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Updated: Aug 8, 2025

Monitoring Colony-level Effects of Sublethal Pesticide Exposure on Honey Bees

Monitoring Colony-level Effects of Sublethal Pesticide Exposure on Honey Bees

Published on: November 15, 2017

Modelling daily weight variation in honey bee hives.

Karina Arias-Calluari^1,2, Theotime Colin^2,3, Tanya Latty²

¹School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.

Plos Computational Biology

|March 1, 2023

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Combining theoretical models and data analysis offers reliable insights into honey bee colony health. This approach accurately estimates foraging success and active foragers, crucial for early detection of colony failure.

Area of Science:

Ecology
Animal Behavior
Mathematical Biology

Background:

Improving honey bee health is vital for global pollination services.
Traditional methods for analyzing bee colony dynamics rely on either theoretical models or statistical analysis of data.
A combined approach is needed for interpretable insights into colony status.

Purpose of the Study:

To develop a method combining theoretical modeling and statistical analysis for understanding bee colony dynamics.
To estimate key indicators of honey bee colony health using time-series data of intra-day weight variation.
To demonstrate the reliability of these estimations for early warning of colony failure.

Main Methods:

Developed a mathematical model using ordinary differential equations to represent foraging and food processing activities affecting hive weight.

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Last Updated: Aug 8, 2025

Monitoring Colony-level Effects of Sublethal Pesticide Exposure on Honey Bees

Monitoring Colony-level Effects of Sublethal Pesticide Exposure on Honey Bees

Published on: November 15, 2017

Obtaining Specimens with Slowed, Accelerated and Reversed Aging in the Honey Bee Model

Obtaining Specimens with Slowed, Accelerated and Reversed Aging in the Honey Bee Model

Published on: August 29, 2013

Measuring Hypopharyngeal Gland Acinus Size in Honey Bee Apis mellifera Workers

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Published on: September 14, 2018

Estimated model parameters from single-day measurements of intra-day hive weight variation.

Analyzed data from 10 different honey bee colonies.

Main Results:

The model successfully estimated crucial indicators of honey bee colony health.
Estimated indicators, including foraging success and the number of active foragers, were statistically reliable.
Results were consistent with previously reported findings and fall within expected ranges.

Conclusions:

A hybrid approach of modeling and data analysis provides reliable insights into honey bee colony health.
Key indicators derived from hive weight variation can serve as early warning signals for potential colony failure.
This quantitative understanding supports efforts to improve bee health and pollination services.