Noise-Driven Transitions in Collective Foraging of Ant Colonies.

Abstract

Understanding the collective foraging strategies of ant colonies is essential for studying self-organization and collective behavior in biological systems. This study introduces a simplified foraging model that classifies worker roles into two functional groups-available workers and active foragers-providing a concise yet effective framework for analyzing foraging dynamics. Our model effectively reproduces the foraging dynamics observed in more complex three-dimensional models, while taking a more tractable form that is more conducive to mathematical analysis. We examine the effects of stochasticity in mortality rates of foragers and workers on foraging state transitions, with a particular emphasis on the critical noise threshold, transition probability, and transition time. While the critical noise threshold is reduced by stochasticity in either of the two mortality rates, that of active foragers has the greatest effect. We find that slight increases in the arrival rate of available workers and the recruitment rate of active foragers enhance the colony's resilience to environmental stochasticity, suggesting that colonies can self-regulate via a feedback loop of foraging and recruitment to maintain their foraging while their environment changes around them. In contrast, varying the mortality rate of available workers had little effect on this resilience, analogously to experimental observations that older or unhealthy worker ants disproportionately transition into foraging roles. This study not only advances our understanding of ant foraging dynamics by simplifying complex models but also provides valuable insights into the robustness of foraging activities under varying environmental conditions.