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Brown hyenas love to go hunting in Baker’s Bay, Namibia. Photo by Marie Lemerle


ARTIFICIAL INTELLIGENCE COULD SOON TURN ANYONE INTO AN EXPERT TRACKER


SCIENTISTS ARE WORKING ON A MACHINE LEARNING TOOL THAT COULD, ONE DAY, IDENTIFY
INDIVIDUAL ANIMALS FROM PHOTOGRAPHS OF THEIR FOOTPRINTS.


AUTHORED BY

by Ryan Truscott



WORDCOUNT

August 12, 2024 | 750 words, about 3 minutes

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Some wild animals are relatively easy to study. Certain penguin populations, for
instance, are so unaccustomed to large predators that they barely fear humans
and will often wander right up to scientists lurking nearby. Namibia’s brown
hyenas are the opposite. These roughly one-meter-long mammals—more closely
related to mongooses than dogs—live in small clans but often travel and hunt
alone. They roam mainly at night and tend to skirt even the most cunningly
placed camera traps. That’s if, like the hyena cubs that devoured the pair of
cameras hyena researcher Marie Lemerle had positioned outside their den, they
don’t destroy them outright. “They managed to open the metal case and then
chewed on the camera, so even the SD card was finished,” says Lemerle, a
researcher with the Brown Hyena Research Project.

So when staff from the US-based nonprofit WildTrack reached out earlier this
year to find out if Lemerle would be interested in collaborating on the
development of a new automated hyena identification system, she was enthused.

Zoe Jewell, a British conservationist, has spent the past 13 years helping
WildTrack develop an artificial intelligence–powered system to identify animals
from pictures of their footprints. The work was inspired by Jewell’s experiences
working alongside Zimbabweans tracking black rhinoceroses. So far, the AI tool
can identify 17 animals, including leopards, lions, and rhinos. But the
WildTrack team’s goal is to produce more fine-grained assessments—teaching their
machine learning system to identify which individual animal left which print.

So, for the past five months, Lemerle has been building up a reference library
of hyena tracks for WildTrack’s training data sets. Each time she finds a clear
hyena footprint at Baker’s Bay, a breeding ground for Cape fur seals on
Namibia’s Atlantic coast where brown hyenas come to hunt, Lemerle reaches for
the 30-centimeter ruler in her backpack, lays it on the sand beside the print,
and takes a photograph with her smartphone.

Then, the WildTrack team, headquartered at North Carolina’s Duke University,
analyzes the footprint’s size and shape in intricate detail. They break each
print into 120 different measurements, which the machine learning software can
compare with others in the database to look for a match. Sometimes, says Jewell,
all they need to tell hyenas apart are subtle differences in the angles between
their toes.

While innate physiological differences set hyena tracks apart, so too do the
scars of life. Like Hunger Games tributes trying to reach the Cornucopia, brown
hyenas wanting to reach the seal colony in Baker’s Bay during daylight hours
have to run a gauntlet of other hyenas and mobs of black-backed jackals intent
on stealing their prey. They receive grisly injuries: shredded ears, gashed
necks, and occasionally a severed foot. Some hyenas limp with broken legs. “If
each individual has a different limp, that probably has to show somehow on their
tracks,” Lemerle says.

The AI-powered tool should, one day, be a huge complement to more traditional
study methods, Lemerle adds. “It would be very nice in the early morning if I
take photos of the tracks and see who was there,” she says.

The tool, says Jewell, should give Lemerle a better idea of where individual
hyenas are going and how they’re using their environment without necessarily
having to see them.

Wesley Gush, a graduate student at the University of Pretoria in South Africa
who was not involved in the research, has studied brown hyenas using camera
traps at the Bubye Valley Conservancy, a vast wildlife reserve in southern
Zimbabwe. “Brown hyenas are one of Africa’s more cryptic large carnivores,” Gush
says, adding that their elusive nature often belies their true numbers.

“The development of an automated tool would have significant potential for
assisting wildlife researchers and managers,” he says. “It would be amazing if
it works.”

Beyond aiding field researchers, the team at WildTrack hopes the system will
help protect wild brown hyenas and other imperiled species.

Fewer than 3,000 adult brown hyenas reside in Namibia, out of less than 10,000
across southern Africa. The animals are considered near threatened, with the
species suffering from collisions with vehicles and revenge killings by
livestock farmers. Jewell says WildTrack’s machine learning system and
associated smartphone app could be used, for example, to prove that tracks found
near farms aren’t those of a brown hyena, which could reduce the number of
retaliatory attacks.

“The model that we develop for [Lemerle] could be used anywhere to help protect
brown hyenas,” says Jewell. “That’s the hope.”


ARTICLE FOOTER AND BOTTOM MATTER




ADDITIONAL CONTRIBUTORS

Edited by Colin Schultz



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CITE THIS ARTICLE:

Cite this Article: Ryan Truscott “Artificial Intelligence Could Soon Turn Anyone
into an Expert Tracker,” Hakai Magazine, Aug 12, 2024, accessed August 12th,
2024,
https://hakaimagazine.com/news/artificial-intelligence-could-soon-turn-anyone-into-an-expert-tracker/.

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