Elucidating Macroevolutionary and Macroecological Patterns in Microbes

Author: ORCID icon orcid.org/0000-0002-0960-4519
Gao, Yingnan, Biology - Graduate School of Arts and Sciences, University of Virginia
Wu, Martin, AS-Biology (BIOL), University of Virginia

Macroevolution studies evolution beyond the species level, and the debate on whether evolution occurs gradually or in pulses is still ongoing. Studies of macroevolution reveal how the tempo and mode of evolution vary across taxonomic and temporal scales. On the other hand, macroecology studies the biodiversity pattern across taxonomic, temporal, and spatial scales. Over the years, models of macroecology proliferates but a unifying theory that predicts macroecological patterns including species abundance distribution, abundance-metabolism relationship and others remains to be fully developed.
Bacteria and archaea are the most ancient, diverse, abundant, widespread, and functionally important forms of life on Earth. Thus, studying macroevolution and macroecology in microbes will provide a robust test of macroevolutionary and macroecological theories that are almost entirely developed by studying animals and plants. Despite such importance, macroevolutionary and macroecological studies in microbes are limited, primarily because of difficulties in measuring microbial traits and surveying microbial communities. Recent advances in DNA sequencing have generated big rich data that can be used to overcome some of these challenges.
In this dissertation, I demonstrated that bacterial and archaeal evolution occurs in pulses across the phylogeny. Based on this observation, I developed an algorithm that can conduct ancestral and hidden state predictions with proper uncertainty measure and implemented the algorithm in two pieces of software: one for continuous traits in general and the other for 16S rRNA gene copy number. For macroecology in microbes, I developed Fractal Maximum Entropy Theory of Ecology, or FIREFLY, a model of community structure based on the principle of maximum entropy. I demonstrated that FIREFLY’s prediction on species abundance distribution and abundance-metabolism relationship captures the observed patterns in microbes.

PHD (Doctor of Philosophy)
macroevolution, macroecology, pulsed evolution, maximum entropy
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