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Quantity discrimination in fish species: fish use non-numerical continuous quantity traits to select shoals

Overview of attention for article published in Animal Cognition, September 2018
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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 (81st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
22 tweeters

Citations

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4 Dimensions

Readers on

mendeley
6 Mendeley
Title
Quantity discrimination in fish species: fish use non-numerical continuous quantity traits to select shoals
Published in
Animal Cognition, September 2018
DOI 10.1007/s10071-018-1214-y
Pubmed ID
Authors

Wei Xiong, Lian-Chun Yi, Zhonghua Tang, Xin Zhao, Shi-Jian Fu

Abstract

Fish typically prefer to live in big shoals due to the associated ecological benefits. Shoaling is a behavior that depends on the ability to quantitatively discriminate. The fundamental mechanism involved in quantity discrimination determines whether fish can discriminate a shoal using numerical discrete cues (e.g., number of shoal members), non-numerical continuous traits (e.g., total body surface area) or both; however, the mechanism is currently a controversial topic. In the present study, we used a spontaneous choice experiment to test whether guppy (Poecilia reticulata), zebrafish (Danio rerio), Chinese crucian carp (Carassius auratus) and qingbo (Spinibarbus sinensis) rely on continuous (i.e., body surface area) or discrete (i.e., number of shoal members) information for shoal selection by altering the body surface area (cumulative body surface area ratio of 3:2 or 1:1) between two stimulus shoals with a different number of members (2 individuals vs 3 individuals). All four fish species preferred to shoal with the stimulus shoal with the larger cumulative surface area even if the shoal had fewer members; however, fish showed no shoal preference when the cumulative surface body areas of both stimulus shoals were equal. Furthermore, qingbo did not numerically discriminate between a shoal with 1 individual and a shoal with 3 individuals when the cumulative surface areas of both stimulus shoals were equal; however, qingbo showed a preference for the shoal with the larger cumulative surface area when the two stimulus shoals each had 3 individuals. In conclusion, the present study demonstrated that all four fish species relied only on non-numerical continuous quantity information for shoal selection, at least under a difficult task (i.e., 2 vs 3).

Twitter Demographics

The data shown below were collected from the profiles of 22 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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 33%
Unspecified 1 17%
Professor 1 17%
Student > Ph. D. Student 1 17%
Student > Doctoral Student 1 17%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 33%
Unspecified 1 17%
Environmental Science 1 17%
Psychology 1 17%
Neuroscience 1 17%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 25 September 2018.
All research outputs
#1,430,138
of 12,701,041 outputs
Outputs from Animal Cognition
#305
of 936 outputs
Outputs of similar age
#49,450
of 263,734 outputs
Outputs of similar age from Animal Cognition
#10
of 20 outputs
Altmetric has tracked 12,701,041 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 936 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.3. This one has gotten more attention than average, scoring higher than 67% 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 263,734 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 81% of its contemporaries.
We're also able to compare this research output to 20 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 50% of its contemporaries.