Collective bumblebee foraging in a controlled stochastic environment

We study bumblebees in a flight chamber with 10 artificial flowers to explore and accurately quantify foraging behavior. An RFID system is employed to identify the individual foragers and detect their presence in flowers as well as entry and exit of the hive. Flowers release rewards upon bee’s visit with a predefined probability and are divided into two groups of separate reward probabilities and color. Furthermore, we impose a reward refractory period, that is a time span that a bee needs to stay away from a recently triggered flower before it is able to trigger it again.
In this study, an entire colony of tagged bees is kept in the foraging chamber for 4-6 days. We study 7 colonies with 40-70 bees each. We analyze and quantify the operant learning of the relation between flower color and reward probability: bees are able to identify the more rewarding flower type, effectively matching the reward probability ratios. However, the number of bees who are able to do so strongly depends on the length of the imposed refractory period.
We conclude that a combined setting of refractory time and reward probability is too challenging for most bumblebees to learn in the given time span and thus leads to suboptimal foraging choices whereas they quickly learn to adapt to Bernoulli trials alone