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A guide to phylogenetic metrics for conservation, community ecology and macroecology

Overview of attention for article published in Biological Reviews, January 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

blogs
1 blog
twitter
85 X users
facebook
3 Facebook pages
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
606 Dimensions

Readers on

mendeley
1687 Mendeley
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1 CiteULike
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Title
A guide to phylogenetic metrics for conservation, community ecology and macroecology
Published in
Biological Reviews, January 2016
DOI 10.1111/brv.12252
Pubmed ID
Authors

Caroline M. Tucker, Marc W. Cadotte, Silvia B. Carvalho, T. Jonathan Davies, Simon Ferrier, Susanne A. Fritz, Rich Grenyer, Matthew R. Helmus, Lanna S. Jin, Arne O. Mooers, Sandrine Pavoine, Oliver Purschke, David W. Redding, Dan F. Rosauer, Marten Winter, Florent Mazel

Abstract

The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify 'anchor' representatives: for α-diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.

X Demographics

X Demographics

The data shown below were collected from the profiles of 85 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 1,687 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 13 <1%
United States 9 <1%
Germany 4 <1%
Mexico 3 <1%
Australia 2 <1%
France 2 <1%
Switzerland 2 <1%
Malaysia 1 <1%
Sweden 1 <1%
Other 8 <1%
Unknown 1642 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 364 22%
Student > Master 264 16%
Researcher 253 15%
Student > Bachelor 162 10%
Student > Doctoral Student 106 6%
Other 271 16%
Unknown 267 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 799 47%
Environmental Science 313 19%
Biochemistry, Genetics and Molecular Biology 91 5%
Earth and Planetary Sciences 34 2%
Engineering 14 <1%
Other 105 6%
Unknown 331 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 57. 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 22 December 2023.
All research outputs
#743,065
of 25,460,285 outputs
Outputs from Biological Reviews
#183
of 1,572 outputs
Outputs of similar age
#13,327
of 403,883 outputs
Outputs of similar age from Biological Reviews
#6
of 16 outputs
Altmetric has tracked 25,460,285 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,572 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 29.9. This one has done well, scoring higher than 88% 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 403,883 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 96% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.