Spatio-temporal variation in click production rates of beaked whales: Implications for passive acoustic density estimation

Click detection rate variability of central North Pacific sperm whales from passive acoustic towed arrays

Passive acoustic monitoring (PAM) is an optimal method for detecting and monitoring cetaceans as they frequently produce sound while underwater. Cue counting, counting acoustic cues of deep-diving cetaceans instead of animals, is an alternative method for density estimation, but requires an average cue production rate to convert cue density to animal density. Limited information about click rates exists for sperm whales in the central North Pacific Ocean. In the absence of acoustic tag data, we used towed hydrophone array data to calculate the first sperm whale click rates from this region and examined their variability based on click type, location, distance of whales from the array, and group size estimated by visual observers. Our findings show click type to be the most important variable, with groups that include codas yielding the highest click rates. We also found a positive relationship between group size and click detection rates that may be useful for acoustic predictions of group size in future studies. Echolocation clicks detected using PAM methods are often the only indicator of deep-diving cetacean presence. Understanding the factors affecting their click rates provides important information for acoustic density estimation.

Narwhal (Monodon monoceros) echolocation click rates to support cue counting passive acoustic density estimation

Estimating animal abundance is fundamental for effective management and conservation. It is increasingly done by combining passive acoustics with knowledge about rates at which animals produce cues (cue rates). Narwhals (Monodon monoceros) are elusive marine mammals for which passive acoustic density estimation might be plausible, but for which cue rates are lacking. Clicking rates in narwhals were investigated using a dataset from sound and movement tag records collected in August 2013-2016 and 2019 in East Greenland. Clicking rates were quantified for ∼1200 one-second-long systematic random samples from 8 different whales. Generalized additive models were used to model (1) the probability of being in a clicking state versus depth and (2) the clicking rate while in a clicking state, versus time and depth. The probability of being in a clicking state increased with depth, reaching ∼1.0 at ∼500 m, while the number of clicks per second (while in a clicking state) increased with depth. The mean cue production rate, weighted by tag duration, was 1.28 clicks per second (se = 0.13, CV = 0.10). This first cue rate for narwhals may be used for cue counting density estimation, but care should be taken if applying it to other geographical areas or seasons, given sample size, geographical, and temporal limitations.

Implications of porpoise echolocation and dive behaviour on passive acoustic monitoring

Harbour porpoises are visually inconspicuous but highly soniferous echolocating marine predators that are regularly studied using passive acoustic monitoring (PAM). PAM can provide quality data on animal abundance, human impact, habitat use, and behaviour. The probability of detecting porpoise clicks within a given area (P̂) is a key metric when interpreting PAM data. Estimates of P̂ can be used to determine the number of clicks per porpoise encounter that may have been missed on a PAM device, which, in turn, allows for the calculation of abundance and ideally non-biased comparison of acoustic data between habitats and time periods. However, P̂ is influenced by several factors, including the behaviour of the vocalising animal. Here, the common implicit assumption that changes in animal behaviour have a negligible effect on P̂ between different monitoring stations or across time is tested. Using a simulation-based approach informed by acoustic biologging data from 22 tagged harbour porpoises, it is demonstrated that porpoise behavioural states can have significant (up to 3× difference) effects on P̂. Consequently, the behavioural state of the animals must be considered in analysis of animal abundance to avoid substantial over- or underestimation of the true abundance, habitat use, or effects of human disturbance.

A sperm whale cautionary tale about estimating acoustic cue rates for deep divers

Passive acoustic density estimation has been gaining traction in recent years. Cue counting uses detected acoustic cues to estimate animal abundance. A cue rate, the number of acoustic cues produced per animal per unit time, is required to convert cue density into animal density. Cue rate information can be obtained from animal borne acoustic tags. For deep divers, like beaked whales, data have been analyzed considering deep dive cycles as a natural sampling unit, based on either weighted averages or generalized estimating equations. Using a sperm whale DTAG (sound-and-orientation recording tag) example we compare different approaches of estimating cue rate from acoustic tags illustrating that both approaches used before might introduce biases and suggest that the natural unit of analysis should be the whole duration of the tag itself.

Comparison of visual and passive acoustic estimates of beaked whale density off El Hierro, Canary Islands

Passive acoustic monitoring (PAM) offers considerable potential for density estimation of cryptic cetaceans, such as beaked whales. However, comparative studies on the accuracy of PAM density estimates from these species are lacking. Concurrent, low-cost drifting PAM, with SoundTraps suspended at 200 m depth, and land-based sightings, were conducted off the Canary Islands. Beaked whale density was estimated using a cue-count method, with click production rate and the probability of click detection derived from digital acoustic recording tags (DTags), and distance sampling techniques, adapted to fixed-point visual surveys. Of 32 870 detections obtained throughout 206 h of PAM recordings, 68% were classified as "certain" beaked whale clicks. Acoustic detection probability was 0.15 [coefficient variation (CV) 0.24] and click production rate was 0.46 clicks s - 1 (CV 0.05). PAM density estimates were in the range of 21.5 or 48.6 whales per 1000 km2 [CV 0.50 or 0.44, 95% confidence interval (CI) 20.7-22.4 or 47-50.9), depending on whether "uncertain" clicks were considered. Density estimates from concurrent sightings resulted in 33.7 whales per 1000 km2 (CV 0.77, 95% CI 8.9-50.5). Cue-count PAM methods under application provide reliable estimates of beaked whale density, over relatively long time periods and in realistic scenarios, as these match the concurrent density estimates obtained from visual observations.

Deep ocean drivers better explain habitat preferences of sperm whales Physeter macrocephalus than beaked whales in the Bay of Biscay

Species Distribution Models are commonly used with surface dynamic environmental variables as proxies for prey distribution to characterise marine top predator habitats. For oceanic species that spend lot of time at depth, surface variables might not be relevant to predict deep-dwelling prey distributions. We hypothesised that descriptors of deep-water layers would better predict the deep-diving cetacean distributions than surface variables. We combined static variables and dynamic variables integrated over different depth classes of the water column into Generalised Additive Models to predict the distribution of sperm whales Physeter macrocephalus and beaked whales Ziphiidae in the Bay of Biscay, eastern North Atlantic. We identified which variables best predicted their distribution. Although the highest densities of both taxa were predicted near the continental slope and canyons, the most important variables for beaked whales appeared to be static variables and surface to subsurface dynamic variables, while for sperm whales only surface and deep-water variables were selected. This could suggest differences in foraging strategies and in the prey targeted between the two taxa. Increasing the use of variables describing the deep-water layers would provide a better understanding of the oceanic species distribution and better assist in the planning of human activities in these habitats.

Recommended snapshot length for acoustic point-transect surveys of intermittently available Cuvier's beaked whales

Acoustic point-transect distance-sampling surveys have recently been used to estimate the density of beaked whales. Typically, the fraction of short time "snapshots" with detected beaked whales is used in this calculation. Beaked whale echolocation pulses are only intermittently available, which may affect the best choice of snapshot length. The effect of snapshot length on density estimation for Cuvier's beaked whale (Ziphius cavirostris) is investigated by sub-setting continuous recordings from drifting hydrophones deployed off southern and central California. Snapshot lengths from 20 s to 20 min are superimposed on the time series of detected beaked whale echolocation pulses, and the components of the density estimation equation are estimated for each snapshot length. The fraction of snapshots with detections, the effective area surveyed, and the snapshot detection probability all increase with snapshot length. Due to compensatory changes in these three components, density estimates show very little dependence on snapshot length. Within the range we examined, 1-2 min snapshots are recommended to avoid the potential bias caused by animal movement during the snapshot period and to maximize the sample size for estimating the effective area surveyed.

Estimating acoustic cue rates in bowhead whales, Balaena mysticetus, during their fall migration through the Alaskan Beaufort Sea

Eight years of passive acoustic data (2007-2014) from the Beaufort Sea were used to estimate the mean cue rate (calling rate) of individual bowhead whales (Balaena mysticetus) during their fall migration along the North Slope of Alaska. Calls detected on directional acoustic recorders (DASARs) were triangulated to provide estimates of locations at times of call production, which were then translated into call densities (calls/h/km²). Various assumptions were used to convert call density into animal cue rates, including the time for whales to cross the arrays of acoustic recorders, the population size, the fraction of the migration corridor missed by the localizing array system, and the fraction of the seasonal migration missed because recorders were retrieved before the end of the migration. Taking these uncertainties into account in various combinations yielded up to 351 cue rate estimates, which summarize to a median of 1.3 calls/whale/h and an interquartile range of 0.5-5.4 calls/whale/h.

Decadal Assessment of Sperm Whale Site-Specific Abundance Trends in the Northern Gulf of Mexico Using Passive Acoustic Data

Passive acoustic monitoring has been successfully used to study deep-diving marine mammal populations. To assess regional population trends of sperm whales in the northern Gulf of Mexico (GoM), including impacts of the Deepwater Horizon platform oil spill in 2010, the Littoral Acoustic Demonstration Center-Gulf Ecological Monitoring and Modeling (LADC-GEMM) consortium collected broadband acoustic data in the Mississippi Valley/Canyon area between 2007 and 2017 using bottom-anchored moorings. These data allow the inference of short-term and long-term variations in site-specific abundances of sperm whales derived from their acoustic activity. A comparison is made between the abundances of sperm whales at specific sites in different years before and after the oil spill by estimating the regional abundance density. The results show that sperm whales were present in the region throughout the entire monitoring period. A habitat preference shift was observed for sperm whales after the 2010 oil spill with higher activities at sites farther away from the spill site. A comparison of the 2007 and 2015 results shows that the overall regional abundance of sperm whales did not recover to pre-spill levels. The results indicate that long-term spatially distributed acoustic monitoring is critical in characterizing sperm whale population changes and in understanding how environmental stressors impact regional abundances and the habitat use of sperm whales.

Deep-diving beaked whales dive together but forage apart

Echolocating animals that forage in social groups can potentially benefit from eavesdropping on other group members, cooperative foraging or social defence, but may also face problems of acoustic interference and intra-group competition for prey. Here, we investigate these potential trade-offs of sociality for extreme deep-diving Blainville's and Cuvier's beaked whales. These species perform highly synchronous group dives as a presumed predator-avoidance behaviour, but the benefits and costs of this on foraging have not been investigated. We show that group members could hear their companions for a median of at least 91% of the vocal foraging phase of their dives. This enables whales to coordinate their mean travel direction despite differing individual headings as they pursue prey on a minute-by-minute basis. While beaked whales coordinate their echolocation-based foraging periods tightly, individual click and buzz rates are both independent of the number of whales in the group. Thus, their foraging performance is not affected by intra-group competition or interference from group members, and they do not seem to capitalize directly on eavesdropping on the echoes produced by the echolocation clicks of their companions. We conclude that the close diving and vocal synchronization of beaked whale groups that quantitatively reduces predation risk has little impact on foraging performance.

Acoustic detection range and population density of Cuvier's beaked whales estimated from near-surface hydrophones

The population density of Cuvier's beaked whales is estimated acoustically with drifting near-surface hydrophone recorders in the Catalina Basin. Three empirical approaches (trial-based, distance-sampling, and spatially explicit capture-recapture) are used to estimate the probability of detecting the echolocation pulses as a function of range. These detection functions are used with two point-transect methods (snapshot and dive-cue) to estimate density. Measurement errors result in a small range of density estimates (3.9-5.4 whales per 1000 km²). Use of multiple approaches and methods allows comparison of the required information and assumptions of each. The distance-sampling approach with snapshot-based density estimates has the most stringent assumptions but would be the easiest to implement for large scale surveys of beaked whale density. Alternative approaches to estimating detection functions help validate this approach. The dive cue method of density estimation has promise, but additional work is needed to understand the potential bias caused by animal movement during a dive. Empirical methods are a viable alternative to the theoretical acoustic modeling approaches that have been used previously to estimate beaked whale density.

A review of unmanned vehicles for the detection and monitoring of marine fauna

Recent technology developments have turned present-day unmanned systems into realistic alternatives to traditional marine animal survey methods. Benefits include longer survey durations, improved mission safety, mission repeatability, and reduced operational costs. We review the present status of unmanned vehicles suitable for marine animal monitoring conducted in relation to industrial offshore activities, highlighting which systems are suitable for three main monitoring types: population, mitigation, and focal animal monitoring. We describe the technical requirements for each of these monitoring types and discuss the operational aspects. The selection of a specific sensor/platform combination depends critically on the target species and its behaviour. The technical specifications of unmanned platforms and sensors also need to be selected based on the surrounding conditions of a particular offshore project, such as the area of interest, the survey requirements and operational constraints.

Diving behaviour of Cuvier's beaked whales (Ziphius cavirostris) off Cape Hatteras, North Carolina

Cuvier's beaked whales exhibit exceptionally long and deep foraging dives. The species is little studied due to their deep-water, offshore distribution and limited time spent at the surface. We used LIMPET satellite tags to study the diving behaviour of Cuvier's beaked whales off Cape Hatteras, North Carolina from 2014 to 2016. We deployed 11 tags, recording 3242 h of behaviour data, encompassing 5926 dives. Dive types were highly bimodal; deep dives (greater than 800 m, n = 1408) had a median depth of 1456 m and median duration of 58.9 min; shallow dives (50-800 m, n = 4518) were to median depths of 280 m with a median duration of 18.7 min. Most surface intervals were very short (median 2.2 min), but all animals occasionally performed extended surface intervals. We found no diel differences in dive depth or the percentage of time spent deep diving, but whales spent significantly more time near the surface at night. Other populations of this species exhibit similar dive patterns, but with regional differences in depth, duration and inter-dive intervals. Satellite-linked tags allow for the collection of long periods of dive records, including the occurrence of anomalous behaviours, bringing new insights into the lives of these deep divers.

Diving behavior of Cuvier's beaked whales inferred from three-dimensional acoustic localization and tracking using a nested array of drifting hydrophone recorders

Echolocation pulses from Cuvier's beaked whales are used to track the whales' three-dimensional diving behavior in the Catalina Basin, California. In 2016, five 2-element vertical hydrophone arrays were suspended from the surface and drifted at ∼100-m depth. Cuvier's beaked whale pulses were identified, and vertical detection angles were estimated from time-differences-of-arrival of either direct-path signals received on two hydrophones or direct-path and surface-reflected signals received on the same hydrophone. A Bayesian state-space model is developed to track the diving behavior. The model is fit to these detection angle estimates from at least four of the drifting vertical arrays. Results show that the beaked whales were producing echolocation pulses and are presumed to be foraging at a mean depth of 967 m (standard deviation = 112 m), approximately 300 m above the bottom in this basin. Some whales spent at least some time at or near the bottom. Average swim speed was 1.2 m s^-1, but swim direction varied during a dive. The average net horizontal speed was 0.6 m s^-1. Results are similar to those obtained from previous tagging studies of this species. These methods may allow expansion of dive studies to other whale species that are difficult to tag.

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.

Automated classification of dolphin echolocation click types from the Gulf of Mexico

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso’s dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori.

Health of marine mammal populations is often considered an indicator of overall marine ecosystem health and resilience, particularly in highly-impacted regions such as the Gulf of Mexico. Marine mammal populations are difficult to monitor given the many challenges of observing animals at sea (e.g. weather, limited daylight, ocean conditions, and expense). An increasingly common approach is the use of underwater acoustic sensors capable of recording marine mammal calls at remote locations for months at a time. Acoustic sensors generate large datasets in which dolphin echolocation clicks are commonly present. Dolphins are the most diverse family of marine mammals, and distinguishing click characteristics have only been described for a small subset of species. We developed a workflow to automatically identify distinct dolphin click types within large datasets without prior knowledge of their distinguishing features. Our algorithm then recognizes these click types in novel recording data across a range of monitoring locations. Known species-specific click types emerge from the data using this approach, as well as new click types potentially associated with additional species. This technique is a key step toward determining species identification for passive acoustic monitoring of offshore populations of dolphins and other toothed whales under a big data paradigm.