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.