Responses of benthic macrofauna to environmental stressors: a synthesis of Chesapeake Bay data

dc.creatorTreda Grayson
dc.date.accessioned2022-01-25T19:05:42Z
dc.date.available2022-01-25T19:05:42Z
dc.date.issued2019
dc.description.abstractChesapeake Bay is the largest estuary in the United States, and is of ecological, historical, economic and cultural importance. The pressures of increased population density, land development, and agricultural practices have resulted in a threatened bay ecosystem that needs ongoing restoration and protection. There are a number of monitoring programs, research institutions, non-profit organizations, and local, state and federal agencies in the Chesapeake region that are dedicated to and focused on collecting, monitoring and analyzing data, as well as developing management practices and tools to preserve and protect the Bay. Physical, chemical and biological data from these various research and assessment programs were used to identify specific individual taxa responses to specific stressors, first with correlation analysis followed by Generalized Additive Models (GAMs) to build models for amphipods Ampelisca abdita, Ampelisca verrilli, and polychaete Spiochaetopterus costarum. These three taxa were shown to have significant relationships to environmental pollutants and water quality variables based on analyses performed. The models were tested with Delaware Bay taxa and one model – A. verilli – performed well. Some model fine-tuning is necessary to make the models broadly applicable to systems outside of Chesapeake Bay. Once achieved, these models have the potential to complement benthic condition tools such as the Benthic Index of Biotic Integrity (B-IBI), to provide decision-makers with information to better manage and direct monitoring and assessment resources.
dc.identifier.urihttps://hdl.handle.net/1920/12257
dc.titleResponses of benthic macrofauna to environmental stressors: a synthesis of Chesapeake Bay data
thesis.degree.disciplineEnvironmental Science and Policy
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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