As part of a larger project on wild rice (Zizania palustris), an ecologically and culturally important plant in Minnesota, I am focusing on wetland biogeochemical cycles tied to the microbiome. Highthroughput sequencing datasets of ITS1 and 16S rRNA can be collated with traditional porewater and surface water chemistry datasets to identify assemblages of microbes involved in the turnover of nitrogen, sulfur, methane, methanol, and iron in the wetland environment. I use a variety of statistical techniques and machine learning algorithms to identify the effect of changes in radial oxygen loss on biogeochemical cycles and associated microbes.