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Cladistic analysis of continuous modularized traits provides phylogenetic signals in Homo evolution

Overview of attention for article published in Nature, May 2008
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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 (92nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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2 blogs
2 tweeters


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Readers on

403 Mendeley
5 CiteULike
1 Connotea
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Cladistic analysis of continuous modularized traits provides phylogenetic signals in Homo evolution
Published in
Nature, May 2008
DOI 10.1038/nature06891
Pubmed ID

Rolando González-José, Ignacio Escapa, Walter A. Neves, Rubén Cúneo, Héctor M. Pucciarelli


Evolutionary novelties in the skeleton are usually expressed as changes in the timing of growth of features intrinsically integrated at different hierarchical levels of development. As a consequence, most of the shape-traits observed across species do vary quantitatively rather than qualitatively, in a multivariate space and in a modularized way. Because most phylogenetic analyses normally use discrete, hypothetically independent characters, previous attempts have disregarded the phylogenetic signals potentially enclosed in the shape of morphological structures. When analysing low taxonomic levels, where most variation is quantitative in nature, solving basic requirements like the choice of characters and the capacity of using continuous, integrated traits is of crucial importance in recovering wider phylogenetic information. This is particularly relevant when analysing extinct lineages, where available data are limited to fossilized structures. Here we show that when continuous, multivariant and modularized characters are treated as such, cladistic analysis successfully solves relationships among main Homo taxa. Our attempt is based on a combination of cladistics, evolutionary-development-derived selection of characters, and geometric morphometrics methods. In contrast with previous cladistic analyses of hominid phylogeny, our method accounts for the quantitative nature of the traits, and respects their morphological integration patterns. Because complex phenotypes are observable across different taxonomic groups and are potentially informative about phylogenetic relationships, future analyses should point strongly to the incorporation of these types of trait.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 403 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Argentina 14 3%
Brazil 11 3%
United States 6 1%
United Kingdom 6 1%
Spain 5 1%
Canada 3 <1%
Germany 3 <1%
France 2 <1%
Portugal 2 <1%
Other 8 2%
Unknown 343 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 114 28%
Student > Ph. D. Student 90 22%
Student > Master 42 10%
Professor > Associate Professor 29 7%
Student > Bachelor 28 7%
Other 87 22%
Unknown 13 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 259 64%
Earth and Planetary Sciences 49 12%
Social Sciences 30 7%
Arts and Humanities 13 3%
Environmental Science 12 3%
Other 24 6%
Unknown 16 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 September 2020.
All research outputs
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Outputs from Nature
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Outputs of similar age
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Outputs of similar age from Nature
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Altmetric has tracked 16,647,928 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 77,477 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 88.7. This one has gotten more attention than average, scoring higher than 59% 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 15,544,412 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 76,482 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.