OBSERVED RELATIONSHIPS BETWEEN WATER CHEMISTRY AND PLANT COMMUNITIES IN GROUNDWATER-DEPENDENT ECOSYSTEMS, ASHLEY NATIONAL FOREST, UINTA MOUNTAINS, UTAH

A variety of groundwater-dependent ecosystems make up the montane wetlands of the Uinta Mountains, northeastern Utah. Unlike other ranges of the Rocky Mountains, these systems have been relatively unstudied. The Department of Geosciences at Weber State University partnered with the U.S. Forest Service, Ashley National Forest, to conduct a multidisciplinary baseline study of the relationships between plant communities and water chemistry within these alpine fens. The drainage basin of Reader Creek, located near the crest of the range on the south slope, was selected for detailed study because of its variety of wetland plant communities, minimal human impact, and homogenous bedrock geology.

Water chemistry data were collected from more than 100 locations over two summer seasons in 2008 and 2009. NAIP CIR orthoimagery from 2006 were used to map 13 plant-community classes by performing a maximum-likelihood supervised classification, based on selected training sites in the field. Representative water samples were also collected for the nine plant classes associated with standing water. This digital-imagery-based classification was also tested in the neighboring Dry Fork basin.

A significant geomorphic characteristic of these wetlands is their compartmentalization by a system of flarks and strings, oriented perpendicular to the dominant surface flow. Deeper portions of the peat work as highly isolated flow cells that store water for extended periods of time. The study area is characterized by relatively narrow range of pH values (5.1 to 7.6), with higher values corresponding to sloping fens with greater topographic relief and lower values observed in valley-bottom fens. Basic parameters including pH, dissolved oxygen, oxidizing-reducing potential, and concentration of phosphates and nitrates were divided into classes ranging from low to high values. Preliminary observations indicate that each of the plant classes displays a unique combination of these parameters, with very little overlap between classes. The relationships between measured chemical parameters and the image-classified plant communities are currently being examined to determine if strong correlations can be identified and subsequently used to map varying groundwater conditions based on wetland types across the Uinta Mountains.