Unexpected similarities between bees and human social life

Bees and humans are as different creatures as you can imagine. But despite many of those differences, the amazing similarities in the way they interact socially have begun to be recognized in the last few years. Currently, a team of researchers at the University of Illinois at Urbana-Champaign have ly measured the social networks of honeybees and how they develop over time, based on previous studies. They found that there are detailed similarities to human social networks, and these similarities are fully explained by new theoretical modeling that adapts statistical physics tools to biology. Experimentally confirmed theories suggest that there are individual differences between honeybees as well as among humans.

The first study to measure the degree of individual variation in honeybee networks is Sang Hyun Choi, a PhD student in physics, the lead author, and Vikyath D. Rao, Adam R. Hamilton, and Swanlund, director of physics at Postdoc. Performed by Tim Gernat. Nigel Goldenfeld and Swanland Entomology Chair Jean E. Robinson (GNDP). Goldenfeld and Robinson are also faculty members at the Karl R. Wars Institute for Genomic Biology, Illinois, and are headed by Robinson. The collaboration consisted of measurements of honeybee social behavior by Hamilton, Gernat, and Robinson, data analysis by Lao, and theoretical modeling and interpretation by Choi and Goldenfeld.Their findings were published in a recent article in the journal. Minutes of the National Academy of Sciences..

“Originally, we wanted to find a way to measure and think about complex societies using bees as a convenient social insect,” said Goldenfeld. “A few years ago, Gene, Tim, Vikyath and I collaborated on a large project to” barcode “bees. This allows us to automatically monitor where the bees enter the hive, where they point, and all interaction partners. In this way, we were able to build a social network in time, called a temporal network. “

The study, conducted a few years ago, used a high-resolution image of a bar-coded honey bee and used an algorithm to detect interaction events by mapping the position and orientation of the honey bee in the image. In those studies, researchers focused on trophalix (the act of moving liquid food from mouth to mouth) in measuring social interactions between bees. Trophallaxis is used not only for eating but also for communication, and is a model system for studying social interactions.

“We decided to consider Trofaraxis because it is the type of bee social interaction that can be accurately tracked,” Choi said. “Bees are physically connected by the contact of the tengu during trophalix, so you can determine if they are actually interacting. In addition, each bee is tagged. , Each individual involved in each interaction event can be identified.

“Our previous study asked how much time bees spend between events they meet with other bees, and showed that they interact in a non-uniform way.” Goldenfeld said. “San Hyun and I used the same dataset, but asked another question. What about the duration of the interaction event, not the time between interactions?”

Looking at the individual interactions, the time spent varied from short to long interactions. Based on these observations, Hee-seop Choi developed the theory that honeybees exhibit individual characteristics of attraction that can be compared to human interactions. For example, humans may prefer to interact with friends and family over strangers.

“We developed this theory based on a very simple idea. If a bee interacts with another bee, it can be thought of as a kind of” virtual fountain “between them. “Goldenfeld said. “Spring strength is a measure of how much they are attracted to each other, so if the spring is weak, the bees will quickly break the spring away and find another bee that will probably interact. This theory. The description is called a minimal model because it allows us to quantitatively capture the phenomenon of interest without the need for excessive and unnecessary microscopic realism. Non-physicists have a detailed understanding and It’s often surprising to know that it’s predictable, with minimal descriptive input. “

Goldenfeld, the mathematical framework of their theory originated in a field of physics called statistical mechanics, originally developed to describe gas atoms in vessels, and then all, including life systems. He explained that it was extended to cover the state of matter. Choi and Goldenfeld’s theory made a correct prediction about the previously collected bee dataset.

Out of curiosity, this theory was applied to human datasets, revealing patterns similar to those of honeybee datasets. Next, Choi and Goldenfeld applied an economic measure of the disparity between human wealth and income (called the Gini coefficient) to show disparities in attractiveness in social interaction, though not as much as humans. I showed that. These results show the surprising universality of patterns of social interaction in both bees and humans.

“Individual differences in humans are obvious, but not so obvious to bees,” said Choi Hee-seop. “Therefore, we investigated honeybee activity level inequality in a theory-independent manner and confirmed that honeybee workers were actually different. Previous studies conducted in our group. So we used the Gini coefficient to quantify the inequality. Since it is a honeybee foraging activity, I thought this method would also help to determine the inequality in trophalix activity. “

“Finding such amazing similarities between bees and humans stimulates interest in discovering the universal principles of biology and their underlying mechanisms,” Robinson said. It was.

Researchers have found that complex societies can have surprisingly simple and universal regularity, which emerges as a resilient and robust community from very different social roles and interactions. It suggests that it may shed light on how to do it. Researchers predict that their minimal theory can be applied to other social insects, as the theory does not contain honeybee-specific features.

Future studies will be able to apply the same techniques as statistical mechanics to understand community cohesiveness through well-characterized pair interactions, Choi and Goldenfeld said.

“This was my first project after I joined Nigel’s group and it took me a long time to find the right way to tackle the problem,” Choi said. “Working on such an interdisciplinary project was fun and rewarding. As a physics student studying biological systems, I didn’t expect to use the concepts of economics. . “

“It was very exciting to see how simple physical ideas could explain such seemingly complex and widespread social phenomena and provide some biological insights,” Golden said. Feld said. “I am very proud of Sang Hyun, who has the tenacity and insight to understand this. Like all interdisciplinary science, this was a very difficult problem to solve, but everything It was incredibly fascinating when we were together. This is a kind of advancement. From the collocation of different scientists in the same laboratory-in this case Karl R. Wars Institute for Genomic Biology. ”

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