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Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea.

Zhang Y, Zhao Z, Dai M, Jiao N, Herndl GJ - Mol. Ecol. (2014)

Bottom Line: Although the composition of both the total and active bacterial community was strongly correlated with environmental factors and weakly correlated with geographic distance, the active bacterial community displayed higher environmental sensitivity than the total community and particularly a greater distance effect largely caused by the active assemblage from deep waters.This might be due to a high competition between active bacterial taxa as indicated by our community network models.Based on these analyses, we speculate that high competition could cause some dispersal limitation of the active bacterial community resulting in a distinct distance-decay relationship.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Marine Environmental Sciences, Xiamen University, Xiang'an, Xiamen, 361101, China; Institute of Marine Microbes and Ecospheres, Xiamen University, Xiang'an, Xiamen, 361101, China.

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Nonmetric multidimensional scaling (NMDS) ordination with two dimensions based on thetaYC distances between heterotrophic bacterial (noncyanobacterial) DNA- (a: all communities; c: communities form cluster II in a) or RNA-based (b: all communities; d: communities from cluster III in b) communities. Each square represents an individual sample in the NMDS charts. Roman numerals represent cluster serial number. Percentages represent community similarities calculated from thetaYC distance.
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fig02: Nonmetric multidimensional scaling (NMDS) ordination with two dimensions based on thetaYC distances between heterotrophic bacterial (noncyanobacterial) DNA- (a: all communities; c: communities form cluster II in a) or RNA-based (b: all communities; d: communities from cluster III in b) communities. Each square represents an individual sample in the NMDS charts. Roman numerals represent cluster serial number. Percentages represent community similarities calculated from thetaYC distance.

Mentions: Cluster analysis based on 2-D NMDS ordination and the unweighted pair group method with arithmetic mean (UPGMA) trees constructed from thetaYC distances (MOTHUR) was performed for the heterotrophic bacterial and cyanobacterial assemblages. The heterotrophic bacterial DNA-based libraries were separated into one cluster containing communities from all surface samples (except for sites P1 and P2), the 50 m sample of site S9 and the bottom water of the sites with a depth <100 m at 51% similarity, and into one cluster of the 200–1000 m water mass at 77% similarity. In addition, communities from the estuarine sites P1 and P2 and from the bathypelagic water (2000 and 35000 m) of site S9 clustered separately at 44% and 59% similarity, respectively (Fig.2a). The chl a maximum layer (75 m) and the bottom of the euphotic zone (100 m) of site S9 were distinct (at 92% similarity) from similar depths in the DNA-based NMDS, but in the RNA-based NMDS they homogenized with similar depths, whereas the A3 site stood out (at 78% similarity) as having different active communities from other sites (Fig.2b). The estuarine sites (P1-2) were consistently distinct from the others, but there was more dispersion in the RNA-based NMDS ordination space for the mesopelagic samples compared with the DNA-based NMDS. The cluster of 100–1000 m in the DNA-based NMDS separated into two subclusters of 100–500 m (off-shore) and 500 (far-shore) to 1000 m at 51% and 30% similarity, respectively, in the RNA-based NMDS. Furthermore, cluster analysis was also performed for the subsets of the communities from the euphotic surface waters (cluster II in the DNA-based NMDS and cluster III in the RNA-based NMDS) when the estuarine and deep-water samples were excluded. The surface samples from sites S11 and 12 clustered separately from the others at 87% similarity in the DNA-based NMDS (Fig.2c). In the RNA-based NMDS, the samples from the surface of site S10 and 75 m of site S9 were distinct from the others, respectively (Fig.2d). Significant differences between pairwise clusters were obtained using the amova test (P < 0.05).


Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea.

Zhang Y, Zhao Z, Dai M, Jiao N, Herndl GJ - Mol. Ecol. (2014)

Nonmetric multidimensional scaling (NMDS) ordination with two dimensions based on thetaYC distances between heterotrophic bacterial (noncyanobacterial) DNA- (a: all communities; c: communities form cluster II in a) or RNA-based (b: all communities; d: communities from cluster III in b) communities. Each square represents an individual sample in the NMDS charts. Roman numerals represent cluster serial number. Percentages represent community similarities calculated from thetaYC distance.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230472&req=5

fig02: Nonmetric multidimensional scaling (NMDS) ordination with two dimensions based on thetaYC distances between heterotrophic bacterial (noncyanobacterial) DNA- (a: all communities; c: communities form cluster II in a) or RNA-based (b: all communities; d: communities from cluster III in b) communities. Each square represents an individual sample in the NMDS charts. Roman numerals represent cluster serial number. Percentages represent community similarities calculated from thetaYC distance.
Mentions: Cluster analysis based on 2-D NMDS ordination and the unweighted pair group method with arithmetic mean (UPGMA) trees constructed from thetaYC distances (MOTHUR) was performed for the heterotrophic bacterial and cyanobacterial assemblages. The heterotrophic bacterial DNA-based libraries were separated into one cluster containing communities from all surface samples (except for sites P1 and P2), the 50 m sample of site S9 and the bottom water of the sites with a depth <100 m at 51% similarity, and into one cluster of the 200–1000 m water mass at 77% similarity. In addition, communities from the estuarine sites P1 and P2 and from the bathypelagic water (2000 and 35000 m) of site S9 clustered separately at 44% and 59% similarity, respectively (Fig.2a). The chl a maximum layer (75 m) and the bottom of the euphotic zone (100 m) of site S9 were distinct (at 92% similarity) from similar depths in the DNA-based NMDS, but in the RNA-based NMDS they homogenized with similar depths, whereas the A3 site stood out (at 78% similarity) as having different active communities from other sites (Fig.2b). The estuarine sites (P1-2) were consistently distinct from the others, but there was more dispersion in the RNA-based NMDS ordination space for the mesopelagic samples compared with the DNA-based NMDS. The cluster of 100–1000 m in the DNA-based NMDS separated into two subclusters of 100–500 m (off-shore) and 500 (far-shore) to 1000 m at 51% and 30% similarity, respectively, in the RNA-based NMDS. Furthermore, cluster analysis was also performed for the subsets of the communities from the euphotic surface waters (cluster II in the DNA-based NMDS and cluster III in the RNA-based NMDS) when the estuarine and deep-water samples were excluded. The surface samples from sites S11 and 12 clustered separately from the others at 87% similarity in the DNA-based NMDS (Fig.2c). In the RNA-based NMDS, the samples from the surface of site S10 and 75 m of site S9 were distinct from the others, respectively (Fig.2d). Significant differences between pairwise clusters were obtained using the amova test (P < 0.05).

Bottom Line: Although the composition of both the total and active bacterial community was strongly correlated with environmental factors and weakly correlated with geographic distance, the active bacterial community displayed higher environmental sensitivity than the total community and particularly a greater distance effect largely caused by the active assemblage from deep waters.This might be due to a high competition between active bacterial taxa as indicated by our community network models.Based on these analyses, we speculate that high competition could cause some dispersal limitation of the active bacterial community resulting in a distinct distance-decay relationship.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Marine Environmental Sciences, Xiamen University, Xiang'an, Xiamen, 361101, China; Institute of Marine Microbes and Ecospheres, Xiamen University, Xiang'an, Xiamen, 361101, China.

Show MeSH
Related in: MedlinePlus