Democratic decision-making observed in baboon troops

Despite clear social hierarchies, baboons are capable of making decisions as a group, scientists say.

Courtesy of Rob Nelson
Members of a baboon troop rest in the shade.

Somewhere, there’s a joke to be made about Congress.

A new study published Thursday in Science Magazine suggests that baboons are capable of shared decision-making. Researchers found that, in spite of a stratified social hierarchy, roaming olive baboon troops appeared to pick directions democratically.

Olive baboons, which are found across equatorial Africa, congregate in what is known as a troop. These groups sometimes travel several miles at a time without splitting up. Troops, which are subject to distinct social hierarchies, consist of both males and females.

“While females stay in the troops they were born into, males disperse and join other troops when they reach sexual maturity,” lead author Ariana Strandburg-Peshkin says. “Troops also have linear dominance hierarchies. A baboon's dominance can influence everything from its access to resources such as food, to its mating opportunities and its stress levels.”

Given this social stratification, researchers wondered how baboons came to a consensus on matters that affected the whole group.

Answering that question took an international effort. Co-author and UC Davis researcher Margaret Crofoot tracked the movements of nearly every member in a baboon troop using high-res GPS. From there, Strandburg-Peshkin and fellow lead author Damien Farine, an Oxford social dynamics expert, analyzed the data in an effort to understand how individuals made movement decisions within the group.

“To do this, we looked at situations called ‘pulls,’” Strandburg-Peshkin says, “where one baboon moved away from another and was either followed, or wasn't followed and returned. We analyzed aggregate patterns across many of these pulls to reveal how baboons make movement decisions.”

“The first thing we found is that, despite their widely-known ability to monopolize resources such as food and mates, dominant individuals were not more likely to be followed,” Strandburg-Peshkin adds. “Instead, we found that baboons were likely to be followed when many individuals pulled together, and in similar directions.”

Strandburg-Peshkin and colleagues also found that baboons were open to compromise – but only when “pullers” were already close to agreement.

“For example, if two groups of baboons pulled in different directions and the angle between them was larger than about 90 degrees, a follower would tend to choose one direction or the other,” Strandburg-Peshkin says. “But if the angle was less than about 90 degrees, a follower would tend to split the difference by moving in an intermediate direction. When choosing a direction, followers typically moved in the direction of the largest group of pullers, essentially going with the majority.”

The results were also consistent with models designed to simulate flocking birds and schools of fish.

“In these models, animals obey simple rules of interaction, such as attraction to nearby neighbors and avoiding collisions,” Strandburg-Peshkin says. “Our results suggest that shared decision-making emerging from simple rules might be widespread, even in complex animal societies.”

Baboons aren’t the only animals to make decisions as a group. Shared decision-making comes with a lot of benefits, after all.

“Shared decision-making is actually quite common in nature,” Strandburg-Peshkin says, “and there is evidence for it in species ranging from insects to primates. There is also plenty of theoretical work showing that decisions made by pooling together information from many individuals are often more accurate than those made by a single individual. This can be the case because different individuals in a group might have access to different pieces of information, so by pooling together that information a group can make better decisions. Group decisions are also often better because any errors that individuals make tend to cancel out when you aggregate across many individuals.”

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