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Phylogenetic Diversity Theory Sheds Light on the Structure of Microbial Communities

Overview of attention for article published in PLoS Computational Biology, December 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

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1 blog
twitter
26 X users
pinterest
1 Pinner

Citations

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57 Dimensions

Readers on

mendeley
285 Mendeley
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4 CiteULike
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Title
Phylogenetic Diversity Theory Sheds Light on the Structure of Microbial Communities
Published in
PLoS Computational Biology, December 2012
DOI 10.1371/journal.pcbi.1002832
Pubmed ID
Authors

James P. O'Dwyer, Steven W. Kembel, Jessica L. Green

Abstract

Microbial communities are typically large, diverse, and complex, and identifying and understanding the processes driving their structure has implications ranging from ecosystem stability to human health and well-being. Phylogenetic data gives us a new insight into these processes, providing a more informative perspective on functional and trait diversity than taxonomic richness alone. But the sheer scale of high resolution phylogenetic data also presents a new challenge to ecological theory. We bring a sampling theory perspective to microbial communities, considering a local community of co-occuring organisms as a sample from a larger regional pool, and apply our framework to make analytical predictions for local phylogenetic diversity arising from a given metacommunity and community assembly process. We characterize community assembly in terms of quantitative descriptions of clustered, random and overdispersed sampling, which have been associated with hypotheses of environmental filtering and competition. Using our approach, we analyze large microbial communities from the human microbiome, uncovering significant variation in diversity across habitats relative to the null hypothesis of random sampling.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 285 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 21 7%
Spain 3 1%
United Kingdom 3 1%
France 3 1%
Canada 3 1%
Sweden 2 <1%
Colombia 2 <1%
Germany 2 <1%
Brazil 1 <1%
Other 8 3%
Unknown 237 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 88 31%
Researcher 69 24%
Professor 24 8%
Student > Master 20 7%
Student > Doctoral Student 16 6%
Other 49 17%
Unknown 19 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 160 56%
Environmental Science 35 12%
Biochemistry, Genetics and Molecular Biology 15 5%
Immunology and Microbiology 10 4%
Computer Science 7 2%
Other 28 10%
Unknown 30 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 18 October 2017.
All research outputs
#1,463,935
of 25,461,852 outputs
Outputs from PLoS Computational Biology
#1,221
of 8,981 outputs
Outputs of similar age
#12,510
of 288,832 outputs
Outputs of similar age from PLoS Computational Biology
#13
of 121 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,981 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 86% of its peers.
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 288,832 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.