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Collective detection based on visual information in animal groups

View ORCID ProfileJacob D. Davidson, Matthew M. G. Sosna, View ORCID ProfileColin R. Twomey, View ORCID ProfileVivek H. Sridhar, Simon P. Leblanc, View ORCID ProfileIain D. Couzin
doi: https://doi.org/10.1101/2021.02.18.431380
Jacob D. Davidson
1Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
2Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
3Department of Biology, University of Konstanz, Konstanz, Germany
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  • ORCID record for Jacob D. Davidson
  • For correspondence: jdavidson@ab.mpg.de icouzin@ab.mpg.de
Matthew M. G. Sosna
4Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
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Colin R. Twomey
5Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
6Mind Center for Outreach, Research, and Education, University of Pennsylvania, Philadelphia, PA, USA
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  • ORCID record for Colin R. Twomey
Vivek H. Sridhar
1Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
2Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
3Department of Biology, University of Konstanz, Konstanz, Germany
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Simon P. Leblanc
4Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
7Blend Labs, San Francisco, CA 94108
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Iain D. Couzin
1Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
2Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
3Department of Biology, University of Konstanz, Konstanz, Germany
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  • ORCID record for Iain D. Couzin
  • For correspondence: jdavidson@ab.mpg.de icouzin@ab.mpg.de
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Abstract

The spatio-temporal distribution of individuals within a group (i.e its internal structure) plays a defining role in how individuals interact with their environment, make decisions, and transmit information via social interactions. Group-living organisms across taxa, including many species of fish, birds, ungulates, and insects, use vision as the predominant modality to coordinate their collective behavior. Despite this importance, there have been few quantitative studies examining visual detection capabilities of individuals within groups. We investigate key principles underlying individual, and collective, visual detection of stimuli (which could include cryptic predators, potential food items, etc.) and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shiner fish (Notemigonus crysoleucas) to relate theory directly to empirical data, using computational reconstruction of the visual fields of all individuals to do so. Our integrative approach allows us to reveal how the external visual information available to each group member depends on the number of individuals in the group, the position within the group, and the location of the external visually-detectable stimulus. We find that in small groups, individuals have detection capability in nearly all directions, while in large groups, occlusion by neighbors causes detection capability to vary with position within the group. We then formulate a simple, and generally applicable, model that captures how visual detection properties emerge due to geometric scaling of the space occupied by the group and occlusion caused by neighbors. We employ these insights to discuss principles that extend beyond our specific system, such as how collective detection depends on individual body shape, and the size and structure of the group.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Added ORCID for V.H. Sridhar and I.D. Couzin.

  • https://github.com/jacobdavidson/collectivedetection

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 19, 2021.
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Collective detection based on visual information in animal groups
Jacob D. Davidson, Matthew M. G. Sosna, Colin R. Twomey, Vivek H. Sridhar, Simon P. Leblanc, Iain D. Couzin
bioRxiv 2021.02.18.431380; doi: https://doi.org/10.1101/2021.02.18.431380
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Collective detection based on visual information in animal groups
Jacob D. Davidson, Matthew M. G. Sosna, Colin R. Twomey, Vivek H. Sridhar, Simon P. Leblanc, Iain D. Couzin
bioRxiv 2021.02.18.431380; doi: https://doi.org/10.1101/2021.02.18.431380

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