Abstract:
The marine fecal indicator Enterococcus is measured at beaches to detect fecal contamination
events, and beaches are closed to bathers when Enterococcus is found to exceed the federally
mandated limit. This dissertation presents evidence that beach sands are an environmental
reservoir of enterococci, tests the relationship between beach sand enterococci and water quality
measurements, examines how real-time environmental conditions measured at beaches can be
used to better understand and predict water quality violations, and uses molecular methods to
provide an alternative characterization of water and sand fecal contamination. Initially, a qPCR
method was developed and applied to monitor enterococci DNA in sands. Subsequently this
qPCR method was used in tandem with traditional detection of culturable enterococci in sand
and water at recreational beaches that have closures every summer. One field season was spent
in Maine at beaches in the Wells National Estuarine Research Reserve, where high frequency
water and weather measurements are routinely collected in situ. Two field seasons were spent at
the beach in Provincetown Harbor, Massachusetts, where a weather station and ADCP were
deployed to characterize the environmental conditions associated with observations of elevated
enterococci. All studies revealed that environmental variables were related to the distribution of
enterococci in sands and water, with water temperature and tides having the strongest
relationship to enterococci in water. In dry weather, elevated enterococci in sands were strongly
related to the increased moisture content of sands during spring tides. These environmental
variables were used in multiple linear regressions to explain a significant amount of the variation
observed in environmental enterococci abundance, which notably had no relationship to
molecular markers of human fecal pollution. Results suggest that under certain conditions sands
can contribute bacteria to the water and that tidal cycles, which are not taken into account in
monitoring schemes, can bias routine sampling.
