An efficient method for sorting and selecting for social behaviour

TL;DR

This paper introduces a systematic experimental approach to sort animals based on socially relevant traits through repeated group behavioral assays and group membership rearrangements, enabling efficient analysis of individual contributions to group behavior.

Contribution

It presents a novel, tag-free method for sorting animals by social traits using group assays and rearrangements, supported by a general model and simulations.

Findings

Sorting increases behavioral variation among groups.

Individuals are efficiently sorted across groups for many models.

Method allows estimation of trait repeatability from experimental data.

Abstract

In this article we provide a systematic experimental method for sorting animals according to socially relevant traits, without assaying them or even tagging them individually. Instead, they are repeatedly subjected to behavioural assays in groups, between which the group memberships are rearranged, in order to test the effect of many different combinations of individuals on a group-level property or feature. We analyse this method using a general model for the group feature, and simulate a variety of specific cases to track how individuals are sorted in each case. We find that in the case where the members of a group contribute equally to the group feature, the sorting procedure increases the between-group behavioural variation well above what is expected for groups randomly sampled from a population. For a wide class of group feature models, the individual phenotypes are efficiently sorted across the groups and thus become available for further analysis on how individual properties affect group behaviour. We also show that the experimental data can be used to estimate the individual-level repeatability of the underlying traits.