ArticleNature communications2021
Markerless tracking of an entire honey bee colony.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- An open-source high-precision hive for long-term honeybee observation and research.Biology open · 2026Article
- SOPAR: Bee Localization and Tracking Using RF Sub-harmonic Oscillating Parametric Resonator in Hive Environments.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2026Article
- Predicting mosquito flight behavior using Bayesian dynamical systems learning.Science advances · 2026Article
- A dataset of fine-grained zebrafish interactions in health and disease.Scientific data · 2026Article
- Love-thy-neighbor: Neural networks for tracking and lineage tracing in budding yeast.bioRxiv : the preprint server for biology · 2026Article
- Love-thy-neighbor: neural networks for tracking and lineage tracing in budding yeast.Bioinformatics advances · 2026Article
- On the movement of the honeybee queen in the hive.Scientific reports · 2025Article
- Article
- Article
- VespAI: a deep learning-based system for the detection of invasive hornets.Communications biology · 2024Article
- Individual honey bee tracking in a beehive environment using deep learning and Kalman filter.Scientific reports · 2024Article
- Rapid automated 3-D pose estimation of larval zebrafish using a physical model-trained neural network.PLoS computational biology · 2023Article
- How honeybees respond to heat stress from the individual to colony level.Journal of the Royal Society, Interface · 2023Article
- Density of predating Asian hornets at hives disturbs the 3D flight performance of honey bees and decreases predation success.Ecology and evolution · 2023Article
- Article
- Bayesian Multi-Targets Strategy to TrackInsects · 2022Article
- Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography.Nature communications · 2022Article
- Semi-automatic detection of honeybee brood hygiene-an example of artificial learning to facilitate ethological studies on social insects.Biology methods & protocols · 2022Article
- Beehive Air Sampling and Sensing Device Operation in Apicultural Applications-Methodological and Technical Aspects.Sensors (Basel, Switzerland) · 2021Article
- Markerless tracking of an entire honey bee colony.Nature communications · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
From cells in tissue, to bird flocks, to human crowds, living systems display a stunning variety of collective behaviors. Yet quantifying such phenomena first requires tracking a significant fraction of the group members in natural conditions, a substantial and ongoing challenge. We present a comprehensive, computational method for tracking an entire colony of the honey bee Apis mellifera using high-resolution video on a natural honeycomb background. We adapt a convolutional neural network (CNN) segmentation architecture to automatically identify bee and brood cell positions, body orientations and within-cell states. We achieve high accuracy (~10% body width error in position, ~10° error in orientation, and true positive rate > 90%) and demonstrate months-long monitoring of sociometric colony fluctuations. These fluctuations include ~24 h cycles in the counted detections, negative correlation between bee and brood, and nightly enhancement of bees inside comb cells. We combine detected positions with visual features of organism-centered images to track individuals over time and through challenging occluding events, recovering ~79% of bee trajectories from five observation hives over 5 min timespans. The trajectories reveal important individual behaviors, including waggle dances and crawling inside comb cells. Our results provide opportunities for the quantitative study of collective bee behavior and for advancing tracking techniques of crowded systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.