Type

Text

Type

Thesis

Advisor

Robert M. Cerrato | Frisk, Michael G. | Adrian Jordaan.

Date

2010-08-01

Keywords

Assessment, Ecosystem, Fisheries, Great South Bay, Historic, Variations | Biology, Oceanography -- Environmental Sciences

Department

Department of Marine and Atmospheric Science

Language

en_US

Source

This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.

Identifier

http://hdl.handle.net/11401/72621

Publisher

The Graduate School, Stony Brook University: Stony Brook, NY.

Format

application/pdf

Abstract

The Great South Bay (GSB) ecosystem has provided marine resources to Long Island residents for well over 300 years. However, various external stressors have threatened this system, marked with declines in multiple stocks and ecosystem indices. A historical review was conducted, indicating GSB has shifted to an dominated by lower trophic groups. Of the twelve stocks with identifiable temporal abundance trends, eight are currently declining. These stock declines have been met with drops in recent harvests of GSB fisheries. In addition to monetary losses to local fishermen, the lack of a commercially dominant shellfish stock may leave GSB without a dominant filter feeder, facilitating the brown tide blooms that have affected stocks of plankton, shellfish, finfish, and eelgrass since 1985. Ecosystem models were developed to elucidate the predominant drivers of the ecosystem and determine the expected impact of external GSB stressors over the last 120 years. Mass-balanced food web models indicated GSB has seen concurrent drops in size and system maturity. Twenty two of the twenty four ecosystem maturity indices measured an overall drop. GSB has experienced consistent reductions in size and structure indicating the system is under stress. Indeed, trends consistent with habitat degradation, alterations to physical conditions, phosphorus loading, and overfishing were observed. Determination of cause and effect between multiple system stressors and modeled ecosystem structure was no achieved but the results can help enhance efforts aimed at restoration by providing an understanding of system changes and historic baselines. Future modeling attempts should address the feasibility of a return to historic baselines and the management strategy that would be required to achieve such a change.

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