Call Source Levels Research Articles

Grouper source levels and aggregation dynamics inferred from passive acoustic localization at a multispecies spawning site.

Four species of grouper (family Epinephlidae), Red Hind (Epinephelus guttatus), Nassau (Epinephelus striatus), Black (Mycteroperca bonaci), and Yellowfin Grouper (Mycteroperca venenosa) share an aggregation site in Little Cayman, Cayman Islands and produce sounds while aggregating. Continuous observation of these aggregations is challenging because traditional diver or ship-based methods are limited in time and space. Passive acoustic localization can overcome this challenge for sound-producing species, allowing observations over long durations and at fine spatial scales. A hydrophone array was deployed in February 2017 over a 9-day period that included Nassau Grouper spawning. Passive acoustic localization was used to find positions of the grouper-produced calls recorded during this time, which enabled the measurement of call source levels and evaluation of spatiotemporal aspects of calling. Yellowfin Grouper had the lowest mean peak-to-peak (PP) call source level, and Nassau Grouper had the highest mean PP call source level (143.7 and 155.2 dB re: 1 μPa at 1 m for 70-170 Hz, respectively). During the days that Nassau Grouper spawned, calling peaked after sunset. Similarly, when Red Hind calls were abundant, calls were highest in the afternoon and evening. The measured source levels can be used to estimate communication and detection ranges and implement passive acoustic density estimation for these fishes.

Echolocating Daubenton's bats are resilient to broadband, ultrasonic masking noise during active target approaches.

Echolocating bats hunt prey on the wing under conditions of poor lighting by emission of loud calls and subsequent auditory processing of weak returning echoes. To do so, they need adequate echo-to-noise ratios (ENRs) to detect and distinguish target echoes from masking noise. Early obstacle avoidance experiments report high resilience to masking in free-flying bats, but whether this is due to spectral or spatiotemporal release from masking, advanced auditory signal detection or an increase in call amplitude (Lombard effect) remains unresolved. We hypothesized that bats with no spectral, spatial or temporal release from masking noise defend a certain ENR via a Lombard effect. We trained four bats (Myotis daubentonii) to approach and land on a target that broadcasted broadband noise at four different levels. An array of seven microphones enabled acoustic localization of the bats and source level estimation of their approach calls. Call duration and peak frequency did not change, but average call source levels (SLRMS, at 0.1 m as dB re. 20 μPa) increased, from 112 dB in the no-noise treatment, to 118 dB (maximum 129 dB) at the maximum noise level of 94 dB re. 20 μPa root mean square. The magnitude of the Lombard effect was small (0.13 dB SLRMS dB-1 of noise), resulting in mean broadband and narrowband ENRs of -11 and 8 dB, respectively, at the highest noise level. Despite these poor ENRs, the bats still performed echo-guided landings, making us conclude that they are very resilient to masking even when they cannot avoid it spectrally, spatially or temporally.

A Monte Carlo approach to modelling detection ranges for killer whales in inshore waters of British Columbia, Canada

Passive underwater listening stations are often used to monitor the presence, distribution and movements of marine mammals. This requires an understanding of the distances at which marine mammal sounds can be detected at a location and at different times given varying ambient noise conditions. Here, we describe a Monte Carlo approach for determining call detection probabilities as a function of distance for networked underwater listening stations deployed by Fisheries and Oceans Canada in the Salish Sea to track endangered Southern Resident Killer Whales. We used ambient sound levels measured in situ, modelled propagation losses determined by two acoustic models, and applied Monte Carlo simulations to capture the variability in call source level and animal depth. Given that only some parts of the call frequency spectrum may be responsible for the maximum detection range, the analysis was carried out independently for consecutive 300 Hz frequency bands. Median detection range estimates ranged from 700 m at the noisiest time and location to 8 km at the quietest. A sensitivity analysis revealed that the frequency distribution of source levels used for the analysis was a major factor affecting detection range results, while differences in propagation losses between summer and winter were less important.

Grouper source levels and aggregation dynamics inferred from passive acoustic localization at a multispecies spawning site

Red hind ( Epinephelus guttatus) and Nassau (E. striatus), black (Mycteroperca bonaci), and yellowfin grouper (M. venenosa) form spawning aggregations in Little Cayman, Cayman Islands and produce sound during these aggregations. Continuous observation of these aggregations is challenging because traditional methods are limited in time and space. Passive acoustic localization can overcome some of these challenges in case of sound-producing species, allowing observations over long durations and fine spatial scales. A hydrophone array was deployed in February 2017 over a nine-day period that included Nassau grouper spawning. Hyperbolic localization was used to find positions of the grouper producing calls during this time, to measure call source levels, and evaluate spatiotemporal aspects of calling. During the days Nassau grouper spawned, calling peaked after sunset from 19:00 to 21:00. Similarly, when red hind calls were most abundant, they peaked from 16:00 to 21:00. The mean peak-to-peak source levels of calls was 143.7 dB for yellowfin grouper and 154.9 dB for Nassau grouper (re: 1 μPa at 1 m for 70 to 170 Hz). The measured source levels can be used to determine communication and detection ranges and develop passive acoustic density estimation methods for these fishes.

Limited vocal compensation for elevated ambient noise in bearded seals: implications for an industrializing Arctic Ocean.

Vocalizing animals have several strategies to compensate for elevated ambient noise. These behaviours evolved under historical conditions, but compensation limits are quickly being reached in the Anthropocene. Acoustic communication is essential to male bearded seals that vocalize for courtship and defending territories. As Arctic sea ice declines, industrial activities and associated anthropogenic noise are likely to increase. Documenting how seals respond to noise and identifying naturally occurring behavioural thresholds would indicate either their resilience or vulnerability to changing soundscapes. We investigated whether male bearded seals modified call amplitudes in response to changing ambient noise levels. Vocalizing seals increased their call amplitudes until ambient noise levels reached an observable threshold, above which call source levels stopped increasing. The presence of a threshold indicates limited noise compensation for seals, which still renders them vulnerable to acoustic masking of vocal signals. This behavioural threshold and response to noise is critical for developing management plans for an industrializing Arctic.

Assessing auditory masking for management of underwater anthropogenic noise.

Masking is often assessed by quantifying changes, due to increasing noise, to an animal's communication or listening range. While the methods used to measure communication or listening ranges are functionally similar if used for vocalizations, they differ in their approaches: communication range is focused on the sender's call, while the listening range is centered on the listener's ability to perceive any signal. How these two methods differ in their use and output is important for management recommendations. Therefore it was investigated how these two methods may alter the conclusions of masking assessments based on Atlantic cod calls in the presence of a commercial air gun array. The two methods diverged with increasing distance from the masking noise source with maximum effects lasting longer between air gun pulses in terms of communication range than listening range. Reductions in the cod's communication ranges were sensitive to fluctuations in the call's source level. That instability was not observed for the listening range. Overall, changes to the cod's communication range were more conservative but very sensitive to the call source level. A high level of confidence in the call is therefore required, while confidence in the receiver's audiogram and soundscape is required for the listening range method.

Lombard effect: Minke whale boing call source levels vary with natural variations in ocean noise

Minke whales were acoustically detected, localized, and tracked on the U.S. Navy's Pacific Missile Range Facility from 2012 to 2017. Animal source levels (SLs) were estimated by adding transmission loss estimates to measured received levels of 42 159 individual minke whale boings. Minke whales off Hawaii exhibited the Lombard effect in that they increased their boing call intensity in increased background noise. Minke whales also decreased the variance of the boing call SL in higher background noise levels. Although the whales partially compensated for increasing background noise, they were unable or unwilling to increase their SLs by the same amount as the background noise. As oceans become louder, this reduction in communication space could negatively impact the health of minke whale populations. The findings in this study also have important implications for acoustic animal density studies, which may use SL to estimate probability of detection.

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 density and distribution estimation using acoustic bearings derived from sparse arrays.

Passive acoustic monitoring of marine mammals is common, and it is now possible to estimate absolute animal density from acoustic recordings. The most appropriate density estimation method depends on how much detail about animals' locations can be derived from the recordings. Here, a method for estimating cetacean density using acoustic data is presented, where only horizontal bearings to calling animals are estimable. This method also requires knowledge of call signal-to-noise ratios, as well as auxiliary information about call source levels, sound propagation, and call production rates. Results are presented from simulations, and from a pilot study using recordings of fin whale (Balaenoptera physalus) calls from Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) hydrophones at Wake Island in the Pacific Ocean. Simulations replicating different animal distributions showed median biases in estimated call density of less than 2%. The estimated average call density during the pilot study period (December 2007-February 2008) was 0.02 calls hr-1 km2 (coefficient of variation, CV: 15%). Using a tentative call production rate, estimated average animal density was 0.54 animals/1000 km2 (CV: 52%). Calling animals showed a varied spatial distribution around the northern hydrophone array, with most detections occurring at bearings between 90 and 180 degrees.

Continued source level reduction during attack in the low‐amplitude bat Barbastella barbastellus prevents moth evasive flight

Abstract Ears evolved independently in many insect taxa due to the selection pressure of echolocating bats. Eared moths perform evasive flight manoeuvres upon hearing approaching bats, thereby substantially increasing survival probability. Accordingly, eared moths constitute only a minor portion of many bats’ diets. In contrast, the barbastelle bat Barbastella barbastellus almost exclusively feeds on eared moths by emitting low‐amplitude stealth echolocation calls that are undetectable by distant moths. While closing in on the prey, however, the calls might become audible. We thus hypothesised that barbastelle bats lower the source level of their calls even further while closing in, such that the level at the moth's ear remains below the moth's hearing threshold and the moth fails to elicit its evasive manoeuvre. We tested these hypotheses by offering tethered moths to barbastelle bats in the wild and in captivity. We reconstructed the bats’ three‐dimensional flight paths based on time‐of‐arrival differences of the echolocation calls at four microphones, measured the received sound levels at the moth's position with an additional miniature microphone, and calculated call source levels. We show that barbastelle bats continuously reduced source level upon detecting a moth, thereby delaying the time and shortening the distance when the moth might detect the bat. The received level at the targeted moth never exceeded the moth's neuronal hearing threshold by more than 10 dB, which is likely sufficiently low to prevent moth evasive flight. Barbastelle bats emit low‐amplitude calls to counter moth hearing. Continued amplitude reduction during an attack extends the time before the prey becomes aware of the predator, if at all. In combination, these two strategies allowed barbastelle bats to access a food resource which is largely unavailable to competing species, thereby probably altering competition between sympatric predators. A plain language summary is available for this article.

Source levels of foraging humpback whale calls.

Humpback whales produce a wide range of low- to mid-frequency vocalizations throughout their migratory range. Non-song "calls" dominate this species' vocal repertoire while on high-latitude foraging grounds. The source levels of 426 humpback whale calls in four vocal classes were estimated using a four-element planar array deployed in Glacier Bay National Park and Preserve, Southeast Alaska. There was no significant difference in source levels between humpback whale vocal classes. The mean call source level was 137 dBRMS re 1 μPa @ 1 m in the bandwidth of the call (range 113-157 dBRMS re 1 μPa @ 1 m), where bandwidth is defined as the frequency range from the lowest to the highest frequency component of the call. These values represent a robust estimate of humpback whale source levels on foraging grounds and should append earlier estimates.

Decadal-scale frequency shift of migrating bowhead whale calls in the shallow Beaufort Sea.

Automated and manual acoustic localizations of bowhead whale calls in the Beaufort Sea were used to estimate the minimum frequency attained by their highly variable FM-modulated call repertoire during seven westerly fall migrations. Analyses of 13 355 manual and 100 009 automated call localizations found that between 2008 and 2014 the proportion of calls that dipped below 75 Hz increased from 27% to 41%, shifting the mean value of the minimum frequency distribution from 94 to 84 Hz. Multivariate regression analyses using both generalized linear models and generalized estimating equations found that this frequency shift persisted even when accounting for ten other factors, including calling depth, call range, call type, noise level, signal-to-noise ratio, local water depth (site), airgun activity, and call spatial density. No single call type was responsible for the observed shift, but so-called "complex" calls experienced larger percentage downward shifts. By contrast, the call source level distribution remained stable over the same period. The observed frequency shift also could not be explained by migration corridor shifts, relative changes in call detectability between different frequency bands, long-term degradation in the automated airgun detector, physiological growth in the population, or behavioral responses to increasing population density (estimated via call density).

Effects of anthropogenic noise on migrating bowhead whales in the Beaufort Sea

Greeneridge Sciences, Inc. (Greeneridge), has conducted multi-year, underwater, acoustic measurements at two study areas offshore of the North Slope of Alaska in the Beaufort Sea. The primary objective of these studies was to measure industrial sounds, e.g., those produced by oil production, seismic exploration, and drilling activities, and to assess their potential effects on the behavior of bowhead whales during their annual fall migration. To meet this objective, during open-water season every year from 2001 to 2016 (BP, Hilcorp) and 2007 to 2014 (Shell), Greeneridge deployed passive acoustic recorders equipped with directional sensors (DASARs) along the continental shelf. Over the course of these studies, millions of bowhead calls were localized, while ambient noise and various types of anthropogenic noise, such as tonal sounds associated with machinery and vessels and seismic airgun pulses, were quantified. The localization capabilities of the DASARs, large numbers of observations, and multi-year time series measurements together permitted, with high statistical power, quantitative evaluation of the effects of anthropogenic noise on bowhead behavior. Here, we’ll review some of our major findings, including the apparent displacement of calling bowhead whales and changes in their calling rate in response to industrial activities, consistency in their call source levels, and a shift in the frequency content of their call repertoire. [Work supported by BP Exploration Alaska, Shell Alaska Venture, and Hilcorp Alaska.]

Source levels of harbor seal underwater reproductive advertisement displays

Harbor seals (Phoca vitulina), along with the majority of other phocid species, mate underwater. During the breeding season, male harbor seals set up underwater territories and use acoustic cues, known as roars, to defend these areas against intruder males and possibly to attract females. Vocalizations are low in frequency, predominately around 60-100 Hz, with some broadband components reaching up to 5 kHz, and range from 4-10 seconds in duration. Previously, source levels of vocalizations have only been estimated. Here we present a method for measuring vocalizations to estimate source levels of harbor seal roars. We used a three-element hydrophone array in Glacier Bay National Park to record harbor seal vocalizations during the breeding season (June—July 2015). Using the array, we localized individual vocalizing animals and calculated source levels of calls in the 40-500 Hz range. Knowledge of source levels for vocalizations of harbor seals is important for understanding how anthropogenic forces, such as noise from vessels, may impact the acoustic behavior and communication range of these animals.

Source levels of dugong (Dugong dugon) vocalizations recorded in Shark Bay

Dugongs (Dugong dugon) spend significant time in shallow, turbid waters and are often active at night, conditions which are not conducive to visual cues. In part, as a result, dugongs vocalize to gain or pass information. Passive acoustic recording is a useful tool for remote detection of vocal marine animals, but its application to dugongs has been little explored compared with other mammals. Aerial surveys, often used to monitor dugong distribution and abundance, are not always financially or logistically viable and involve inherent availability and perception bias considerations. Passive acoustic monitoring is also subject to sampling biases and a first step to identifying these biases and understanding the detection or communication range of animal calls is to determine call source level. In March 2012, four dugongs were fitted with satellite tags in Shark Bay, Western Australia by the Department of Environment and Conservation. During this, acoustic recordings were taken at 5.1 m range. Source levels for each of five call types (two types of chirp, bark, squeak, and quack) were estimated, assuming spherical spreading as the transmission loss. Mean source levels for these call types were 139 (n = 19), 135 (12), 142 (2), 158 (1), and 136 (9) dB re 1 μPa at 1 m, respectively.

Bryde's whale calls recorded in the Gulf of Mexico

Bryde's whale calls recorded in the Gulf of Mexico

Source levels of fin whale 20 Hz pulses measured in the Northeast Pacific Ocean

Source levels of fin whale calls can be used to determine range to recorded vocalizations and to model maximum communication range between animals. In this study, source levels of fin whale calls were estimated using data collected on a network of eight ocean bottom seismometers in the Northeast Pacific Ocean. The acoustic pressure levels measured at the instruments were adjusted for the propagation path between the calling whales and the instruments using the call location and estimating losses along the acoustic travel path. A total of 1241 calls were used to estimate an average source level of 189 ± 5.8 dB re 1μPa at 1 m. This variability is largely attributed to uncertainties in the horizontal and vertical position of the fin whale at the time of each call and the effect of these uncertainties on subsequent calculations. Variability may also arise from station to station differences within the network. For call sequences produced by a single vocalizing whale, no consistent increase or decrease in source level was observed over the duration of a dive. Calls within these sequences that immediately followed gaps of 27 s or longer were classified as backbeat calls and were consistently lower in both frequency and amplitude.

In situ source levels of mulloway (Argyrosomus japonicus) calls

Mulloway (Argyrosomus japonicus) in Mosman Bay, Western Australia produce three call categories associated with spawning behavior. The determination of call source levels and their contribution to overall recorded sound pressure levels is a significant step towards estimating numbers of calling fish within the detection range of a hydrophone. The source levels and ambient noise also provide significant information on the impacts anthropogenic activity may have on the detection of A. japonicus calls. An array of four hydrophones was deployed to record and locate individual fish from call arrival-time differences. Successive A. japonicus calls produced samples at various ranges between 1 and 100 m from one of the array hydrophones. The three-dimensional localization of calls, together with removal of ambient noise, allowed the determination of source levels for each call category using observed trends in propagation losses and interference. Mean source levels (at 1 m from the hydrophone) of the three call categories were calculated as 163 ± 16 dB re 1 μPa for Category 1 calls (short call of 2-5 pulses); 172 ± 4 dB re 1 μPa for Category 2 calls (long calls of 11-32 pulses); and 157 ± 5 dB re 1 μPa for Category 3 calls (series of successive calls of 1-4 pulses, increasing in call rate).

Effects of noise levels and call types on the source levels of killer whale calls

Accurate parameter estimates relevant to the vocal behavior of marine mammals are needed to assess potential effects of anthropogenic sound exposure including how masking noise reduces the active space of sounds used for communication. Information about how these animals modify their vocal behavior in response to noise exposure is also needed for such assessment. Prior studies have reported variations in the source levels of killer whale sounds, and a more recent study reported that killer whales compensate for vessel masking noise by increasing their call amplitude. The objectives of the current study were to investigate the source levels of a variety of call types in southern resident killer whales while also considering background noise level as a likely factor related to call source level variability. The source levels of 763 discrete calls along with corresponding background noise were measured over three summer field seasons in the waters surrounding the San Juan Islands, WA. Both noise level and call type were significant factors on call source levels (1-40 kHz band, range of 135.0-175.7 dB(rms) re 1 [micro sign]Pa at 1 m). These factors should be considered in models that predict how anthropogenic masking noise reduces vocal communication space in marine mammals.

Source level reduction and sonar beam aiming in landing big brown bats (Eptesicus fuscus)

Reduction of echolocation call source levels in bats has previously been studied using set-ups with one microphone. By using a 16 microphone array, sound pressure level (SPL) variations, possibly caused by the scanning movements of the bat, can be excluded and the sonar beam aiming can be studied. During the last two meters of approach flights to a landing platform in a large flight room, five big brown bats aimed sonar beams at the landing site and reduced the source level on average by 7 dB per halving of distance. Considerable variation was found among the five individuals in the amount of source level reduction ranging from 4 to 9 dB per halving of distance. These results are discussed with respect to automatic gain control and intensity compensation and the combination of the two effects. It is argued that the two effects together do not lead to a stable echo level at the cochlea. This excludes a tightly coupled closed loop feed back control system as an explanation for the observed reduction of signal SPL in landing big brown bats.