AI accelerates first census of Africa’s elusive golden cat
A continent-wide effort is delivering the first range-wide population estimates for the African golden cat, a rarely seen forest felid found across Central and West Africa. Led by conservation biologist Mwezi Mugerwa and the African Golden Cat Conservation Alliance, the standardised camera-trap survey spans 30 sites in 19 countries, with Panthera’s AI used to identify individual cats by their coat patterns. Early results indicate very low densities – about 16 individuals per 100 square kilometres in Uganda and Gabon – with full findings expected in 2026, offering data to guide protection and support nature-based tourism planning.
The research links snaring to steep declines, with areas under hunting restrictions showing up to 50% higher populations and wider distribution. Mugerwa’s Embaka project engages more than 8,000 households in Gabon, Angola, the Democratic Republic of Congo, South Sudan and Uganda to report sightings and deploy camera traps, while providing community incentives to reduce poaching. The approach aims to curb accidental bycatch in bushmeat snares – 80 cats were reported trapped in three Ugandan forests in 2019, 88% unintentionally – and strengthen the biodiversity assets that underpin forest tourism. Mugerwa received the Indianapolis Prize Emerging Conservationist Award earlier in 2025.
Source: CNN
