"Spatial issues in Bayesian analyses of scientific surveys with application to Chesapeake Bay"
Probabilistic surveys are important for risk-averse fisheries management in deriving accurate estimates of animal abundance. Spatial information collected during fisheries surveys could be utilized to improve abundance estimates and link them to habitat conditions. I have conducted researches in enhancing analyses of spatial scientific surveys, and the sampling designs using Bayesian methods. The specific aims were (1) to estimate the abundance and its associated uncertainty through spatial modelling; (2) to learn the structures of ecosystem factors affecting the population dynamic through network analyses; (3) to design surveys and sampling through spatial simulation studies. The developments centered around Chesapeake bay blue crab. A case study in watershed storm-water control will also be presented.