Biogeographic Patterns in Members of Globally Distributed and Dominant Taxa Found in Port Microbial Communities
Abstract
Microbes are ubiquitous throughout the world and are highly diverse. Characterizing the extent of variation in the microbial diversity across large geographic spatial scales is a challenge yet can reveal a lot about what biogeography can tell us about microbial populations and their behavior. Machine learning approaches have been used mostly to examine the human microbiome and, to some extent, microbial communities from the environment. Here, we display how supervised machine learning approaches can be useful to understand microbial biodiversity and biogeography using microbes from globally distributed shipping ports. Our findings indicate that the members of globally dominant phyla are important for differentiating locations, which reduces the reliance on rare taxa to probe geography. Further, this study displays how global biogeographic patterning of aquatic microbial communities (and other systems) can be assessed through populations of the highly abundant and ubiquitous taxa that dominant the system.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 26, 2020
- Source ID
- 10.1128/msphere.00481-19
Entities
People
- Laura G Schaerer
- Ryan B Ghannam
- Stephen M. Techtmann
- Timothy M. Butler
Organizations
- Michigan Technological University