Researchers from Warddeken Land Management, Charles Darwin University, and the CSIRO have demonstrated how AI can assist Indigenous-led wildlife monitoring while keeping Traditional Owners central to decisions about Country.
The collaboration applied the MegaDetector AI model to the Mayh (animal) wildlife monitoring program in the Warddeken Indigenous Protected Area in West Arnhem, in the Northern Territory, where rangers use camera traps to track animals of cultural and conservation significance.
After processing 1,572 hours of ranger-collected data, MegaDetector reduced the number of images requiring analysis from 925,088 to 172,290 – a reduction of 81.4 per cent. The processing period fell from six months to two, while average data-processing time dropped from 52.6 hours per fortnight to 41.8.
The time saved allowed rangers to focus more on species identification, land management, language documentation, and producing reports, newsletters, and videos to share knowledge with younger generations.
Warddeken ecological monitoring officer and CDU researcher Dr Cara Penton said the aim was to use AI to make work more rewarding without sidelining people or their expertise.
“People are still part of the verification. People are still part of the process,” Penton said in a statement.
She said strong data depended on people being involved in its collection, verification, and processing, with decisions about how information informs stewardship remaining with local communities.
Warddeken senior Daluk Ranger and Bininj Nawarddeken woman Suzanna Nabulwad said consultation with Elders was essential to using technology appropriately on Country.
“It is important to talk to our elders, so we use technology the right way on Country, that way we can make sure we look after it and protect the animals,” Nabulwad said.
"I have been a ranger for a long time. Using technology and doing work with cameras and looking at the images, it helps make the job more interesting. It is important to teach new rangers how to do it so that they enjoy their jobs."
The research highlights how AI can reduce repetitive workloads while supporting Indigenous knowledge, cultural priorities and community-led conservation.
Reimagining artificial intelligence applications for Indigenous-led community-based wildlife monitoring: Insights from biodiversity surveys in the Warddeken Indigenous protected area in northern Australia was published in the journal Conservation Science and Practice.
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