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Wild cricket social networks show stability across generations

Overview of attention for article published in BMC Ecology and Evolution, July 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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6 news outlets
blogs
1 blog
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22 X users
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1 Google+ user

Citations

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55 Mendeley
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Title
Wild cricket social networks show stability across generations
Published in
BMC Ecology and Evolution, July 2016
DOI 10.1186/s12862-016-0726-9
Pubmed ID
Authors

David N. Fisher, Rolando Rodríguez-Muñoz, Tom Tregenza

Abstract

A central part of an animal's environment is its interactions with conspecifics. There has been growing interest in the potential to capture these interactions in the form of a social network. Such networks can then be used to examine how relationships among individuals affect ecological and evolutionary processes. However, in the context of selection and evolution, the utility of this approach relies on social network structures persisting across generations. This is an assumption that has been difficult to test because networks spanning multiple generations have not been available. We constructed social networks for six annual generations over a period of eight years for a wild population of the cricket Gryllus campestris. Through the use of exponential random graph models (ERGMs), we found that the networks in any given year were able to predict the structure of networks in other years for some network characteristics. The capacity of a network model of any given year to predict the networks of other years did not depend on how far apart those other years were in time. Instead, the capacity of a network model to predict the structure of a network in another year depended on the similarity in population size between those years. Our results indicate that cricket social network structure resists the turnover of individuals and is stable across generations. This would allow evolutionary processes that rely on network structure to take place. The influence of network size may indicate that scaling up findings on social behaviour from small populations to larger ones will be difficult. Our study also illustrates the utility of ERGMs for comparing networks, a task for which an effective approach has been elusive.

X Demographics

X Demographics

The data shown below were collected from the profiles of 22 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 18%
Student > Ph. D. Student 7 13%
Student > Bachelor 7 13%
Student > Master 7 13%
Student > Doctoral Student 3 5%
Other 7 13%
Unknown 14 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 40%
Environmental Science 3 5%
Economics, Econometrics and Finance 2 4%
Social Sciences 2 4%
Computer Science 1 2%
Other 5 9%
Unknown 20 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 62. 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 July 2018.
All research outputs
#689,137
of 25,374,917 outputs
Outputs from BMC Ecology and Evolution
#139
of 3,714 outputs
Outputs of similar age
#13,772
of 379,940 outputs
Outputs of similar age from BMC Ecology and Evolution
#6
of 76 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done particularly well, scoring higher than 96% 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 379,940 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 96% of its contemporaries.
We're also able to compare this research output to 76 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 92% of its contemporaries.