If you have ever observed ants marching in and out of a nest, you might have been reminded of a highway buzzing with traffic. To Iain Couzin, such a comparison is a cruel insult - to the ants.
Americans spend a 3.7 billion hours a year in congested traffic. But you will never see ants stuck in gridlock.
Army ants, which Couzin has spent much time observing in Panama, are particularly good at moving in swarms. If they have to travel over a depression in the ground, they erect bridges so that they can proceed as quickly as possible.
PHOTO: NY TIMES NEWS SERVICE
"They build the bridges with their living bodies," said Couzin, a mathematical biologist at Princeton University and the University of Oxford. "They build them up if they're required, and they dissolve if they're not being used."
The reason may be that the ants have had a lot more time to adapt to living in big groups. "We haven't evolved in the societies we currently live in," Couzin said.
By studying army ants - as well as birds, fish, locusts and other swarming animals - Couzin and his colleagues are starting to discover simple rules that allow swarms to work so well. Those rules allow thousands of relatively simple animals to form a collective brain able to make decisions and move like a single organism.
Deciphering those rules is a big challenge, however, because the behavior of swarms emerges unpredictably from the actions of thousands or millions of individuals.
"No matter how much you look at an individual army ant," Couzin said, "you will never get a sense that when you put 1.5 million of them together, they form these bridges and columns. You just cannot know that."
To get a sense of swarms, Couzin builds computer models of virtual swarms. Each model contains thousands of individual agents, which he can program to follow a few simple rules. To decide what those rules ought to be, he and his colleagues head out to jungles, deserts or oceans to observe animals in action.
What Couzin wanted to know was why army ants do not move to and from their colony in a mad, disorganized scramble. To find out, he built a computer model based on some basic ant biology. Each simulated ant laid down a chemical marker that attracted other ants while the marker was still fresh. Each ant could also sweep the air with its antennas; if it made contact with another ant, it turned away and slowed down to avoid a collision.
Couzin analyzed how the ants behaved when he tweaked their behavior. If the ants turned away too quickly from oncoming insects, they lost the scent of their trail. If they did not turn fast enough, they ground to a halt and forced ants behind them to slow down. Couzin found that a narrow range of behavior allowed ants to move as a group as quickly as possible.
It turned out that these optimal ants also spontaneously formed highways. If the ants going in one direction happened to become dense, their chemical trails attracted more ants headed the same way. This feedback caused the ants to form a single packed column. The ants going the other direction turned away from the oncoming traffic and formed flanking lanes.
To test this model, Couzin and Nigel Franks, an ant expert at the University of Bristol in England, filmed a trail of army ants in Panama. Back in England, they went through the film frame by frame, analyzing the movements of 226 ants. "Everything in the ant world is happening at such a high tempo it was very difficult to see," Couzin said.
Eventually they found that the real ants were moving in the way that Couzin had predicted would allow the entire swarm to go as fast as possible. They also found that the ants behaved differently if they were leaving the nest or heading back. When two ants encountered each other, the outgoing ant turned away further than the incoming one. As a result, the ants headed to the nest end up clustered in a central lane, while the outgoing ants form two outer lanes. Couzin has been extending his model for ants to other animals that move in giant crowds, like fish and birds. And instead of tracking individual animals himself, he has developed programs to let computers do the work.
The more Couzin studies swarm behavior, the more patterns he finds common to many different species. He is reminded of the laws of physics that govern liquids. "You look at liquid metal and at water, and you can see they're both liquids," he said. "They have fundamental characteristics in common. That's what I was finding with the animal groups - there were fundamental states they could exist in."
Just as liquid water can suddenly begin to boil, animal swarms can also change abruptly thanks to some simple rules.
Understanding how animals swarm and why they do are two separate questions, however.
In some species, animals may swarm so that the entire group enjoys an evolutionary benefit. All the army ants in a colony, for example, belong to the same family. So if individuals cooperate, their shared genes associated with swarming will become more common.
But in the deserts of Utah, Couzin and his colleagues discovered that giant swarms may actually be made up of a lot of selfish individuals.
Mormon crickets will sometimes gather by the millions and crawl in bands stretching more than 2km long. Couzin and his colleagues ran experiments to find out what caused them to form bands. They found that the forces behind cricket swarms are very different from the ones that bring locusts together. When Mormon crickets cannot find enough salt and protein, they become cannibals.
"Each cricket itself is a perfectly balanced source of nutrition," Couzin said. "So the crickets, every 17 seconds or so, try to attack other individuals. If you don't move, you're likely to be eaten."
This collective movement causes the crickets to form vast swarms. "All these crickets are on a forced march," Couzin said. "They're trying to attack the crickets who are ahead, and they're trying to avoid being eaten from behind."
Swarms, regardless of the forces that bring them together, have a remarkable ability to act like a collective mind. A swarm navigates as a unit, making decisions about where to go and how to escape predators together.
Couzin and his colleagues have been finding support for this model in real groups of animals. They have even found support in studies on mediocre swarmers - humans.
To study humans, Couzin teamed up with researchers at the University of Leeds. They recruited eight people at a time to play a game. Players stood in the middle of a circle, and along the edge of the circle were 16 cards, each labeled with a number. The scientists handed each person a slip of paper and instructed the players to follow the instructions printed on it while not saying anything to the others. Those rules correspond to the ones in Couzin's models. And just as in his models, each person had no idea what the others had been instructed to do.
In one version of the experiment, each person was instructed simply to stay with the group. As Couzin's model predicted, they tended to circle around in a doughnut-shaped flock. In another version, one person was instructed to head for a particular card at the edge of the circle without leaving the group. The players quickly formed little swarms with their leader at the head, moving together to the target.
The scientists then sowed discord by telling two or more people to move to opposite sides of the circle. The other people had to try to stay with the group even as leaders tried to pull it apart.
As Couzin's model predicted, the human swarm made a quick, unconscious decision to follow the largest group of leaders.
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