Stinging or not stinging? The alarm pheromone plays a crucial role in bees’ willingness to sting – and their group size, scientists from the University of Konstanz have now explained.
As the saying goes, “You can catch more flies with honey than with vinegar.” However, honeybees prefer to avoid hunting anything, but their honey attracts many predators to the colony. Some are very easy to deter, such as flies. Other predators are much larger than bees and are willing to accept many honeybee stings for sweet nutrients. To fend off them, honeybees must band together in a collective stinging attack.
This defensive reaction is usually initiated by temporarily specialized honey bees, called sentinel bees. They observe the surroundings of the colony. If they spot a large animal approaching the colony, the guard bees react either by stinging the intruder, or by extruding their stinger and fanning their wings, sometimes while running to the hive where their nest mates are.
“In both cases, their behavior triggers the release of the sting alarm pheromone, a complex scent mixture that is carried directly onto the sting,” says neuroscientist Morgan Novian.
This chemical signal excites nearby honeybees and recruits them to the site of the disturbance. There, they decide whether or not to participate in the defensive effort by stinging or otherwise harassing the predator. Hence the sting alarm pheromone plays a major role in the defensive reaction of the colony. but does group size also play a role?
An interdisciplinary study investigates how conditions affect the defensive responses of individual bees
that multidisciplinary collaboration Two early-career researchers — biologist Dr Morgan Novian and computer scientist Professor Young Tatjana Petrov of the Center for the Advanced Study of Collective Behavior at the University of Konstanz — have developed a model and methodology for determining how the response to an alarm pheromone develops during a defensive event, for any given group size. The results have been published in Computational Biology PLOS On September 15, 2022.
“Our biological goal is to study the effect of ambient conditions on the defensive response of individual bees,” says recent author Morgan Novian. In this work, the research team focused on the effect of group size, as previous studies have found that this factor can influence aggressive responses in social insects.
“Tackling this biological target has opened up new challenges for computer science,” Petrov said. Understanding social reactions – how group behavior adapts to changes in group size – requires dealing with complex and limited models experimental dataand thus integrating model-based and data-driven methodologies.”
double search approach
The authors first observed the behavior of groups of bees confronting a fake predator, a spinning doll, and determined their defensive reaction by counting the number of stings in the doll at the end of the experiment. Next, they proposed a mathematical model of group dynamics, which transparently correlates the probabilistic selection of a single bee stinging at a specific alarm pheromone concentration, with the collective outcome observed in the experiment.
Extracting the behavior of individuals from data at the group level is an interesting problem from the point of view of computer science on several levels. “First, models of group behavior that enumerate each possible social context of the individual suffer from the consensual explosion of states, but also from an increasing number of model parameters,” says Tatjana Petrov. “Furthermore, many sources of uncertainty such as random selections of individuals, unknown parameters, or limited data sample size require new ways to measure uncertainty.”
Bees weigh in their social context when making the decision to sting
Collaboration between computer scientists and neurobiologists gives both sides a new perspective on research. “On the computational side, we proposed a new methodology for extracting individual behavior from population data,” Petrov says. “To this end, we have uniquely combined modern formal methods with statistical inference.”
a software tool Created by the authors, all steps of the analysis process modally integrate. The programme, developed and maintained by doctoral student Matij Hejnal, makes it possible to focus on the biological issue, with a clear model explanation on the one hand, and an estimate of uncertainty on the other.
“On the biological side, we provide evidence that bees weigh in their social context when making the decision to sting,” Novian says. “We arrive at this evidence by performing our analysis on each group size separately, and then comparing the dose-response curve with the obtained alarm pheromone.” The authors explain that recruitment becomes less effective as group size increases, and thus social inhibition plays a role on top of excitatory pheromone communication.
“Our methodology addresses a specific social phenomenon in honeybees, but can also be taken as a proof-of-concept for the current challenge of ‘opening’ black box models of observed collective behavior, and providing explainable behavioral hypotheses at a level, says Petrov. She predicts that her approach can be applied to a range of biological systems. Other.” “With regard to the broader application of our approach, we have already identified new computational challenges, particularly in providing scalability and uncertainty estimation in the case of, for example, large populations, imprecise measurements and richer cognitive ability of individuals.”
Tatjana Petrov et al, Extracting individual characteristics from population data reveals negative social influence during honey bee defense, Computational Biology PLOS (2022). DOI: 10.1371 / journal.pcbi.1010305
University of Constance
the quote: Honeybees less likely to sting in larger groups (2022, September 15) Retrieved September 15, 2022 from
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