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Testing Adaptive Hypotheses of Convergence with Functional Landscapes: A Case Study of Bone-Cracking Hypercarnivores

Overview of attention for article published in PLOS ONE, May 2013
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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 (87th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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1 blog
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7 X users

Citations

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56 Dimensions

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114 Mendeley
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1 CiteULike
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Title
Testing Adaptive Hypotheses of Convergence with Functional Landscapes: A Case Study of Bone-Cracking Hypercarnivores
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0065305
Pubmed ID
Authors

Zhijie Jack Tseng

Abstract

Morphological convergence is a well documented phenomenon in mammals, and adaptive explanations are commonly employed to infer similar functions for convergent characteristics. I present a study that adopts aspects of theoretical morphology and engineering optimization to test hypotheses about adaptive convergent evolution. Bone-cracking ecomorphologies in Carnivora were used as a case study. Previous research has shown that skull deepening and widening are major evolutionary patterns in convergent bone-cracking canids and hyaenids. A simple two-dimensional design space, with skull width-to-length and depth-to-length ratios as variables, was used to examine optimized shapes for two functional properties: mechanical advantage (MA) and strain energy (SE). Functionality of theoretical skull shapes was studied using finite element analysis (FEA) and visualized as functional landscapes. The distribution of actual skull shapes in the landscape showed a convergent trend of plesiomorphically low-MA and moderate-SE skulls evolving towards higher-MA and moderate-SE skulls; this is corroborated by FEA of 13 actual specimens. Nevertheless, regions exist in the landscape where high-MA and lower-SE shapes are not represented by existing species; their vacancy is observed even at higher taxonomic levels. Results highlight the interaction of biomechanical and non-biomechanical factors in constraining general skull dimensions to localized functional optima through evolution.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Unknown 112 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 23%
Student > Master 18 16%
Researcher 14 12%
Student > Bachelor 8 7%
Student > Doctoral Student 7 6%
Other 19 17%
Unknown 22 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 44%
Earth and Planetary Sciences 18 16%
Environmental Science 6 5%
Biochemistry, Genetics and Molecular Biology 3 3%
Engineering 3 3%
Other 7 6%
Unknown 27 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 14 September 2022.
All research outputs
#2,832,109
of 23,864,690 outputs
Outputs from PLOS ONE
#35,898
of 203,924 outputs
Outputs of similar age
#24,238
of 197,095 outputs
Outputs of similar age from PLOS ONE
#847
of 4,761 outputs
Altmetric has tracked 23,864,690 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 203,924 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one has done well, scoring higher than 82% 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 197,095 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 87% of its contemporaries.
We're also able to compare this research output to 4,761 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.