Katie Hossler (Advisor), Megan A. Rúa (Advisor), Don Cipollini (Committee Member)
Master of Science (MS)
In the contiguous US, an estimated 50% of original wetland areas have been lost since the late 1700s. In growing recognition of the importance of preserving wetland ecosystem function, federal and state agencies have developed proxy-based functional-assessment procedures to manage and preserve remaining wetland areas. Ohio uses the Ohio Rapid Assessment Method (ORAM) to score wetland quality based on six metrics: wetland size, buffer width and surrounding land use, hydrology, habitat alteration and development, special wetland communities, and vegetation. Currently, the ORAM, and many other wetland scoring systems, do not consider microorganisms when determining wetland quality. This is particularly notable, because fungi are considered the primary decomposers of organic material in many wetlands making them important players in nutrient cycling. In this thesis I aim to (1) quantify differences in fungal diversity, community composition, and function between freshwater marshes of different quality ratings, (2) quantify differences in soil physicochemical properties (e.g. nutrient availability, bulk density) between freshwater marshes of different quality ratings and determine the role of soil physicochemical properties in structuring fungal communities in freshwater marshes, and (3) quantify differences in plant community composition between freshwater marshes of different quality ratings and determine the role of vegetation in structuring fungal communities in freshwater marshes. To achieve these three aims I identified six depressional emergent marshes in the state of Ohio belonging to each of the three ORAM quality categories, and surveyed the vegetation at each to identify sampling stations. Using a stratified random sampling design, I then sampled soil from each wetland for soil physicochemical properties and DNA. Soil physicochemical properties measured include soil bulk density (BD), pH, soil organic matter (SOM), gravimetric water content (soil moisture), Phosphorous (P), Nitrogen (N), Carbon (C), and soil texture (%Sand, %Silt, %Clay). Extracted DNA was amplified using the fungal specific ITS1F and ITS2 PCR primers, and then sequenced on the Illumina MiSeq platform at the Ohio State University Molecular Imaging Center. Sequences were processed using the bioinformatics pipeline Quantitative Insights into Microbial Ecology 2. My results indicate that the current ORAM scoring methodology weakly explains differences in fungal community composition between wetlands and that individual ORAM metrics are stronger predictor variables for fungal community composition. I also found that soil physicochemical properties are strong drivers of fungal community composition, particularly BD, pH, SOM, soil moisture, N, and C. I recommend that assessment methods be improved through the reweighting of current metrics and the inclusion of more quantitative measures of vegetation and soil physicochemical properties so that soil microorganism communities are better accounted for in assessment methods.
Department or Program
Department of Biological Sciences
Year Degree Awarded
Copyright 2018, all rights reserved. My ETD will be available under the "Fair Use" terms of copyright law.