Figure legends
Fig. 1 The composition and diversity metrics of the bacterial communities in the Beibu Gulf sediment. a Community composition at the phylum level; b Community richness (log transformed) for the whole community, the abundant and the rare subcommunities; c Community dissimilarity for the whole community, abundant and rare subcommunities. The Bray-Curtis dissimilarity was calculated and used for community dissimilarity.
Fig. 2 Spatial scaling patterns followed by sedimental microbes in Beibu Gulf. a Taxa-area relationship (TAR) for the whole community, the abundant and the rare subcommunitiesm, by investigating the relationship between log-transformed richness and area; bDistance decay relationship (DDR) for the whole community, the abundant and the rare subcommunities, by investigating the relationship between log-transformed community similarity (1-Bray-Curthis dissimilarity) and geographic distance; c The slope coefficient (z-value) of the diversity-area relationships (DARq) with different diversity orders (q ) by extending TAR to DARq and the slope coefficient (d -value) of the distance decay relationship (DDRq) with diversity order (q ) by extending DDR to DDRq.
Fig. 3 Linking microbial spatial scaling diversity metrics with environmental heterogeneity. a The association between environmental heterogeneity and differed species richness of the whole community, the abundant subcommunities and the rare subcommunities. The number of unique taxa in two sample pairs were calculated for differed richness. b Association between community similarity and environmental heterogeneity. The community similarity was calculated as 1-Bray-Curtis dissimilarity. The Euclidean distance based on normalized environmental variables was calculated to represent the environmental heterogeneity between different samples.
Fig. 4 Properties of microbial taxa at the levels of whole community, abundant subcommunities, and rare subcommunities. aPercentage of microbial ASVs mapped to the deep sequencing dataset;b Percentage of reads mapped to the deep sequencing dataset;c Niche breadth of microbial ASVs; d Niche overlap of microbial ASVs. The Levin’s and Pianka’s indices were respectively calculated for niche breadth and niche overlap.
Fig. 5 Local community mechanisms driving the compositional variations of sedimental microbial communities in the Beibu Gulf. Local community mechanisms were quantified for the whole community (a ), the abundant subcommunities (b ), and the rare subcommunities (c ). The contribution of five different ecological processes, including homogeneous selection (HoS), heterogeneous selection (HeS), drift (DF), dispersal limitation (DL), and homogeneous dispersal (HD), were quantified.