TLDR: Scientists at Bournemouth University have developed an AI tool that uses sound analysis to count barn owl chicks, eliminating the need for intrusive video cameras and reducing stress on the birds. This innovation, led by PhD student Kavisha Jayathunge and engineer Brian Cresswell, allows for monitoring in natural, often inaccessible, nest sites.
A groundbreaking artificial intelligence (AI) tool has been developed to revolutionize the monitoring of barn owl chicks, allowing researchers to gather crucial data without disturbing their sensitive nesting sites. This innovative project, spearheaded by PhD student Kavisha Jayathunge at Bournemouth University, in collaboration with biologist-turned-electronics engineer Brian Cresswell, utilizes sound analysis to accurately count and identify individual barn owl chicks.
Traditionally, monitoring barn owl breeding success has often involved the installation of video cameras, which can cause stress to the young birds and their parents. The new AI-powered system circumvents this issue by analyzing the unique sounds made by the owlets. Mr. Jayathunge explained, ‘We’re using AI to count baby barn owls by sound instead of disturbing them in their nests with video cameras. This helps reduce stress on the birds and could give us data from natural nest sites, which are often inaccessible for monitoring, not just the artificial nest boxes where most of the data we currently have comes from.’
The AI technology is designed to identify subtle distinctions in the owlets’ hissing calls that are imperceptible to the human ear. By analyzing differences in frequency, the model can determine the number of birds present and even identify individual owlets. Mr. Jayathunge emphasized the positive synergy, stating, ‘Bringing AI and ecology together in such a positive way is a great example of how this technology can be used for good.’
Brian Cresswell, who assisted in testing the technology on nest boxes in north Dorset, highlighted the importance of this data: ‘This basic data is important for monitoring breeding success of barn owls, which can vary greatly between years and breeding sites.’ He also noted the AI model’s potential as a research tool to study the behavior of young owls and the purpose of their hissing, which is believed to be a means of negotiating food delivery from parents. Furthermore, there is potential for the hissing analysis to indicate the owlets’ hunger levels, providing additional valuable data for breeding success monitoring.
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The long-term vision for the project is to develop the technology to a point where volunteers and conservationists can easily capture the sounds of hissing owlets at their nests. Since barn owl hissing is loud, audio recorders can be placed at a distance, adhering to the strict protocols that protect barn owls and their nests under Schedule One of the Wildlife and Countryside Act.
