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
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2017
• Subjects: Passive acoustic monitoring; Odontocete; Echolocation click logger; Lagenorhynchus albirostris
• Online Access: https://research-portal.st-andrews.ac.uk/en/researchoutput/categorizing-click-trains-to-increase-taxonomic-precision-in-echolocation-click-loggers(87e5b840-f395-41d8-84ce-cb35829fe627).html; https://doi.org/10.1121/1.4996000; https://research-repository.st-andrews.ac.uk/bitstream/10023/12721/1/Palmer_2017_Categorizing_click_trains_JASA_AAM.pdf

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.