Midge swarm study suggests complexities to collective animal behavior
Mathematical models of collective animal behavior are the foundation for Hollywood’s depictions of Nemo’s schooling fish, Tolkein’s rampaging orcs, and The Lion King’s stampeding wildebeests. But a new study of flying midge swarms suggests that these models may not reflect the complex behaviors that govern motion within that collective group.
“People have been very successful in making these reasonable models that work fairly well, but we’re still investigating the actual rules the animals follow in order to generate their collective states,” said Yale associate professor of mechanical engineering & materials science Nicholas T. Ouellette, principal investigator of new research published April 23 in the journal Scientific Reports.
Through observing midge swarms in their lab, Ouellette’s team found clear evidence that a short-range “repulsion force,” a key component of most models of collective behavior, does in fact cause midges to accelerate away from one another before they get close enough to collide. The repulsion takes effect when the midges fly within a wingspan of each other.
However, models of collective behavior also posit “attraction forces” that prevent the animals from getting too far away from one another. Unexpectedly, the researchers did not observe conclusive long-range interactions that would support this theory, despite the insects swarming in a tightly bound area.
“You actually see apparent attraction to every feature of the swarm you pick, whether it’s the nearest neighboring insect or the most empty space in the swarm,” said Ouellette. But he adds that if everything seems attractive, then nothing is actually exerting an observable strong attractive force. “Instead, our statistics suggest that individual interactions in the swarm are rare, though we do expect that there’s some kind of interaction here because the swarm has an observable boundary.”
These conclusions are based on insect movement in the swarms recorded using synchronized high-speed cameras and analytical tools developed for turbulent flow studies, which Ouellette and co-authors James G. Puckett, a postdoctoral researcher at Yale, and Douglas H. Kelley, an assistant professor at the University of Rochester, used to measure the three-dimensional positions, velocities, and accelerations of individual insects during 20 separate swarming events.
“Social collective motion happens on every scale from cells to fish and birds to whales,” said Ouellette. “The behavior is also very robust, with no particular leader involved, so it works even if a bird flock gets divided in half or a few fish are swallowed by a predator. If we can understand the principles of that behavior and harness them for, say, a swarm of autonomous robots, then that’s a nice thing to have in your engineering toolkit.”