An excerpt from an academic oral presentation on rainforest wildlife monitoring states:
"In our bioacoustics study across the Tambopata National Reserve in southeastern Peru, our research team deployed 32 solar-powered autonomous audio recording units across four distinct forest layers. To document nocturnal biodiversity, the automated microphones operated continuously between 6:00 PM and 5:00 AM, capturing over 12,000 hours of audio files. By applying machine-learning algorithms to isolate sound signatures above 8 kilohertz, the software cataloged 47 unique amphibian call types and identified 15 rare insect species previously undetected by visual transects. Furthermore, to verify automated detection accuracy, field technicians conducted manual spot-checks on exactly 10% of the flagged sound files."
Based on the supporting details presented in the audio excerpt, match each monitoring metric or component with its specific factual measurement.
- Daily operating schedule of the automated microphonesBetween 6:00 PM and 5:00 AM
- Frequency threshold applied by machine-learning algorithmsAbove 8 kilohertz
- Number of amphibian call types identified by software47 unique types
- Percentage of flagged files audited through manual spot-checksExactly 10%