The African golden cat (Caracal aurata) is one of the continent’s most elusive wildcats, living deep in the tropical forests of Central and Western Africa. So rare and secretive, experts have long struggled to determine how many remain in the wild.
Conservationists have relied on camera traps placed across 30 sites in 19 countries to gather data, but manually analyzing thousands of images proved overwhelming. To tackle this challenge, scientists partnered with the wildlife nonprofit Panthera, using artificial intelligence to identify individual cats based on their unique coat patterns — similar to methods used for tigers.
Early results indicate that African golden cats occur at very low densities. For instance, surveys in Uganda and Gabon suggest roughly 16 individuals per 100 square kilometers, even in protected areas.
Beyond counting numbers, conservation efforts also focus on reducing threats. Snares set for bushmeat frequently catch golden cats by accident, so local communities are being trained to report sightings and remove traps. Over 8,000 families across multiple countries are participating, including former poachers who now help protect the forests.
Tracking and protecting the golden cat is crucial. The species is currently listed as Vulnerable on the IUCN Red List, but exact population figures have remained unknown due to its elusive nature. Combining AI technology with community-led initiatives is now providing a clearer understanding of their population and distribution, paving the way for more effective conservation strategies.
Source: Thepressradio.com
