The Journal of the Acoustical Society of America

In a loudness-matching paradigm, a reduction in the loudness of sounds with bandwidths less than one-half octave compared to a tone of equal sound pressure level has been observed previously for five-tone complexes at 60 dB SPL centered at 1 kHz. Here, this loudness-reduction phenomenon is explored using band-limited noise across wide ranges of frequency and level. Additionally, these measurements are simulated by a model of loudness judgement based on neural ensemble averaging (NEA), which serves as a proxy for central auditory signal processing. Multi-frequency equal-loudness contours (ELC) were measured for each of the adult participants (N=100) with pure-tone average (PTA) thresholds that ranged from normal to moderate hearing loss using a categorical-loudness-scaling (CLS) paradigm. Presentation level and center frequency of the test stimuli were determined on each trial according to a Bayesian adaptive algorithm, which enabled multi-frequency ELC estimation within about five minutes of testing. Three separate test conditions differed by stimulus type: (1) pure-tone, (2) quarter-octave noise and (3) octave noise. For comparison, loudness judgements for all three stimulus types were also simulated by the NEA model, which comprised a nonlinear, active, time-domain cochlear model with an appended stage of neural spike generation. Mid-bandwidth loudness reduction was observed to be greatest at moderate stimulus levels and frequencies near 1 kHz. This feature was approximated by the NEA model, which suggests involvement of an early stage of the central auditory system in the formation of loudness judgements.

Cochlear implant (CI) users typically experience difficulties perceiving musical harmony due to a restricted spectro-temporal resolution at the electrode-nerve interface, resulting in limited pitch perception. We investigated how stimulus parameters affect discrimination of complex-tone triads (three-voice chords), aiming to identify conditions that maximize perceptual sensitivity. Six post-lingually deafened CI listeners completed a same/different task with harmonic complex tones, while spectral complexity, voice(s) containing a pitch change, and temporal synchrony (simultaneous vs. sequential triad presentation) were manipulated. CI listeners discriminated harmonically relevant one-semitone pitch changes within triads when spectral complexity was reduced to three or five components per voice, with significantly better performance for three-component compared to nine-component tones. Sensitivity was observed for pitch changes in the high voice or in both high and low voices, but not for changes in only the low voice. Single-voice sensitivity predicted simultaneous-triad sensitivity when controlling for spectral complexity and voice with pitch change. Contrary to expectations, sequential triad presentation did not improve discrimination. An analysis of processor pulse patterns suggests that difference-frequency cues encoded in the temporal envelope rather than place-of-excitation cues underlie perceptual triad sensitivity. These findings support reducing spectral complexity to enhance chord discrimination for CI users based on temporal cues.

Listeners face many challenges when trying to maintain attention to a target source in everyday settings; for instance, reverberation distorts acoustic cues and interruptions capture attention. However, little is known about how these challenges affect the ability to maintain selective attention. Here, we measured syllable recall accuracy and pupil dilation during a spatial selective attention task that was sometimes disrupted. Participants heard two competing, temporally interleaved syllable streams presented in pseudo-anechoic or reverberant environments. On randomly selected trials, a sudden interruption occurred mid-sequence. Compared to anechoic trials, reverberant performance was worse overall, and the interrupter disrupted performance. In uninterrupted trials, reverberation reduced peak pupil dilation both when it was consistent across all stimuli in a block and when it was randomized trial to trial, suggesting temporal smearing reduced clarity of the scene and the salience of events in the ongoing streams. Pupil dilations in response to interruptions indicated perceptual salience was strong across reverberant and anechoic conditions. Specifically, baseline pupil size before trials did not vary across room conditions, and mixing or blocking of trials (altering stimulus expectations) had no impact on pupillary responses. Together, these findings highlight that stimulus salience drives cognitive load more strongly than does task performance.

Information about eye movements is necessary for linking auditory and visual information across space. Recent work has suggested that such signals are incorporated into processing at the level of the ear itself (Gruters, Murphy et al. 2018). Here we report confirmation that the eye movement signals that reach the ear can produce perceptual consequences, via a case report of an unusual participant with tensor tympani myoclonus who hears sounds when she moves her eyes. The sounds she hears could be recorded with a microphone in the ear in which she hears them (left), and occurred for large leftward eye movements to extreme orbital positions of the eyes. The sounds elicited by this participants eye movements were reminiscent of eye movement-related eardrum oscillations (EMREOs, (Gruters, Murphy et al. 2018, Brohl and Kayser 2023, King, Lovich et al. 2023, Lovich, King et al. 2023, Lovich, King et al. 2023, Abbasi, King et al. 2025, Sotero Silva, Kayser et al. 2025, King and Groh 2026, Leon, Ramos et al. 2026, Sotero Silva, Brohl et al. 2026)), but were larger and longer lasting than classical EMREOs, helping to explain why they were audible to her. Overall, the observations from this patient help establish that (a) eye movement-related signals specifically reach the tensor tympani muscle and that (b) when there is an abnormality involving that muscle, such signals can lead to actual audible percepts. Given that the tensor tympani contributes to the regulation of sound transmission in the middle ear, these findings support that eye movement signals reaching the ear have functional consequences for auditory perception. The findings also expand the types of medical conditions that produce gaze-evoked tinnitus, to date most commonly observed in connection with acoustic neuromas.

Computational bioacoustics has seen significant advances in recent decades. However, the rate of insights from automated analysis of bioacoustic audio lags behind our rate of collecting the data - due to key capacity constraints in data annotation and bioacoustic algorithm development. Gaps in analysis methodology persist: not because they are intractable, but because of resource limitations in the bioacoustics community. To bridge these gaps, we advocate the open science method of data challenges, structured as public contests. We conducted a bioacoustics data challenge named BioDCASE, within the format of an existing event (DCASE). In this work we report on the procedures needed to select and then conduct useful bioacoustics data challenges. We consider aspects of task design such as dataset curation, annotation, and evaluation metrics. We report the three tasks included in BioDCASE 2025 and the resulting progress made. Based on this we make recommendations for open community initiatives in computational bioacoustics.

Conductive hearing loss (CHL) with a normal otoscopic exam can be difficult to diagnose because routine clinical measures such as audiometric air-bone gaps (ABGs) can identify a conductive component but often cannot distinguish among specific underlying mechanical pathologies (e.g., stapes fixation versus superior canal dehiscence, which may produce similar audiograms). Wideband tympanometry (WBT) is a fast, noninvasive test that can provide additional mechanical information across a broad range of frequencies (200 Hz to 8 kHz). However, WBT metrics are influenced by variations in ear canal geometry and probe placement and can be challenging to interpret clinically. In this study, we extend prior WBT absorbance-based classification work by estimating the middle ear input impedance at the tympanic membrane (ZME), a WBT-derived metric intended to reduce ear canal effects. To estimate ZME, we fit an analog circuit model of the ear canal, middle ear, and inner ear to raw WBT data collected at tympanometric peak pressure (TPP). Data from 27 normal ears, 32 ears with superior canal dehiscence, and 38 ears with stapes fixation were analyzed. A multinomial logistic regression classifier was trained using principal component analysis (retaining 90% variance) and stratified 5-fold cross-validation with regularization. We compared feature sets based on ABGs alone, ABGs combined with absorbance, and ABGs combined with the magnitude of ZME. The combination of ABGs and the magnitude of ZME produced the best performance, achieving an overall accuracy of 85.6% compared to 80.4% for ABGs alone and 78.4% for ABGs combined with absorbance. These results suggest that incorporating model-derived middle ear impedance features with standard audiometric measures (ABGs) can improve automated pathology classification for stapes fixation and superior canal dehiscence.

In mammals, loud, high-pitched, and harsh-sounding calls typically accompany heightened emotional arousal, particularly during distress such as separation. However, whether subtle arousal reductions can be detected through acoustic analysis within a single negative context remains unclear. We investigated whether source-related acoustic parameters of puppy whines reflect arousal modulations induced by calming interventions during maternal separation. Thirty-five eight-week-old Beagle puppies were recorded under four conditions combining synthetic appeasing pheromone and a pressure harness. Vocal behavior, activity, whine duration, and intensity, did not significantly differ across treatments, suggesting interventions did not suppress separation-related vocal responses. Nevertheless, calming products selectively altered acoustic parameters known to index arousal in dog vocalizations. Puppies receiving combined treatments produced whines with lower fundamental frequency (fo) and reduced fo variability, while pheromone exposure increased call tonality, reflected by reduced jitter and shimmer and elevated harmonics-to-noise ratios. Spectral entropy remained unchanged, possibly because the proportion of whines containing nonlinear phenomena did not vary across conditions. Reductions in fo, fo variability, and acoustic roughness are consistent with established correlates of lower arousal in mammals, suggesting source-related vocal parameters sensitively capture subtle arousal shifts even when overt vocal behavior remains stable, supporting their use as bioacoustic indicators for evaluating welfare interventions.

Eye movement-related eardrum oscillations (EMREOs) appear to consist of a pulse of oscillation occurring in conjunction with saccades. However, this apparent pulse could occur either because there is an increase in energy at that frequency at the time of saccades (a true pulse), or because there is saccade-related phase resetting of ongoing energy at that frequency band, thus appearing like a pulse when averaged in the time domain across many trials. Here we conducted a spectral analysis at the individual trial level in humans performing a visually guided saccade task to determine whether the power at the EMREO frequency (30-45 Hz) is higher during saccades than during steady fixation. We found both an increase in sound power in the EMREO frequency band associated with saccades, i.e. sound pulses at the individual trial level, as well as, phase resetting at saccade onset/offset. While both factors contribute to the apparently pulse-like EMREO signal, phase resetting appears to be more prevalent across participants. The prevalence of phase resetting has implications for the underlying mechanism(s) producing EMREOs as well as functional consequences for how the ear might respond to incoming sound in an eye-position dependent fashion.

Functional near infrared spectroscopy (fNIRS) is increasingly used in hearing and communication research, with advantages such as robustness to movement artifacts, improved spatial resolution, and flexibility of contexts in which it can be applied. At the same time, the field is progressively moving towards more continuous, naturalistic listening paradigms resulting in the widespread adoption of speech tracking analyses such as temporal response functions (TRFs) in electroencephalography (EEG) and magnetoencephalography (MEG) studies. However, it remains unclear whether these analyses can be applied to slower haemodynamic signals measured by fNIRS. In the present study, we investigated whether a TRF framework can similarly be applied to fNIRS data recorded during continuous speech perception. Eight participants listened to speech simultaneously while fNIRS signals were acquired in a hyperscanning setup. Speech features were regressed onto the haemodynamic responses to test the feasibility and interpretability of fNIRS-based TRFs. Prediction correlations between observed and modelled fNIRS signals across speech features were higher than those typically reported for EEG- and comparable to those reported for MEG-TRF studies. Moreover, these correlations did not overlap with a null distribution generated from triallJmismatched fNIRS data, confirming statistical significance and were slightly greater than those obtained from a conventional GLM approach. Our findings support that TRF estimation method can yield meaningful and statistically significant responses from fNIRS data. HighlightsO_LITRF modelling can be meaningfully applied to fNIRS data acquired during speech listening tasks. C_LIO_LIPrediction correlations between actual and modelled fNIRS signals were above chance level, with values comparable to previous EEG/MEG studies. C_LIO_LITRFs explained more fNIRS variance than a conventional GLM approach. C_LI

The rat vestibular system plays a critical role in anti-gravity responses such as the tail-lift reflex and the air-righting reflex. In a previous study in male rats, we obtained evidence that these two reflexes depend on the function of non-identical populations of vestibular sensory hair cells (HC). Here, we caused graded lesions in the vestibular system of female rats by exposing the animals to several different doses of an ototoxic chemical, 3,3-iminodipropionitrile (IDPN). After exposure, we assessed the anti-gravity responses of the rats and then assessed the loss of type I HC (HCI) and type II HC (HCII) in the central and peripheral regions of the crista, utricle and saccule. As expected, we recorded a dose-dependent loss of vestibular function and loss of HCs. The relationship between hair cell loss and functional loss was examined using non-linear models fitted by orthogonal distance regression. The results indicated that both the tail-lift reflex and the air-righting reflexes mostly depend on HCI function. However, a different dependency was found on the epithelium triggering the reflex: while the tail-lift response is sensitive to loss of crista and/or utricle HCIs, the air-righting response rather depends on utricular and/or saccular integrity.

Objectives: Patients with Cystic fibrosis (CF) often receive aminoglycosides (AGs) to manage recurrent pulmonary infections, placing them at risk for ototoxicity. Chronic AG use can lead to complex cochlear damage affecting inner and outer hair cells, the stria vascularis, and spiral ganglion neurons. The greatest damage is typically in the basal cochlear region, which encodes high-frequency hearing, with additional involvement of more apical regions. While extended-high-frequency (EHF) hearing loss (EHFHL; 9-16 kHz) is often the earliest sign of AG ototoxicity, speech in noise (SiN) effects are rarely studied. Our overall hypothesis is that SiN perception difficulties in individuals with CF, treated with AGs, are related to combined cochlear and neural damage, primarily in the EHF range but also in the standard frequency (SF; 0.25-8 kHz) range. Three mechanisms that contribute to SiN perception were evaluated in children and young adults: 1) a primary effect of reduced EHF sensitivity, measured by pure-tone audiometry (PTA) and transient-evoked otoacoustic emissions (TEOAEs); 2) a secondary effect of subclinical damage in the SF range, measured by PTA and TEOAEs; and 3) additional neural effects, measured by middle ear muscle reflex (MEMR) threshold (afferent) and growth functions (efferent).Design:A total of 185 participants were enrolled; 101 individuals with CF treated with intravenous AGs and 84 age and sex-matched Controls without hearing concerns or CF. Assessments included EHF and SF PTA; the Bamford-Kowal-Bench (BKB)-SIN test for SiN perception; double-evoked TEOAEs with chirp stimuli from 0.71 to 14.7 kHz; and ipsilateral and contralateral wideband MEMR thresholds and growth functions using broadband stimuli. Results: Reduced sensitivity at EHFs (PTA, TEOAEs) was not associated with impaired SiN perception in the CF group. SF hearing, regardless of EHF status, was the primary predictor of SiN performance in the CF group. Increased MEMR growth was also significantly associated with poorer SiN in the CF group. Conclusions: In CF, impaired SiN perception was primarily predicted by SF hearing impairment, with additional involvement of the efferent auditory pathway through increased MEMR growth. These results build on prior evidence for efferent neural effects due to ototoxic exposures, supporting both sensory (afferent) and neural (efferent) mechanisms that contribute to listening difficulties in CF. Thus, preventive and intervention strategies should consider these combined mechanisms in people with AG ototoxicity to address their SiN problems.

BackgroundIn hibernating mammals, the timing of den entry and exit reflects complex interactions among environment, physiology, and energetic constraints, with consequences for fitness. Consequently, shifts in denning phenology can affect population dynamics, particularly under climate change. Reliable estimation of denning timing is therefore critical, yet current methods often rely on GPS-derived movement data, limited by coarse sampling intervals, detection issues, and the inability to distinguish true inactivity from active presence at the den site. In this study, we developed and apply a method to estimate denning phenology in a brown bear population in south-central Sweden using accelerometer-derived activity data. Our approach employs adaptive, individual-specific thresholds to account for variation in baseline activity across bears, focusing on day-to-day changes to identify the start and end of inactivity periods. This method allows flexible and reproducible detection of den entry and exit dates, overcoming limitations associated with fixed thresholds and small sample sizes. ResultsWe compared activity-based estimates with GPS-derived den occupancy and examined variation in denning behavior across demographic groups. Analyzing 388 bear-winters, the method successfully identified inactivity periods in 360 cases. The method failed to identify clear start and end dates of hibernation for 28 (7%) bear-winters, which were characterized by unusually high or low daily activity levels at the boundaries of the inactivity period. Den site occupancy ranged from September 5 to June 2, with durations of 112-260 days, whereas inactivity periods detected from activity data extended from September 6 to May 13, lasting 83-217 days. Our comparison of activity-based and GPS-based methods indicates that bears may arrive at the den site several weeks before the onset of inactivity, with timing varying among demographic groups. ConclusionWe show that activity-based analysis provides a robust framework for estimating denning phenology, distinguishing actual inactivity from site presence, and improving understanding of the timing and variability of bear denning behavior. Applying an individual-level activity-based method improves accuracy in assessing ecological mechanisms underlying hibernation in bears and other hibernators, while also enhancing interpretation of environmental drivers and providing a reliable tool to monitor phenological shifts in response to climate change.

Many animals communicate using sequences of signals, but identifying recurrent, non-random signal combinations remains methodologically challenging. Collocation analyses are increasingly popular approaches for detecting which signals animals combine at rates greater than expected by chance. However, existing methods for animal collocation analysis face several limitations that reduce their statistical rigour: they lack uncertainty estimates, fail to control for non-independence in sampled data, and do not account for inflated family-wise error rates when identifying attraction among many different signal types. These limitations restrict the broader applicability of animal collocation analysis, including preventing robust comparisons of signal combination strength between cohorts (e.g. populations, sexes or age classes). We adapt a novel form of Multiple Distinctive Collocation Analysis using Pearson residuals (MDCA-Pr) that addresses these statistical limitations, and validate its use in animal communication research in three ways: first, using numerous simulated datasets of different sizes and levels of signal recombination; second, using simulated data to evaluate the performance of MDCA-Pr in intercohort comparisons, and third, by demonstrating how MDCA-Pr can be applied to compare the vocal sequences produced by male and female captive-living common marmosets (Callithrix jacchus). MDCA-Pr shows high sensitivity, including at small sample sizes, and generally low false-positive rates, which we further reduce by applying additional criteria for identifying attraction between signals. During intercohort comparisons, MDCA-Pr is conservative, with low false-positive rates, and statistical power increases with sample size. MDCA-Pr is a robust method for evaluating signal attraction in animal communication and enables accurate intercohort comparison of animal signal combinations. Significance StatementBy assessing the performance of MDCA-Pr on simulated animal-like data, we demonstrate that this method reliably detects signal combinations within and across animal cohorts, while overcoming statistical limitations of previous collocation analyses. We present an analytical pipeline for applying MDCA-Pr to animal signal data, including for intercohort comparisons, enabling identification and comparison of combinatorial strategies across entire signal repertoires. We illustrate this approach by comparing call combination strategies of male and female common marmosets when presented with food under experimental conditions, finding similar combinatorial strategies between sexes. MDCA-Pr therefore permits rigorous characterization of animal signal combinatoriality and opens avenues for investigating how demographic, social, and group-level factors influence combinatorial patterns.

Coral restoration is recognised as a critical tool to mitigate pantropical degradation of reef ecosystems. Robust monitoring of restoration progress is crucial for projects to evaluate their success, improve practice, and share knowledge. However, traditional visual surveys often fail to capture the full impact of coral restoration on reef function. Therefore, we employed Passive Acoustic Monitoring (PAM) to assess whether the soundscape of a coral restoration site in the Seychelles differs from adjacent healthy and degraded reference reefs. We applied two methods of soundscape analysis: manual detection of unidentified fish sounds; and machine learning-based Uniform Manifold Approximation and Projection analysis. Results were approach-specific: the manual approach highlighted similarities in fish calls between the restoration site and the healthy reference reef, while the machine learning approach extracted broader soundscape patterns, clustering the restoration site alongside the degraded reference reef. Although this is a single-site study, these findings suggest that a) coral restoration alters reef soundscapes, though recovery time may be taxon-specific, and b) multiple metrics are needed to bridge single-taxon and broad soundscape scales. This study contributes to the evolving field of soundscape ecology in coral reef ecosystems, highlighting the utility of PAM in monitoring changes to reef function through coral restoration.

Passive acoustic monitoring (PAM) is increasingly applied in biodiversity research, yet its reliability as a proxy for biodiversity remains insufficiently evaluated. In particular, the spatiotemporal autocorrelation inherent in acoustic indices of PAM is rarely quantified, despite its importance for the standardized application of acoustic monitoring. We conducted an integrated study to investigate these issues using a complete grid-based monitoring system covering the entire region (100 grids of 1 km x 1 km) in southern subtropical climatic zones. Acoustic data from 58 valid sites were combined with camera-trapping and vegetation surveys to evaluate six commonly used acoustic indices in PAM. We found that these indices were more strongly associated with relative abundance and community diversity metrics of bird and mammal than with species richness. Spatially, autocorrelation ranges of some acoustic indices extended to approximately 4 km (i.e., the Bioacoustic Index (BIO) and Normalized difference soundscape index (NDSI)). Temporally, all indices exhibited significant autocorrelation over 2-5 days, exceeding the typical short-term turnover of bird and mammal activity (1-2 days). Our results indicate that acoustic indices are not direct proxies for species richness but provide complementary information on soundscape dynamics. By explicitly quantifying spatiotemporal autocorrelation, this study offers practical guidance for sampling design and statistical analysis in passive acoustic monitoring, supporting more reliable and efficient biodiversity assessment.

Predicting the time point when an event will occur is fundamental for adaptive behavior, yet it remains unresolved whether temporal prediction can be influenced by low-frequency rhythmic modulation of sensory stimuli. Here, we tested whether external rhythmic sensory stimulation at a frequency in the delta range (0.5 - 3 Hz) alters performance in a visual temporal prediction task. Participants judged whether a moving visual stimulus reappeared too early or too late after disappearing behind an occluder, while the temporal structure of crossmodal sensory input was manipulated across two behavioral sessions. Results indicated that in the visual-auditory conditions, oscillatory stimulation in either the visual or auditory modality improved performance, whereas decaying sensory intensity over time impaired performance. In visual-tactile conditions, oscillatory visual stimulation also enhanced sensitivity, but rhythmic tactile stimulation did not produce a comparable benefit in performance. Critically, tactile stimulation improved performance only when aligned to the expected disappearance of the visual stimulus, demonstrating that the phase relationship between sensory input and intrinsic delta oscillations is behaviorally relevant. Together, these findings indicate that temporal prediction depends on the temporal structure of sensory input and support the relevance of delta-band oscillations in predictive behavior across and within sensory modalities. Hence, rhythmic modulation of sensory stimuli may provide a tool to enhance temporal prediction accuracy by stimulating oscillatory neural dynamics.

This study examines the temporal dynamics of expressive piano performance by means of a quantitative analysis of motor timing in an elite pianist, with particular reference to stylistic contrasts between Baroque and Romantic repertoire. In line with kinematic models of expressive timing, which describe musical performance as reflecting principles of biological motion, we examined whether a common temporal structure underlies stylistically divergent executions. Despite marked differences in structural complexity and gesture density, both performances exhibited a shared low-frequency oscillatory pattern ([~]0.36 Hz) in beat-level timing variability. This infra-delta rhythmic modulation is consistent with the presence of an underlying motor timing scaffold and suggests a common temporal organization across expressive behaviors. These findings support the hypothesis that musical performance relies on a rhythmically structured control architecture, potentially shared with other complex motor activities such as speech and locomotion.

The use of domestic pigs in clinical training and biomedical research is expanding rapidly, increasing the need for reliable, noninvasive indicators of health and welfare. Vocal analysis offers a non-invasive promising tool, yet the acoustic repertoire of adult domestic pigs remains poorly defined. However, the vocalization repertoire of adult domestic pigs has yet to be characterized. This study characterizes the vocal repertoire of adult pigs housed in a biomedical research laboratory. Twelve mixed-breed pigs (2-3 months old; 5 males, 7 females) were recorded during routine husbandry and experimental procedures. Vocal classification was conducted using perceptual and objective clustering techniques. First, aural- visual (AV) inspection of spectrograms was used to construct a hierarchical repertoire. Second, a two-step cluster analysis based on six acoustic parameters (5% frequency, first quartile frequency, center frequency, 90% bandwidth, interquartile range bandwidth, and 90% duration) provided an objective classification. Agreement between methods was evaluated using Cramers V. A total of 1,136 vocalizations from 69 recordings were analyzed. AV classification revealed five major vocal classes-- grunt, squeal, complex, scream, and bark--subdividing into 16 distinct call types. Standardized definitions integrating descriptive and quantitative criteria are provided. The two-step cluster analysis identified two clusters as the optimal statistical solution, with moderate agreement between methods (Cramers V = 0.67, p < 0.0001). Most AV-defined call types aligned with previously reported repertoires, although whines, yelps, and stable screams were unique to this study. While two-cluster solutions are commonly reported, our findings indicate that richer acoustic structure exists and that high gradation among pig calls may limit the resolution of statistical clustering. These results establish a detailed acoustic framework for adult pig vocalizations and provide essential groundwork for developing predictive models to enhance welfare assessment and support comparative research in laboratory-housed pigs.

Vessel-whale collisions are a growing global concern and remain challenging to quantify. Therefore, the use of proxies, such as Close Encounters (CEs) that comprise Surprise Encounters (SEs) and Near-Miss Events (NMEs), has been proposed and widely employed to assess collision risk. To better understand this risk in the Eastern North Atlantic, where maritime traffic is intensive, this study aimed to redefine and quantify CEs, and to assess detectability-related variables that may affect CE identification. CEs were assessed using a cetacean occurrence dataset collected between 2012 and 2024 on board cargo ships and oceanographic vessels. CEs thresholds were redefined based on Time to Potential Collision (TPC), rather than distance alone (as described in literature), to allow a more dynamic, risk-based, and speed-sensitive approach. In total, 1226 sightings of whales (baleen, sperm, and beaked whales) were recorded, of which 37.4% were classified as SEs and 2.0% as NMEs. The sperm whale, Physeter macrocephalus, was the species most frequently involved in CEs (13.9% of all CEs), followed by the Cuviers beaked whale, Ziphius cavirostris (11.8%). A Generalized Additive Model was used to assess the influence of detectability-related variables (i.e., meteorological conditions, whale taxa, vessel characteristics, and Marine Mammals Observers (MMOs) experience) on TPC. Significantly lower TPC values were observed with beaked whales, cargo ships, poor visibility conditions, and less experienced MMOs. The results of this study provide an CEs assessment in this region and contribute to the ongoing efforts to standardize CE quantification, by using TPC as a metric. This work also highlights the importance of decreased speeds and the presence of experienced MMOs on board to increase detection probability and TPC, thereby potentially minimizing collision risk.

Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.