In a first for marine science, researchers have successfully tracked the behaviour of the elusive whitespotted eagle ray using a specially developed biologging device.
The new multi-sensor tags, created by scientists at Florida Atlantic University, were attached to rays in Harrington Sound, a semi-enclosed water body in Bermuda in the North Atlantic Ocean.
The study findings, published in the journal Animal Biotelemetry, offer new insights into the movement, feeding and social behaviour of these graceful and mysterious animals.
Whitespotted eagle ray: a mysterious ocean giant
Whitespotted eagle rays (Aetobatus narinari) are powerful, fast-swimming predators that glide through tropical and subtropical coastal waters.
Growing more than 2 metres (6.5 feet) wide and weighing several hundred kilograms, they feed primarily on hard-shelled animals such as clams and conch.
Despite their ecological importance in marine food webs, little is known about how they behave in the wild. Until now, their smooth skin and lack of a prominent dorsal fin have made it nearly impossible to attach tracking equipment securely.
While biologging has become a vital tool in studying species such as sharks and sea turtles, rays – especially pelagic (open ocean) ones – have been left behind. This lack of data has concerned scientists, especially as many batoid species (which include skates, rays and stingrays) are under increasing threat from habitat loss and overfishing.
How the biologging tag works
The custom-built tag integrates several tools into a single lightweight design, including a motion sensor, underwater microphone, video camera, satellite transmitter and acoustic tracker.
A major innovation lies in how the tag is attached: using silicone suction cups and specially designed straps that secure near the ray’s spiracles – small openings just behind the eyes. This method proved both fast and minimally invasive, say the researchers, allowing the tag to remain in place for up to 60 hours, even in strong ocean currents.
This marks the longest recorded attachment time for an external tag on a pelagic ray, making it a significant achievement in marine tagging technology, say the researchers.
What the researchers found
The detailed data collected by the tag revealed not only where the rays travelled, but also how they fed, interacted and navigated their environment.
Researchers used the tag’s video and sound recordings to identify key behaviours, including ‘browsing’, ‘swimming’ and ‘digging’.
The team trained a supervised machine learning model, known as a Random Forest model, to detect foraging behaviours based on sensor data. This model was first calibrated using labelled video footage and then tested on other data to predict behaviour with surprising accuracy.
“Feeding in the field followed a repetitive sequence,” the researchers document in the study, “descent to the sediment, ‘browsing’ (raising and lowering the rostrum along the sand while moving forward), occasionally ‘digging’ into the sediment, winnowing sand away… Once prey pickup occurred, the ray immediately ascended out of the sediment, usually >1 m, and glided back downward while processing the prey item.”
Notably, the researchers found that some feeding activities could be recognised using only movement and sound – without the need for video. This means simpler, more efficient tags could potentially be deployed on a wider scale, enabling long-term ecological monitoring of rays and other understudied species, say the team.
“Our work marks a turning point in how we study elusive marine species like pelagic rays,” says co-author Cecilia M. Hampton. “We’ve shown that complex behaviours – like the crunching of clams – can be identified using sound and movement data alone, even without video. This opens up exciting possibilities for long-term ecological monitoring using simpler, more efficient tags.”
What’s next?
The researchers say the success of the study demonstrates how biologging technology, when combined with machine learning, can revolutionise the way scientists observe marine animals. With some adaptation, the tag could be used on other ray species, helping to fill important gaps in our knowledge of marine ecosystems.
“As biologging technologies advance, combining data streams like movement, sound and video – and applying machine learning for behaviour classification – could turn rays into mobile surveyors of ocean health and benthic habitats,” adds senior author of the study Matt Ajemian.
Find out more about the study: Sticking with it: a multi-sensor tag to reveal the foraging ecology and fine-scale behavior of elusive durophagous stingrays
Top image: whitespotted eagle ray tagging. Credit: FAU Harbor Branch
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