Modeling and forecasting the distribution ofVibrio vulnificusin Chesapeake Bay
| Autor: | Wen Long, Robert Wood, Chris W. Brown, Andrew K. Leight, Matt R. Rhodes, John M. Jacobs, Raleigh R. Hood |
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| Rok vydání: | 2014 |
| Předmět: |
Salinity
Virulence Factors Ecological forecasting Vibrio vulnificus Applied Microbiology and Biotechnology Abundance (ecology) Turbidity geography Models Statistical geography.geographical_feature_category biology Temperature Empirical modelling Statistical model Estuary General Medicine biology.organism_classification Fishery Oceanography Bays Environmental science Water quality Water Microbiology Forecasting Biotechnology |
| Zdroj: | Journal of Applied Microbiology. 117:1312-1327 |
| ISSN: | 1364-5072 |
| DOI: | 10.1111/jam.12624 |
| Popis: | Aim To construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters of Chesapeake Bay for implementation in ecological forecasting systems. Methods and Results We evaluated and applied previously published qPCR assays to water samples (n = 1636) collected from Chesapeake Bay from 2007–2010 in conjunction with State water quality monitoring programmes. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. Significance and Impact of the Study This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions. |
| Databáze: | OpenAIRE |
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