ArticlePloS one2018
Using within-day hive weight changes to measure environmental effects on honey bee colonies.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Review
- Continuous Non-Invasive Monitoring of Hive Entrance Activity Reveals Honey Bee Colony Dynamics.Biology · 2026Article
- FAIRHiveFrames-1K: A Public FAIR Dataset of 1265 Annotated Hive Frame Images with Preliminary YOLOv8 and YOLOv11 Baselines.Sensors (Basel, Switzerland) · 2026Article
- A Wireless Sensor Platform for Beehive Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Spectral Components of Honey Bee Sound Signals Recorded Inside and Outside the Beehive: An Explainable Machine Learning Approach to Diurnal Pattern Recognition.Sensors (Basel, Switzerland) · 2025Article
- A review of short-term weather impacts on honey production.International journal of biometeorology · 2025Review
- Shift in distribution of division of labour in chronically stressed honeybee colonies after perturbation.The Journal of experimental biology · 2024Article
- Beehive Smart Detector Device for the Detection of Critical Conditions That Utilize Edge Device Computations and Deep Learning Inferences.Sensors (Basel, Switzerland) · 2024Article
- Hive Orientation and Colony Strength Affect Honey Bee Colony Activity during Almond Pollination.Insects · 2024Article
- Effects of Different Levels of Dietary Zinc-Threonine and Zinc Oxide on the Zinc Bioavailability, Biological Characteristics and Performance of Honey Bees (Apis mellifera L.).Biological trace element research · 2023Article
- Modelling daily weight variation in honey bee hives.PLoS computational biology · 2023Article
- Integration of Scales and Cameras in Nondisruptive Electronic Beehive Monitoring: On the Within-Day Relationship of Hive Weight and Traffic in Honeybee (Sensors (Basel, Switzerland) · 2022Article
- Energy-Efficient Wireless Weight Sensor for Remote Beehive Monitoring.Sensors (Basel, Switzerland) · 2021Article
- Markerless tracking of an entire honey bee colony.Nature communications · 2021Article
- Sublethal concentrations of clothianidin affect honey bee colony growth and hive COScientific reports · 2021Article
- Winter weight loss of different subspecies of honey bee Apis mellifera colonies (Linnaeus, 1758) in southwestern Sweden.PloS one · 2021Article
- Landscape factors influencing honey bee colony behavior in Southern California commercial apiaries.Scientific reports · 2020Article
- Exposure to sublethal concentrations of methoxyfenozide disrupts honey bee colony activity and thermoregulation.PloS one · 2019Article
- Article
- The development of honey bee colonies assessed using a new semi-automated brood counting method: CombCount.PloS one · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patterns in within-day hive weight data from two independent datasets in Arizona and California were modeled using piecewise regression, and analyzed with respect to honey bee colony behavior and landscape effects. The regression analysis yielded information on the start and finish of a colony's daily activity cycle, hive weight change at night, hive weight loss due to departing foragers and weight gain due to returning foragers. Assumptions about the meaning of the timing and size of the morning weight changes were tested in a third study by delaying the forager departure times from one to three hours using screen entrance gates. A regression of planned vs. observed departure delays showed that the initial hive weight loss around dawn was largely due to foragers. In a similar experiment in Australia, hive weight loss due to departing foragers in the morning was correlated with net bee traffic (difference between the number of departing bees and the number of arriving bees) and from those data the payload of the arriving bees was estimated to be 0.02 g. The piecewise regression approach was then used to analyze a fifth study involving hives with and without access to natural forage. The analysis showed that, during a commercial pollination event, hives with previous access to forage had a significantly higher rate of weight gain as the foragers returned in the afternoon, and, in the weeks after the pollination event, a significantly higher rate of weight loss in the morning, as foragers departed. This combination of continuous weight data and piecewise regression proved effective in detecting treatment differences in foraging activity that other methods failed to detect.
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