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BirdNET: Automated Detection for Monitoring Critically Endangered Lemurs from the Maromizaha Forest.

Valeria Ferrario1,2, Giacomo Versaci3, Giulia Dall'Ava1

  • 1Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy.

Integrative Zoology
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Summary

Passive acoustic monitoring (PAM) combined with BirdNET AI effectively tracks endangered lemurs. This machine learning approach offers a scalable solution for wildlife research and conservation efforts.

Keywords:
CNNPAMblack‐and‐white ruffed lemurecoacousticsindri

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Area of Science:

  • Wildlife ecology
  • Bioacoustics
  • Machine learning in conservation

Background:

  • Passive acoustic monitoring (PAM) generates vast datasets for wildlife research but presents computational challenges.
  • Machine learning models, like BirdNET, show promise for automated species identification from acoustic data.

Purpose of the Study:

  • To assess the efficacy of integrating PAM with a retrained BirdNET model for monitoring two critically endangered lemur species (Indri indri and Varecia variegata).
  • To analyze lemur vocalization patterns and inform conservation strategies.

Main Methods:

  • Collected over 55,000 acoustic recordings in Madagascar over four years.
  • Retrained the BirdNET convolutional neural network for lemur vocalization detection using labeled data.
  • Tested various model configurations and confidence thresholds to achieve high performance (∼90% accuracy).

Main Results:

  • Developed a high-performing BirdNET model for detecting Indri indri and Varecia variegata vocalizations.
  • Indri indri displayed diurnal calling patterns, peaking in the morning and warm season.
  • Varecia variegata exhibited irregular, including nocturnal, calling patterns with no distinct seasonal peaks.

Conclusions:

  • Combining PAM with machine learning provides a feasible, scalable, and cost-effective method for long-term primate monitoring.
  • The study highlights the value of AI-driven acoustic analysis for understanding species ecology and guiding conservation actions.