Contractor And Volunteer
CurrentDeveloping a predictive statistical model that associates estuarine community characteristics and composition with water quality data. Geo-referenced community and water quality databases have been constructed from multiple public and private data sources. Temporally, the data span 20 years and the spatial includes three National Parks; Biscayne Bay, Everglades, and Dry Tortugas. An Arc-GIS platform is used for spatial representations and geo-statistical interpolations. The model approach uses both discriminant function analysis and multi-dimensional scaling to predict community characteristics from water quality, percent surface ambient light reaching the benthos, and substrate qualities.The project has importance to water management relative to habitat integrity for a variety of wading and diving seabirds, several important fish species to the sport fishing industry, and the commercially important pink shrimp industry.Below is a recent exercise making use of USGS data. Is sea level change altering sediment elevation on mud banks across Florida Bay? A reevaluation of data from 1996 to 2007 using R and 3-D graphing. The reevaluation illustrates the value of using spatial representations rather than means when examining landscape effects. In several cases it appears that turbulence around benchmarks is causing erosion.