Comparing manual and automated species recognition in the detection of four common south-east Australian forest birds from digital field recordings

Abstract

Understanding and monitoring biological communities requires accurate species inventories using reliable and efficient methods of detection. Automated recorders deployed in the field have the potential to substantially reduce observer bias and the cost of human-based inventories, but their reliability and efficiency, particularly for common species of birds, are largely untested. Using digital audio data collected in 2013 by automated recorders within the Grampians National Park, Australia, we compared the performance of two species detection methods for four species of forest birds; manually scanning spectrograms and automating the identification of vocalisations by creating species-specifi..