Random walks with spatial and temporal resets can explain individual and colony-level searching patterns in ants

Area of Science:

• Ecology
• Mathematical Biology
• Animal Behavior

Background:

• Central place foragers, like ants, utilize resources around their nest.
• The collective foraging range of ant colonies emerges from individual ant movements, but the underlying mechanisms are not fully understood.

Purpose of the Study:

• To model ant foraging movements using a random walk with stochastic resetting.
• To investigate how different resetting mechanisms influence the emergent foraging range of ant colonies.
• To compare model predictions with empirical data from laboratory and field observations.

Main Methods:

• Developed a random walk model incorporating stochastic resetting, simulating ants returning to their nest at random times.
• Analyzed the mathematical properties of the model to predict the spatial distribution of foraging ants.
• Compared model outputs with experimental data on ant movement patterns.

Main Results:

• All tested resetting mechanisms robustly predict an exponential distribution of foraging ants with respect to their distance from the nest.
• A decreasing probability of ants returning to the nest aligns with empirical data, suggesting foragers may extend their range over time.
• The model successfully captures key aspects of ant foraging behavior.

Conclusions:

• Stochastic resetting random walk models are vital for understanding central place foraging.
• Ant foraging behavior is influenced by the probability and timing of returning to the nest.
• This research opens new avenues for studying ant searching strategies and colony-level foraging dynamics.