Title: | Flow-mediated olfactory communication in honeybee swarms |
Author(s): | Nguyen DMT; Iuzzolino ML; Mankel A; Bozek K; Stephens GJ; Peleg O; |
Address: | "Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309. BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80309. Department of Physics, University of Colorado Boulder, Boulder, CO 80309. Biological Physics Theory Unit, Okinawa Institute of Technology, Okinawa 904-0495, Japan. Center for Molecular Medicine Cologne, University of Cologne, 50931 Cologne, Germany. Department of Physics and Astronomy, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands. Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309; orit.peleg@colorado.edu. Santa Fe Institute, Santa Fe, NM 87501" |
ISSN/ISBN: | 1091-6490 (Electronic) 0027-8424 (Print) 0027-8424 (Linking) |
Abstract: | "Honeybee swarms are a landmark example of collective behavior. To become a coherent swarm, bees locate their queen by tracking her pheromones. But how can distant individuals exploit these chemical signals, which decay rapidly in space and time? Here, we combine a behavioral assay with the machine vision detection of organism location and scenting (pheromone propagation via wing fanning) behavior to track the search and aggregation dynamics of the honeybee Apis mellifera L. We find that bees collectively create a scenting-mediated communication network by arranging in a specific spatial distribution where there is a characteristic distance between individuals and directional signaling away from the queen. To better understand such a flow-mediated directional communication strategy, we developed an agent-based model where bee agents obeying simple, local behavioral rules exist in a flow environment in which the chemical signals diffuse and decay. Our model serves as a guide to exploring how physical parameters affect the collective scenting behavior and shows that increased directional bias in scenting leads to a more efficient aggregation process that avoids local equilibrium configurations of isotropic (nondirectional and axisymmetric) communication, such as small bee clusters that persist throughout the simulation. Our results highlight an example of extended classical stigmergy: Rather than depositing static information in the environment, individual bees locally sense and globally manipulate the physical fields of chemical concentration and airflow" |
Keywords: | "*Animal Communication Animals Bees/*physiology Female High-Throughput Screening Assays Machine Learning *Models, Biological Nesting Behavior/physiology Pheromones/*chemistry Smell/*physiology Spatio-Temporal Analysis agent-based model computer vision hone;" |
Notes: | "MedlineNguyen, Dieu My T Iuzzolino, Michael L Mankel, Aaron Bozek, Katarzyna Stephens, Greg J Peleg, Orit eng Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. 2021/03/25 Proc Natl Acad Sci U S A. 2021 Mar 30; 118(13):e2011916118. doi: 10.1073/pnas.2011916118" |