Honey bees and social wasps reach convergent architectural solutions to nest-building problems.

The hexagonal cells built by honey bees and social wasps are an example of adaptive architecture; hexagons minimize material use, while maximizing storage space and structural stability. Hexagon building evolved independently in the bees and wasps, but in some species of both groups, the hexagonal cells are size dimorphic-small worker cells and large reproductive cells-which forces the builders to join differently sized hexagons together. This inherent tiling problem creates a unique opportunity to investigate how similar architectural challenges are solved across independent evolutionary origins. We investigated how 5 honey bee and 5 wasp species solved this problem by extracting per-cell metrics from 22,745 cells. Here, we show that all species used the same building techniques: intermediate-sized cells and pairs of non-hexagonal cells, which increase in frequency with increasing size dimorphism. We then derive a simple geometric model that explains and predicts the observed pairing of non-hexagonal cells and their rate of occurrence. Our results show that despite different building materials, comb configurations, and 179 million years of independent evolution, honey bees and social wasps have converged on the same solutions for the same architectural problems, thereby revealing fundamental building properties and evolutionary convergence in construction behavior.

Best practices for instrumenting honey bees.

Honey bees are vital pollinators and can be used to monitor the landscape. Consequently, interest in mounting technologies onto bees to track foraging behaviors is increasing. The barrier to entry is steep, in part because the methodology for fastening tags to bees, and the success rates, are often missing from publications. We tested six factors suspected to influence the presence and tag retention rates of nurse honey bees after their introduction to hives, and followed bees until foraging age. We also compared reintroducing foragers to their maternal colony using the best method for nurse bees to releasing them in front of their maternal hive and allowing them to fly back unaided. Nurses were most likely to be present in the hive with their tag still attached when introduced using an introduction cage at night. Glue type was important, but may further be influenced by tag material. Foragers were most likely to be present with a tag attached if released in front of their colony. Preparation and introduction techniques influence the likelihood of tagged honey bee survival and of the tags remaining attached, which should be considered when executing honey bee tagging and tracking experiments.

Imperfect comb construction reveals the architectural abilities of honeybees.

Honeybees are renowned for their perfectly hexagonal honeycomb, hailed as the pinnacle of biological architecture for its ability to maximize storage area while minimizing building material. However, in natural nests, workers must regularly transition between different cell sizes, merge inconsistent combs, and optimize construction in constrained geometries. These spatial obstacles pose challenges to workers building perfect hexagons, but it is unknown to what extent workers act as architects versus simple automatons during these irregular building scenarios. Using automated image analysis to extract the irregularities in natural comb building, we show that some building configurations are more difficult for the bees than others, and that workers overcome these challenges using a combination of building techniques, such as: intermediate-sized cells, regular motifs of irregular shapes, and gradual modifications of cell tilt. Remarkably, by anticipating these building challenges, workers achieve high-quality merges using limited local sensing, on par with analytical models that require global optimization. Unlike automatons building perfectly replicated hexagons, these building irregularities showcase the active role that workers take in shaping their nest and the true architectural abilities of honeybees.

System design for inferring colony-level pollination activity through miniature bee-mounted sensors.

In digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems.

Artificial shaking signals in honey bee colonies elicit natural responses.

Honey bee signals are primarily studied through natural observation combined with manipulations of the colony or environment, not direct manipulation of the signal stimulus or receivers. Consequently, we know little about which signal aspects are necessary to reproduce behavioral responses. Here, we focus on the shaking signal, wherein a worker grabs onto another bee and vibrates. All castes receive shaking signals, but individual responses depend on context, and the signal may be multi-modal (mechanical, odor, sound, etc.). We designed a tool to mimic the shaking signal. We tested whether a purely mechanical stimulus elicited the same behavioral response as a natural shaking signal, teasing apart the effects of signal and receiver characteristics. We found that both workers and drones increased their movement after being artificially shaken, and that shaken drones were more likely to engage in feeding and grooming than a sham control. These behavioral changes support the idea that the shaking signal serves to generally increase worker activity, but also serves to activate male reproductives (drones). With this tool, we show that vibration itself is responsible for eliciting much of the shaking signal's behavioral response, in one of the few examples of direct playback in social insects.

A review of collective robotic construction.

The increasing need for safe, inexpensive, and sustainable construction, combined with novel technological enablers, has made large-scale construction by robot teams an active research area. Collective robotic construction (CRC) specifically concerns embodied, autonomous, multirobot systems that modify a shared environment according to high-level user-specified goals. CRC tightly integrates architectural design, the construction process, mechanisms, and control to achieve scalability and adaptability. This review gives a comprehensive overview of research trends, open questions, and performance metrics.