Work

Precise, individualized foraging flights in honeybees revealed by multicopter drone-based tracking

Year: 2026

Type: article

Abstract: Honeybees routinely fly hundreds or thousands of meters between their hive and established foraging locations. 1 , 2 , 3 To navigate these long distances, they are known to combine both landmark use 4 , 5 , 6 , 7 and path integration 8 , 9 , 10 , 11 and have been hypothesized to build a cognitive map. 12 , 13 , 14 Due to technical challenges inherent in tracking these small insects, obtaining three-dimensional, high-resolution measurements of individual navigational precision, and thus a detailed understanding of their strategies, has been difficult. Here, we utilize a novel multicopter drone-based tracking system 15 to measure the individual flight paths of honeybees in a structured agricultural landscape at unprecedented spatial and temporal resolution. Although bees could choose from multiple routes, we discovered that individual bees follow idiosyncratic paths with striking and repeatable precision. Flight path variability was highest over visually sparse regions and lowest near prominent proximal landmarks. Furthermore, individual strategies differed: some bees flew directly toward the hive before maneuvering around a specific tree, while others flew directly to a gap between a hedgerow and the tree. Thus, each animal varies in how it uses visual information and selects between behavioral strategies. The level of precision exhibited by their flight paths exceeds that reported in the waggle dance, implying that dance variability does not reflect a limit in the bee's underlying spatial representation. Our results demonstrate the remarkable precision of individual bee navigation and illustrate the potential of this new drone-based tracking method to illuminate fine-scale behavioral mechanisms across a spectrum of honeybee ecology and cognition.

Source: Current Biology

DOI: 10.1016/j.cub.2026.01.045

Authors: Rachael Stentiford, Michael J.M. Harrap, Victor V. Titov, Stephan Lochner, Andrew D. Straw

Institution: University of Freiburg

Language: English

Topic: Insect and Arachnid Ecology and Behavior

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $7,030

Funders: Deutsche Forschungsgemeinschaft, Volkswagen Foundation