journal article·2024-02-19Open access

Winter Carbon Dioxide Measurement in Honeybee Hives

Michael I. Newton, Luke Chamberlain, Adam McVeigh, Martin Bencsik

Applied Sciences· Volume 14· Issue 4

Abstract

Sensor technologies have sufficiently advanced to provide low-cost devices that can quantify carbon dioxide levels in honeybee hives with high temporal resolution and in a small enough package for hive deployment. Recent publications have shown that summer carbon dioxide levels vary throughout the day and night over ranges that typically exceed 5000 ppm. Such dramatic changes in a measurable parameter associated with bee physiology are likely to convey information about the colony health. In this work, we present data from four UK-based hives collected through the winter of 2022/2023, with a focus on seeing if carbon dioxide can indicate when colonies are at risk of failure. These hives have been fitted with two Sensirion SCD41 photoacoustic non-dispersive infrared (NDIR) carbon dioxide sensors, one in the queen excluder, at the top of the brood box, and one in the crown board, at the top of the hive. Hive scales have been used to monitor the hive mass, and internal and external temperature sensors have been included. Embedded accelerometers in the central frame of the brood box have been used to measure vibrations. Data showed that the high daily variation in carbon dioxide continued throughout the coldest days of winter, and the vibrational data suggested that daily fanning may be responsible for restoring lower carbon dioxide levels. The process of fanning will draw in colder air to the hive at a time when the bees should be using their energy to maintain the colony temperature. Monitoring carbon dioxide may provide feedback, prompting human intervention when the colony is close to collapse, and a better understanding may contribute to discussions on future hive design.
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Research context

OpenAlex topics: Insect and Pesticide Research · Insect and Arachnid Ecology and Behavior · Animal Ecology and Behavior Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK

Harry Butler Institute, Murdoch University, Perth, WA 6150, Australia

Funding

cOmputatiOnal-assisted Decision-making (B-GOOD) Consortium

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