Infection levels of eastern oysters by the unicellular pathogen Perkinsus marinus have been associated with anthropogenic influences in laboratory studies. However, these relationships have been difficult to investigate in the field because anthropogenic inputs are often associated with natural influences such as freshwater inflow, which can also affect infection levels. We addressed P. marinus-land use associations using field-collected data from Murrells Inlet, South Carolina, USA, a developed, coastal estuary with relatively minor freshwater inputs. Ten oysters from each of 30 reefs were sampled quarterly in each of 2 years. Distances to nearest urbanized land class and to nearest stormwater outfall were measured via both tidal creeks and an elaboration of Euclidean distance. As the forms of any associations between oyster infection and distance to urbanization were unknown a priori, we used data from the first and second years of the study as exploratory and confirmatory datasets, respectively. With one exception, quarterly land use associations identified using the exploratory dataset were not confirmed using the confirmatory dataset. The exception was an association between the prevalence of moderate to high infection levels in winter and decreasing distance to nearest urban land use. Given that the study design appeared adequate to detect effects inferred from the exploratory dataset, these results suggest that effects of land use gradients were largely insubstantial or were ephemeral with duration less than 3 months.

Web mashup is a lightweight technology used to integrate data from remote sources without direct access to their databases. As a data consumer, a Web mashup application creates new contents by retrieving data through the Web application programming interface (API) provided by the external sources. As a data provider, the service program publishes its Web API and implements the specified functions. In the project reported by this thesis, we have implemented two Web mashup applications to enhance the Web site oystersentinel.org: the Perkinsus marinus model and the Oil Spill model. Each model overlay geospatial data from a local database on top of a coastal map from Google Maps. In addition, we have designed a Web-based data publishing service. In this experimental system, we illustrated a successful Web mashup interface that allows outside developers to access the data about the local oyster stock assessment.