BirdNET: applications, performance, pitfalls and future opportunities

• DOI: 10.1111/ibi.13193
• Publication Date: 2023-02-28T06:53:45Z
• Authors: Cristian Pérez‐Gr...
• Keywords: Popularity; Identification

Automated recognition software is paramount for effective passive acoustic monitoring. BirdNET a free and recently developed bird sound recognizer. I performed literature review to evaluate the current applications performance of BirdNET, which growing in popularity but has been subject few assessments, provide recommendations future studies using BirdNET. Prior research employed wide range purposes have linked detections ecological processes or real‐world monitoring schemes. Among evaluated studies, average precision (% correctly identified) usually ranged around 72–85%, recall rate target species vocalizations detected) 33–84%. Some did not assess performance, hampers interpretation results may poorly informed decisions. Recommendations on how efficiency are provided. The impact confidence score threshold, user‐selected parameter as minimum reported, output although variable among consistent. use high thresholds increases percentage classified lowers proportion calls detected. selection an optimal depend priorities user goals. great tool automated it should be used with caution due inherent challenges identification. continued refinement suggests further improvements coming years.