Date of Award

May 2022

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Biological Sciences

First Advisor

Emily Latch

Committee Members

Filipe Alberto, Peter Dunn, Gerlinde Hoebel, Rafael Rodriguez

Keywords

conservation, evolutionary biology, phylogeny, phylogeography, population genetics, population genomics

Abstract

Molecular evolution refers to a broad field of studies ranging from microevolution (e.g., population genetics) to macroevolution (e.g., phylogeny), including the bridging field of phylogeography. In natural populations, molecular studies are also combined with biogeography that links biological diversity with geographic distributions to provide a comprehensive understanding of evolutionary processes. The field of molecular evolution has been largely advanced from early exploratory descriptions to statistical tests on biological hypotheses and integrative analyses using sophisticated modeling. However, studies of molecular evolution still face some unresolved questions and challenges, especially in non-model systems. For example, the application of new technology has largely lagged behind in non-model systems, leaving plenty of knowledge gaps that also constrain developments of evolutionary theories. In addition, non-model organisms comprise the majority of global biodiversity and are urgently in need of conservation management, which requires better understanding of their evolution, biogeographic history, and population genetic structure. One of the non-model systems urgently in need of research is bats (order Chiroptera), the second largest mammalian order with > 1,400 globally distributed species. Bats have mysterious evolutionary histories and unique adaptations such as echolocation, powered flight, morphological convergence, adaptation in diverse ecological niches, and tolerance to viruses. The recent spillovers of bat-carrying viruses additionally call for research on bat ecology, distribution, and evolution, to help predict and control future virus spillovers as well as for better conservation management of bats. In my doctoral dissertation, I studied the molecular evolution and biogeography of the cosmopolitan bat genus Eptesicus (family Vespertilionidae) with a focus on the New World species. First, I analyzed the phylogenetic relationships among New World Eptesicus species, including the morphological genus Histiotus which is endemic to South America and has been found closely related to New World Eptesicus. Second, I studied the range-wide nuclear phylogeography of the widespread Eptesicus species in North America, the big brown bat (Eptesicus fuscus). Third, I estimated the effects of nonrandom missing data on the population genetic structure inferred by the Principal Component Analysis (PCA). I found that the Old World Eptesicus bats most likely colonized the New World via the trans-Atlantic route from North Africa to the northern Neotropics in early to mid-Miocene. Cryptic diversity was indicated in the Neotropics, and the Histiotus species were found more closely related to Eptesicus fuscus. I found that distribution shifts of the North American E. fuscus during the Pleistocene glaciation cycles might have initiated the phylogeographic divergence shown by mitochondrial and nuclear DNA as well as morphological subspecies. On the other hand, strong secondary gene flow might have been merging the once diverged western phylogeographic lineages. In addition, I found that the population structure illustrated by PCA could be misinterpreted when using mean imputation of large amounts of nonrandom missing data, which could be common in non-model systems. I found that individuals biased with high amounts of missing data would be dragged towards the PCA origin and could be indistinguishable from truly admixed individuals. Accordingly, my dissertation research on Eptesicus bats covered a broad spatial-temporal scale to study their evolutionary history, biogeographic divergence, and inform conservation management. I showcase how the application of genomics and integrative analyses in non-model systems can shed new light on our empirical as well as theoretical understanding of evolution and biodiversity.

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