Long-term tracking and quantification of individual behavior in bumble bee colonies

• Published in: Artificial life and robotics Vol. 27; no. 2; pp. 401 - 406
• Main Authors: Smith, Matthew A.-Y., Easton-Calabria, August, Zhang, Tony, Zmyslony, Szymon, Thuma, Jessie, Cronin, Kayleigh, Pasadyn, Cassandra L., de Bivort, Benjamin L., Crall, James D.
• Format: Journal Article
• Language: English
• Published: Tokyo Springer Japan 01.05.2022; Springer Nature B.V
• Subjects: Artificial Intelligence; Bees; Colonies; Computation by Abstract Devices; Computer Science; Control; Insect ecology; Insects; Mechatronics; Monitoring; Original Article; Perturbation; Pesticides; Pose estimation; Robotics; Tracking; Individuality; Neonicotinoid; Behavior; Collective response; Bumble bee
• ISSN: 1433-5298; 1614-7456
• DOI: 10.1007/s10015-022-00762-x

Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee ( Bombus spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).