Collective Olfactory Communication in Honeybee Swarms

点击翻译按钮获取中文摘要

Pheromones are a prevalent volatile communication signal in nature, but their range and noise tolerance of information exchange are limited by the spatiotemporal decay of these signals. Using honeybees as a model organism, the researchers will study the communication network of honeybee swarms that locate their queen by tracking her pheromones. Specifically, how can honeybees that are far away from the queen locate her? Bees disperse information about the queen's location via a pheromone gland located on their abdomen. Importantly, bees not only passively diffuse these pheromones but also actively fan their wings, which draws air along their anteroposterior axis. The researchers will study the localized airflow, which the PI hypothesized that it creates a directional bias in the diffusion of the pheromones to ensure the signal reaches the rest of the swarm. As bees arrange in a specific spatial distribution where there is a characteristic distance between individuals and a characteristic direction in which individuals broadcast the signal, the researchers will study (1) how this dynamic network recruits new broadcasting bees over time as the pheromones traveled a distance which is orders of magnitude the size of an individual; and (2) how the swarm overcomes local obstacles such as solid objects as well as turbulent airflow and opposing chemical signals. Our world is full of living creatures who routinely exchange information with each other in order to survive and reproduce. Understanding these communication signals is not just a problem in biology, but also one in physics - given the energetic cost, compression, and detectability of the exchanged information. Since the energetic cost of signal production drives bees to push the envelope in terms of minimal signal design and maximal signal to noise ratios, these fascinating communication strategies could reveal new optimalities in signal design and signal processing. Harnessing these natural solutions - honed by eons of evolution, selection, and refinement - we can not only more deeply understand collective animal behavior, but also leverage that understanding to create bio-inspired system designs in the fields of swarm robotics and distributed communication, not to mention in agriculture.Honeybee swarms hold an impressive skill-set when it comes to manipulating large length-scale physical fields such as mechanical strains and flow-mediated temperatures. But to become a coherent swarm in the first place, honeybees must locate their queen by tracking her pheromones that decay rapidly in time and space. Unlike the traditional isotropic chemical signaling (as seen in early embryonic development and aggregation of amoebae), bees use a new artifice to direct their communication signal - airflow. In this complex system, the individual building blocks (an insect) can sense their micro-environment and respond in a way that promotes survival; typically, the response changes the macro-environment the individual is embedded in, thus creating a perpetual coupling between the individuals, the group and the environment. When combined with quantitative analysis and computations, the researchers will integrate the sensing of the environmental cues (pheromone concentration and airflow) and convert them to behavioral outputs that allow the swarm to remain coherent. Hence, this work expands the traditional view of collective behavior via stigmergy (wherein organisms respond to local cues with little or no long-range effects) to establish long-range interactions mediated by physics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.