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Testing the role of ecology and life history in structuring genetic variation across a landscape: a trait-based phylogeographic approach

Overview of attention for article published in Molecular Ecology, July 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

twitter
43 tweeters

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
205 Mendeley
citeulike
1 CiteULike
Title
Testing the role of ecology and life history in structuring genetic variation across a landscape: a trait-based phylogeographic approach
Published in
Molecular Ecology, July 2015
DOI 10.1111/mec.13275
Pubmed ID
Authors

Andrea Paz, Roberto Ibáñez, Karen R. Lips, Andrew J. Crawford

Abstract

Hypotheses to explain phylogeographic structure traditionally invoke geographic features, but often fail to provide a general explanation for spatial patterns of genetic variation. Organism's intrinsic characteristics might play more important roles than landscape features in determining phylogeographic structure. We developed a novel comparative approach to explore the role of ecological and life-history variables in determining spatial genetic variation and tested it on frog communities in Panama. We quantified spatial genetic variation within 31 anuran species based on mitochondrial DNA sequences, for which hierarchical approximate Bayesian computation analyses rejected simultaneous divergence over a common landscape. Regressing ecological variables on genetic divergence allowed us to test the importance of individual variables revealing that body size, current landscape resistance, geographic range, biogeographic origin, and reproductive mode were significant predictors of spatial genetic variation. Our results support the idea that phylogeographic structure represents the outcome of an interaction between organisms and environment, and suggest a conceptual integration we refer to as ecophylogeography. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 43 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 205 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Brazil 3 1%
France 1 <1%
Japan 1 <1%
Portugal 1 <1%
Unknown 193 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 25%
Researcher 30 15%
Student > Master 30 15%
Student > Doctoral Student 20 10%
Student > Bachelor 20 10%
Other 35 17%
Unknown 18 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 139 68%
Environmental Science 20 10%
Biochemistry, Genetics and Molecular Biology 15 7%
Computer Science 3 1%
Earth and Planetary Sciences 2 <1%
Other 6 3%
Unknown 20 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 21 July 2020.
All research outputs
#1,031,601
of 17,371,891 outputs
Outputs from Molecular Ecology
#529
of 5,318 outputs
Outputs of similar age
#16,796
of 239,538 outputs
Outputs of similar age from Molecular Ecology
#12
of 123 outputs
Altmetric has tracked 17,371,891 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 5,318 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one has done particularly well, scoring higher than 90% 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 239,538 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 92% of its contemporaries.
We're also able to compare this research output to 123 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.