Broad-scaled Avian Biodiversity Assessment with Passive Acoustic Monitoring and Artificial Intelligence

Many bird species are highly vocal, and this provides opportunities to monitor avian biodiversity by acoustic surveys. In recent decades, the use of Autonomous Recording Units (ARUs) has gained popularity as a mechanism to census birds through passive acoustic monitoring. Further, automatic algorithms for identifying bird species by their vocalizations have been developed to improve the efficiency and accuracy in analyzing acoustic data. In this project, I will explore the potential applications and limitations of passive acoustic monitoring in avian research. Specifically, passive acoustic monitoring will be used to answer ecological questions, including individual identification within species, species-level song activity, and community-level diversity assessment.

Intern: 
Yi-Chin Tseng
Faculty Supervisor: 
Ken Otter
Province: 
British Columbia
Partner University: 
Program: