Behavioural variation among workers promotes feed-forward loops in a simulated insect colony

Area of Science:

• Behavioral Ecology
• Network Science
• Computational Biology

Background:

• Eusocial insect colonies exhibit coordinated responses through worker interaction networks.
• Feed-forward loops (FFLs) are known structural motifs in biological networks, but their generation and impact in insect colonies are understudied.
• Understanding FFLs is crucial for deciphering collective information processing in social insects.

Purpose of the Study:

• To investigate how individual variation in activity and movement generates FFLs in insect colony interaction networks.
• To determine the consequences of FFLs and individual variation on information flow within simulated insect colonies.
• To test the hypothesis that FFLs enhance collective functioning and information transfer.

Main Methods:

• Agent-based modeling of a simulated insect colony.
• Analysis of interaction networks to identify FFLs.
• Quantification of information flow speed and efficiency under varying individual behaviors.

Main Results:

• Variation in individual activity levels led to an over-representation of FFLs by influencing interaction directionality.
• Despite FFLs, individual activity variation did not enhance the speed or efficiency of information flow.
• Individual variation in movement trajectory, independent of FFLs, significantly improved information flow by increasing network connectivity.

Conclusions:

• FFLs in insect interaction networks are generated by individual activity variation but do not necessarily improve collective information processing.
• Individual movement patterns, rather than FFLs, are key drivers of efficient information transfer in insect colonies.
• The study challenges the assumption that FFLs are universally selected for enhanced collective functioning in social insects.