Researchers have overcome this with satellite tags that
report locations when whales or seals or turtles come to the surface. And there
are tags that automatically release and float to the surface, where they can
report their positions.
But tracking a fish that stays down in the water can be a
problem, so researchers have adopted sound waves as their tracking systems.
One solution has been acoustic monitoring, since sound
travels well in the water. It works this way: you set up an array of precisely
located listening devices on the reef. Then you attach small noisemakers to
fish, and the sounds collected on the listening devices give you a sense of
when fish are present and which microphone they’re closest to.
New research is fine-tuning the information.
“Previous methods were not formulated with the fish, ocean
and acoustics in mind. They therefore do not exploit all available information,
such as the biology of the fish limiting its range of possible movement.” Martin
W. Pedersen, a UH Mānoa postdoctoral fellow.
Pedersen and Kevin C. Weng, manager of the Pelagic Fisheries
Research Program at the University of Hawai‘i at Mānoa, published their new fish
tracking model in the scientific journal Methods in Ecology and Evolution.
Pedersen and Weng’s new state-space model for estimating
individual fish movement is two-part—one part that models the fish behavior,
and one that models the detection of that behavior.
The system uses data on fish behavior, along with
information on where fish are detected and where they are not detected to help
pin down their precise locations.
“Knowing where the fish
is not located actually tells you a lot about where it is located, and with our
new method, we are able to utilize that information and achieve a better
accuracy,” Pedersen said.
Their tracking model was tested in remote Palmyra Atoll, far
to the south of Hawai`i, where 51 underwater observation stations were
established. They were able to create maps that helped show where the fish were
and how they moved.
“It helps us to better understand how they feed, breed and
rest,” Weng said. “Ultimately, more
accurate movement information will help us to conserve these species.”
© Jan TenBruggencate 2013
Citation: Pedersen, M. W., Weng, K. C. (2013),
Estimating individual animal movement from observation networks. Methods in
Ecology and Evolution. doi: 10.1111/2041-210X.12086
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