One of the cool things about bees is that they are highly social animals. Over the last century or so, we have learned that bees share food, communicate information, and work together in ways that have stretched concepts of “animal intelligence” and supposedly unique human attributes.
This month a research group at University of Illinois at Urbana Champaign (which is becoming a hive of bee research) report a new study of bee socializing . The goal is to measure the interactions in a bee hive as a temporal network –not just who talks to who, but when.
To observe these interactions, they tagged all the individual bees with tiny (2.1mm2 ) barcodes, they call “bCodes” . High resolution digital images were recorded every second, and image processing was used to detect Trophallaxis interactions (face to face touching while feeding). This yielded a wealth of detailed who-what-when data for the observed hives.
The data shows that, like human social networks, the bee interactions are “bursty” (i.e., interactions are bunched). However, unlike human networks, the bee network propagates information faster than the comparison random networks.
The data from this study could not determine the mechanism that causes the relatively fast propagation through the network. The study did show that this propagation was robust when the network was perturbed, indicating that it doesn’t depend on the particular bees or their personal (apial?) history. The researchers note that the insects (probably) do not recognize each other as individuals, so they interact opportunistically.
Rapid spreading of information is one thing, but the same interaction is conducive to rapid spread of disease. Therefore, it seems likely that colonies will self-organize to slow transmission of diseases, perhaps “by dynamically adapting interaction patterns to the health status of individual bees.”
If confirmed in further research, these findings might be an important model for other networks. It would be particularly interesting to learn if and how bees might adapt or moderate interactions to optimize both communication and resistance to disease, i.e., selectively speed and slow propagation.
- Tim Gernat, Vikyath D. Rao, Martin Middendorf, Harry Dankowicz, Nigel Goldenfeld, and Gene E. Robinson, Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks. Proceedings of the National Academy of Sciences, 2018. http://www.pnas.org/content/early/2018/01/26/1713568115.abstract
- Claudia Lutz, Reach out and feed someone: Automated system finds rapid honey bee communication networks, in Phys.org – News. 2018. https://phys.org/news/2018-01-automated-rapid-honey-bee-networks.html