From eye anatomy to navigation: a biologically accurate model of bees polarisation vision

Skylight polarisation patterns provide a critical navigational cue for many insects. Bees perceive these patterns through specialised ommatidia in the dorsal rim area of their compound eyes, enabling them to estimate the suns direction and navigate between food sources and the hive. Although polarisation-based navigation has been extensively studied behaviourally, computational models that link DRA anatomy with navigational performance are lacking. Here, we simulate polarisation vision in honeybees (Apis mellifera) and bumblebees (Bombus terrestris) using real sky polarisation images to capture biologically relevant skylight properties. Our biologically grounded simulation incorporates species-specific DRA anatomy, including ommatidial optical axis directions, photoreceptor receptive fields, and microvillar orientations. We evaluate navigational accuracy and consistency across sun elevations under two distinct, potentially complementary navigational models: the matched filter, which requires scanning across body orientations to identify the solar axis, and the vector-sum model, which generates instantaneous sun azimuth estimates from a single body orientation, making it independent of active scanning. Matched filter errors in estimating solar axis are below 5{degrees} across most sun elevations and in both species. Absolute errors in the vector-sum model are lower for honeybees than bumblebees (median [~]10{degrees} and [~]30{degrees}, respectively), reflecting differences in DRA anatomy, particularly viewing direction and microvillar arrangement. Both models allow stable course control across most sun elevations in both species, yet the matched filter, being limited to solar axis alignment, only enables positive or negative phototaxis. Overall, this work provides a mechanistic and comparative framework based on realistic DRA anatomy to study polarisation-based navigation, generating testable predictions for insect navigation under natural sky conditions. Author SummaryMany insects, including bees, navigate with the help of skylight polarisation patterns which hold information about the suns position even when it is not visible. Bees detect these patterns through the dorsal rim area (DRA) of their complex eyes. How differences in DRA anatomy between bee species translate into differences in navigational ability has remained unclear. Here, we built a biologically realistic simulation of polarisation vision in honeybees and bumblebees. We used real sky images to examine what polarisation information is available to each species. We then tested two models of sun position estimation based on the polarisation pattern: one that requires the bee to actively scan the sky, and one that generates an instantaneous estimate from a single body orientation. In both species, both models show that accurate sun position estimation and stable navigation are possible using just polarisation information under a wide range of sun elevations. Differences in navigational performance between honeybees and bumblebees arise because the two DRAs look at different parts of the sky. Our results provide a robust framework for understanding how DRA anatomy shapes polarisation-based navigation in bees.