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Big Data reveals the secret lives of animals

Person inserting acoustic tracker into fish.

Merking av sjøaure i Tvedestrandfjorden.

Photo: Arnbjørg Aagesen / IMR

New and improved technology allows researchers to track the movements of fish and other animals from second to second.

Understanding how fish and other animals move is crucial to understand how they find food, avoid predators, attract mates and (interact); in short, how they live.

In a new article in Science, researchers show how new technology and big data give us a better understanding of the lives of animals.

“Technological innovations and decreasing costs mean that we can follow individual animal movements with unprecedented detail in their natural habitat. This new behavioural knowledge could support conservation measures,” says Christopher Monk. He is a postdoctoral researcher at the Institute for Marine Research (IMR) and coauthor of the new study.

From hours to seconds

Until recently tracking animals was difficult. For example, researchers needed to chase tagged animals with an antenna to collect several locations of an animal in a day. Alternatively, they had to use very expensive GPS transmitters for automated tracking. With new technology and better data management tools, it is possible to collect locations every second from multiple individual animals at the same time for months to years at regional scales.

The study cites examples of how higher data resolution can reveal aspects of animal’s behavior that would otherwise go unnoticed, such as whether fish avoid fishing vessels.

Researchers can achieve this from technological advances in Reverse-GPS systems, which use acoustic signals in the water and radio signals on land, GPS loggers or radar systems.

“These new approaches give us a more complete insight into the personalities, migrations, social interactions, evolution and threats of animals,” Monk explains.

Tracking fish in Southern Norway

Monk’s colleagues at the IMR research station in Flødevigen, Arendal have pioneered an acoustic telemetry system using Reverse-GPS where cod, sea trout and pollock are being tracked year-round.

For example, they have used the system to observe how cod change their home-range throughout a season. They found that the least bold and exploratory cod shrunk their home-ranges the most during summers when high temperature can become stressful (link to article).

The same telemetry system has also allowed researchers to observe how a no-take marine reserve in Tvedestrand helps to preserve behavioral diversity in sea trout (link to article).

Merking

Fifteen hours of movement from Atlantic cod tracked in Tvedestrand fjord using high-resolution acoustic telemetry. Yellow circles represent locations of individual cod and tails show the past 15 minutes of movement.

The cod are fit with acoustic transmitters that send an ultrasonic coded signal once every two to three minutes. The signal is received by a network of underwater microphones in the fjord and based on the time difference of arrival the position of the fish can be solved in 2d. Pressure sensors in the transmitter add the third dimension.

In this visualization from February 2018, you can see several fish deep (indicated by open circles) in the middle of the fjord near the bottom, while most other fish tend to not swim far from a fixed location.


Researchers have to learn new methods

Smaller and more efficient batteries and more powerful computers are among the developments that have facilitated what researchers describe as a “big-data revolution” in behavioural science.

Although technology offers many new possibilities, researchers also point to some challenges. Not least of these is how not to become overwhelmed with data.

“The new technologies in the study of animal movement are generating data at a faster pace than researchers can analyze. This means we need to acquire new analysis and computing methods to fully benefit from the big-data revolution,” says Christopher Monk.

He and his co-authors suggest that this could be done by reaching out to other disciplines, such as genomics, remote sensing, or human mobility, which have also transitioned from data “poor” to “data rich” in recent years.

The review article involved researchers from NINA, NORCE and IMR in Norway together with researchers from across Europe and North America, led by Nathan Ran at the Hebrew University of Jerusalem in Israel.

Reference

Nathan, Ran et al. “Big-data approaches lead to an increased understanding of the ecology of animal movement”. Science 375, vol. 6582 (2021). Link: https://doi.org/10.1126/science.abg1780