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Recommended Literature about Passive Acoustic Monitoring (PAM)
Introduction
The following may prove useful for those conducting their own Passive Acoustic Monitoring (PAM) projects. The authors include:
- Connor Wood (BirdNET Ecology Lead)
- Stefan Kahl (BirdNET Technology Lead)
Suggested by Connor Wood
Study Design
- Choosing survey duration and recording schedule for passive acoustic bird surveys
- Power analysis to determine how many sites are necessary
- Conceptualizing surveys and interpreting bird observations
- Guidelines for appropriate use of BirdNET output scores
- Expert-level multispecies dynamic occupancy model that accommodates false positives designed for BirdNET
- Synthesizing passive acoustic monitoring and mark-recapture data for an ecosystem-scale abundance estimate
Study Examples
- Example of using BirdNET-derived observations of one bird species for applied ecological research
- Example of using BirdNET for many bird species
- Example of using BirdNET for two amphibians
- Example of using BirdNET for wolves and coyotes
- Example of using BirdNET for one primate (with some sample code for basic occupancy modeling)
Suggested by Stefan Kahl
- BirdNET: A deep learning solution for avian diversity monitoring
- Guidelines for appropriate use of BirdNET output scores
- Deep learning algorithm outperforms experienced human observer at detection of blue whale D-calls: a double-observer analysis
- Feature embeddings from large-scale acoustic bird classifiers enable few-shot transfer learning
Related Articles
- Best Practices for Passive Acoustic Monitoring and Using BirdNET and Raven Pro
- Add BirdNET V2.4 to Raven Pro
- Custom Machine Learning Models with BirdNET Analyzer GUI
- Acoustic analysis with BirdNET and (almost) no coding: practical instructions
- Best Practices for Data Management
- Machine Learning Detector – Quick Start Guide