Abstract

Coordinated responses in eusocial insect colonies arise from worker interaction networks that enable collective processing of ecologically relevant information. Previous studies have detected a structural motif in these networks known as the feed-forward loop, which functions to process information in other biological regulatory networks (e.g. transcriptional networks). However, the processes that generate feed-forward loops among workers and the consequences for information flow within the colony remain largely unexplored. We constructed an agent-based model to investigate how individual variation in activity and movement shaped the production of feed-forward loops in a simulated insect colony. We hypothesized that individual variation along these axes would generate feed-forward loops by driving variation in interaction frequency among workers. We found that among-individual variation in activity drove over-representation of feed-forward loops in the interaction networks by determining the directionality of interactions. However, despite previous work linking feed-forward loops with efficient information transfer, activity variation did not promote faster or more efficient information flow, thus providing no support for the hypothesis that feed-forward loops reflect selection for enhanced collective functioning. Conversely, individual variation in movement trajectory, despite playing no role in generating feed-forward loops, promoted fast and efficient information flow by linking together otherwise unconnected regions of the nest.

Highlights

  • In many group-living species, social interaction patterns play an important role in shaping fitness outcomes, such as by impacting royalsocietypublishing.org/journal/rsos R

  • We investigated how the production of feed-forward loops within an interaction network is influenced by individual variation in activity and movement patterns, and the influence this has on within-colony information flow

  • Triangle transitivity was significantly higher when activity levels varied among individuals and activity determined interaction direction compared with instances in which these conditions were not met

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Summary

Introduction

In many group-living species, social interaction patterns play an important role in shaping fitness outcomes, such as by impacting royalsocietypublishing.org/journal/rsos R. A minority of highly interactive individuals can accelerate the spread of information or disease throughout a population by linking together otherwise unconnected individuals [2] and modular social structures can contain the spread of information within tightly knit communities [3]. These group-level properties are probably especially important in eusocial insect colonies in which only one or a few colony members reproduce, such that the fitness of individual workers is tightly linked to colony collective performance [4]

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