Whistle Classification of Sympatric False Killer Whale Populations in Hawaiian Waters Yields Low Accuracy Rates

Cetaceans are ecologically important marine predators, and designating individuals to distinct populations can be challenging. Passive acoustic monitoring provides an approach to classify cetaceans to populations using their vocalizations. In the Hawaiian Archipelago, three genetically distinct, sympatric false killer whale (Pseudorca crassidens) populations coexist: a broadly distributed pelagic population and two island-associated populations, an endangered main Hawaiian Islands population and a Northwestern Hawaiian Islands population. The mechanisms that sustain the genetic separation between these overlapping populations are unknown but previous studies suggest that the acoustic diversity between populations may correspond to genetic differences. Here, we investigated whether false killer whale whistles could be correctly classified to population based on their characteristics to serve as a method of identifying populations when genetic or photographic-identification data are unavailable. Acoustic data were collected during line-transect surveys using towed hydrophone arrays. We measured 50 time and frequency parameters from whistles in 16 false killer whale encounters identified to population and used those measures to train and test random forest classification models. Random forest models that included three populations correctly classified 42 percent of individual whistles overall and resulted in a low kappa coefficient, κ = 0.15, indicating low agreement between models, and the true population. Whistles from the main Hawaiian Islands population showed the highest correct classification rate (52 percent) compared to pelagic and Northwestern Hawaiian Islands population whistles (42 and 36 percent, respectively). Pairwise random forest models classifying pelagic and main Hawaiian Islands whistles proved slightly more accurate (62 percent accuracy, κ = 0.24), though a similar pelagic-Northwestern Hawaiian Islands model did not (56 percent accuracy, κ = 0.12). Results suggest that the time-frequency whistle characteristics are not suitable to confidently classify encounters to a specific false killer whale population, although certain features of whistles produced by the endangered MHI population allow for overall higher classification accuracy. Inclusion of other vocalization types, such as echolocation clicks, and alternative whistle variables may improve correct classification success for these sympatric populations.

Barkley Y, Oleson EM, Oswald JN, Franklin EC. 2019. Whistle Classification of Sympatric False Killer Whale Populations in Hawaiian Waters Yields Low Accuracy Rates. Published in Frontiers in Marine Science. https://doi.org/10.3389/fmars.2019.00645.