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https://theconversation.com/diving-with-penguins-tech-gives-ocean-scientists-a-birds-eye-view-of-foraging-in-antarctic-waters-233286>
"Chinstrap penguins are members of Antarctica’s brush-tailed group of penguins.
They’re easily identified by the feature that gives them their name – a black
strap that runs from ear to ear below the chin. The species is found mostly in
the Western Antarctic Peninsula region, on far-flung isles such as the South
Shetland Islands, the South Sandwich Islands and the South Orkney Islands.
Chinstrap penguins are highly specialised predators, feeding on marine
crustaceans called Antarctic krill. The birds are still very abundant
(estimates suggest there are between 3 million and 4 million breeding pairs).
But many of their colonies are unfortunately experiencing population declines.
The trend may be linked to krill becoming less available because of climate
change, increasing populations of other marine predators (like baleen whales,
which also eat krill) and commercial krill fishing.
So, it’s important to understand how much krill chinstrap penguins and other
marine predators are consuming. This can help scientists to predict future
population trends and inform conservation and ecosystem management strategies.
It’s challenging to observe directly how penguins catch their underwater prey
in areas of remote ocean habitat. However, thanks to innovations in technology
that have allowed for ever more powerful remote monitoring, our understanding
of their foraging behaviour has rapidly grown during the last decades.
We are part of a team of researchers that recently published a study
underpinned by just such a technological innovation. Using animal-borne video
and movement sensor data to train machine learning algorithms, we were able to
quantify how much krill chinstrap penguins catch. We used “deep learning”, a
subset of machine learning, to detect the penguins’ feeding events. In our
study, these algorithms not only performed classification tasks faster than
human observers would be able to, but also detected patterns in the data that
were difficult to observe visually.
To date, estimates of krill consumption by penguins have typically been derived
from bio-energetic models which are based on principles of physiology like
metabolic rates and how energy is assimilated from food. These estimates often
can’t be empirically validated. Another antiquated method, stomach flushing, is
highly invasive.
Animal-borne sensors provide continuous, high-resolution data on movement and
behaviours, allowing large amounts of data to be recorded. But all that data
needs to be analysed, which is not an easy task for humans. Machine learning
algorithms can rapidly process these large datasets."
Cheers,
*** Xanni ***
--
mailto:xanni@xanadu.net Andrew Pam
http://xanadu.com.au/ Chief Scientist, Xanadu
https://glasswings.com.au/ Partner, Glass Wings
https://sericyb.com.au/ Manager, Serious Cybernetics
