Climate

What 500,000 hours of Yellowstone sound can tell us about wolves

Read full article at source ↗

Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 19/10/2026, 20:09:24 UTC.

Briefings

A project called Cry Wolf uses 500,000 hours of Yellowstone sound recordings to analyze wolf vocalizations via machine learning. Since 2023, it has isolated over 8,000 continuous hours of wolf recordings, creating the largest database of wild wolf communication. Researchers are testing if voice differences can identify individuals and track movements, with similar experiments planned in Europe's Po Valley for livestock warning. The project aims to replace expensive radio collaring with passive audio monitoring.

Key points

• The Cry Wolf Project launched in 2023 by Jeffrey Reed to analyze wolf vocalizations using machine learning on 500,000 hours of Yellowstone recordings.
• Researchers have isolated more than 8,000 continuous hours of wolf recordings, creating the largest database of wild wolf communication available.

Context

Passive audio monitoring offers a cost-effective alternative to radio collaring for tracking wolves in Yellowstone. Similar experiments are being tested in Europe's Po Valley to warn communities of approaching wolves.

Limitations

Only a fifth of the archive has been manually annotated by Jeffrey Reed. The project is still in early testing phases, and the ability to identify individuals via voice remains unproven.

Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 19/10/2026, 20:10:17 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.

View archived briefing on IPFS
bafybeidaig665c2v23t6pwbj3vm4pzodcyeqyoyp6hjiudfvgno55y73zm