Biology subjects

Nguyen, D. M. T.

Publications and source records attributed to Nguyen, D. M. T..

4 recordsLinked to original sources

bioRxiv2022

Honey Bees Find the Shortest Path: A CollectiveFlow-Mediated Approach

Honey bees (Apis mellifera L.) are social insects that makes frequent use of volatile pheromone signals to collectively navigate unpredictable and unknown environments. Ants have been shown to effectively use pheromone trails to find the shortest path between two points, the nest and the food source. The ant pheromone trails are accomplished by depositing of pheromones which are then diffused passively, creating isotropic (i.e., non-directional and axi-symmetric) signals. In this study, we report the first instance of the honey bees ability to solve the shortest path problem to localize the queen and aggregate around her by using a collective flow-mediated scenting strategy. In this strategy, individual bees not only emit pheromones, but also fan their wings to actively direct the flow of the signals, providing colony members with directional messages to the queens location. We use computer vision and deep learning approaches to perform automatic and accurate image analysis. As a result, we quantify the number of bees in the short and long paths, and show that the short path is frequented by significantly more bees over time. We also reconstruct attractive surfaces using the positions and directions of scenting bees, and show that this surface is more "attractive" along the short path and around the queen as scenting bees send out directional messages and the swarm makes their way to the queen. Overall, we show that the honey bees can effectively use the collective scenting behavior to overcome local and volatile pheromone communication and find the shortest path to the queen.

animal behavior and cognition↗

bioRxiv2022

Physical Obstacles Constrain Behavioral Parameter Space of Successful Localization in Honey Bee Swarms

Honey bees (Apis mellifera L.) localize the queen and aggregate into a swarm by forming a collective scenting network to directionally propagate volatile pheromone signals. Previous experiments show the robustness of this communication strategy in the presence of physical obstacles that partially block pheromone flow and the path to the queen. Specifically, there is a delay in the formation of the scenting network and aggregation compared to a simple environment without perturbations. To better understand the effect of obstacles beyond temporal dynamics, we use the experimental results as inspiration to explore how the behavioral parameter space of collective scenting responds to obstacle. We extend an agent-based model previously developed for a simple environment to account for the presence of physical obstacles. We study how individual agents with simple behavioral rules for scenting and following concentration gradients can give rise to collective localization and swarming. We show that the bees are capable of navigating the more complex environment with a physical obstacle to localize the queen and aggregate around her, but their range of behavioral parameters is more limited and less flexible as a result of the spatial density heterogeneity in the bees imposed by the obstacle.

animal behavior and cognition↗

bioRxiv2021

Robustness of Collective Scenting in the Presence of Physical Obstacles

Honey bees (Apis mellifera L.) aggregate around the queen by collectively organizing a communication network to propagate volatile pheromone signals. Our previous study shows that individual bees "scent" to emit pheromones and fan their wings to direct the signal flow, creating an efficient search and aggregation process. In this work, we introduce environmental stressors in the form of physical obstacles that partially block pheromone signals and prevent a wide open path to the queen. We employ machine learning methods to extract data from the experimental recordings, and show that in the presence of an obstacle that blocks most of the path to the queen, the bees need more time but can still effectively employ the collective scenting strategy to overcome the obstacle and aggregate around the queen. Further, we increase the complexity of the environment by presenting the bees with a maze to navigate to the queen. The bees require more time and exploration to form a more populated communication network. Overall, we show that given volatile pheromone signals and only local communication, the bees can collectively solve the swarming process in a complex unstructured environment with physical obstacles.

animal behavior and cognition↗

bioRxiv2020

Flow-Mediated Olfactory Communication in Honey Bee Swarms

Honey bee 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 novel behavioral assay with the machine vision detection of organism location and scenting behavior to track the search and aggregation dynamics of the honey bee Apis mellifera L. We find that bees collectively create a communication network to propagate pheromone signals, by arranging in a specific spatial distribution where there is a characteristic distance between individuals and a characteristic direction in which individuals broadcast the signals. To better understand such a flow-mediated directional communication strategy, we connect our experimental results to an agent-based model where virtual bees with simple, local behavioral rules, exist in a flow environment. Our model shows that increased directional bias leads to a more efficient aggregation process that avoids local equilibrium configurations of isotropic communication, such as small bee clusters that persist throughout the simulation. Our results highlight a novel 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.

animal behavior and cognition↗