Sediments are key reservoirs for rare bacterial biospheres that provide broad ecological services and resilience in riverine ecosystems. Compared with planktons, there is a lack of knowledge regarding the ecological differences between abundant and rare taxa in benthic bacteria along a large river. Here, we offer comprehensive insights into the spatiotemporal distributions, co-occurrence networks, and assembly processes of three divided categories namely always rare taxa (ART), conditionally rare taxa (CRT), and conditionally rare and abundant taxa (CRAT) in sediments covering a distance of 4,300 km in the Yangtze River. Our study demonstrated that ART/CRT contributed greatly to the higher Chao-1 index, Shannon-Wiener index, and phylogenetic alpha diversity of benthic bacteria in autumn than in spring. ART showed high overall beta diversity, and CRT/CRAT exhibited more significant distance-decay patterns than ART in both seasons, mainly corresponding to macroscopic landform types. CRT predominated the nonrandom co-occurrence network, with 97% of the keystone species mostly affiliated with Acidobacteriota flourishing in the lower-reach plain. Two selection processes had the greatest influences on the assembly of CRT (74.7-77.6%), whereas CRAT were driven primarily by dispersal limitation (74.9-86.8%) and ART were driven by heterogeneous selection (33.9-48.5%) and undominated stochasticity (32.7-36.5%). Natural factors such as river flow and channel slope exhibited more significant correlations with community variation than nutrients in all three groups, and total organic carbon mediated the balance among the distinct assembly processes of the ART and CRT in both seasons. Taken together, these results provide an improved ecological understanding of the discrepancy in biogeographic patterns between abundant and rare bacterial taxa in the sediments of Asia's largest river.
Keywords: abundant and rare taxa; assembling processes; biogeography; co-occurrence network; sedimentary bacteria; the Yangtze River.
Copyright © 2024 Zhang, Liu, Du, Li, Wu, Liu and Wang.