Fin whale tracks recorded by a seismic network on the Juan de Fuca Ridge, Northeast Pacific Ocean

Hydroacoustic study of fin whales around the Southern Wake Island: Type, vocal behavior, and temporal evolution from 2010 to 2022

The progress of fin whale study is hindered by the debate about whether the two typical type-A and type-B calls (characterized by central source frequencies of 17-20 Hz and 20-30 Hz, respectively) originate from a single fin whale or two individual fin whales. Here, hydroacoustic data is employed to study the type, vocal behavior, and temporal evolution of fin whale calls around the Southern Wake Island from 2010 to 2022. It is identified that (1) type-A and type-B calls come from two individuals based on the large source separation of the two calls through high-precision determination of source location; (2) type-A fin whales exhibit vocal influence on type-B fin whales, where type-B fin whales become paired with type-A calls and vocalize regularly when type-A fin whales appear, and type-A fin whales always lead the call sequences; and (3) some type-A fin whales stop calling when another type-A fin whale approaches at a distance of about 1.6 km. During 2010-2022, type-A calls occur every year, whereas type-B calls are prevalent only after November 2018. A culture transmission is proposed from type-A fin whales to type-B fin whales and/or a population increase of type-B fin whales in the region after November 2018.

Estimating distances to baleen whales using multipath arrivals recorded by individual seafloor seismometers at full ocean depth

Ocean bottom seismometer networks can record opportunistic data sets of 20-Hz fin whale calls. Because networks are often too sparse for multi-station tracking, single-station methods are needed to estimate call density. We investigated a method to range to singing fin whales at full ocean depths using the spacing of water column multiples. Calls were detected by cross-correlating a spectrogram with a template call. To enhance multipath signals, we considered 20-min windows and either summed the spectrograms of all calls aligned on the strongest detection before measuring the multipath spacing or measured the spacing directly from the autocorrelation of the cross correlation time series. We evaluated the methods at five sites with contrasting seafloor and subsurface properties, bathymetric relief, and water depths of 4000-6000 m, using fin whale songs at four sites and a sei whale song at the fifth. The autocorrelation method works best, and ranges can be obtained to >15 km. Ranging at sedimented sites requires careful accounting for subsurface reflections. Ranges have considerable uncertainty in regions of bathymetric relief. The method requires that the time between calls is different from that of the multipaths and does not work reliably when more than one whale is singing nearby.

Occurrence and patterns of fin whale songs reveal alternative migration strategies in Svalbard Islands, Norway

The Arctic marine environment is highly affected by global warming with notable changes in habitat conditions, which have great consequences on migrating species. For example, the timing of their migration can be altered leading to changes in their occurrence in suitable areas, which are critical for their survival. In this study, seven years of acoustic data were analysed in Svalbard Islands from 2014 to 2020, revealing that the occurrence of fin whales (Balaenoptera physalus) happened all year-round. The sea surface temperature recorded reveals conditions which could be favorable for these species to persist until the Polar Night. The occurrence of songs indicated that certain individuals did not undertake the migratory journey through the southern breeding grounds, possibly using the area for mating purposes. The analyses of the Inter-Note-Interval (INI) demonstrated that over the years songs with different patterns were found. This suggests that either the fin whales are able to switch their INI patterns or that populations with different INIs are visiting during the Winter. Therefore, this study unveils the undertaking of an alternative strategy to migration movements, and the possible potential origin of the fin whales overwintering in Svalbard.

Detection probability and density estimation of fin whales by a Seaglider

A single-hydrophone ocean glider was deployed within a cabled hydrophone array to demonstrate a framework for estimating population density of fin whales (Balaenoptera physalus) from a passive acoustic glider. The array was used to estimate tracks of acoustically active whales. These tracks became detection trials to model the detection function for glider-recorded 360-s windows containing fin whale 20-Hz pulses using a generalized additive model. Detection probability was dependent on both horizontal distance and low-frequency glider flow noise. At the median 40-Hz spectral level of 97 dB re 1 μPa²/Hz, detection probability was near one at horizontal distance zero with an effective detection radius of 17.1 km [coefficient of variation (CV) = 0.13]. Using estimates of acoustic availability and acoustically active group size from tagged and tracked fin whales, respectively, density of fin whales was estimated as 1.8 whales per 1000 km² (CV = 0.55). A plot sampling density estimate for the same area and time, estimated from array data alone, was 1.3 whales per 1000 km² (CV = 0.51). While the presented density estimates are from a small demonstration experiment and should be used with caution, the framework presented here advances our understanding of the potential use of gliders for cetacean density estimation.

An overview of ambient sound using Ocean Observatories Initiative hydrophones

The Ocean Observatories Initiative (OOI) sensor network provides a unique opportunity to study ambient sound in the north-east Pacific Ocean. The OOI sensor network has five low frequency (Fs = 200 Hz) and six broadband (Fs = 64 kHz) hydrophones that have been recording ambient sound since 2015. In this paper, we analyze acoustic data from 2015 to 2020 to identify prominent features that are present in the OOI acoustic dataset. Notable features in the acoustic dataset that are highlighted in this paper include volcanic and seismic activity, rain and wind noise, marine mammal vocalizations, and anthropogenic sound, such as shipping noise. For all low frequency hydrophones and four of the six broadband hydrophones, we will present long-term spectrograms, median time-series trends for different spectral bands, and different statistical metrics about the acoustic environment. We find that 6-yr acoustic trends vary, depending on the location of the hydrophone and the spectral band that is observed. Over the course of six years, increases in spectral levels are seen in some locations and spectral bands, while decreases are seen in other locations and spectral bands. Last, we discuss future areas of research to which the OOI dataset lends itself.

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

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.

Acoustic tracking of fin whales: Habitat use and movement patterns within a Canadian Pacific fjord system

Fin whale 20 Hz calls were detected, localized, and tracked using a 10 km aperture network of three acoustic receivers deployed for 11 months in a Pacific Canadian fjord system. The area has been historically important for fin whales and is located along a route that tankers will begin using in 2024. A total of 6712 calls were localized, and trajectories were fitted for 55 acoustic tracks. Fin whale tracks occurred throughout the monitoring site. Call activity peaked in September and was low during winter months. Swimming characteristics varied significantly between day- and nighttime: at night, whales swam faster (7.1 vs 4.0 km/h median, +75.2%), which resulted in longer (+34.7%), less predictable (-70.6%) tracks as compared to daylight hours. Call frequencies varied between 16 and 32 Hz. Beside stereotypical song frequencies, fin whales also used irregular frequency components, which contributed the majority of calls in the summer but did not occur in the winter. The results suggest that the area is primarily used as a summer feeding ground, where fin whales follow a diel behavioral cycle. The observed activity patterns will aid in the assessment of strike risk and harassment mitigation and provide a baseline to document behavioral change.

Seismic crustal imaging using fin whale songs

Fin whale calls are among the strongest animal vocalizations that are detectable over great distances in the oceans. We analyze fin whale songs recorded at ocean-bottom seismometers in the northeast Pacific Ocean and show that in addition to the waterborne signal, the song recordings also contain signals reflected and refracted from crustal interfaces beneath the stations. With these data, we constrain the thickness and seismic velocity of the oceanic sediment and basaltic basement and the P-wave velocity of the gabbroic lower crust beneath and around the ocean bottom seismic stations. The abundant and globally available fin whale calls may be used to complement seismic studies in situations where conventional air-gun surveys are not available.

On the use of the Lloyd's Mirror effect to infer the depth of vocalizing fin whales

The interference between the direct path and the sea surface reflection of a signal as measured by a receiver is called Lloyd's Mirror effect (LME). It results in a frequency-dependent interference pattern that can be observed in a spectrogram. LME depends on the receiver depth, signal source depth, signal frequency, and slant range between source and receiver. Knowing three of these parameters a priori, LME can be used to estimate the third parameter, such as source depth. Here, the work in Pereira et al. (2016) was expanded to estimate the depth of a vocalizing fin whale recorded by an ocean-bottom seismometer (OBS). In Pereira et al. (2016), the depth of a vocalizing fin whale was inferred by manually comparing spectrograms of LME transmission loss models with observed LME. This study developed an automated procedure to perform the same task using the LME interference pattern observed in the spectrograms of the hydrophone and the vertical channel of the OBS. The results show that the joint use of the two channels was the best approach to estimate a source depth using LME. LME provides a non-intrusive approach for estimating the depth at which a fin whale was vocalizing.

Fin whale acoustic presence and song characteristics in seas to the southwest of Portugal

Fin whales were once abundant in the seas to the southwest of Portugal, but whaling activities decreased their numbers considerably. Acoustic data from ocean bottom seismometers provide an opportunity to detect fin whales from their notes, data that would otherwise be logistically challenging and expensive to obtain. Based on inter-note interval and frequency bandwidth, two acoustic patterns produced by fin whales were detected in the study area: pattern 1, described from fin whales in the Mediterranean Sea, and pattern 2, associated with fin whales from the northeast North Atlantic Ocean (NENA). NENA fin whales travel into the western Mediterranean Sea, but the Mediterranean population has not been documented to travel regularly into the NENA. In this study, 11 months of acoustic data recorded southwest of Portugal in the NENA were used to characterize 20-Hz fin whale notes into these patterns. Pattern 2 was the most common and occurred mostly in November-January. Pattern 1 occurred less frequently and mostly in September-December, February and April, which suggested a limited excursion of whales from the Mediterranean Sea. There were also occasions when the two patterns were recorded simultaneously. Results suggest that fin whales from the NENA and Mediterranean Sea might mix in the area during part of the year.

Fauna of the Kemp Caldera and its upper bathyal hydrothermal vents (South Sandwich Arc, Antarctica)

Faunal assemblages at hydrothermal vents associated with island-arc volcanism are less well known than those at vents on mid-ocean ridges and back-arc spreading centres. This study characterizes chemosynthetic biotopes at active hydrothermal vents discovered at the Kemp Caldera in the South Sandwich Arc. The caldera hosts sulfur and anhydrite vent chimneys in 1375-1487 m depth, which emit sulfide-rich fluids with temperatures up to 212°C, and the microbial community of water samples in the buoyant plume rising from the vents was dominated by sulfur-oxidizing Gammaproteobacteria. A total of 12 macro- and megafaunal taxa depending on hydrothermal activity were collected in these biotopes, of which seven species were known from the East Scotia Ridge (ESR) vents and three species from vents outside the Southern Ocean. Faunal assemblages were dominated by large vesicomyid clams, actinostolid anemones, Sericosura sea spiders and lepetodrilid and cocculinid limpets, but several taxa abundant at nearby ESR hydrothermal vents were rare such as the stalked barnacle Neolepas scotiaensis. Multivariate analysis of fauna at Kemp Caldera and vents in neighbouring areas indicated that the Kemp Caldera is most similar to vent fields in the previously established Southern Ocean vent biogeographic province, showing that the species composition at island-arc hydrothermal vents can be distinct from nearby seafloor-spreading systems. δ ¹³C and δ ¹⁵N isotope values of megafaunal species analysed from the Kemp Caldera were similar to those of the same or related species at other vent fields, but none of the fauna sampled at Kemp Caldera had δ ¹³C values, indicating nutritional dependence on Epsilonproteobacteria, unlike fauna at other island-arc hydrothermal vents.

Comparison of estimated 20-Hz pulse fin whale source levels from the tropical Pacific and Eastern North Atlantic Oceans to other recorded populations

Passive acoustic monitoring, mitigation, animal density estimation, and comprehensive understanding of the impact of sound on marine animals all require accurate information on vocalization source level to be most effective. This study focused on examining the uncertainty related to passive sonar equation terms that ultimately contribute to the variability observed in estimated source levels of fin whale calls. Differences in hardware configuration, signal detection methods, sample size, location, and time were considered in interpreting the variability of estimated fin whale source levels. Data from Wake Island in the Pacific Ocean and off Portugal in the Atlantic Ocean provided the opportunity to generate large datasets of estimated source levels to better understand sources of uncertainty leading to the observed variability with and across years. Average seasonal source levels from the Wake Island dataset ranged from 175 to 188 dB re 1 μPa m, while the 2007-2008 seasonal average detected off Portugal was 189 dB re 1 μPa m. Owing to the large inherent variability within and across this and other studies that potentially masks true differences between populations, there is no evidence to conclude that the source level of 20-Hz fin whale calls are regionally or population specific.

Fin whale singing decreases with increased swimming speed

The attributes of male acoustic advertisement displays are often related to a performer's age, breeding condition and motivation, but these relationships are particularly difficult to study in free-ranging marine mammals. For fin whale singers, we examined the relationships between a singer's swimming speed, song duration and amount of singing. We used a unique set of fin whale singing and swimming data collected in support of the US Navy's marine mammal monitoring programme associated with the Navy's Integrated Undersea Surveillance System. A goal of the programme is to improve understanding of the potential effects of anthropogenic sound sources on baleen whale behaviours and populations. We found that as whales swam faster, some continued to sing, while others did not. If swimming speed is an indication of male stamina, then singing while swimming faster could be a display by which females and/or other males assess a singer's physical fitness and potential reproductive quality. Results have implications for interpreting fin whale singing behaviour and the possible influences of anthropogenic sounds on fin whale mating strategies and breeding success.

Spatial and temporal trends in fin whale vocalizations recorded in the NE Pacific Ocean between 2003-2013

In order to study the long-term stability of fin whale (Balaenoptera physalus) singing behavior, the frequency and inter-pulse interval of fin whale 20 Hz vocalizations were observed over 10 years from 2003–2013 from bottom mounted hydrophones and seismometers in the northeast Pacific Ocean. The instrument locations extended from 40°N to 48°N and 130°W to 125°W with water depths ranging from 1500–4000 m. The inter-pulse interval (IPI) of fin whale song sequences was observed to increase at a rate of 0.54 seconds/year over the decade of observation. During the same time period, peak frequency decreased at a rate of 0.17 Hz/year. Two primary call patterns were observed. During the earlier years, the more commonly observed pattern had a single frequency and single IPI. In later years, a doublet pattern emerged, with two dominant frequencies and IPIs. Many call sequences in the intervening years appeared to represent a transitional state between the two patterns. The overall trend was consistent across the entire geographical span, although some regional differences exist. Understanding changes in acoustic behavior over long time periods is needed to help establish whether acoustic characteristics can be used to help determine population identity in a widely distributed, difficult to study species such as the fin whale.

Estimating range to a vocalizing fin whale using the timing and amplitude of multipath arrivals

A semi-automated method is described to range to vocalizing fin whales using the timing and amplitude of multipath arrivals measured on seafloor receivers. Calls are detected and multipath arrivals identified with a matched filter. Multipath times and relative amplitudes are predicted as a function of range by ray tracing. Because the direct and first water-column multiple arrivals are not always observed, different hypotheses for the observed arrival paths must be considered. For two arrivals, an amplitude threshold is used to determine if the first arrival is the direct path and if not, the call is disregarded as distant. When three or more arrivals are detected, three hypotheses for the paths of arrivals are considered; the solution is the hypothesis and range that minimizes the timing and optionally, amplitude ratio or absolute amplitude residual. The method is tested with data from two ocean bottom seismometers, one on the Juan de Fuca Ridge and the other in the Cascadia Basin. Solutions obtained by minimizing a combined residual from timing and an empirical absolute amplitude model extracted from the data yield reliable ranges up to 5 km at both sites, and are sufficient to estimate call density using point transect distance sampling.

Observations and Bayesian location methodology of transient acoustic signals (likely blue whales) in the Indian Ocean, using a hydrophone triplet

A notable sequence of calls was encountered, spanning several days in January 2003, in the central part of the Indian Ocean on a hydrophone triplet recording acoustic data at a 250 Hz sampling rate. This paper presents signal processing methods applied to the waveform data to detect, group, extract amplitude and bearing estimates for the recorded signals. An approximate location for the source of the sequence of calls is inferred from extracting the features from the waveform. As the source approaches the hydrophone triplet, the source level (SL) of the calls is estimated at 187 ± 6 dB re: 1 μPa-1 m in the 15-60 Hz frequency range. The calls are attributed to a subgroup of blue whales, Balaenoptera musculus, with a characteristic acoustic signature. A Bayesian location method using probabilistic models for bearing and amplitude is demonstrated on the calls sequence. The method is applied to the case of detection at a single triad of hydrophones and results in a probability distribution map for the origin of the calls. It can be extended to detections at multiple triads and because of the Bayesian formulation, additional modeling complexity can be built-in as needed.

Using accelerometers to determine the calling behavior of tagged baleen whales

Low-frequency acoustic signals generated by baleen whales can propagate over vast distances, making the assignment of calls to specific individuals problematic. Here we report the novel use of acoustic recording tags equipped with high-resolution accelerometers to detect vibrations on the surface of two tagged fin whales that directly match the timing of recorded acoustic signals. A tag deployed on a buoy in the vicinity of calling fin whales, and a recording from a tag that had just fallen off of a whale, were able to detect calls acoustically but did not record corresponding accelerometer signals that were measured on calling individuals. Across the hundreds of calls measured on two tagged fin whales, the accelerometer response was generally anisotropic across all three axes, appeared to depend on tag placement, and increased with the level of received sound. These data demonstrate that high-sample-rate accelerometry can provide important insights into the acoustic behavior of baleen whales that communicate at low frequencies. This method helps identify vocalizing whales, which in turn enables the quantification of call rates, a fundamental component of models used to estimate baleen whale abundance and distribution from passive acoustic monitoring.

Sounds in the ocean at 1-100 Hz

Very-low-frequency sounds between 1 and 100 Hz propagate large distances in the ocean sound channel. Weather conditions, earthquakes, marine mammals, and anthropogenic activities influence sound levels in this band. Weather-related sounds result from interactions between waves, bubbles entrained by breaking waves, and the deformation of sea ice. Earthquakes generate sound in geologically active regions, and earthquake T waves propagate throughout the oceans. Blue and fin whales generate long bouts of sounds near 20 Hz that can dominate regional ambient noise levels seasonally. Anthropogenic sound sources include ship propellers, energy extraction, and seismic air guns and have been growing steadily. The increasing availability of long-term records of ocean sound will provide new opportunities for a deeper understanding of natural and anthropogenic sound sources and potential interactions between them.

Applying distance sampling to fin whale calls recorded by single seismic instruments in the northeast Atlantic

Automated methods were developed to detect fin whale calls recorded by an array of ocean bottom seismometers (OBSs) deployed off the Portuguese coast between 2007 and 2008. Using recordings collected on a single day in January 2008, a standard seismological method for estimating earthquake location from single instruments, the three-component analysis, was used to estimate the relative azimuth, incidence angle, and horizontal range between each OBS and detected calls. A validation study using airgun shots, performed prior to the call analysis, indicated that the accuracy of the three-component analysis was satisfactory for this preliminary study. Point transect sampling using cue counts, a form of distance sampling, was then used to estimate the average probability of detecting a call via the array during the chosen day. This is a key step to estimating density or abundance of animals using passive acoustic data. The average probability of detection was estimated to be 0.313 (standard error: 0.033). However, fin whale density could not be estimated due to a lack of an appropriate estimate of cue (i.e., vocalization) rate. This study demonstrates the potential for using a sparse array of widely spaced, independently operating acoustic sensors, such as OBSs, for estimating cetacean density.