Collective detection based on visual information in animal groups
Abstract
We investigate key principles underlying individual, and collective, visual detection of stimuli, 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. This reveals 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 neighbours causes detection capability to vary with position within the group. To understand the principles that drive detection in groups, we 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 neighbours. 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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 01, 2021
- Source ID
- 10.1098/rsif.2021.0142
Entities
People
- Colin R Twomey
- Iain Couzin
- Jacob D Davidson
- Matthew M. G. Sosna
- Simon P. Leblanc
- Vivek H. Sridhar
Organizations
- German Research Foundation
- Heidelberg Academy for Sciences and Humanities
- Max Planck Institute of Animal Behavior
- National Science Foundation
- Office of Naval Research
- Princeton University
- University of Konstanz
- University of Pennsylvania