A method for tracking blue whales (Balaenoptera musculus) with a widely spaced network of ocean bottom seismometers

• Published in: PLOS ONE
• Main Authors: Wilcock, William S. D., Hilmo, Rose S.
• Other Authors: Deng, Zhiqun Daniel, Office of Naval Research Global
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2021
• Subjects: Balaenoptera musculus; Blue whale
• Online Access: http://dx.doi.org/10.1371/journal.pone.0260273; https://dx.plos.org/10.1371/journal.pone.0260273

Passive acoustic monitoring is an important tool for studying marine mammals. Ocean bottom seismometer networks provide data sets of opportunity for studying blue whales ( Balaenoptera musculus ) which vocalize extensively at seismic frequencies. We describe methods to localize calls and obtain tracks using the B call of northeast Pacific blue whale recorded by a large network of widely spaced ocean bottom seismometers off the coast of the Pacific Northwest. The first harmonic of the B call at ~15 Hz is detected using spectrogram cross-correlation. The seasonality of calls, inferred from a dataset of calls identified by an analyst, is used to estimate the probability that detections are true positives as a function of the strength of the detection. Because the spacing of seismometers reaches 70 km, faint detections with a significant probability of being false positives must be considered in multi-station localizations. Calls are located by maximizing a likelihood function which considers each strong detection in turn as the earliest arrival time and seeks to fit the times of detections that follow within a feasible time and distance window. An alternative procedure seeks solutions based on the detections that maximize their sum after weighting by detection strength and proximity. Both approaches lead to many spurious solutions that can mix detections from different B calls and include false detections including misidentified A calls. Tracks that are reliable can be obtained iteratively by assigning detections to localizations that are grouped in space and time, and requiring groups of at least 20 locations. Smooth paths are fit to tracks by including constraints that minimize changes in speed and direction while fitting the locations to their uncertainties or applying the double difference relocation method. The reliability of localizations for future experiments might be improved by increasing sampling rates and detecting harmonics of the B call.