Abstract
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.
Highlights
Passive acoustic monitoring is an important tool for studying the spatial and temporal distribution, population density and habitat usage of vocalizing marine mammals, that complements visual surveys and tagging [1]
We describe the development of a semi-automated algorithm to track Northeast Pacific blue whales using a large network of widely spaced ocean bottom seismometers in a setting where many calling animals can be present and noise levels are reasonably high because of shipping and climatology
The seismic data used to track blue whales comes from a network of ocean bottom seismometer (OBS) deployed as part of the Cascadia Initiative experiment, supplemented by seismometers on the Ocean Networks Canada (ONC) NEPTUNE cabled observatory (Fig 1)
Summary
Passive acoustic monitoring is an important tool for studying the spatial and temporal distribution, population density and habitat usage of vocalizing marine mammals, that complements visual surveys and tagging [1]. When acoustic sensors are deployed on the seafloor in suitably configured networks, they can be used to locate calls using multi-station methods [2]. Tracking blue whales with a widely spaced network of ocean bottom seismometers two networks with network codes 7D (Cascadia Initiative Community Experiment - OBS Component, http://ds.iris.edu/mda/7D/#7D_201101-01_2017-12-31) and NV (NEPTUNE Canada, http://ds.iris.edu/mda/NV/). The location identifier for this data is not set. The IRIS DMC provides a variety of tools for downloading waveform data which are documented at https://ds.iris.edu/ds/nodes/dmc/ data/types/waveform-data/. For this study the MATLAB irisFetch software was used The blue whale detection data set is provided in the Supporting Information Dataset S1 Dataset.zip
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