Ecological Patterns Among Bacteria and Microbial Eukaryotes Derived from Network Analyses in a Low-Salinity Lake.

Abstract

Microbial communities are comprised of complex assemblages of highly interactive taxa. We employed network analyses to identify and describe microbial interactions and co-occurrence patterns between microbial eukaryotes and bacteria at two locations within a low salinity (0.5-3.5ppt) lake over an annual cycle. We previously documented that the microbial diversity and community composition within Lake Texoma, southwest USA, were significantly affected by both seasonal forces and a site-specific bloom of the harmful alga, Prymnesium parvum. We used network analyses to answer ecological questions involving both the bacterial and microbial eukaryotic datasets and to infer ecological relationships within the microbial communities. Patterns of connectivity at both locations reflected the seasonality of the lake including a large rain disturbance in May, while a comparison of the communities between locations revealed a localized response to the algal bloom. A network built from shared nodes (microbial operational taxonomic units and environmental variables) and correlations identified conserved associations at both locations within the lake. Using network analyses, we were able to detect disturbance events, characterize the ecological extent of a harmful algal bloom, and infer ecological relationships not apparent from diversity statistics alone.