Assessing wetland ecological condition in the Cuyahoga River Watershed.

We used an assessment approach combining the USEPA EMAP probabilistic sampling design with existing Ohio wetland assessment tools, including the Ohio rapid assessment method (ORAM), the modified Penn State Stressor Checklist, the Vegetation IBI and the Amphibian IBI, along with a landscape analysis (the Landscape Development Intensity Index) to evaluate the ecological condition of wetlands in the 1,300 km Cuyahoga River watershed. Sample sites were selected using the Generalized Random Tesselation Stratified (GRTS) survey design, which provides a geospatially balanced, stratified random sample. The Ohio Wetland Inventory was used as the sample frame for the population of wetlands in the watershed. We evaluated 366 mapped wetland sites and assessed 243 wetlands to determine condition and report on their response to surrounding land-use. Of the 366 sites, we determined that 243 points (66.4 %) were wetlands while the remainder (16.4 %) were characterized as non-wetlands (n = 60) or duplicate points (n = 18). In 12.3 % of the cases (n = 45), field crews were denied site access by property owners. For the wetlands sampled, ORAM scores were normally distributed with a minimum of 16.0, a maximum of 94.0, and a mean of 55.6 (± 14.5 SD). Across the entire watershed, 9.1% of wetlands were in poor condition, 13.2% in fair condition, 51.0% in good condition, and 26.7% in very good condition. There was dramatic decline in the numbers of Category 3 wetlands from the upper parts of the watershed in Geauga county (49.3% of all wetlands sampled), to the middle parts of the watershed in Portage (18.5% and Summit (19.6%) counties, and the near disappearance of Category 3 wetlands in Cuyahoga county (8.3%). Using the Landscape Development Index (LDI), we evaluated the scale at which the effects of land-use are strongest over six buffer widths: 100, 250, 500, 1000, 2000, and 4000 m. ORAM scores were negatively correlated with increasing intensity of land use (high LDI scores) for depressional, riverine, and slope wetlands for each buffer width to a distance of 1000 m, with the strongest correlations for the 100 and 250 m buffer distances. For impoundments, land-use in the first three buffer distances through 500 m did not relate to ORAM score. Overall, land use intensity in the watershed can be characterized as in "low" to "moderately-low". Wetlands in Geauga county had significantly lower LDI scores across most buffer distances than wetlands _________ 1. Department of Biology, Kenyon College, Gambier, Ohio 43022, fennessym@kenyon.edu. 2. Cleveland Metroparks, 4600 Valley Parkway, Fairview Park, Ohio 44126, jjm@clevelandmetroparks.com. 3. Department of Biology, Kenyon College, Gambier, Ohio 43022 4. Cuyahoga River Community Planning Organization, NOACA building, 1299 Superior Avenue, Cleveland, OH 44114, sullivanm@cuyahogariverrap.org. 5. Penn State Cooperative Wetlands Center, 110 Land and Water Research Building, University Park, PA, 16802, jab190@psu.edu. 6. School of Forest Resources and Conservation, University of Florida, 328 Newins-Ziegler Hall, P.O. Box 110410, Gainesville, FL, 32611, mjc@ufl.edu 7. Division of Surface Water, Ohio Environmental Protection Agency, 4675 Homer-Ohio Lane, Groveport, Ohio, 43125 Summit, and Portage counties, particularly for the 1000 m, 2000 m, and 4000 m buffers. The predictive in