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Cuvier’s beaked whale foraging dives identified via machine learning using depth and triaxial acceleration

David A. Sweeney, Gregory S. Schorr*, Erin A. Falcone, Brenda K. Rone, Russel D. Andrews, Shannon N. Coates, Stephanie L. Watwood, Stacy L. DeRuiter, Mark P. Johnson, David J. Moretti

*Corresponding author:

ABSTRACT: Knowledge of Cuvier’s beaked whale (Ziphius cavirostris) behavior has expanded through the utilization of animal-borne tags. However, many tag types do not record sound—preventing echolocation click detections to identify foraging—or have short deployments that sample a limited range of behaviors. As the quantity of tag data grows, so too does the need for robust methods of detecting foraging from non-acoustic data. We used 692 dives from five sound-recording tags on Cuvier’s beaked whales in Southern California to develop extreme gradient boosting tree models to detect foraging based on 1 Hz depth and 16 Hz triaxial acceleration data. We performed repeated 10-fold cross validation using classification accuracy to tune 500 models with randomly partitioned training and testing datasets. An average of 99.9% and 99.2% of training and testing dataset dives, respectively, were correctly classified across the 500 models. Dives without associated sound recordings (n = 2069 from seven whales including four non-acoustic tags) were classified via a model that maximized training information using dive depth and duration, ascent and descent rates, bottom-phase average vertical speed, and roll circular variance during dive descents and bottom phases. Of all long, deep dives (conventionally assumed to contain foraging), 2.4% were classified as non-foraging dives, while 0.3% of short, shallow dives were classified as foraging dives. Results confirm that conventional depth and/or duration classifiers provide reasonable estimates of longer-term foraging patterns. However, additional variables previously listed enhance foraging detections for unusual dives (notably non-foraging deep dives) for Southern California Cuvier’s beaked whales.