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Relating Phylogenetic and Functional Diversity among Denitrifiers and Quantifying their Capacity to Predict Community Functioning

Overview of attention for article published in Frontiers in Microbiology, January 2012
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Title
Relating Phylogenetic and Functional Diversity among Denitrifiers and Quantifying their Capacity to Predict Community Functioning
Published in
Frontiers in Microbiology, January 2012
DOI 10.3389/fmicb.2012.00209
Pubmed ID
Authors

Joana Falcão Salles, Xavier Le Roux, Franck Poly

Abstract

Genetic diversity of phylogenetic or functional markers is widely used as a proxy of microbial diversity. However, it remains unclear to what extent functional diversity (FD), gene sequence diversity and community functioning are linked. For a range of denitrifying bacteria, we analyzed the relationships between (i) the similarity of functional traits evaluated from metabolic profiles (BIOLOG plates) or from N(2)O accumulation patterns on different carbon sources and (ii) the similarity of phylogenetic (16S rRNA gene) or functional (nir gene) markers. We also calculated different proxies for the diversity of denitrifier community based on taxa richness, phylogenetic (16S rRNA gene) or functional similarities (based either on metabolic profiles or N(2)O accumulation patterns), and evaluated their performance in inferring the functioning of assembled denitrifying communities. For individual strains, the variation in the 16S rRNA gene sequence was weakly correlated with the variation in metabolic patterns (ρ = 0.35) and was not related to N(2)O accumulation. The latter was correlated with the similarity of nitrite reductase residues. When nir genes were analyzed separately, the similarity in amino acids coded by the nirS genes was highly correlated with the observed patterns of N(2)O accumulation (ρ = 0.62), whereas nirK amino acid residues were unrelated to N(2)O accumulation. For bacterial assemblages, phylogenetic diversity (average similarity among species in a community) and mean community dissimilarity (average distance between species) calculated using 16S rRNA gene sequences, and FD measures associated with metabolic profiles, poorly predicted the variation in the functioning of assembled communities (≤15%). In contrast, the proxies of FD based on N(2)O accumulation patterns performed better and explained from 23 to 42% of the variation in denitrification. Amongst those, community niche was the best metric, indicating the importance of complementarity for resources in the context of bacterial community functioning.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Netherlands 1 <1%
Brazil 1 <1%
France 1 <1%
Japan 1 <1%
United Kingdom 1 <1%
Unknown 103 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 37%
Researcher 22 20%
Student > Doctoral Student 11 10%
Student > Master 11 10%
Student > Bachelor 5 4%
Other 9 8%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 55 49%
Environmental Science 22 20%
Biochemistry, Genetics and Molecular Biology 5 4%
Engineering 2 2%
Mathematics 1 <1%
Other 7 6%
Unknown 20 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 February 2013.
All research outputs
#17,664,478
of 22,675,759 outputs
Outputs from Frontiers in Microbiology
#16,905
of 24,472 outputs
Outputs of similar age
#191,318
of 244,088 outputs
Outputs of similar age from Frontiers in Microbiology
#176
of 317 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,472 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 244,088 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.