Inherent noise can facilitate coherence in collective swarm motion

C. A. Yates, R. Erban, C. Escudero, I. D. Couzin, J. Buhl, I. G. Kevrekidis, P. K. Maini, D. J. T. Sumpter

Research output: Contribution to journalArticlepeer-review

212 Scopus citations

Abstract

Among the most striking aspects of the movement of many animal groups are their sudden coherent changes in direction. Recent observations of locusts and starlings have shown that this directional switching is an intrinsic property of their motion. Similar direction switches are seen in self-propelled particle and other models of group motion. Comprehending the factors that determine such switches is key to understanding the movement of these groups. Here, we adopt a coarse-grained approach to the study of directional switching in a self-propelled particle model assuming an underlying one-dimensional Fokker-Planck equation for the mean velocity of the particles. We continue with this assumption in analyzing experimental data on locusts and use a similar systematic Fokker-Planck equation coefficient estimation approach to extract the relevant information for the assumed Fokker-Planck equation underlying that experimental data. In the experiment itself the motion of groups of 5 to 100 locust nymphs was investigated in a homogeneous laboratory environment, helping us to establish the intrinsic dynamics of locust marching bands. We determine the mean time between direction switches as a function of group density for the experimental data and the self-propelled particle model. This systematic approach allows us to identify key differences between the experimental data and the model, revealing that individual locusts appear to increase the randomness of their movements in response to a loss of alignment by the group. We give a quantitative description of how locusts use noise to maintain swarm alignment. We discuss further how properties of individual animal behavior, inferred by using the Fokker-Planck equation coefficient estimation approach, can be implemented in the self-propelled particle model to replicate qualitatively the group level dynamics seen in the experimental data.
Original languageEnglish (US)
Pages (from-to)5464-5469
Number of pages6
JournalProceedings of the National Academy of Sciences
Volume106
Issue number14
DOIs
StatePublished - Mar 31 2009
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: This work was supported by Engineering and Physical Sciences Research Council and Biotechnology and Biological Sciences Research Council (C.A.Y.), the Ministry of Education and Science (Spain, Project FIS2005-01729) (C.E.), the Air Force Office of Scientific Research (I.G.K.), a Searle Scholar Award and Defense Advanced Research Planning Agency Grant HR001-05-1-0057 to Princeton University (I.D.C), St. John's College, Linacre College and Somerville College, Oxford (R.E.). This publication is based partially on work supported by King Abdullah University of Science and Technology Award No. KUK-C1-013-04 (R.E.). P.K.M. was partially supported by a Royal Society-Wolfson Merit Award. This work was partially supported by the Oxford-Princeton Partnership grant (P.K.M. and I.G.K.).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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