Killer whales (Orcinus orca) communicate through a wide range of vocalizations, including pulsed calls, whistles, and echolocation clicks (Ford, 1989, 1991; Thomsen et al., 2002). The ability to produce, perceive, and interpret these sounds is essential for their survival, as it enables critical behaviors such as social interaction, reproduction, and hunting (Ford, 1989; Miller, 2006). Pulsed calls, in particular, likely support intra-group communication, with pods typically sharing between 7 and 17 distinct call types that are structurally unique (Ford, 1989). These discrete calls are highly stereotyped and specific to individual pods, allowing researchers to identify populations and track their movements across oceans (Ford, 1991; Yurk et al., 2002). Pulsed calls and whistles are thought to be communication signals (Ford, 1989; Thomsen et al., 2002) used by killer whales in a variety of behavioural contexts, including social interactions (Ford, 1989; Filatova et al., 2013). These calls are thought to facilitate contact between members of the social group, ensuring cohesion despite physical separation (Ford, 1989, 1991).The characteristics of killer whale vocalizations can also vary depending on ecological circumstances and prey specialization. For instance, Shetland herring-eating killer whales produce a specific call type that matches a vocalization previously identified in Icelandic killer whales (Deecke et al., 2011). This call, thought to function as a herding call, likely aids in concentrating herring during feeding. Additionally, the structure and frequency of discrete calls are influenced by their functional context (Miller, 2006). Analysis of frequency in resident killer whales of the Northeast Pacific, revealed two distinct types: biphonic calls, which include overlapping high-frequency components, and monophonic calls, which do not (Filatova et al., 2009; Filatova, 2020). Biphonic calls exhibit higher source levels, suggesting a larger active space compared to monophonic calls, and likely serve different communicative purposes.

In addition to variations in the structure of vocalizations, sound production patterns also exhibit considerable variability across species and contexts. Studies on primates, for example, highlight the diversity in vocal production across different species, shedding light on its ecological and social drivers (Schneiderová et al., 2020). Among cetaceans, this variability has been explored extensively, particularly in odontocetes, where vocalizations are used to monitor presence and abundance in remote locations through passive acoustic monitoring (PAM) (André et al., 2011; Hanson et al., 2013; Fleishman et al., 2023). Additionally, vocalization patterns often vary with behavioral states, such as activity levels or arousal, which must be accounted for to improve detection probabilities (Bain, 1986; Buckstaff, 2004; Holt et al., 2013; Probert et al., 2021).

For example, in bottlenose dolphins (Tursiops truncatus), whistle emission rates can fluctuate dramatically depending on environmental or social factors. Moore and Ridgway (1996) observed that the number of whistles emitted by two female dolphins over a year ranged from 1,682 to 6,793 per 24-hour period, with sound production negatively correlated with progesterone levels. Similarly, Buckstaff (2004) found that dolphins whistle more frequently during the onset of vessel approaches, possibly reflecting heightened arousal or an adaptive response to signal masking in noisy environments. In contrast, Quick and Janik (2008) noted that whistle rates decreased in larger groups where signal masking by conspecifics might hinder communication. Geographic and ecological factors further contribute to variability in vocal behavior, as highlighted by Oswald et al. (2008), who identified significant differences in whistle rates among small odontocetes in temperate and tropical regions, influenced by predator density, group composition, and environmental conditions.

Killer whales exhibit considerable variability in their vocalization patterns, influenced by behavioral states, social dynamics, and ecological contexts. Early studies (Ford, 1989; van Opzeeland et al., 2005) demonstrated how call sequences, rather than isolated call types, are more strongly associated with group behaviors such as foraging. For example, during carousel feeding, the temporal organization of call sequences appears critical for maintaining group coordination and synchronizing movements. Changes in vocal activity have also been linked to ecological specialization, as shown by (Deecke et al., 2011), who observed distinct patterns of call production in seal-hunting and herring-eating killer whale populations. Seal-hunting groups exhibited lower call rates, possibly to avoid detection by acoustically sensitive prey, whereas herring-eating groups employed higher call rates, including specific herding calls, to concentrate prey during feeding.

Vocalization rates in killer whales also vary depending on environmental and social factors. van Opzeeland et al. (2005) observed fluctuations in call rates linked to activity states, with increased rates during socializing compared to traveling or resting. Additionally, Poupard et al. (2021) noted behavioral responses, such as increased call rates and changes in vocalization patterns, when killer whales encountered external stimuli, including vessels. These findings suggest that vocalization patterns in killer whales are not static but instead dynamically adapt to their ecological and social environments.

Vocalization rates in animals are often linked to levels of arousal, reflecting responses to social and environmental stimuli. In terrestrial mammals such as silver foxes, vocal production rates increase during both positive and negative arousal states, while rhesus monkeys emit higher-frequency calls in negative contexts like aggression (Whitham and Miller, 2024). Among cetaceans, the relationship between vocal activity and arousal has been explored extensively, particularly in bottlenose dolphins (Tursiops truncatus). Whistle production rates have been shown to increase during foraging, human interactions, mother-calf separations, and perceived stress, reflecting heightened arousal in these situations (Eskelinen et al., 2022). In dolphins under human care, peaks in vocal activity are often associated with feeding and training sessions, indicating a connection to anticipatory behaviors and social coordination, while decreases occur during resting periods, particularly at night (Therrien et al., 2012; Probert et al., 2021, 2023). Furthermore, sound production rates during cooperative interactions are higher than during solitary activities, highlighting the role of vocalizations in coordinating social behaviors (Eskelinen et al., 2016).

In killer whales, Weiss et al. (2007); Rehn et al. (2007) explored vocal activity in relation to arousal across different social contexts in the Northern Resident population off Vancouver Island. Their findings revealed significant changes in vocal behavior depending on the presence and identity of accompanying whales. Specifically, high-arousal call types, such as family-specific call subtypes and aberrant calls, were emitted at greater rates during intergroup encounters, while low-arousal calls were more commonly used in less dynamic social settings. These results suggest that killer whale vocalization rates and types are closely tied to social arousal.

Building on these findings (Probert et al., 2021, 2023) emphasized the potential of vocal behavior as a non-invasive tool for monitoring welfare in animals under human care. In their study, vocalization rates and characteristics were associated with scheduled events such as feeding and human interaction, and were thought to reflect underlying emotional states. They proposed that establishing baseline vocalization patterns for individuals provides a valuable index for detecting abnormal changes, which could indicate shifts in welfare state. While increased arousal may not always distinguish between positive and negative emotional states, monitoring vocal behavior offers critical insights into the animals’ experiences and welfare, both in natural settings and under human care.

The use of vocalizations as a proxy for monitoring animal welfare has gained significant attention, beginning with terrestrial mammals. Early studies suggested that vocal behavior can reflect emotional and physiological states, providing a non-invasive means of assessing welfare (Manteuffel et al., 2004; Schön et al., 2004; Hewson, 2004). Advances in automated acoustic analysis have further facilitated the application of vocal monitoring for detecting stress, positive emotions, and even early indicators of disease in animals (Laurijs et al., 2021; Whitham and Miller, 2024; Jones et al., 2024). Notably, studies on bottlenose dolphins have identified the so-called “victory squeal”—a distinct burst-pulse vocalization emitted upon successful task completion or prey capture—as a potential acoustic indicator of positive affect, possibly mediated by dopaminergic activation (Ridgway et al., 2015).

In cetaceans, vocal behavior has similarly been used to infer welfare-related states. Bottlenose dolphins (Tursiops truncatus) increase whistle rates during stressful contexts such as capture-release events and medical procedures or boat presence, while decreases in vocal activity have been observed following significant stressors, such as transportation in belugas (Delphinapterus leucas) (Buckstaff, 2004; Castellote and Fossa, 2006; Esch et al., 2009; Jones et al., 2021; Wong et al., 2023). Conversely, elevated vocalization rates have been linked to positive states, such as cooperative activities and anticipatory behaviors (Eskelinen et al., 2016; Probert et al., 2021). These insights have been operationalized at the US Navy Marine Mammal Program in San Diego, where the Welfare Acoustic Monitoring System (WAMS) employs real-time acoustic monitoring to detect deviations in vocal behavior, enabling proactive welfare management (Winship and Jones, 2023).

For killer whales, studies on vocalizations in welfare contexts remain limited. Filatova et al. (2009) found that biphonic calls were more frequent during inter-pod interactions, suggesting a role in cohesion or agonistic signaling. Similarly, Graham and Noonan (2010) identified specific call types associated with rare aggressive chase events in captive orcas, providing a potential acoustic signature for agonistic interactions. However, comprehensive studies linking vocalization rates to arousal or welfare states are lacking, leaving an essential gap in understanding how killer whale vocal behavior may reflect both positive and negative emotional states.

While vocal behavior has been widely recognized as a valuable indicator of affective states in various species, including cetaceans, there is a significant lack of evidence on its applicability as a welfare proxy for killer whales. Existing studies have identified vocalizations associated with agonistic behaviors and negative affective states in orcas, yet comprehensive data linking vocalization rates to welfare remain scarce. This gap highlights the urgent need for systematic research to explore the potential of vocal behavior as an indicator of both positive and negative affective states in this species, as emphasized in the broader field of animal welfare science (Whitham and Miller, 2024).

To address this gap, the goal of this study is to evaluate the potential value of vocalization rate and overall vocal activity, specifically focusing on pulsed calls, as indicators of welfare in killer whales. This research is essential for establishing a robust framework for both welfare monitoring and population assessments. Ultimately, such efforts aim to advance our understanding of welfare in managed care settings while also providing valuable acoustic benchmarks for conservation studies in the wild, enabling more informed and proactive management decisions that prioritize the well-being of killer whales.

While animal welfare is inherently an individual-level construct, this study explored the potential for vocal activity measured at the group level to serve as a practical, non-invasive proxy for monitoring collective welfare dynamics in a socially complex species. Given that vocalizations could not be attributed to specific individuals due to the use of a single hydrophone and the absence of distinctive individual acoustic markers, all acoustic analyses were conducted at the group level. We acknowledge this limitation and interpret our findings with appropriate caution. Nonetheless, group-level vocal activity may still reflect meaningful changes in social cohesion, arousal, or stress, particularly in structured social groups where individual states may influence group-wide behavior. As such, this work represents an initial step toward identifying vocal parameters that could inform welfare assessment frameworks, even when individual vocal attribution is not feasible.

An additional limitation of this study is the small sample size and the potential influence of social structure on vocal behavior within the group. Although vocalizations were analyzed at the group level, differences in individual vocal output—driven by dominance, age, sex, or social role—may affect the overall acoustic patterns detected. In a socially complex species such as the killer whale, a small number of highly vocal individuals could disproportionately influence group-level acoustic metrics, particularly in the absence of individual call attribution. As such, the interpretation of vocal activity in relation to welfare must consider the social composition and stability of the group under study. This limitation underscores the importance of integrating complementary behavioural and contextual data when using passive acoustic monitoring as a welfare tool.

The analysis of nearly 1.5 million orca vocalizations recorded at Orca Ocean revealed distinct temporal patterns, characterized by a pronounced diurnal rhythm with reduced vocal activity during nocturnal hours ( Figure 1 ). These findings align with previous studies indicating elevated vocal activity associated with group behaviors in wild killer whales (Ford, 1989; van Opzeeland et al., 2005). Similar patterns have also been observed in dolphins under human care, where vocal peaks coincide with feeding and training sessions, suggesting that vocal production may serve roles in anticipatory behaviors and social coordination (Therrien et al., 2012; Probert et al., 2021, 2023). In the present study, vocal peaks were observed at 07:00, corresponding to the start of human activities at the facility, and at 11:00, and 16:00, aligning with training sessions and public presentations. These results further support the hypothesis that vocalization rates are modulated by arousal levels and social engagement (Ford, 1989; van Opzeeland et al., 2005; Graham and Noonan, 2010; Holt et al., 2013; Poupard et al., 2021). However, caution should be exercised in interpreting the elevated vocalization rates observed at dawn, as they may be influenced by the controlled setting and human presence. In contrast, the vocalization rates calculated for day and night more closely align with patterns described for wild populations (Ford, 1989; van Opzeeland et al., 2005).

Although the vocal activity levels reported in this study cannot be directly compared with those of wild populations due to differing contexts and methodologies, the range of call rates observed is broadly consistent with those reported in studies of resident killer whales under naturalistic conditions (Ford, 1989; van Opzeeland et al., 2005; Filatova et al., 2009; Holt et al., 2013; Poupard et al., 2021), suggesting potential functional similarities in vocal behavior. Given that previous research has demonstrated that call rate is not significantly affected by the number of individuals present (Holt et al., 2013), these findings would support the hypothesis that the structure of vocal activity remains relatively stable across different environments. While these values are not suitable for estimating orca abundance using passive acoustic monitoring (PAM) (Holt et al., 2013),provide additional evidence that vocalization rates are influenced by social interactions and arousal rather than external environmental factors. Notably, the median vocal activity per minute during the day (0.571) was not substantially different from that recorded at night (0.500), despite a higher percentage of active minutes occurring during daylight hours. This suggests that variations in vocal activity are primarily driven by fluctuations in the proportion of active minutes rather than substantial changes in call rate per minute across diel phases. Notably, the presence of nighttime vocal activity aligns with previous observations of social and foraging behaviors occurring during nocturnal periods in both wild and managed-care delphinids (Kremers et al., 2014; Deconto and Monteiro-Filho, 2016; Sol et al., 2024).

Analysis of vocal activity throughout the year suggests that the diurnal structure of vocal production persists despite seasonal fluctuations. A notable increase in vocal activity was observed during the initial months of the year, a pattern that remained evident even in months with lower overall activity levels ( Figure 2 ). These results support previous findings that killer whale vocalization rates are closely linked to social arousal (Weiss et al., 2007). However, we acknowledge that in a controlled environment where management routines such as feeding, enrichment, and training are maintained consistently across the year, seasonal or annual shifts in vocal behavior are not necessarily expected, nor are they assumed to be direct indicators of welfare status. The inclusion of seasonal and annual comparisons in this study was not intended to attribute biological significance to temporal variation, but rather to determine whether vocal activity in this managed population is distributed homogeneously or heterogeneously over time. Understanding such distribution patterns provides context for the interpretation of behavioural correlations and helps establish appropriate baselines for welfare monitoring. Nonetheless, the variability in sampling effort across the analyzed period limits the conclusiveness of this trend, and further research with more homogeneous data collection is needed to confirm the annual vocal pattern.

The relationship between vocalization and welfare-related behavioral parameters was explored using performance in trainer-requested tasks as a proxy for cognitive engagement and emotional state (Clegg et al., 2015, 2017). To explore whether vocal activity patterns at different times of day were differentially related to behavioural or cognitive indicators, correlations were conducted using vocal metrics calculated separately for dawn, day, dusk, and night periods. While this approach introduces some redundancy due to the use of overlapping daily data, it was employed in an exploratory framework to assess whether specific temporal windows might offer enhanced sensitivity to welfare-relevant changes. However, to avoid potential issues of pseudo-replication and misinterpretation, only correlations based on daily aggregated vocal indices should be considered in the interpretation of welfare associations. Social imbalance was evaluated based on instances where individuals refused to execute a requested behavior, separated from trainer control, or displaced conspecifics. Low-performance and social imbalance events were relatively infrequent, indicating a high level of behavioral consistency among the animals.

The low frequency of these events raises questions about their suitability as robust indicators of welfare or social balance. However, previous studies have also documented low rates of agonistic interactions in this group, with occurrence rates below 1% (Sánchez–Hernández et al., 2019), a finding further supported by recent activity budget analyses of killer whales under professional care (Hill et al., 2025). This suggests that while these behavioral metrics may not be strong welfare indicators on their own, their low prevalence is consistent with the overall social stability and structured behavioral patterns observed in this managed orca population.

Prior studies have documented substantial modifications in cetacean vocal behavior in response to acute stressors. For example, beluga whales ceased vocalizations entirely following transportation events (Castellote and Fossa, 2006), while bottlenose dolphins increased whistle rates in response to watercraft noise (Buckstaff, 2004) and construction activities (Wong et al., 2023). In orcas, controlled environment studies have demonstrated increased call rates during aggressive events (Graham and Noonan, 2010). In contrast, the present study found only weak correlations between vocal activity and indicators of social imbalance or cognitive bias. This discrepancy may be due to the relatively subtle nature of the social and cognitive challenges assessed, which likely reflect minor fluctuations in welfare rather than significant stressors. Alternatively, it is possible that the orcas in this study did not experience substantial welfare challenges during the observation period. Additionally, the behavioral metrics used to assess cognitive bias and social imbalance may require further refinement to better capture nuances in orca welfare.

The observed variation in vocal activity across different time periods, together with prior findings on orcas (Graham and Noonan, 2010), provided the primary rationale for evaluating vocalization as a potential welfare indicator. Previous studies have demonstrated that reductions in vocal rates are associated with significant stressors in cetaceans (Buckstaff, 2004; Castellote and Fossa, 2006; Esch et al., 2009; Jones et al., 2021; Wong et al., 2023), while increased vocalization rates have been linked to positive welfare states (Eskelinen et al., 2016; Probert et al., 2021). However, the Spearman correlation analysis suggests that, in orcas, this relationship may operate inversely, with low-performance and social imbalance indices positively correlated with vocal production, whereas normal-performance indices were negatively correlated. This finding aligns with previous research indicating that call rates increase during aggressive events (Graham and Noonan, 2010) and that certain vocalizations, such as biphonic calls, occur more frequently during inter-pod interactions (Filatova et al., 2009), suggesting a complex interplay between vocalization patterns and social dynamics.

It is important to note that the observed increase in vocalization rate in this study was calculated using the daily integrated sound rate to ensure comparability with behavioral and cognitive data, which were also assessed at the daily scale. Consequently, these results cannot be directly applied to finer temporal scales, such as diel variations, as the effects were measured within a different timeframe. Future studies should investigate vocal activity and behavior at finer temporal resolutions to determine whether vocal indicators—both qualitative and quantitative—can reliably reflect welfare-related changes over shorter timescales.

Given the weak correlation coefficients (Spearman r < 0.2), these relationships explain only a small proportion of the variance in vocal activity, indicating that additional, unmeasured factors likely exert stronger influences on vocal production in killer whales. Nevertheless, the results suggest a subtle connection between vocalization patterns and welfare, highlighting the potential relevance of vocal parameters as indicators of well-being. Seasonal and monthly variations in vocal activity add further complexity, potentially reflecting external environmental or social influences. Additionally, these fluctuations may be affected by operational constraints of the recording system, leading to nonhomogeneous sampling periods rather than genuine seasonal trends in vocal behavior. Ultimately, the weak statistical associations observed underscore the need for further investigation into the broader ecological, social, and cognitive factors shaping orca vocalization patterns. In particular, future studies should incorporate qualitative acoustic analyses—such as the classification of call types and the identification of nonlinear vocal phenomena—as these structural features may reflect arousal or emotional valence and could offer greater sensitivity for assessing welfare at both the group and individual level (Sportelli et al., 2022).

While this study was conducted on killer whales under managed care, some behavioural patterns observed—such as the diel modulation of vocal activity or correlations with social dynamics—may reflect more general features of orca acoustic behavior. Nonetheless, caution is warranted when drawing parallels between captive and wild populations. Animals in zoological settings are subject to different ecological constraints, social structures, and acoustic environments than their wild counterparts, and these differences can influence both the rate and function of vocal output. In particular, the absence of natural foraging and predation and the presenceo of human interaction routines may modify vocal behavior. However, controlled conditions also provide opportunities for long-term, fine-scale monitoring and individual-level analysis that are difficult to achieve in the wild. Therefore, while findings from managed-care studies are not directly generalizable, they can offer hypotheses and methodological frameworks—such as vocal monitoring as a welfare proxy—that may be adapted for wild populations using passive acoustic monitoring, especially in resident groups with known vocal dialects and social cohesion patterns.