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A POTENTIAL ECOFORECAST FOR PROTOZOAL INFECTIONS OF THE EASTERN OYSTER (CRASSOSTREA VIRGINICA)
Citation:
McLaughlin, S. AND S J. Jordan. A POTENTIAL ECOFORECAST FOR PROTOZOAL INFECTIONS OF THE EASTERN OYSTER (CRASSOSTREA VIRGINICA). N.J. Valette-Silver & D. Scavia (ed.), NOAA TECHNICAL MEMORANDUM NOS NCCOS 1. U.S. Department of Commerce, Washington, DC, , 73-79, (2003).
Impact/Purpose:
Discuss population dynamics model as a potential tool for forecasting oyster disease in the upper Chesapeake Bay.
Description:
McLaughlin, Shawn M. and Stephen J. Jordan. 2003. Potential Ecoforecast for Protozoal Infections of the Eastern Oyster (Crassostrea virginica) in the Upper Chesapeake Bay. In: Ecological Forecasting: New Tools for Coastal Marine Ecosystem Management. Nathalie Valette-Silver and Donald Scavia, Editors. NOAA Technical Memorandum NOS NCCOS 1. Pp. 73-79. (ERL,GB X1057).
Perkinsus marinus and Haplosporidian nelsoni cause devastating infections in populations of the eastern oyster, Crassostrea virginica, along the US Atlantic coast and Gulf of Mexico. Salinity and temperature are considered major controlling factors in the prevalence and infection intensity of these two parasites. Fishery managers and oyster growers use this relationship to make short-term predictions of potential outbreaks of disease in oyster populations and to determine the best timing, or sites, for planting and harvesting of oysters. Predicting medium or long term fluctuations in oyster disease in the Chesapeake Bay is limited; however, by the inability to accurately predict medium-and long-term fluctuations in weather patterns such as occurrence and duration of drought conditions.
Several mathematic models have been developed to assess the health of oyster populations in the Gulf of Mexico and Chesapeake and Delaware Bays. An impediment to the accuracy of mathematical models is the current sever gap in knowledge regarding the parasites, the host, and their interactions. Continuous advances in shellfish pathology research can be expected to improve the precision of predictive models. A population dynamics model recently developed by Jordan and Vanisko (submitted) is discussed as a potential tool for forecasting oyster disease in the upper Chesapeake Bay.