Gulf of Maine Contaminated Sediments Database

The overall objective of this project is to create a database of existing data on contaminants in sediment for the Gulf of Maine region that will be useful to persons throughout the region for scientific and management purposes. This task involves identification of data sources, entry of data into the database format, validation or scientific editing of the database, some analysis and synthesis of the compiled data, and publication of the database and associated bibliographies. The tasks of locating and entering data are being shared among the principle investigators in this project because they require a thorough knowledge of the geographic regions under consideration, an understanding of the types of data identified, and familiarity with active research in these regions. This cooperative approach insures that a more thorough identification and collection of data occurs than could take place from one institution. It also insures that the compiled database will be used by all the participants and their colleagues in the future.

Objectives of the work:

1) Develop a comprehensive inventory (database) of available information on sediment contaminants, both inorganic and organic, for the Gulf of Maine

2) Encourage the cooperation and active participation of multiple agencies and organizations in locating, incorporating, and utilizing the data.

3) Place these and ancillary data in interactive, user-friendly, and readily exchangeable forms (such as desktop computer, FTP, and CD-ROM).

4) Map and analyze sediment contaminant distributions in order to provide the best assemblage of information possible for use in determining contaminant baselines

5) Utilize the database to address specific scientific questions about transport and fate of contaminants in the GOM system.

6) Provide guidance for other agencies and organizations to further the usefulness of the data in research, resource management, and public policy decisions.

7) Provide guidance on where to sample and how to analyze samples in the future to make more effective use of limited resources