Monday, May 26, 2008 - 11:00 AM
52

Comparison of benthic macroinvertebrate response models to urban intensity in nine metropolitan areas of the conterminous united states

Thomas F. Cuffney1, Gerard McMahon1, Ian R. Waite2, Jason T. May3, and Robin A. Brightbill4. (1) North Carolina Water Science Center, U.S. Geological Survey, 3916 Sunset Ridge Road, Raleigh, NC 27607, (2) Oregon Water Science Center, U.S. Geological Survey, 2130 SW 5th Avenue, Portland, OR 97201, (3) California Water Science Center, U.S. Geological Survey, 600 J. Street, Placer Hall, Sacramento, CA 95819, (4) Pennsylvania Water Science Center, U.S. Geological Survey, 215 Limekiln Road, New Cumberland, PA 17070

The effects of urbanization on macroinvertebrates were studied in nine metropolitan areas (Boston, MA; Raleigh, NC; Atlanta, GA; Birmingham, AL; Milwaukee-Green Bay, WI; Denver, CO; Dallas-Fort Worth, TX; Salt Lake City, UT; Portland, OR) as part of the U.S. Geological Survey’s National Water-Quality Assessment Program. Regression models relating responses (i.e., ordination site scores and metrics) to urban intensity, population, infrastructure, and land-cover variables were developed for each metropolitan area.  These models were compared on their ability (R2) to depict changes along the urban gradient and to predict responses in other metropolitan areas (e.g., using the Atlanta, GA model to predict changes in Raleigh, NC). Ordination models derived from first-axis ordination (CA or NMDS) site scores were more strongly related (R2 = 0.49-0.82) to urban intensity than were models based on metrics (R2 = 0.14-0.49).  Multiple regression models relating land cover, infrastructure, and population density to ordination site scores and metrics tended to be better predictors (multiple R2 = 0.44-0.91) of responses than were models based solely on urban intensity.  Ordination models were better able to predict responses in other metropolitan areas than were models based on metrics provided the metropolitan areas had similar invertebrate assemblages. 


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