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Although protists (microbial eukaryotes) provide an important link between bacteria and Metazoa in food webs, we do not yet have a clear understanding of the spatial scales on which protist diversity varies. Here, we use a combination of DNA fingerprinting (denaturant gradient gel electrophoresis or DGGE) and high-throughput sequencing (HTS) to assess the ciliate community in the class Spirotrichea at varying scales of 1–3 km sampled in three locations separated by at least 25 km—offshore, midshelf and inshore—along the New England shelf. Analyses of both abundant community (DGGE) and the total community (HTS) members reveal that: 1) ciliate communities are patchily distributed inshore (i.e. the middle station of a transect is distinct from its two neighboring stations), whereas communities are more homogeneous among samples within the midshelf and offshore stations; 2) a ciliate closely related to Pelagostrobilidium paraepacrum ‘blooms’ inshore and; 3) environmental factors may differentially impact the distributions of individual ciliates (i.e. OTUs) rather than the community as a whole as OTUs tend to show distinct biogeographies (e.g. some OTUs are restricted to the offshore locations, some to the surface, etc.). Together, these data show the complexity underlying the spatial distributions of marine protists, and suggest that biogeography may be a property of ciliate species rather than communities. [ABSTRACT FROM AUTHOR]

Reports from state health departments and the Centers for Disease Control and Prevention indicate that the annual number of reported human vibriosis cases in New England has increased in the past decade. Concurrently, there has been a shift in both the spatial distribution and seasonal detection of Vibrio spp. throughout the region based on limited monitoring data. To determine environmental factors that may underlie these emerging conditions, this study focuses on a long-term database of Vibrio parahaemolyticus concentrations in oyster samples generated from data collected from the Great Bay Estuary, New Hampshire over a period of seven consecutive years. Oyster samples from two distinct sites were analyzed for V. parahaemolyticus abundance, noting significant relationships with various biotic and abiotic factors measured during the same period of study. We developed a predictive modeling tool capable of estimating the likelihood of V. parahaemolyticus presence in coastal New Hampshire oysters. Results show that the inclusion of chlorophyll a concentration to an empirical model otherwise employing only temperature and salinity variables, offers improved predictive capability for modeling the likelihood of V. parahaemolyticus in the Great Bay Estuary. [ABSTRACT FROM AUTHOR]