THEORETICAL AND QUANTITATIVE METHODS CONNECTING CHARACTERIZING MICORIBAL METABOLISM DIVERSITY: IMPLCIATIONS FROM PHYLOGENETICS, COMMUNITY DIVERSITY, AND ORGANIC GEOCHEMISTRY

Biogeochemistry is controlled by microorganisms obtaining nutrients and energy. Thus, microbial metabolisms directly link microbial ecology and geochemistry. The extent that microbial ecology and geochemistry microbial ecology and geochemistry affects the other requires constraint on the spatiotemporal distribution and abundance of microbial metabolisms with respect to geochemistry, or the microbial niches. Elucidating microbial metabolisms was challenging prior to the advent of ‘omics sequencing technologies, as most microbial lineages lack cultured representatives. Although revolutionizing microbial ecology, challenges still exist in fully leveraging information derived from ‘omics technologies. This dissertation attempts to address a small subset of these challenges that include quantifying the generalizability of microbial metabolism with respect to phylogeny, relating metagenomic sequencing effort to in situ genome discovery rates, quantifying and generalizing the relative contribution to a net ecosystem function by community members, and relating geochemistry gradients to microbial metabolism gradients. As a part of this work, theoretical and quantitative measures are proposed for evaluating microbial metabolism diversity with respect to phylogenetics (permutational multivariate ANOVA and variance component modeling), community diversity (generalized coupon collector equation, parametric diversity), and in situ geochemistry at the field site, White Oak River estuary, North Carolina (USA). Numerical simulations (community rarefaction, community extinction events, and reaction-transport modeling) and public data repositories (Reference Sequence Database, GenBank, Integrated Microbial Genome and Microbiomes, and Sequence Read Archive) are used for the testing efficacy of the proposed theoretical and quantitative methods. The results indicate that numerical simulations and public data repositories can be used for developing and testing ecological theory and concepts. The theoretical and quantitative methods proposed here can now be used in exploring microbial niche distributions in nature.