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Microbial communities are vital components of freshwater ecosystems due to their role in nutrient cycling and energy flow; however, the mechanisms driving their variation are still being explored. In aquatic systems, water flow (hydrology) can impact microbial community composition through community connectivity; however, the details of hydrology’s effects on microbial connectivity remain unclear. To address this question, we used 16S rRNA metabarcoding to determine bacterial community composition and connectivity across flow transects in three connected Great Lakes waterbodies with very different water-flow regimes: the Little River (high flow), the Detroit River (moderate flow), and Lake Erie (low flow). Bacterial alpha diversity (Chao1) did not differ among the three locations or sample sites along the transects. Analyses of beta diversity using community dissimilarity matrices identified significant differences among the three locations and among sample sites within locations. Bacterial community connectivity varied among the three locations, with a significant distance–decay relationship observed only in the low-flow location, which is indicative of connectivity driven by spatial proximity. Directional analyses showed that the water-flow direction affected bacterial similarity, consistent with the expected hydrological effects on community connectivity and previous published work. Our results indicate that (1) microbial community composition varies within and among even geographically close sampling locations and (2) the specific water-flow regime appears to affect bacterial community connectivity. Including hydrology in models of bacterial community composition will improve our understanding of the relative roles of selection versus stochastic effects on bacterial community diversity and composition in freshwater ecosystems.
Sadeghi et al. (Sun,) studied this question.