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Combining allele frequency and tree‐based approaches improves phylogeographic inference from natural history collections

Overview of attention for article published in Molecular Ecology, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
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Article details
Title
Combining allele frequency and tree‐based approaches improves phylogeographic inference from natural history collections
Published in
Molecular Ecology, February 2018
DOI 10.1111/mec.14491
Pubmed ID
Authors
Abstract

Model selection approaches in phylogeography have allowed researchers to evaluate the support for competing demographic histories, which provides a mode of inference and a measure of uncertainty in understanding climatic and spatial influences on intraspecific diversity. Here, to rank all models in the comparison set, and determine what proportion of the total support the top-ranked model garners, we conduct model selection using two analytical approaches -allele frequency-based, implemented in fastsimcoal2, and gene tree-based, implemented in PHRAPL. We then expand this model-selection framework by including an assessment of absolute fit of the models to the data. For this, we utilize DNA isolated from existing natural history collections that span the distribution of red alder (Alnus rubra) in the Pacific Northwest of North America to generate genomic data for the evaluation of 13 demographic scenarios. The quality of DNA recovered from herbarium specimen leaf tissue was assessed for its utility and effectiveness in demographic model selection, specifically in the two approaches mentioned. We present strong support for the use of herbarium tissue in the generation of genomic DNA, albeit with the inclusion of additional quality control checks prior to library preparation and analyses with multiple approaches that incorporate various data. Analyses with allele frequency spectra and gene trees predominantly support A. rubra having experienced an ancient vicariance event with intermittent and frequent gene flow between the disjunct populations. Additionally, the data consistently fit the most frequently selected model, corroborating the model selection techniques. Finally, these results suggest that the A. rubra disjunct populations do not represent separate species. This article is protected by copyright. All rights reserved.

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The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

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The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 15 26%
Researcher 8 14%
Other 5 9%
Student > Master 5 9%
Student > Bachelor 4 7%
Other 7 12%
Unknown 14 24%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 28 48%
Biochemistry, Genetics and Molecular Biology 7 12%
Environmental Science 5 9%
Computer Science 1 2%
Economics, Econometrics and Finance 1 2%
Other 1 2%
Unknown 15 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 13 February 2018.
All research outputs
#5,131,350
of 28,071,745 outputs
Outputs from Molecular Ecology
#2,230
of 7,084 outputs
Outputs of similar age
#96,147
of 462,316 outputs
Outputs of similar age from Molecular Ecology
#47
of 92 outputs
Altmetric has tracked 28,071,745 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,084 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has gotten more attention than average, scoring higher than 68% 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 462,316 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 79% of its contemporaries.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.