Synthesizing Phylogeography and Community Ecology to Understand Patterns of Community Diversity

• Main Author: Williams, Trevor J.
• Format: Others
• Published: BYU ScholarsArchive 2021
• Subjects: Approximate Bayesian Computation; community ecology; dispersal; diversity; habitat filtering; history; metacommunity ecology; phylogeography; population genetics; process-pattern; synthesis; Life Sciences
• Online Access: https://scholarsarchive.byu.edu/etd/9176; https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10185&context=etd

Community ecology is the study of the patterns and processes governing species abundance, distribution, and diversity within and between communities. Likewise, phylogeography is the study of the historic processes controlling genetic diversity across space. Both fields investigate diversity, albeit at different temporal, spatial and taxonomic scales and therefore have varying assumptions. Community ecology typically focuses on contemporary mechanisms whereas phylogeography studies historic ones. However, new research has discovered that both genetic and community diversity can be influenced by contemporary and historic processes in tandem. As such, a growing number of researchers have called for greater integration of phylogeography and ecology to better understand the mechanisms structuring diversity. In this dissertation I attempt to add to this integration by investigating ways that phylogeography and population genetics can enhance studies on community ecology. First, I review traditional studies on freshwater fish community assembly using null model analyses of species co-occurrence, which shows that fish are largely structured by deterministic processes, though the importance of different mechanisms varies across climates, habitats, and spatial scales. Next, I show how phylogeographic data can greatly enhance inferences of community assembly in freshwater fish communities in Costa Rica and Utah respectively. My Costa Rican analyses indicate that historic eustatic sea-level change can be better at predicting community structure within a biogeographic province than contemporary processes. In comparison, my Utah analyses show that historic dispersal between isolated basins in conjunction with contemporary habitat filtering, dispersal limitation, and extinction dynamics both influence community assembly through time. Finally, I adapt a forward-time population genetics stochastic simulation model to work in a metacommunity context and integrate it with Approximate Bayesian Computation to infer the processes that govern observed community composition patterns. Overall, I show that community ecology can be greatly enhanced by including information and methods from different but related fields and encourage future ecologists to further this research to gain a greater understanding of biological diversity.