Erratum to: Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies

Abstract Microbial communities inhabiting river ecosystems play crucial roles in global biogeochemical cycling and pollution attenuation. Spatial variations in local microbial assemblages are important for detailed understanding of community assembly and developing robust biodiversity sampling strategies. Here, we intensely analyzed twenty water samples collected from a one-meter spaced transect from the near-shore to the near-center in the Meramec River in eastern Missouri, USA and examined the microbial community composition with 16S rRNA gene amplicon sequencing. Riverine microbiomes across the transect exhibited extremely high similarity, with Pearson’s correlation coefficients above 0.9 for all pairwise community composition comparisons. However, despite the high similarity, PERMANOVA revealed significant spatial differences between near-shore and near-center communities ( p = 0.001). Sloan’s neutral model simulations revealed that within-transect community composition variation was largely explained by demographic stochasticity ( R 2 = 0.89). Despite being primarily explained by neutral processes, LefSe analyses also revealed taxa from ten families of which relative abundances differed directionally from the bank to the river center, indicating an additional role of environmental filtering. Notably, the local variations within a river transect can have profound impacts on the documentation of alpha diversity. Taxon-accumulation curves indicated that even twenty samples did not fully saturate the sampling effort at the genus level, yet four, six and seven samples were able to capture 80% of the phylum-level, family-level, and genus-level diversity, respectively. This study for the first time reveals hyperlocal variations in riverine microbiomes and their assembly mechanisms, demanding attention to more robust sampling strategies for documenting microbial diversity in riverine systems.