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Scientists Discover New "Intermediary Roar" in African Lions — AI Reveals Hidden Vocal Type

University of Exeter scientists have identified a new "intermediary roar" in African lions, distinct from the familiar full-throated roar. Using AI to analyse recordings, the team showed that single roaring bouts can contain multiple acoustic components, enabling more objective classification. With Africa home to an estimated 20,000–25,000 lions and populations having halved in 25 years, researchers say AI-enhanced passive acoustic monitoring could offer a scalable tool for conservation, pending further field validation.

10:29 PM, 11/21/2025Science
Scientists Discover New "Intermediary Roar" in African Lions — AI Reveals Hidden Vocal Type

Researchers at the University of Exeter have identified a previously undescribed vocalisation in African lions: an "intermediary roar" distinct from the species' well-known full-throated roar. Using artificial intelligence to analyse acoustic patterns, the team found that single roaring bouts can contain at least two acoustically different components, a discovery that changes how scientists understand lion communication.

In a study published in the journal Ecology and Evolution, the researchers documented and classified the intermediary roar and demonstrated that automated methods can reliably separate it from the full-throated roar. This is the first time machine-learning techniques have been used to differentiate these roar types at scale, reducing reliance on subjective expert judgement.

"Lion roars are not just iconic, they are unique signatures that can be used to estimate population sizes and monitor individual animals," said Dr Jonathan Growcot, a University of Exeter biologist who applies modern technology to the conservation of large carnivores. "Our new approach using AI promises more accurate and less subjective monitoring, which is crucial for conservationists working to protect dwindling lion populations."

The African lion is listed as Vulnerable on the IUCN Red List. Africa is estimated to host between 20,000 and 25,000 wild lions, and populations have declined by roughly half over the past 25 years. Accurate, repeatable monitoring methods are therefore a conservation priority.

The finding aligns with recent research showing multiple vocalisations in other large carnivores, such as the spotted hyena, and highlights the growing role of AI in bioacoustics. The authors argue that passive acoustic monitoring, enhanced by AI-driven classification, could become a more accessible, cost-effective and less-biased complement to traditional survey tools like camera traps or spoor counts.

While the results are promising, the researchers note that further field validation is needed to confirm how well AI-based acoustic monitoring performs across different habitats and lion populations. If validated, this approach could help conservationists track population trends, monitor individual animals, and prioritise protection measures more efficiently.

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