Publication Date


Document Type


First Advisor

Swingley, Wesley D.

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Biological Sciences


Critical ecosystem functions, such as decomposition and nutrient cycling, are driven by microbial communities within soil. As such, it is important to examine the effect of restoration practices, such as the presence of native grazers and prescribed burning, on these microbes and the soil they inhabit. The Nachusa Grasslands provides a chronosequence of restored tallgrass prairies ranging in restoration age from 5 to 33 years, as well as remnant prairies, and agricultural fields. These sites were sampled seasonally from 2013-2020 and microbial ribosomal RNA genes were surveyed to characterize soil microbial communities and assess how common restoration practices affect these communities. Geochemical analyses were performed to quantify soil carbon and nitrogen content, pH, and moisture. These data were compared to microbial community compositions between and within sites to assess the impact of burn regime, bison introduction, restoration age, seasonal variation, and soil geochemistry. Every soil and land management variable had significant associations with microbial community dynamics as well as other variables, demonstrating the interconnected nature of these restorations. Site age since restoration had the greatest impact on relative abundance of the most abundant microbial groups and was positively correlated with biodiversity metrics and soil geochemistry values. Bison presence was significantly correlated with changes in soil geochemistry and microbial biodiversity that corresponded with similar changes in remnant prairies. Prescribed fire was significantly correlated with changes in community diversity metrics at the alpha level. The aim of this research was to discover how differences in microbial community structure in grasslands are driven by these land management practices and their effects on the soil ecosystem. Informed with this knowledge, land managers, scientists, and policy makers may use these data to guide prairie restoration planning and to forecast restoration success.


68 pages




Northern Illinois University

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