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Phenotypic Novelty in EvoDevo: The Distinction Between Continuous and Discontinuous Variation and Its Importance in Evolutionary Theory

Overview of attention for article published in Evolutionary Biology, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

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9 X users
wikipedia
4 Wikipedia pages

Citations

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30 Dimensions

Readers on

mendeley
125 Mendeley
Title
Phenotypic Novelty in EvoDevo: The Distinction Between Continuous and Discontinuous Variation and Its Importance in Evolutionary Theory
Published in
Evolutionary Biology, April 2016
DOI 10.1007/s11692-016-9372-9
Pubmed ID
Authors

Tim Peterson, Gerd B. Müller

Abstract

The introduction of novel phenotypic structures is one of the most significant aspects of organismal evolution. Yet the concept of evolutionary novelty is used with drastically different connotations in various fields of research, and debate exists about whether novelties represent features that are distinct from standard forms of phenotypic variation. This article contrasts four separate uses for novelty in genetics, population genetics, morphology, and behavioral science, before establishing how novelties are used in evolutionary developmental biology (EvoDevo). In particular, it is detailed how an EvoDevo-specific research approach to novelty produces insight distinct from other fields, gives the concept explanatory power with predictive capacities, and brings new consequences to evolutionary theory. This includes the outlining of research strategies that draw attention to productive areas of inquiry, such as threshold dynamics in development. It is argued that an EvoDevo-based approach to novelty is inherently mechanistic, treats the phenotype as an agent with generative potential, and prompts a distinction between continuous and discontinuous variation in evolutionary theory.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
United States 1 <1%
Unknown 123 98%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 29 23%
Student > Ph. D. Student 23 18%
Student > Bachelor 17 14%
Researcher 11 9%
Student > Master 11 9%
Other 12 10%
Unknown 22 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 49 39%
Biochemistry, Genetics and Molecular Biology 37 30%
Environmental Science 3 2%
Earth and Planetary Sciences 2 2%
Engineering 2 2%
Other 5 4%
Unknown 27 22%
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 01 April 2024.
All research outputs
#4,572,898
of 25,075,028 outputs
Outputs from Evolutionary Biology
#89
of 329 outputs
Outputs of similar age
#65,465
of 305,043 outputs
Outputs of similar age from Evolutionary Biology
#4
of 7 outputs
Altmetric has tracked 25,075,028 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 329 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has gotten more attention than average, scoring higher than 73% 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 305,043 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 78% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.