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dc.contributor.authorLichvar, Robert.-
dc.contributor.authorGoulet, Jennifer J.-
dc.description.abstractAbstract: This study explored methods for collecting and analyzing data during challenges to wetland ratings on the National Wetland Plant List (NWPL) to determine if study area size and landscape type affect wetland frequency and ratings. Data were collected in three different-sized study areas with different types of landscapes. Wetland frequency was calculated by using the original and an adjusted formula; and wetland ratings were predicted by using a Bayesian model. The original formula produced fewer hydrophytic ratings than the adjusted formula and the Bayesian model. In the smallest study areas (100 km²), wetland ratings varied with landscape characteristics. The same wetland frequencies and ratings were produced in moderately large (20,000 km²) and large (742,800 km²) study areas provided sample size was adequate. These results suggest that a wetland determination should be made for each sample unit based on the presence or absence of wetland indicators. Sample size should be large enough to achieve a confidence interval of 95% and a 3%–5% margin of error. When wetland frequency is close to 33%, Bayesian models could provide support for wetland rating determinations. The National Technical Committee for Wetland Vegetation and the National Panel of the NWPL will work with challengers to create a study design appropriate for each species.en_US
dc.description.sponsorshipWetlands Regulatory Assistance Program (U.S.)en_US
dc.publisherCold Regions Research and Engineering Laboratory (U.S.)en_US
dc.publisherEngineer Research and Development Center (U.S.)en_US
dc.subjectIndicator statusen_US
dc.subjectNational Wetland Plant Listen_US
dc.subjectVegetation surveysen_US
dc.subjectWetland ecologyen_US
dc.subjectWetland frequencyen_US
dc.titleTesting methods for challenging the National Wetland Plant List : using Tsuga canadensis (L.) Carr. (Eastern Hemlock) as a case studyen_US
Appears in Collections:Technical Report

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