Inferring social influence in animal groups across multiple timescales

Author:

Sridhar Vivek H.1234ORCID,Davidson Jacob D.123ORCID,Twomey Colin R.56,Sosna Matthew M. G.7,Nagy Máté12389ORCID,Couzin Iain D.123ORCID

Affiliation:

1. Department of Biology, University of Konstanz, 78464 Konstanz, Germany

2. Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany

3. Department of Collective Behaviour, Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany

4. Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, 78467 Konstanz, Germany

5. Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA

6. Mind Center for Outreach, Research, and Education, University of Pennsylvania, Philadelphia, PA 19104, USA

7. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA

8. MTA-ELTE Statistical and Biological Physics Research Group, Hungarian Academy of Sciences, Budapest 1117, Hungary

9. MTA-ELTE ‘Lendület’ Collective Behaviour Research Group, Hungarian Academy of Sciences, Eötvös Loránd University, Budapest 1117, Hungary

Abstract

Many animal behaviours exhibit complex temporal dynamics, suggesting there are multiple timescales at which they should be studied. However, researchers often focus on behaviours that occur over relatively restricted temporal scales, typically ones that are more accessible to human observation. The situation becomes even more complex when considering multiple animals interacting, where behavioural coupling can introduce new timescales of importance. Here, we present a technique to study the time-varying nature of social influence in mobile animal groups across multiple temporal scales. As case studies, we analyse golden shiner fish and homing pigeons, which move in different media. By analysing pairwise interactions among individuals, we show that predictive power of the factors affecting social influence depends on the timescale of analysis. Over short timescales the relative position of a neighbour best predicts its influence and the distribution of influence across group members is relatively linear, with a small slope. At longer timescales, however, both relative position and kinematics are found to predict influence, and nonlinearity in the influence distribution increases, with a small number of individuals being disproportionately influential. Our results demonstrate that different interpretations of social influence arise from analysing behaviour at different timescales, highlighting the importance of considering its multiscale nature. This article is part of a discussion meeting issue ‘Collective behaviour through time’.

Funder

Deutsche Forschungsgemeinschaft

Magyar Tudományos Akadémia

Marie Sklodowska-Curie Actions

Office of Naval Research Global

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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