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ACCOUNTING FOR RATE VARIATION AMONG LINEAGES IN COMPARATIVE DEMOGRAPHIC ANALYSES

Overview of attention for article published in Evolution, July 2014
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Title
ACCOUNTING FOR RATE VARIATION AMONG LINEAGES IN COMPARATIVE DEMOGRAPHIC ANALYSES
Published in
Evolution, July 2014
DOI 10.1111/evo.12469
Pubmed ID
Authors

Andrew G. Hope, Simon Y. W. Ho, Jason L. Malaney, Joseph A. Cook, Sandra L. Talbot

Abstract

Genetic analyses of contemporary populations can be used to estimate the demographic histories of species within an ecological community. Comparison of these demographic histories can shed light on community responses to past climatic events. However, species experience different rates of molecular evolution, and this presents a major obstacle to comparative demographic analyses. We address this problem by using a Bayesian relaxed-clock method to estimate the relative evolutionary rates of 22 small mammal taxa distributed across northwestern North America. We found that estimates of the relative molecular substitution rate for each taxon were consistent across the range of sampling schemes that we compared. Using three different reference rates, we rescaled the relative rates so that they could be used to estimate absolute evolutionary timescales. Accounting for rate variation among taxa led to temporal shifts in our skyline-plot estimates of demographic history, highlighting both uniform and idiosyncratic evolutionary responses to directional climate trends for distinct ecological subsets of the small mammal community. Our approach can be used in evolutionary analyses of populations from multiple species, including comparative demographic studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 2%
United States 1 2%
Germany 1 2%
Brazil 1 2%
Unknown 46 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 28%
Researcher 11 22%
Student > Master 6 12%
Professor > Associate Professor 4 8%
Other 3 6%
Other 7 14%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 52%
Biochemistry, Genetics and Molecular Biology 9 18%
Environmental Science 5 10%
Chemical Engineering 1 2%
Unknown 9 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 June 2014.
All research outputs
#17,538,675
of 25,712,965 outputs
Outputs from Evolution
#5,002
of 5,924 outputs
Outputs of similar age
#144,074
of 240,350 outputs
Outputs of similar age from Evolution
#35
of 45 outputs
Altmetric has tracked 25,712,965 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,924 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.