increase statistical power. I collated data from 45 sampling points across 15 beaches in the greater Boston area. For H1, fecal pollution sources were compared to median contamination rates at each beach. For H2, the variables precipitation, sunlight and tide were analyzed by multiple regression to explain variation in the DCR database of enterococci contamination from 2005-2022. For H3, data for the variables water temperature, salinity and pH were collected and analyzed to improve prediction of enterococci contamination in Nahant Bay. For H4, measurements were collected and analyzed against measurements gathered as daily averages for the same variables. Regression analysis found that significant fecal pollution sources to metropolitan Boston beaches did not impact bacteria contamination rates but Stacey Brook outfalls in Nahant Bay were highly significant. Sunlight, precipitation and tide were correlated to enterococci contamination but with low explanatory power. Water temperature, salinity and pH did not improve prediction of contamination rates, and concurrent sampling in 2022 did not increase statistical power. Because environmental variables can be highly variable, prediction of marine water contamination is difficult to determine on a large scale. For this reason, local analysis is crucial in shaping beach management policy.