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Extinction in Phylogenetics and Biogeography: From Timetrees to Patterns of Biotic Assemblage

Overview of attention for article published in Frontiers in Genetics, March 2016
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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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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19 X users

Citations

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163 Mendeley
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Title
Extinction in Phylogenetics and Biogeography: From Timetrees to Patterns of Biotic Assemblage
Published in
Frontiers in Genetics, March 2016
DOI 10.3389/fgene.2016.00035
Pubmed ID
Authors

Isabel Sanmartín, Andrea S. Meseguer

Abstract

Global climate change and its impact on biodiversity levels have made extinction a relevant topic in biological research. Yet, until recently, extinction has received less attention in macroevolutionary studies than speciation; the reason is the difficulty to infer an event that actually eliminates rather than creates new taxa. For example, in biogeography, extinction has often been seen as noise, introducing homoplasy in biogeographic relationships, rather than a pattern-generating process. The molecular revolution and the possibility to integrate time into phylogenetic reconstructions have allowed studying extinction under different perspectives. Here, we review phylogenetic (temporal) and biogeographic (spatial) approaches to the inference of extinction and the challenges this process poses for reconstructing evolutionary history. Specifically, we focus on the problem of discriminating between alternative high extinction scenarios using time trees with only extant taxa, and on the confounding effect introduced by asymmetric spatial extinction - different rates of extinction across areas - in biogeographic inference. Finally, we identify the most promising avenues of research in both fields, which include the integration of additional sources of evidence such as the fossil record or environmental information in birth-death models and biogeographic reconstructions, the development of new models that tie extinction rates to phenotypic or environmental variation, or the implementation within a Bayesian framework of parametric non-stationary biogeographic models.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
France 1 <1%
Brazil 1 <1%
Unknown 160 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 24%
Student > Ph. D. Student 24 15%
Student > Bachelor 21 13%
Student > Master 17 10%
Student > Doctoral Student 12 7%
Other 29 18%
Unknown 21 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 88 54%
Biochemistry, Genetics and Molecular Biology 14 9%
Environmental Science 12 7%
Earth and Planetary Sciences 6 4%
Mathematics 2 1%
Other 11 7%
Unknown 30 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 08 June 2017.
All research outputs
#3,554,120
of 25,079,481 outputs
Outputs from Frontiers in Genetics
#1,040
of 13,489 outputs
Outputs of similar age
#54,532
of 306,271 outputs
Outputs of similar age from Frontiers in Genetics
#12
of 75 outputs
Altmetric has tracked 25,079,481 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,489 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 92% 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 306,271 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 75 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.