Linking Microbial Community Structure to Ecosystem Function Using Microbiome Association Mapping and Artificial Ecosystem Selection

Abstract

Microbiomes mediate a variety of important ecosystem functions. However,it remains unclear what attributes of the microbiome are important for determining the rate of ecosystem functions. Past attempts to elucidate this relationship have either looked too broadly at microbiome diversity or have assumed a priori that we know which taxa are limiting to the rate of function. To overcome this challenge, I borrowed strategies from population genetics including association mapping and artificial selection to robustly identify microbial markers of ecosystem function. I observed high heritability of methane oxidation rate in soil microbiomes demonstrating that variation in the microbial community can generate variation in ecosystem function independent of the environment. In addition, I characterized soil metagenomes along a land-use change gradient with increasing methane emissions. By looking agnostically across all microbial metabolic pathways, I identifed a surprising relationship between the relative abundance of nitrogen fixation genes and the rate of methane emissions. Using this conceptual framework to investigate biodiversity-ecosystem function relationships will deepen our understanding of microbiome function for ecosystem services and human health. This dissertation includes previously published co-authored material.