New Video-Based Method Revolutionizes How Scientists Measure Animal Energy Use

[andyermjuert]

Energy scarcity is a fundamental force shaping animal behavior and evolution. The incredible diversity of life on Earth reflects countless biological solutions to the challenge of acquiring and maintaining energy. Yet, despite its importance, accurately measuring energy consumption in living organisms remains difficult.

Movement is one of the major energy drains for many animals, making it a useful window for estimating energy expenditure, especially in highly mobile species. Existing methods for measuring movement-based energy usage have been highly effective, but they rely on wearable equipment that limits their application.

Now, researchers from the Marine Biophysics Unit at the Okinawa Institute of Science and Technology (OIST), in collaboration with Professor Amatzia Genin from the Hebrew University of Jerusalem, have introduced a new approach. Their study, published in the Journal of Experimental Biology, describes a method using video and 3D-tracking powered by deep learning to estimate energy consumption during movement.

"The best methods for measuring energy use have historically been off-limits for about half of the world’s species, because they require wearable devices," said Dr. Kota Ishikawa, the study’s first author. "Now, with video-based tracking, we can study energy expenditure more inclusively across a much wider range of animals."

Dynamic Body Acceleration (DBA) has long been the gold standard for estimating energy use during movement. Traditionally, DBA combines oxygen consumption measurements—an excellent proxy for energy use—with accelerometer data to establish a strong correlation between movement and energy expenditure in the lab. Researchers then measure DBA in wild animals using small accelerometers.

However, wearable devices pose limitations. To avoid affecting the animal's natural behavior, any attached equipment must weigh less than one-tenth of the animal’s body weight. With accelerometers and batteries weighing 10–20 grams, animals under 100 grams—around half of all vertebrate species—could not be studied reliably. Furthermore, the added weight can distort natural movements, especially in swimming or flying animals where drag efficiency is critical.

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The new solution is simple yet powerful: instead of relying on wearable devices, researchers use two cameras to record an animal's movement from different angles. They then reconstruct the animal’s behavior in 3D space using deep learning algorithms that track specific body points, such as the eyes.

By measuring movement-related acceleration from video footage, researchers can estimate energy consumption without ever touching the animal. Once cameras are in place, the method can be applied in both laboratory and field settings.

This video-based DBA opens exciting new possibilities, such as studying collective behaviors. For instance, Dr. Ishikawa highlights that the energetic cost of fish schooling has long been a mystery.

"Do leading fish expend more energy? Is schooling an energy-efficient form of movement? These questions have ecological and evolutionary significance," he said.

Thanks to this new method, scientists can now measure energy use in small, free-ranging animals, unlocking research opportunities across a vast portion of the animal kingdom that was previously inaccessible.