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.

Correlated evolution between body size and echolocation in bats (order Chiroptera).

BACKGROUND: Body size and echolocation call frequencies are related in bats. However, it is unclear if this allometry applies to the entire clade. Differences have been suggested between nasal and oral emitting bats, as well as between some taxonomic families. Additionally, the scaling of other echolocation parameters, such as bandwidth and call duration, needs further testing. Moreover, it would be also interesting to test whether changes in body size have been coupled with changes in these echolocation parameters throughout bat evolution. Here, we test the scaling of peak frequency, bandwidth, and call duration with body mass using phylogenetically informed analyses for 314 bat species. We specifically tested whether all these scaling patterns differ between nasal and oral emitting bats. Then, we applied recently developed Bayesian statistical techniques based on large-scale simulations to test for the existence of correlated evolution between body mass and echolocation. RESULTS: Our results showed that echolocation peak frequencies, bandwidth, and duration follow significant allometric patterns in both nasal and oral emitting bats. Changes in these traits seem to have been coupled across the laryngeal echolocation bats diversification. Scaling and correlated evolution analyses revealed that body mass is more related to peak frequency and call duration than to bandwidth. We exposed two non-exclusive kinds of mechanisms to explain the link between size and each of the echolocation parameters. CONCLUSIONS: The incorporation of Bayesian statistics based on large-scale simulations could be helpful for answering macroevolutionary patterns related to the coevolution of traits in bats and other taxonomic groups.

Accurate species classification of Arctic toothed whale echolocation clicks using one-third octave ratios.

Passive acoustic monitoring has been an effective tool to study cetaceans in remote regions of the Arctic. Here, we advance methods to acoustically identify the only two Arctic toothed whales, the beluga (Delphinapterus leucas) and narwhal (Monodon monoceros), using echolocation clicks. Long-term acoustic recordings collected from moorings in Northwest Greenland were analyzed. Beluga and narwhal echolocation signals were distinguishable using spectrograms where beluga clicks had most energy >30 kHz and narwhal clicks had a sharp lower frequency limit near 20 kHz. Changes in one-third octave levels (TOL) between two pairs of one-third octave bands were compared from over one million click spectra. Narwhal clicks had a steep increase between the 16 and 25 kHz TOL bands that was absent in beluga click spectra. Conversely, beluga clicks had a steep increase between the 25 and 40 kHz TOL bands that was absent in narwhal click spectra. Random Forest classification models built using the 16 to 25 kHz and 25 to 40 kHz TOL ratios accurately predicted the species identity of 100% of acoustic events. Our findings support the use of echolocation TOL ratios in future automated click classifiers for acoustic monitoring of Arctic toothed whales and potentially for other odontocete species.

Echo detection thresholds in big brown bats (Eptesicus fuscus) vary with echo spectral content.

Echolocating big brown bats (Eptesicus fuscus) broadcast downward frequency-modulated sweeps covering the ultrasonic range from 100-23 kHz in two harmonics. They perceive target range from the time delay between each broadcast and its returning echo. Previous experiments indicated that the bat's discrimination acuity for broadcast-echo delay declines when the lowest frequencies (23-35 kHz) in the first harmonic of an echo are removed. This experiment examined whether echo detection is similarly impaired. Results show that detection thresholds for echoes missing these lowest frequencies are raised. Increased thresholds for echoes differing in spectra facilitates the bat's ability to discriminate against clutter.

Molecular adaptations underlying high-frequency hearing in the brain of CF bats species.

BACKGROUND: The majority of bat species have developed remarkable echolocation ability, especially for the laryngeally echolocating bats along with high-frequency hearing. Adaptive evolution has been widely detected for the cochleae in the laryngeally echolocating bats, however, limited understanding for the brain which is the central to echolocation signal processing in the auditory perception system, the laryngeally echolocating bats brain may also undergo adaptive changes. RESULT: In order to uncover the molecular adaptations related with high-frequency hearing in the brain of laryngeally echolocating bats, the genes expressed in the brain of Rhinolophus ferrumequinum (CF bat) and Myotis pilosus (FM bat) were both detected and also compared. A total of 346,891 genes were detected and the signal transduction mechanisms were annotated by the most abundant genes, followed by the transcription. In hence, there were 3,088 DEGs were found between the two bat brains, with 1,426 highly expressed in the brain of R. ferrumequinum, which were significantly enriched in the neuron and neurodevelopmental processes. Moreover, we found a key candidate hearing gene, ADCY1, playing an important role in the R. ferrumequinum brain and undergoing adaptive evolution in CF bats. CONCLUSIONS: Our study provides a new insight to the molecular bases of high-frequency hearing in two laryngeally echolocating bats brain and revealed different nervous system activities during auditory perception in the brain of CF bats.

Bioinspiration from bats and new paradigms for autonomy in natural environments.

Achieving autonomous operation in complex natural environment remains an unsolved challenge. Conventional engineering approaches to this problem have focused on collecting large amounts of sensory data that are used to create detailed digital models of the environment. However, this only postpones solving the challenge of identifying the relevant sensory information and linking it to action control to the domain of the digital world model. Furthermore, it imposes high demands in terms of computing power and introduces large processing latencies that hamper autonomous real-time performance. Certain species of bats that are able to navigate and hunt their prey in dense vegetation could be a biological model system for an alternative approach to addressing the fundamental issues associated with autonomy in complex natural environments. Bats navigating in dense vegetation rely on clutter echoes, i.e. signals that consist of unresolved contributions from many scatters. Yet, the animals are able to extract the relevant information from these input signals with brains that are often less than 1 g in mass. Pilot results indicate that information relevant to location identification and passageway finding can be directly obtained from clutter echoes, opening up the possibility that the bats' skill can be replicated in man-made autonomous systems.

Effects of insect pursuit on the Doppler shift compensation in a hipposiderid bat.

Doppler shift compensation (DSC) is a unique feature observed in certain species of echolocating bats and is hypothesized to be an adaptation to detecting fluttering insects. However, current research on DSC has primarily focused on bats that are not engaged in foraging activities. In this study, we investigated the DSC performance of Pratt's roundleaf bat, Hipposideros pratti, which was trained to pursue insects in various motion states within a laboratory setting. Our study yielded three main results. First, H. pratti demonstrated highly precise DSC during insect pursuit, aligning with previous findings of other flutter-detecting foragers during orientation or landing tasks. Second, we found that the motion state of the insect prey had little effect on the DSC performance of H. pratti. Third, we observed variations in the DSC performance of H. pratti throughout the course of insect pursuit. The bats exhibited the highest DSC performance during the phase of maximum flight speed but decreased performance during the phase of insect capture. These findings of high precision overall and the time-dependent performance of DSC during insect pursuit support the hypothesis that DSC is an adaptation to detecting fluttering insects.

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.

Hector's dolphins (Cephalorhynchus hectori) produce both narrowband high-frequency and broadband acoustic signals.

Odontocetes produce clicks for echolocation and communication. Most odontocetes are thought to produce either broadband (BB) or narrowband high-frequency (NBHF) clicks. Here, we show that the click repertoire of Hector's dolphin (Cephalorhynchus hectori) comprises highly stereotypical NBHF clicks and far more variable broadband clicks, with some that are intermediate between these two categories. Both NBHF and broadband clicks were made in trains, buzzes, and burst-pulses. Most clicks within click trains were typical NBHF clicks, which had a median centroid frequency of 130.3 kHz (median -10 dB bandwidth = 29.8 kHz). Some, however, while having only marginally lower centroid frequency (median = 123.8 kHz), had significant energy below 100 kHz and approximately double the bandwidth (median -10 dB bandwidth = 69.8 kHz); we refer to these as broadband. Broadband clicks in buzzes and burst-pulses had lower median centroid frequencies (120.7 and 121.8 kHz, respectively) compared to NBHF buzzes and burst-pulses (129.5 and 130.3 kHz, respectively). Source levels of NBHF clicks, estimated by using a drone to measure ranges from a single hydrophone and by computing time-of-arrival differences at a vertical hydrophone array, ranged from 116 to 171 dB re 1 µPa at 1 m, whereas source levels of broadband clicks, obtained from array data only, ranged from 138 to 184 dB re 1 µPa at 1 m. Our findings challenge the grouping of toothed whales as either NBHF or broadband species.

Characterising underwater noise and changes in harbour porpoise behaviour during the decommissioning of an oil and gas platform.

Many man-made marine structures (MMS) will have to be decommissioned in the coming decades. While studies on the impacts of construction of MMS on marine mammals exist, no research has been done on the effects of their decommissioning. The complete removal of an oil and gas platform in Scotland in 2021 provided an opportunity to investigate the response of harbour porpoises to decommissioning. Arrays of broadband noise recorders and echolocation detectors were used to describe noise characteristics produced by decommissioning activities and assess porpoise behaviour. During decommissioning, sound pressure spectral density levels in the frequency range 100 Hz to 48 kHz were 30-40 dB higher than baseline, with vessel presence being the main source of noise. The study detected small-scale (< 2 km) and short-term porpoise displacement during decommissioning, with porpoise occurrence increasing immediately after this. These findings can inform the consenting process for future decommissioning projects.

A bat biomimetic model for scenario recognition using echo Doppler information.

The flying bat can detect the difference in Doppler frequency between its echolocation transmission signal and the echoes in its surroundings, enabling it to distinguish between various scenarios effectively. By examining the bio-sonar biomimetic model of a flying bat that uses echo Doppler information for environmental recognition, it may enhance the scene recognition capability of human ultrasound sonar during movement. The paper establishes a three-dimensional clutter model of the flying state of bat bio-sonar for bats emitting constant frequency signals. It proposes a scene recognition method that combines multi-scale time-frequency feature analysis with a convolutional neural network (CNN). The short-time Fourier transform of different scales extract the Doppler and range dimensions, which are then fused to create a multi-scale feature plane containing both Doppler and range information. Combined with CNN's powerful image classification and recognition capabilities, extract features from multi-scale feature planes of different clutter scenes to achieve environment recognition based on the differences in Doppler and range dimensions of echoes in various directions. Through computer simulations, this study provides a numerical interpretation of the environmental classification and perception capabilities of bats in flight. The algorithm significantly improves scenario classification and recognition performance according to simulation results, with accuracy exceeding 98% in varied clutter scenarios at 30 dB signal noise ratio. Based on computer simulations, an experimental scene was constructed and actual echo signals were collected and analyzed. The experiments demonstrate that utilizing Doppler information enables the classification and recognition of cluttered environments. The effectiveness of the proposed algorithm was also verified. Ultrasonic sonar systems, such as navigation robots and helicopter obstacle avoidance, can apply this biomimetic model and algorithm for environmental recognition during motion.

The effects of range and echo-phase on range resolution in bottlenose dolphins (Tursiops truncatus) performing a successive comparison taska).

Echolocating bats and dolphins use biosonar to determine target range, but differences in range discrimination thresholds have been reported for the two species. Whether these differences represent a true difference in their sensory system capability is unknown. Here, the dolphin's range discrimination threshold as a function of absolute range and echo-phase was investigated. Using phantom echoes, the dolphins were trained to echo-inspect two simulated targets and indicate the closer target by pressing a paddle. One target was presented at a time, requiring the dolphin to hold the initial range in memory as they compared it to the second target. Range was simulated by manipulating echo-delay while the received echo levels, relative to the dolphins' clicks, were held constant. Range discrimination thresholds were determined at seven different ranges from 1.75 to 20 m. In contrast to bats, range discrimination thresholds increased from 4 to 75 cm, across the entire ranges tested. To investigate the acoustic features used more directly, discrimination thresholds were determined when the echo was given a random phase shift (±180°). Results for the constant-phase versus the random-phase echo were quantitatively similar, suggesting that dolphins used the envelope of the echo waveform to determine the difference in range.

Bionic study of distance-azimuth discrimination of multi-scattered point objects in bat bio-sonar.

This paper presents a novel approach to enhance the discrimination capacity of multi-scattered point objects in bat bio-sonar. A broadband interferometer mathematical model is developed, incorporating both distance and azimuth information, to simulate the transmitted and received signals of bats. The Fourier transform is employed to simulate the preprocessing step of bat information for feature extraction. Furthermore, the bat bio-sonar model based on convolutional neural network (BS-CNN) is constructed to compensate for the limitations of conventional machine learning and CNN networks, including three strategies: Mix-up data enhancement, joint feature and hybrid atrous convolution module. The proposed BS-CNN model emulates the perceptual nerves of the bat brain for distance-azimuth discrimination and compares with four conventional classifiers to assess its discrimination efficacy. Experimental results demonstrate that the overall discrimination accuracy of the BS-CNN model is 93.4%, surpassing conventional CNN networks and machine learning methods by at least 5.9%. This improvement validates the efficacy of the BS-CNN bionic model in enhancing the discrimination accuracy in bat bio-sonar and offers valuable references for radar and sonar target classification.

A tradeoff evolution between acoustic fat bodies and skull muscles in toothed whales.

Toothed whales have developed specialized echolocation abilities that are crucial for underwater activities. Acoustic fat bodies, including the melon, extramandibular fat body, and intramandibular fat body, are vital for echolocation. This study explores the transcriptome of acoustic fat bodies in toothed whales, revealing some insight into their evolutionary origins and ecological significance. Comparative transcriptome analysis of acoustic fat bodies and related tissues in a harbor porpoise and a Pacific white-sided dolphin reveals that acoustic fat bodies possess characteristics of both muscle and adipose tissue, occupying an intermediate position. The melon and extramandibular fat body exhibit specific muscle-related functions, implying an evolutionary connection between acoustic fat bodies and muscle tissue. Furthermore, we suggested that the melon and extramandibular fat body originate from intramuscular adipose tissue, a component of white adipose tissue. The extramandibular fat body has been identified as an evolutionary homolog of the masseter muscle, supported by the specific expression of MYH16, a pivotal protein in masticatory muscles. The intramandibular fat body, located within the mandibular foramen, shows possibilities of the presence of several immune-related functions, likely due to its proximity to bone marrow. Furthermore, this study sheds light on leucine modification in the catabolic pathway, which leads to the accumulation of isovaleric acid in acoustic fat bodies. Swallowing without chewing, a major toothed whale feeding ecology adaptation, makes the masticatory muscle redundant and leads to the formation of the extramandibular fat body. We propose that the intramuscular fat enlargement in facial muscles, which influences acoustic fat body development, is potentially related to the substantial reorganization of head morphology in toothed whales during aquatic adaptation.

Musculoskeletal morphogenesis supports the convergent evolution of bat laryngeal echolocation.

The order Chiroptera (bats) is the second largest group of mammals. One of the essential adaptations that have allowed bats to dominate the night skies is laryngeal echolocation, where bats emit ultrasonic pulses and listen to the returned echo to produce high-resolution 'images' of their surroundings. There are two possible scenarios for the evolutionary origin of laryngeal echolocation in bats: (1) a single origin in a common ancestor followed by the secondary loss in Pteropodidae, or (2) two convergent origins in Rhinolophoidea and Yangochiroptera. Although data from palaeontological, anatomical, developmental and genomic studies of auditory apparatuses exist, they remain inconclusive concerning the evolutionary origin of bat laryngeal echolocation. Here we compared musculoskeletal morphogenesis of the larynx in several chiropteran lineages and found distinct laryngeal modifications in two echolocating lineages, rhinolophoids and yangochiropterans. Our findings support the second scenario that rhinolophoids and yangochiropterans convergently evolved advanced laryngeal echolocation through anatomical modifications of the larynx for ultrasonic sound generation and refinement of the auditory apparatuses for more detailed sound perception.

Melon and rostral muscle morphology of Gervais' beaked whale (Mesoplodon europaeus): Alternating patterns of bilateral asymmetry.

Toothed whales utilize specialized nasal structures such as the lipid-rich melon to produce sound and propagate it into the aquatic environment. Very little nasal morphology of mesoplodont beaked whales has been described in the literature, and the anatomy of the melon and associated musculature of Gervais' beaked whale (Mesoplodon europaeus) remains undescribed. Heads of three (n = 3) Gervais' beaked whales were examined in detail via dissection as well as computed tomography (CT) and magnetic resonance imaging (MRI). Two additional Gervais' beaked whale individuals (n = 2) were studied via archived CT and MRI scans. Representative transverse dissection sections of the melon were processed for polarized light imaging to verify the presence of tendons inserting into the melon tissue. Three-dimensional (3D) CT reconstructions of the melon, rostral muscles, and associated structures were performed to assess morphology and spatial relationships. In all individuals, the melon's main body demonstrated a bilaterally asymmetrical, curvilinear geometry. This curvilinear shape was defined by a pattern of alternating asymmetry in the medial rostral muscles that projected into the melon's tissue. In transverse polarized light imaging, a network of tendons originating from these asymmetrical rostral muscle projections was observed permeating the melon's lipid tissue. This curvilinear melon morphology and associated asymmetrical musculature suggest a means of lengthening the lipid pathway within a relatively short dimensional footprint. In addition, the species-specific arrangement of muscular projections suggests complex fine-tuning of the melon's geometry during echolocation. Further studies may lend additional insight into the function of this unusual melon morphology.

Drivers of morphological evolution in the toothed whale jaw.

Toothed whales (odontocetes) emit high-frequency underwater sounds (echolocate)-an extreme and unique innovation allowing them to sense their prey and environment. Their highly specialized mandible (lower jaw) allows high-frequency sounds to be transmitted back to the inner ear. Echolocation is evident in the earliest toothed whales, but little research has focused on the evolution of mandibular form regarding this unique adaptation. Here, we use a high-density, three-dimensional geometric morphometric analysis of 100 living and extinct cetacean species spanning their ∼50-million-year evolutionary history. Our analyses demonstrate that most shape variation is found in the relative length of the jaw and the mandibular symphysis. The greatest morphological diversity was obtained during two periods of rapid evolution: the initial evolution of archaeocetes (stem whales) in the early to mid-Eocene as they adapted to an aquatic lifestyle, representing one of the most extreme adaptive transitions known, and later on in the mid-Oligocene odontocetes as they became increasingly specialized for a range of diets facilitated by increasingly refined echolocation. Low disparity in the posterior mandible suggests the shape of the acoustic window, which receives sound, has remained conservative since the advent of directional hearing in the aquatic archaeocetes, even as the earliest odontocetes began to receive sounds from echolocation. Diet, echolocation, feeding method, and dentition type strongly influence mandible shape. Unlike in the toothed whale cranium, we found no significant asymmetry in the mandible. We suggest that a combination of refined echolocation and associated dietary specializations have driven morphology and disparity in the toothed whale mandible.

Validation of the F-POD-A fully automated cetacean monitoring system.

The F-POD, an echolocation-click logging device, is commonly used for passive acoustic monitoring of cetaceans. This paper presents the first assessment of the error-rate of fully automated analysis by this system, a description of the F-POD hardware, and a description of the KERNO-F v1.0 classifier which identifies click trains. Since 2020, twenty F-POD loggers have been used in the BlackCeTrends project by research teams from Bulgaria, Georgia, Romania, Türkiye, and Ukraine with the aim of investigating trends of relative abundance in populations of cetaceans of the Black Sea. Acoustic data from this project analysed here comprises 9 billion raw data clicks in total, of which 297 million were classified by KERNO-F as Narrow Band High Frequency (NBHF) clicks (harbour porpoise clicks) and 91 million as dolphin clicks. Such data volumes require a reliable automated system of analysis, which we describe. A total of 16,805 Detection Positive Minutes (DPM) were individually inspected and assessed by a visual check of click train characteristics in each DPM. To assess the overall error rate in each species group we investigated 2,000 DPM classified as having NBHF clicks and 2,000 DPM classified as having dolphin clicks. The fraction of NBHF DPM containing misclassified NBHF trains was less than 0.1% and for dolphins the corresponding error-rate was 0.97%. For both species groups (harbour porpoises and dolphins), these error-rates are acceptable for further study of cetaceans in the Black Sea using the automated classification without further editing of the data. The main sources of errors were 0.17% of boat sonar DPMs misclassified as harbour porpoises, and 0.14% of harbour porpoise DPMs misclassified as dolphins. The potential to estimate the rate at which these sources generate errors makes possible a new predictive approach to overall error estimation.

Flexible control of vocal timing in Carollia perspicillata bats enables escape from acoustic interference.

In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.

An Eocene insect could hear conspecific ultrasounds and bat echolocation.

Hearing has evolved independently many times in the animal kingdom and is prominent in various insects and vertebrates for conspecific communication and predator detection. Among insects, katydid (Orthoptera: Tettigoniidae) ears are unique, as they have evolved outer, middle, and inner ear components, analogous in their biophysical principles to the mammalian ear. The katydid ear consists of two paired tympana located in each foreleg. These tympana receive sound externally on the tympanum surface (usually via pinnae) or internally via an ear canal (EC). The EC functions to capture conspecific calls and low frequencies, while the pinnae passively amplify higher-frequency ultrasounds including bat echolocation. Together, these outer ear components provide enhanced hearing sensitivity across a dynamic range of over 100 kHz. However, despite a growing understanding of the biophysics and function of the katydid ear, its precise emergence and evolutionary history remains elusive. Here, using microcomputed tomography (µCT) scanning, we recovered geometries of the outer ear components and wings of an exceptionally well-preserved katydid fossilized in Baltic amber (∼44 million years [Ma]). Using numerical and theoretical modeling of the wings, we show that this species was communicating at a peak frequency of 31.62 (± 2.27) kHz, and we demonstrate that the ear was biophysically tuned to this signal and to providing hearing at higher-frequency ultrasounds (>80 kHz), likely for enhanced predator detection. The results indicate that the evolution of the unique ear of the katydid, with its broadband ultrasonic sensitivity and analogous biophysical properties to the ears of mammals, emerged in the Eocene.