An index of ecosystem integrity for Northern Chesapeake Bay |
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| Institution: | 1. Gulf Coast Research Laboratory, University of Southern Mississippi, 703 E. Beach Dr., Ocean Springs, MS, 39564, United States;2. Center for Coastal Physical Oceanography, Department of Ocean, Earth and Atmospheric Sciences, 4111 Monarch Way, 3rd Floor, Old Dominion University, Norfolk, VA, 23529, United States;3. Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Ave., Port Norris, NJ, 08349, United States;4. Virginia Institute of Marine Science, College of William and Mary, P.O. Box 1346, Gloucester Point, VA, 23062, United States;1. Institute of Marine Environment and Ecology, National Taiwan Ocean University, Keelung 20224, Taiwan, ROC;2. Institute of Marine Biology, National Taiwan Ocean University, Keelung 20224, Taiwan, ROC;3. Center of Excellence of the Oceans, National Taiwan Ocean University, Keelung 20224, Taiwan, ROC;1. Department of Ocean, Earth, and Atmospheric Sciences, Old Dominion University, Norfolk, VA 23529, USA;2. Department of Biological Sciences, University of Rhode Island, Kingston, RI 02881, USA;3. School of Oceanography, University of Washington, Seattle, WA 98195, USA;1. School of Civil, Environmental and Mining Engineering, The University of Western Australia, Australia;2. UWA Oceans Institute, Australia;3. School of Earth and Environment, The University of Western Australia, Australia |
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| Abstract: | We propose a theoretical approach to evaluating the quality of large ecosystems under anthropogenic stress, and present a partial application of these ideas. We synthesized data from a variety of Chesapeake Bay monitoring programs into composite variables expressing ecosystem integrity. The analysis spanned most of the larger Maryland tributaries to the Bay (tidal fresh to mesohaline areas) for nine years (1986–1994). An index modeled on the Index of Biotic Integrity (IBI) and a multivariate ordination and ranking method combined information on aquatic plant, plankton, benthic and fish assemblages with water quality-based habitat goals. The multivariate method proved superior to the IBI approach in discriminating ecosystem integrity. A logistic regression model with watershed land use characteristics and water depth as independent variables explained a significant amount of variation in the multivariate rank index. Urban land use had the most negative effect on the index, whereas forested land had the most positive effect. |
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