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Phylogenetic analysis suggests that habitat filtering is structuring marine bacterial communities across the globe.

Pontarp M, Canbäck B, Tunlid A, Lundberg P - Microb. Ecol. (2012)

Bottom Line: Different bacterial types seem to have different ecological niches that dictate their survival in different habitats.Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed.The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

View Article: PubMed Central - PubMed

Affiliation: Theoretical Population Ecology and Evolution Group, Lund University, Lund, Sweden. mikael.pontarp@biol.lu.se

ABSTRACT
The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

Show MeSH
a Morisita’s index of similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between Morisita’s index data and difference in water temperature, −0.64. b Phylogenetic similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between phylogenetic similarity and difference in water temperature, −0.50
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Fig3: a Morisita’s index of similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between Morisita’s index data and difference in water temperature, −0.64. b Phylogenetic similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between phylogenetic similarity and difference in water temperature, −0.50

Mentions: Although the pairwise significance tests, above, give high values, the Unifrac jackknife analysis show patterns of differentiation between localities. Two nodes in the Unifrac dendrogram was recovered in >99.9% of the randomised jackknife resampling analysis implying the different localities to be clustered into three distinct clusters (Fig. 2). In addition, four nodes in the dendrogram were recovered in >50% of the resampling procedure, implying further structuring below the three main clusters. Temperature differences were negatively correlated with differences in community composition (Morisita’s index) and phylogeny (Unifrac metric) (Fig. 3a, b). Although weak, the same relationship was also found between latitude and community composition (data not shown).Figure 2


Phylogenetic analysis suggests that habitat filtering is structuring marine bacterial communities across the globe.

Pontarp M, Canbäck B, Tunlid A, Lundberg P - Microb. Ecol. (2012)

a Morisita’s index of similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between Morisita’s index data and difference in water temperature, −0.64. b Phylogenetic similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between phylogenetic similarity and difference in water temperature, −0.50
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3375428&req=5

Fig3: a Morisita’s index of similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between Morisita’s index data and difference in water temperature, −0.64. b Phylogenetic similarity from pairwise comparisons between samples plotted against difference in water temperature at sample site at sampling occasion. Correlation coefficient between phylogenetic similarity and difference in water temperature, −0.50
Mentions: Although the pairwise significance tests, above, give high values, the Unifrac jackknife analysis show patterns of differentiation between localities. Two nodes in the Unifrac dendrogram was recovered in >99.9% of the randomised jackknife resampling analysis implying the different localities to be clustered into three distinct clusters (Fig. 2). In addition, four nodes in the dendrogram were recovered in >50% of the resampling procedure, implying further structuring below the three main clusters. Temperature differences were negatively correlated with differences in community composition (Morisita’s index) and phylogeny (Unifrac metric) (Fig. 3a, b). Although weak, the same relationship was also found between latitude and community composition (data not shown).Figure 2

Bottom Line: Different bacterial types seem to have different ecological niches that dictate their survival in different habitats.Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed.The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

View Article: PubMed Central - PubMed

Affiliation: Theoretical Population Ecology and Evolution Group, Lund University, Lund, Sweden. mikael.pontarp@biol.lu.se

ABSTRACT
The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

Show MeSH