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Bee Lab

Bee Cognition Lab

Cognitive Bee Lab

Location: Fir 223, Surrey campus

Current Projects

“Foraging behaviour on occupied flowers: Is Bombus impatiens aggression greater towards heterospecifics or conspecifics?

Student Researchers: Emily & Jeremy Shea, and Amanda Dumoulin

Bumblebees show a marked preference for flowers that are occupied by another bee, compared with flowers that are unoccupied. Our goal is to investigate the conditions under which workers engage in cheating behaviour, and how aggression in foraging could play a role in the success of the forager’s ability to contribute to the colony. Bombus impatiens workers exploring the inside of a 3m x 3m x 3m flight cage encountered artificial flowers occupied with one of three different 3D printed artificial bees, representing both heterospecific and conspecific species. Opalithplättchen number tags were used to monitor individuals and record their foraging behaviour with 3 Vivotek IP8172P IP cameras. Results are available upon completion of this experiment.

Student Researcher: Katie Johnson

Although the physical brain structures of bumblebees (Bombus impatiens) are very small in size, previous research suggests that bees are capable of performing various associative behavioural tasks and solving complex problems (Giurfa, Zhang, Jenett, Menzel & Srinivasan, 2001; Loukola, Perry, Coscos & Chittka 2017, Muth, Papaj & Leonard, 2017; Strang & Sherry, 2014). In the present study, we plan to test the cognitive computational load capacity of bumblebees using the exclusive-or (XOR) problem based on a physical robotic model of sameness/difference principles (Cyr, Avarguès-Weber & Thériault, 2017). Operant conditioning procedures will be implemented through a discrimination task to teach workers to make the correct associative response to simple and 2-bit, 3-bit, and 4-bit compound stimuli. The bumblebees will be released into a T-maze apparatus and presented with a set of black, white and black/white combination squares. Access to a feeder of sugar-water acts as a reward for making a correct response of turning left or right. If the bees are able to learn the rules of the XOR problem, it is presumed that they possess high-functioning neural networks that allow them to overcome linear-separability problems. In the future results, the level of computational load capacity will lead us to a better understanding of the cognitive processing and perceptual skills of bumblebees.