Facial recognition techniques have long been used to identify primates, including humans.
But, up ’til now, there’s really been no effective way of identifying wild species like the grizzly (brown) bear who, unlike the zebra or giraffe, lacks unique and consistent body markings.
In co-operation with two US software developers, four scientists from the University of Victoria, Canada, brought the idea to reality. They tested their system on grizzlies at two locations – Knight Inlet, British Columbia, CA, and Katmai National Park, Alaska, US. After taking thousands of pictures, they were able to positively identify 132 individuals with almost eighty-four percent accuracy.
The technology enables wildlife monitoring on larger scales and in higher resolution than before. And it can be applied, not only to the grizzly, but to many other mammals, as well. This, in turn, could allow conservationists and lawmakers to tackle global challenges such as biodiversity and habitat loss.
Knight Inlet, one of the two locations for the research, is home to a First Nations Lodge where bear-watching forms part of the local eco-tourism industry.
A band official there, Dallas Smith is impressed with the results.
“This amazing technology will help us identify individual bears and better understand their movement and interactions throughout our territories, which will enable us to build better management plans around habitat protection. It will also help us manage and mitigate the impact of wildlife viewing, as well as positioning ourselves to more effectively and efficiently deal with bear-human conflicts that are becoming more and more prevalent.”
These new techniques, described as a “deep learning approach,” were published recently in the journal, Ecology and Evolution.
Top photo: An adult female grizzly. All images by Melanie Clapham, U of Victoria, Canada.
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