Simulation and analysis of Chesapeake Bay oyster population data
(Advisers: R. Lipcius, L. Shaw, J.P. Shi)
This project will combine advanced mathematical modeling and statistical analysis of field data on analyzing distribution patterns of seagrass meadows and oyster reefs, whose preservation and restoration are of critical importance to the function of marine and estuarine ecosystems. The data sets to be analyzed are available through field programs at Virginia Institute of Marine Science (VIMS), and include unique high-resolution 20 year time series of images of seagrass beds and widely distributed oyster reefs over 30+ hectares in various locations throughout Chesapeake Bay. The student research project will be specifically on the following two elements: (i) with seagrass data, we will use Geographic Information Systems (GIS), statistical methods (spatial pattern analysis) and mathematical models (partial differential equations) to characterize the type of self-organization in spatial patterns and the temporal evolution of those patterns; and (ii) with oyster data, we will examine self-organization at several spatial scales, including oysters within a cluster, clusters within a reef, and reefs within a network, using similar statistical techniques and mathematical models. The Lipcius lab in VIMS will conduct further field studies with native oyster and seagrass populations, so that students will also be involved in field and laboratory studies.Additional pre-requisites: Math 302 or Math 345, Math 351.
