Categorizing click trains to increase taxonomic precision in echolocation click loggers

• Published in: The Journal of the Acoustical Society of America
• Main Authors: Palmer, K. J., Brookes, Kate, Rendell, Luke
• Other Authors: University of St Andrews.School of Biology, University of St Andrews.Centre for Social Learning & Cognitive Evolution, University of St Andrews.Sea Mammal Research Unit, University of St Andrews.Marine Alliance for Science & Technology Scotland, University of St Andrews.Bioacoustics group, University of St Andrews.Centre for Biological Diversity
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2018
• Subjects: Passive acoustic monitoring; Odontocete; Echolocation click logger; GC Oceanography; QH301 Biology; Acoustics and Ultrasonics; NDAS; GC; QH301; Lagenorhynchus albirostris
• Online Access: https://hdl.handle.net/10023/12721; https://doi.org/10.1121/1.4996000

L.R. and K.J.P. were supported by Marine Scotland Science and the Marine Alliance for Science and Technology for Scotland (MASTS) pooling initiative and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. Passive acoustic monitoring is an efficient way to study acoustically active animals but species identification remains a major challenge. C-PODs are popular logging devices that automatically detect odontocete echolocation clicks. However, the accompanying analysis software does not distinguish between delphinid species. Click train features logged by C-PODs were compared to frequency spectra from adjacently deployed continuous recorders. A generalized additive model was then used to categorize C-POD click trains into three groups: broadband click trains, produced by bottlenose dolphin (Tursiops truncatus) or common dolphin (Delphinus delphis), frequency-banded click trains, produced by Risso's (Grampus griseus) or white beaked dolphins (Lagenorhynchus albirostris), and unknown click trains. Incorrect categorization rates for broadband and frequency banded clicks were 0.02 (SD 0.01), but only 30% of the click trains met the categorization threshold. To increase the proportion of categorized click trains, model predictions were pooled within acoustic encounters and a likelihood ratio threshold was used to categorize encounters. This increased the proportion of the click trains meeting either the broadband or frequency banded categorization threshold to 98%. Predicted species distribution at the 30 study sites matched well to visual sighting records from the region. Peer reviewed