Constructing a GIS geodatabase to assess and analyze the factors enabling proliferation of a noxious seaweed along the south-facing coast of Harwich, Cape Cod, Massachusetts

Presently, there is a paucity of knowledge about Pilayella littoralis and the factors influencing its proliferation on the southern facing coast of Cape Cod, MA. Over the past 20 years, the seaweed has moved along the coast from Falmouth to Chatham, and there is concern for the effects on onshore and nearshore habitats. The goal of this research project is to provide a science-based mapping methodology for analyzing spatially referenced coastal phenomena, specifically, coastal distributions of Pilayella littoralis and associated seaweed assemblages, to identify areas of proliferation and accumulation of these seaweeds, and to obtain a detailed timeline of anthropogenic construction along the coast necessary for the analysis of possible causes of the phenomena. This project uses Geographic Information System (GIS) to produce a temporal and spatial framework for quantifying the accumulation and proliferation of distributions of Pilayella littoralis and associated seaweeds along the coast, with respect to natural and human constructed rocky features. The GIS database framework consists of: 1) Bathymetry (accomplished from raster application); and 2) Data layers, including aerial photos, maps, charts, and other existing GIS data layers. GIS database construction and data integration are accomplished using ESRI ArcGIS 9.3.1. ArcSDE and SQL. The database implements data layers based on: 1) historical aerial photographs; 2) bathymetry; 3) and digital maps documenting the construction and timeline of human constructed defenses along the study site. GIS modeling and analysis is performed using the geodatabase to construct models of compartments formed by natural and human rocky structures along the coast where the algae flourish. In addition, GPS data collection and remote sensing field survey (via Hyper-spectroradiometry) is applied to obtain spatial event information and to estimate biomass and to estimate biomass and productivity in aquatic vegetation.