↓ Skip to main content

Locust Dynamics: Behavioral Phase Change and Swarming

Overview of attention for article published in PLoS Computational Biology, August 2012
Altmetric Badge

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 (75th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
4 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

dimensions_citation
88 Dimensions

Readers on

mendeley
94 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Locust Dynamics: Behavioral Phase Change and Swarming
Published in
PLoS Computational Biology, August 2012
DOI 10.1371/journal.pcbi.1002642
Pubmed ID
Authors

Chad M. Topaz, Maria R. D'Orsogna, Leah Edelstein-Keshet, Andrew J. Bernoff

Abstract

Locusts exhibit two interconvertible behavioral phases, solitarious and gregarious. While solitarious individuals are repelled from other locusts, gregarious insects are attracted to conspecifics and can form large aggregations such as marching hopper bands. Numerous biological experiments at the individual level have shown how crowding biases conversion towards the gregarious form. To understand the formation of marching locust hopper bands, we study phase change at the collective level, and in a quantitative framework. Specifically, we construct a partial integrodifferential equation model incorporating the interplay between phase change and spatial movement at the individual level in order to predict the dynamics of hopper band formation at the population level. Stability analysis of our model reveals conditions for an outbreak, characterized by a large scale transition to the gregarious phase. A model reduction enables quantification of the temporal dynamics of each phase, of the proportion of the population that will eventually gregarize, and of the time scale for this to occur. Numerical simulations provide descriptions of the aggregation's structure and reveal transiently traveling clumps of gregarious insects. Our predictions of aggregation and mass gregarization suggest several possible future biological experiments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Germany 2 2%
Switzerland 1 1%
Israel 1 1%
Mauritania 1 1%
Unknown 86 91%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 17 18%
Student > Ph. D. Student 16 17%
Researcher 16 17%
Student > Master 8 9%
Professor 5 5%
Other 15 16%
Unknown 17 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 36%
Engineering 7 7%
Mathematics 6 6%
Biochemistry, Genetics and Molecular Biology 5 5%
Neuroscience 4 4%
Other 17 18%
Unknown 21 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 08 July 2022.
All research outputs
#5,452,627
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#4,153
of 8,964 outputs
Outputs of similar age
#36,172
of 174,095 outputs
Outputs of similar age from PLoS Computational Biology
#39
of 101 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 53% 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 174,095 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 75% of its contemporaries.
We're also able to compare this research output to 101 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.