Strong and weak environmental perturbations cause contrasting restructure of ant transportation networks

TL;DR

This study shows how ant transportation networks respond differently to strong versus weak environmental disruptions, affecting their efficiency and resilience.

Contribution

The research introduces a dynamic simulation model validated with 10 years of empirical data to study how ant transportation networks restructure under environmental perturbations.

Findings

Strong targeted perturbations persistently decrease network efficiency, unlike random or weak ones.

Strong perturbations reduce network robustness and hinder recovery from future disruptions.

Transportation networks relying on key resources struggle to recover quickly after their loss.

Abstract

Dynamic transportation networks are embedded in all levels of biological organization. Ever-growing anthropogenic disturbances and an increasingly variable climate highlight the importance of understanding how these networks restructure under environmental perturbations. Polydomous wood ants provide a convenient model system to study the resilience of self-organizing multi-source, multi-sink transportation networks. We used 10 years of longitudinal empirical data on both unperturbed and experimentally manipulated colony networks to develop and validate a comprehensive dynamic simulation model to study network restructuring after resource removal. We performed simulation experiments to study the effects of excluding food sources with varying importance, either temporarily or permanently, imitating pulse and press perturbations of the networks. We found that removing heavily used resources, corresponding to a strong targeted perturbation, persistently decreased network efficiency, unlike random or weak perturbations. We also found that strong perturbations had excessively adverse effects on robustness and function, reducing the networks’ ability to withstand potential future perturbations. When transportation networks develop around the efficient use of a few key resources, they may be unable to quickly recover from the loss of these through self-organized restructuring. Our findings highlight the importance of considering the interaction of perturbation strength and network structure in studying transportation network dynamics.

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