Additional file 1 of Taxonomic dependency and spatial heterogeneity in assembly mechanisms of bacteria across complex coastal waters
Creators: name: Yan, Huizhen
name: Lin, Dandan
name: Gu, Gaoke
name: Huang, Yujie
name: Hu, Xuya
name: Yu, Zhenhao
name: Hou, Dandi
name: Zhang, Demin
name: Campbell, Barbara J.
name: Wang, Kai
Publisher: name: figshare
Year: 2024
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified

description: Additional file 1: Supplementary methods. Figure S1. The map of sampling stations from eight coastal zones. The colors of the stations correspond to different zones, and the stations in the Zhoushan archipelago were grouped into three subzones including ZSI_north (northern part of the archipelago), ZSI_mouth (in the mouth of HZ), and ZSI_other (others), which were shown as square, circle, and triangle symbols, respectively. Figure S2. Fit of the neutral model for bacterial ZOTUs with bacterial metacommunity across the sampling zones as the source. R2 values present the goodness of fit of the neutral model, ranging from 0 (no fit) to 1 (perfect fit). The ZOTUs that occurred more frequently than predicted by the model are shown in green, while those occurred less frequently than predicted are shown in orange (A). The ZOTUs are colored by their taxonomy at the phylum level and at the class level for the phylum Proteobacteria (B). Dashed lines represent 95% confidence intervals around the model prediction and the ZOTUs fall within the confidence intervals were considered as neutrally distributed. Figure S3. Mantel correlograms showing significant phylogenetic signal in between-ZOTU niche differences across short phylogenetic distances for total bacterial and key bacterial communities. Solid and open symbols present significant (P &lt; 0.05 after Holm correction, 999 permutations) and non-significant Pearson correlations between niche differences and phylogenetic distances, respectively, across phylogenetic distance classes. Absent circle symbols indicate that no phylogenetic distance value is assigned to the corresponding distance class. Figure S4. The percentage of ecological processes governing the spatial turnover of total bacterial communities or seven taxonomic groups in all pairwise comparisons between stations according to βNTI or RCbray values. Figure S5. The geographic distribution of the ecological processes governing the spatial turnover of total bacterial community and seven taxonomic groups in all pairwise comparisons between stations according to βNTI and RCbray values. Each column corresponds to a specific ecological process as noted at the top. Figure S6. The optimal number of resource states when setting different number of groups for the partition based on the simple structure index (SSI) using K-means partitioning (1,000,000 iterations) (A). Spatial distribution of the resource states determined by K-means partitioning based on water environmental conditions (B). The colors of the stations correspond to different resource states. Figure S7. Box plots illustrating the ecological features of total bacterial community and seven taxonomic groups, including ratio of relative abundance of non-neutrally distributed ZOTUs to that of neutrally distributed ZOTUs, standardized Levins’ niche breadth, alpha diversity indices including phylogenetic diversity, ZOTU richness, and Shannon–Wiener index, relative abundance, and the features of microbial associations including cohesion ratio (|negative cohesion/positive cohesion|), modularity, and average degree across sampling stations. Different communities sharing the same letter above the boxes are not significantly different from each other, whereas two communities with different letters are significantly different (multiple comparisons after Kruskal–Wallis test, P &lt; 0.05). Figure S8. Cumulative relative abundance of habitat specialists and generalists in the total bacterial community and the seven taxonomic groups. ZOTUs with standardized niche breadth (BA) value &gt; 0.5 were regarded as habitat generalists, and ZOTUs with BA &lt; 0.05 were defined as specialists. This criterion was chosen according to the frequency distribution of BA value for all ZOTUs. Figure S9. Distance-based redundancy analysis (db-RDA) plots based on Bray–Curtis dissimilarity illustrating environmental constraints of compositional variation of total bacterial communities and seven bacterial groups. Environmental variables were normalized to reduce the effect of unit differences. The “vif.cca” and “envfit” functions of the “vegan” package in R environment were used to identify nonredundant (variance inflation factors &lt; 10) and significant (P &lt; 0.05) constraints for generating the final ordinations. DO, dissolved oxygen; SP, suspended particle; COD, chemical oxygen demand; Chl-a, chlorophyll-a. HZ, Hangzhou Bay; ZSI, Zhoushan archipelago; XS, Xiangshan Bay; SM, Sanmen Bay; SP, Shipu; JS, Jiushan; YS, Yushan Reserve; BIC, the east boundary of the Island-chain. Dataset S1. Numbers of reads and ZOTUs of dominant bacterial taxa (cumulative proportion of reads &gt; 2% in the whole dataset).