Sat. Oct 1st, 2022
Large flock of jackdaws in silhouette flying in the evening sky over the trees.
enlarge Large flock of jackdaws in silhouette flying in the evening sky over the trees.

There is rarely time to write about every cool science story that comes our way. So this year we’ve got another special series Twelve Days of Christmas, highlighting a science story that fell through the cracks in 2020, every day from December 25th through January 5th. Today: Why swarms chew their flight patterns depending on whether they return to their roosts, or band together to repel predators.

Flocks of feral jackdaws will change their flight patterns depending on whether they return to their roosts or band together to repel predators, according to research originally scheduled to be presented at the APS March 2020 meeting, which was canceled due to the coronavirus pandemic. The work builds on previous findings published in a November 2019 paper in Nature Communications. This could one day lead to the development of autonomous robotic swarms capable of changing their interaction rules to perform various tasks in response to environmental cues.

Co-author Nicholas Ouellette (no relation), a physicist turned environmental engineer at Stanford University, has long been fascinated by biological swarms after noticing how flocks of starlings formed unusual patterns in flight that, in the eye of his physicist , much like turbulence. He thought there must be underlying mechanisms behind the formation of those patterns — possibly even a set of universal laws that could apply to collective behavior of different kinds.

The sticking point is that despite the ubiquity of flocks and swarms in nature, each species swarms or swarms a little differently in terms of the underlying mechanisms at work. Ouellette himself carefully distinguishes between “flocked” and swarming, although the terms are often used interchangeably. For him, “flocked” refers to net ordered movement, while “swarming” applies to collective movement that has no net general order. .

Research on swarming and flocking was largely delegated to observational biologists for decades. But in the 1980s, Craig Reynolds, a computer graphics specialist, developed the so-called “boids” program, an agent-based computer model that has dominated collective behavioral studies ever since. In such a model, each individual unit in a swarm is a dot moving in a straight line at a constant speed. By introducing a few simple rules regarding interactions between dots, a flow pattern will develop once the dots become sufficiently dense. Another set of rules will produce a swarm pattern, and so on.

A herd generated by a
enlarge A herd generated by a ‘boids’ program, an agent-based computational model for collective behavior.

Ouellette thinks this approach isn’t enough to really understand what’s going on at the most fundamental level. Computer simulations may produce patterns similar to swarms and swarms, but that doesn’t mean different species behave that way in their natural habitat. You still need old-fashioned observation data from fieldwork. He therefore opted for a two-pronged approach, adding a large-screen, hands-on experimental component to standard particle modeling and statistical mechanics.

I covered Ouellette’s experiments with swarms of mosquitoes for Physics World in 2018. He treats his swarms of mosquitoes as chunks of material, poking and poking that material to measure its response. That means manipulating the environmental conditions in the lab to see how the swarms react. He and his team used high-speed cameras to determine the position, speed and acceleration of each mosquito, then used a particle-tracking computer program to mimic individual trajectories. The hardest part is analyzing the data to extract large-scale swarm features from the sound.

Ouellette used the same basic setup for his work on chewing herds, except this time the cameras were outside and equipped with longer-range lenses. He teamed up with Alex Thornton – a biologist at the University of Exeter in England who has studied jackdaws for many years with the Cornish Jackdaw Project – to collect the sighting data by filming wild jackdaws in Cornwall, England.

Self-propelled particle model captures the phase transition in mobbing chewing flocks.
enlarge Self-propelled particle model captures the phase transition in mobbing chewing flocks.

Hangjian Ling et al./Nature Communications

Ouellette and his collaborators registered 16 flocks and identified two different varieties. Transit swarms form when the birds fly to their roosts at night, while mobbing swarms occur when the birds unite to ward off predators such as falcons or foxes. “A falcon definitely wins in a one-on-one dogfight between a falcon and a jackdaw,” Ouellette told Ars. “But a hundred jackdaws probably beat a falcon.” The researchers started the bullying by presenting the chewing herds with a stuffed fox holding a fake fluttering bird in its beak. They also played recordings of the scolding calls that jackdaws commonly use to warn their neighbors of a predator’s presence and provoke them into action.

Jackdaws are a member of the crow family, just like crows. “All corvids are smart, and all corvids have fairly well-developed social systems, in addition to collective behavior and herd,” Ouellette said. Jackdaws also mate for life, and those pairs form a kind of substructure that goes beyond just individual birds and flocks. They nest and raise their young in late spring and summer. During that period, one half of a mated pair will remain in the nest with the offspring, while the other will forage for sustenance. As a result, large chewing flocks rarely form. In winter, the chicks have fledged, so there is no need for pairs to separate, and large transit pairs generally form.

His camera tracking system enabled him to determine which birds in a flock were mated and the fraction of paired birds compared to solo birds. Given that structure, Ouellette wondered if it would be possible to tell the difference between a couple that contains pairs and a couple that doesn’t. The group found that the jackdaws position themselves during transport by checking how many neighbors are nearby — a certain number of birds (usually seven or eight), regardless of the distance between them. But in transit flocks with a high percentage of pairs, the interaction of distance was smaller (usually around three neighboring birds).

In contrast, mobbing jackdaws would orient themselves only by keeping a certain distance from other birds. †[Mobbing] couples interact with neighbors based on physical distance, not counting,” Ouellette said. And bullying couples no longer exhibit mating, probably because both partners in a pair are unlikely to be pulled from the nest to join the crowd to add.

Jackdaws form disorderly crowds at first, but once a critical mass of birds is reached, the crowd moves into order.

Ouellette and his collaborators also noted that in the mobbing flocks, a phase transition — the emergence of order from chaos — occurred when the flock density, or number of birds, crossed a critical threshold, never seen before in birds. (See the embedded video above.) Small groups of mobbing were disordered and suddenly transitioned to an ordered state once the number of birds passed the critical threshold. The transit couples, on the other hand, maintained order regardless of the size and density of the couples. “You get the herd close enough that enough of them interact with each other and the individuals will spontaneously develop polarization, all in the same direction,” Ouellette said.

“Our results show that local interactions vary considerably even within the same species in different ecological contexts,” the authors wrote in their 2019 paper. to robustly optimize their group function and maximize fitness benefits.”

“One of the real takeaways here is that you can take the same animal with the same social structure and you can put them in two different contexts,” Ouellette said. “They behave collectively in both cases, but the way they do it is not the same at all. It’s not as simple as saying, ‘There are couples and this is the way couples work.’ So you can’t ignore the external environment when modeling collective behavior in biological systems.”

DOI: Nature Communications, 2019. 10.1038/s41467-019-13281-4 (About DOIs).

By akfire1

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