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Locust Dynamics: Behavioral Phase Change and Swarming

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

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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%