Member Symposium
Machine Learning and AI
Clare Rittschof (she/her/hers)
Associate Professor
University of Kentucky
Lexington, Kentucky
Adaptive decision-making reflects a balance of reward and risk. For example, honey bees (Apis mellifera L.) prefer certain high quality floral resources, and they use a social signal, the waggle dance, to recruit nestmates to these floral rewards. As resources become scarce, foragers accept and recruit for lower value rewards. The factors that impact perception and communication of risk during foraging, in contrast, are poorly understood. Honey bees are risk-averse, performing an inhibitory “stop signal” to prevent nestmate recruitment to dangerous food resources. However, resource scarcity in late summer triggers an aggressive and risky foraging strategy called honey robbing where foragers switch from collecting nectar from flowers to fighting with other honey bees to steal honey from their hives. Despite attacks from victim bees, foragers persist in recruiting their nestmates to steal food, suggesting their risk tolerance and communication change during honey robbing. We tested the hypothesis that seasonal declines in resource availability and a concomitant increase in honey robbing incidence correspond to greater forager risk tolerance. We found that foragers are less likely to produce inhibitory stop signals during periods of seasonal resource scarcity, and individuals are more persistent at resources despite being attacked. Our findings reveal an environmentally induced shift in risk perception and social communication; in addition to adjusting their reward response, honey bees adopt riskier behaviors to optimize colony survival during resource scarcity. Understanding how risk and reward act in combination to shape foraging behavior is critical for predicting pollination performance in human-impacted ecosystems.