Literature DB >> 33023396

Pair formation in insect swarms driven by adaptive long-range interactions.

Dan Gorbonos1, James G Puckett2, Kasper van der Vaart3, Michael Sinhuber3, Nicholas T Ouellette3, Nir S Gov1.   

Abstract

In swarms of flying insects, the motions of individuals are largely uncoordinated with those of their neighbours, unlike the highly ordered motion of bird flocks. However, it has been observed that insects may transiently form pairs with synchronized relative motion while moving through the swarm. The origin of this phenomenon remains an open question. In particular, it is not known if pairing is a new behavioural process or whether it is a natural by-product of typical swarming behaviour. Here, using an 'adaptive-gravity' model that proposes that insects interact via long-range gravity-like acoustic attractions that are modulated by the total background sound (via 'adaptivity' or fold-change detection) and that reproduces measured features of real swarms, we show that pair formation can indeed occur without the introduction of additional behavioural rules. In the model, pairs form robustly whenever two insects happen to move together from the centre of the swarm (where the background sound is high) towards the swarm periphery (where the background sound is low). Due to adaptivity, the attraction between the pair increases as the background sound decreases, thereby forming a bound state since their relative kinetic energy is smaller than their pair-potential energy. When the pair moves into regions of high background sound, however, the process is reversed and the pair may break up. Our results suggest that pairing should appear generally in biological systems with long-range attraction and adaptive sensing, such as during chemotaxis-driven cellular swarming.

Keywords:  adaptivity; insect swarm; long-range interactions; pair formation; swarming

Mesh:

Year:  2020        PMID: 33023396      PMCID: PMC7653370          DOI: 10.1098/rsif.2020.0367

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  20 in total

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8.  Determining asymptotically large population sizes in insect swarms.

Authors:  James G Puckett; Nicholas T Ouellette
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10.  Emergent dynamics of laboratory insect swarms.

Authors:  Douglas H Kelley; Nicholas T Ouellette
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