Remote Sensing and Modeling of Vibrio Bacteria in the Chesapeake Bay
Embargo until
2015-08-01
Date
2014-04-16
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Publisher
Johns Hopkins University
Abstract
Estuaries and coastal waters are dynamic environments, subject to mixing processes that produce high temporal and spatial variability in water properties relevant to water quality and ecology. These environments are also increasingly vulnerable to adverse environmental and biological change under pressures of human population growth, sea level rise, and climate change. In coastal regions such as the Chesapeake Bay, for example, it has been suggested that the occurrence of Vibrio spp. bacteria is increasing throughout the near shore environments. As environmental conditions continue to change in poorly characterized and unpredicted ways, there is a need for more advanced and spatially complete coastal monitoring networks. The objective of this dissertation focused on using environmental predictors to develop a Vibrio spp. bacteria estimation method for the Chesapeake Bay with near-real time forecasting potential. This dissertation work has involved development of a satellite-derived surface salinity product generalizable to the Chesapeake Bay, geospatial interpolation of remotely sensed surface water temperature and salinity, comparison of satellite-derived and hydrodynamically modeled estimates of environmental predictors relevant to Vibrio occurrence, development and validation of Vibrio spp. likelihood and abundance models, and lastly sensitivity in modeled response of Vibrio to observed and projected temperature and salinity changes in the Chesapeake Bay. The intended outcome of this research is to use the information of the satellite, interpolation, and modeled products to inform operational and public health risk models for Vibrio spp. in shellfish and recreational waters in the Chesapeake Bay. Though Vibrio spp. does not pose a serious health threat in the Chesapeake Bay, using the Chesapeake Bay as a model “test bed” has provided valuable model information, and help quantifying model uncertainty that will later be extended to other regions of the world significantly aiding in the prediction and, potentially, prevention of Vibrio outbreaks.
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Keywords
Vibrio bacteria, Chesapeake Bay, Geospatial Interpolation, Remote Sensing, Salinity, Empirical Modeling