OIST Researchers Build Model From 100 Ants to Predict Invasive Species Navigation
Updated
Updated · EurekAlert · Aug 6
OIST Researchers Build Model From 100 Ants to Predict Invasive Species Navigation
2 articles · Updated · EurekAlert · Aug 6
Summary
More than 100 yellow crazy ants collected around Okinawa let OIST researchers build a physics-based model of how individual ants explore unfamiliar spaces, in work published in PLOS Computational Biology.
Video from lab arenas was processed with a neural network that tracked body positions, turning each ant’s movement into trajectories the team could analyze quantitatively.
The model uses stochastic methods—common in diffusion and bacterial-motion studies—to reproduce key features of the ants’ paths without trying to measure every biological and environmental variable.
Those simulations could help predict how the invasive species moves in new urban environments and eventually support studies on predation, foraging and containment of spreading ant populations.
Could a physics model predicting the erratic, acid-spraying yellow crazy ant's movements hold the key to stopping their global urban invasion?
Does tracking solitary ants in a lab truly reveal how massive invasive colonies conquer complex urban landscapes, or does swarm intelligence take over?
How might the crown-shaped random movement patterns of a single invasive ant inspire the next generation of autonomous search-and-rescue drones?