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Acoustic signals are vital in animal communication, and quantifying them is fundamental for understanding animal behaviour and ecology. Vocalizations can be classified into acoustically and functionally or contextually distinct categories, but establishing these categories can be challenging. Newly developed methods, such as machine learning, can provide solutions for classification tasks. The plains zebra is known for its loud and specific vocalizations, yet limited knowledge exists on the structure and information content of its vocalzations. In this study, we employed both feature-based and spectrogram-based algorithms, incorporating supervised and unsupervised machine learning methods to enhance robustness in categorizing zebra vocalization types. Additionally, we implemented a permuted discriminant function analysis to examine the individual identity information contained in the identified vocalization types. The findings revealed at least four distinct vocalization types—the ‘snort’, the ‘soft snort’, the ‘squeal’ and the ‘quagga quagga’—with individual differences observed mostly in snorts, and to a lesser extent in squeals. Analyses based on acoustic features outperformed those based on spectrograms, but each excelled in characterizing different vocalization types. We thus recommend the combined use of these two approaches. This study offers valuable insights into plains zebra vocalization, with implications for future comprehensive explorations in animal communication.

Vocal individuality has been widely documented in the Tawny owl (Strix aluco); however, all statistical tools employed thus far to discriminate individual vocalisations have relied on prior knowledge regarding number and identity of individuals. In this study, we tested the effectiveness of four unsupervised clustering algorithms in distinguishing among eight Tawny owl males, solely based on acoustic characteristics of their vocalisations. We also employed both traditional bound-based and robust measurements of acoustic signal to compare their efficacy. We finally evaluated the applicability of this method in identifying the number and distribution of the remaining males recorded in our study area. Three of the four unsupervised techniques had a high rate of success in discriminating among vocalisations of the eight males. In all cases, the best results were obtained using robust measurements. However, when extending the analysis to the remaining unknown males recorded, the highest rate of misclassification errors made results more difficult to interpret. Our study provided a useful tool to discriminate male Tawny owls when only their call recordings are available. Furthermore, this method could be extended to other nocturnal and vociferous species, representing one of the few existing approaches for unsupervised classification of individuals based on acoustic features. [ABSTRACT FROM AUTHOR]

Simple Summary: The remaining European populations of the capercaillie are restricted to isolated mountains, and population declines have led to local extinctions across Western and Central Europe. The majority of studies related to individually distinct vocalizations focused on various versions of tonal and harmonic signals, while non-harmonic noisy signals have not been studied in such detail, even though these signals are frequent in some birds including gallinaceous species. We described the structure of capercaillie song and showed how temporal and frequency acoustic variables contribute to individual-specific expression. The combination of temporal and frequency variables showed the best classification result. Capercallie song represents a complex signal of non-harmonic 'noisy' sounds formed by different acoustic components organized into four main phases. We tested which song phase makes the largest contribution to coding individual identity. The best contribution to individual variation was found in more complex phases. Recordings from males originating from seven countries also suggest geographical variation underlying capercaillie song. The such geographic variation could reflect the potential genetic differentiation of distant populations. Our results revealed that males from Sweden and Norway (Boreal area) formed a distinct cluster from males in the Czech Republic, Germany, and Poland (Sumava and Carpathian area). Individually distinct acoustic signals, produced mainly as tonal and harmonic sounds, have been recorded in many species; however, non-tonal 'noisy' signals have received little attention or have not been studied in detail. The capercaillies (Tetrao urogallus) produce complex courtship songs composed of non-tonal noisy signals in four discrete phases. We analyzed recordings from 24 captive male capercaillies in breeding centres in the Czech Republic, Poland, and Germany, and songs from wild males in Sweden, Norway, Finland, and Estonia to test whether a non-harmonic song can encode individual-specific information. We also analyzed the intra-population variation of the male song from three separate areas: Carpathian (Polish and Czech Beskid), Sumava, and Boreal (boreal range of species distribution). Temporal and frequency characteristics can reliably distinguish capercaillies at the individual level (91.7%). DFA model testing geographic variation assigned 91% of songs to the correct area (Carpathian, Sumava, Boreal). The cluster analysis revealed that males from the Boreal area formed a distinct cluster. Our analysis shows clear geographical patterns among our study males and may provide a valuable marker for identifying inter-population dynamics and could help to characterize the evolutionary histories of wood grouse. We discuss the potential use of this marker as a non-invasive monitoring tool for captive and free-roaming capercaillies. [ABSTRACT FROM AUTHOR]

The classification of vocal individuality for passive acoustic monitoring (PAM) and census of animals is becoming an increasingly popular area of research. Nearly all studies in this field of inquiry have relied on classic audio representations and classifiers, such as Support Vector Machines (SVMs) trained on spectrograms or Mel-Frequency Cepstral Coefficients (MFCCs). In contrast, most current bioacoustic species classification exploits the power of deep learners and more cutting-edge audio representations. A significant reason for avoiding deep learning in vocal identity classification is the tiny sample size in the collections of labeled individual vocalizations. As is well known, deep learners require large datasets to avoid overfitting. One way to handle small datasets with deep learning methods is to use transfer learning. In this work, we evaluate the performance of three pretrained CNNs (VGG16, ResNet50, and AlexNet) on a small, publicly available lion roar dataset containing approximately 150 samples taken from five male lions. Each of these networks is retrained on eight representations of the samples: MFCCs, spectrogram, and Mel spectrogram, along with several new ones, such as VGGish and stockwell, and those based on the recently proposed LM spectrogram. The performance of these networks, both individually and in ensembles, is analyzed and corroborated using the Equal Error Rate and shown to surpass previous classification attempts on this dataset; the best single network achieved over 95% accuracy and the best ensembles over 98% accuracy. The contributions this study makes to the field of individual vocal classification include demonstrating that it is valuable and possible, with caution, to use transfer learning with single pretrained CNNs on the small datasets available for this problem domain. We also make a contribution to bioacoustics generally by offering a comparison of the performance of many state-of-the-art audio representations, including for the first time the LM spectrogram and stockwell representations. All source code for this study is available on GitHub. [ABSTRACT FROM AUTHOR]

Individually distinct acoustic signals, produced mainly as tonal and harmonic sounds, have been recorded in many species; however, non-tonal ‘noisy’ signals have received little attention or have not been studied in detail. The capercaillies (Tetrao urogallus) produce complex courtship songs composed of non-tonal noisy signals in four discrete phases. We analyzed recordings from 24 captive male capercaillies in breeding centres in the Czech Republic, Poland, and Germany, and songs from wild males in Sweden, Norway, Finland, and Estonia to test whether a non-harmonic song can encode individual-specific information. We also analyzed the intra-population variation of the male song from three separate areas: Carpathian (Polish and Czech Beskid), Sumava, and Boreal (boreal range of species distribution). Temporal and frequency characteristics can reliably distinguish capercaillies at the individual level (91.7%). DFA model testing geographic variation assigned 91% of songs to the correct area (Carpathian, Sumava, Boreal). The cluster analysis revealed that males from the Boreal area formed a distinct cluster. Our analysis shows clear geographical patterns among our study males and may provide a valuable marker for identifying inter-population dynamics and could help to characterize the evolutionary histories of wood grouse. We discuss the potential use of this marker as a non-invasive monitoring tool for captive and free-roaming capercaillies.

Acoustic signals are vital in animal communication, and quantifying them is fundamental for understanding animal behaviour and ecology. Vocalizations can be classified into acoustically and functionally or contextually distinct categories, but establishing these categories can be challenging. Newly developed methods, such as machine learning, can provide solutions for classification tasks. The plains zebra is known for its loud and specific vocalizations, yet limited knowledge exists on the structure and information content of its vocalzations. In this study, we employed both feature-based and spectrogram-based algorithms, incorporating supervised and unsupervised machine learning methods to enhance robustness in categorizing zebra vocalization types. Additionally, we implemented a permuted discriminant function analysis to examine the individual identity information contained in the identified vocalization types. The findings revealed at least four distinct vocalization types-the 'snort', the 'soft snort', the 'squeal' and the 'quagga quagga'-with individual differences observed mostly in snorts, and to a lesser extent in squeals. Analyses based on acoustic features outperformed those based on spectrograms, but each excelled in characterizing different vocalization types. We thus recommend the combined use of these two approaches. This study offers valuable insights into plains zebra vocalization, with implications for future comprehensive explorations in animal communication., Competing Interests: We declare we have no competing interests., (© 2024 The Author(s).)

Previous research has shown that African lions (Panthera leo) have the ability to discriminate between conspecific vocalisations, but little is known about how individual identity is conveyed in the spectral structure of roars. Using acoustic – accelerometer biologgers that allow vocalisations to be reliably associated with individual identity, we test for vocal individuality in the fundamental frequency (f0) of roars from 5 male lions, firstly by comparing simple f0 summary features and secondly by modelling the temporal pattern of the f0 contour. We then assess the application of this method for discriminating between individuals using passive acoustic monitoring. Results indicate that f0 summary features only allow for vocal discrimination with 70.7% accuracy. By comparison, vocal discrimination can be achieved with an accuracy of 91.5% based on individual differences in the temporal pattern of the f0 sequence. We further demonstrate that passively recorded lion roars can be localised and differentiated with similar accuracy. The existence of individually unique f0 contours in lion roars and their relatively lower attenuation indicates a likely mechanism enabling individual lions to identify conspecifics over long distances. These differences can be exploited by researchers to track individuals across the landscape and thereby supplement conventional lion monitoring approaches. [ABSTRACT FROM AUTHOR]

Passive acoustic monitoring – an approach that utilizes autonomous acoustic recording units – allows for non-invasive monitoring of individuals, assuming that it is possible to acoustically distinguish individuals. However, identifying effective analytical approaches for individual identification remains a challenge. Our study investigates how the use of different feature representations impacts our ability to distinguish between individual female Northern grey gibbons (Hylobates funereus). We broadcast pre-recorded calls from twelve gibbon females and re-recorded the calls at varying distances (directly under the tree to ∼400 m away) using autonomous recording units. We evaluated the effectiveness of using different automated feature extraction approaches to classify gibbon calls: Mel-frequency cepstral coefficients (MFCCs), embeddings from three pre-trained neural networks (BirdNET, VGGish, and Wav2Vec2), and four commonly used acoustic indices. We used a supervised classification approach (random forest) to classify calls to the respective female and compared two unsupervised clustering approaches (affinity propagation clustering and hierarchical density-based spatial clustering) to evaluate which features were most effective for distinguishing female calls without using class labels. We used MFCCs as a baseline as previous work has shown they can be used to distinguish high-quality calls of individual gibbon females. Human annotators could only identify calls in spectrograms from recordings <350 m from the playback speaker with signal-to-noise ratio ∼ 0 dB, so our results focus on these recordings. Using supervised classification, our results confirmed the efficiency of MFCCs and the use of embeddings from one neural network (BirdNET) for effective acoustic classification of gibbon individuals at closer recording distances (signal-to-noise ratio > 10 dB), while the remaining features did not perform well. Contrary to our expectations, we found that MFCCs outperformed all other features for the unsupervised clustering tasks at closer distances and none of the features performed well at farther distances. The ability to acoustically discriminate animals under noisy conditions and from low signal-to-noise ratio calls has important implications for monitoring populations of endangered animals, such as gibbons. Focusing only on high signal-to-noise ratio calls for individual discrimination may not be possible for rare sounds, and future work should focus on developing effective approaches of feature extraction that can perform well across noisy, real-world conditions with a limited number of training samples. • We evaluate the performance of 5 feature sets for classification and clustering of individual gibbon calls. • MFCCs and BirdNET embeddings were best for classification. MFCCs were most reliable for clustering. • Signal-to-noise ratio impacted performance of all features, however MFCCs were most robust to noisy conditions. • Future research will be crucial to improve our ability to acoustically distinguish individuals in noisy conditions. [ABSTRACT FROM AUTHOR]

Vocal individuality has been used as a monitoring tool, and two criteria are a prerequisite: high variation among individuals and low variation within individuals, and vocal consistency within and across seasons. We examined individual variation in the territorial hoot calls of the tawny owl (Strix aluco) to discriminate between males and to assess a possible conservation technique that would allow for monitoring individuals within a study area. The territorial calls were recorded from five males in the Naejang Mountain National Park in South Korea during the breeding season in 2015 and 2016 and analyzed both quantitatively and qualitatively to determine the amount of variation within and between individuals. Our results showed that the territorial calls were specific to individuals within a population and that the acoustic distances between males living in the same territory during the two years were the smallest for the four nesting sites. Our results suggest that territorial calls of the tawny owls are individually identifiable over two years and that this acoustic technique can be useful for monitoring individual site fidelity.

Reproduction involves communication. Males usually evolve elaborate displays that may declare their qualities and attract females to mate, using signals from different modalities. Females may use cues encoded in courtship signals to evaluate males and make choices concerning their qualities. We investigated the acoustic element of the elaborate display of the small Cavia rodents, the guinea pigs, Cavia porcellus. We verified the potentiality of the courtship call (purr) to reflect male identity and social status, through variations in acoustic structure and male vocal performance. Our results suggest that the purr encodes individuality but not male dominance status. Vocal performance and purr's structural parameters differed between individuals, but there was no correlation between acoustic parameters and male dominance status. Courtship in cavies is a multimodal display, and male quality may be encoded in visual and chemical signals. This study is the first evidence of individuality in the purr. Further studies may reveal the role of each communication channel in the courting process of Cavia. • Male guinea pigs perform an elaborate courtship, including a vocalization (purr). • We examined whether purr acoustic structure encodes identity or social status. • Purr encodes individuality, but not male dominance status. • Male quality may be encoded in visual and chemical signals. [ABSTRACT FROM AUTHOR]

The classification of vocal individuality for passive acoustic monitoring (PAM) and census of animals is becoming an increasingly popular area of research. Nearly all studies in this field of inquiry have relied on classic audio representations and classifiers, such as Support Vector Machines (SVMs) trained on spectrograms or Mel-Frequency Cepstral Coefficients (MFCCs). In contrast, most current bioacoustic species classification exploits the power of deep learners and more cutting-edge audio representations. A significant reason for avoiding deep learning in vocal identity classification is the tiny sample size in the collections of labeled individual vocalizations. As is well known, deep learners require large datasets to avoid overfitting. One way to handle small datasets with deep learning methods is to use transfer learning. In this work, we evaluate the performance of three pretrained CNNs (VGG16, ResNet50, and AlexNet) on a small, publicly available lion roar dataset containing approximately 150 samples taken from five male lions. Each of these networks is retrained on eight representations of the samples: MFCCs, spectrogram, and Mel spectrogram, along with several new ones, such as VGGish and stockwell, and those based on the recently proposed LM spectrogram. The performance of these networks, both individually and in ensembles, is analyzed and corroborated using the Equal Error Rate and shown to surpass previous classification attempts on this dataset; the best single network achieved over 95% accuracy and the best ensembles over 98% accuracy. The contributions this study makes to the field of individual vocal classification include demonstrating that it is valuable and possible, with caution, to use transfer learning with single pretrained CNNs on the small datasets available for this problem domain. We also make a contribution to bioacoustics generally by offering a comparison of the performance of many state-of-the-art audio representations, including for the first time the LM spectrogram and stockwell representations. All source code for this study is available on GitHub.

Recent bioacoustic advances have facilitated large‐scale population monitoring for acoustically active species. Animal sounds, however, can of information that is underutilized in typical approaches to passive acoustic monitoring (PAM) that treat sounds simply as detections. We developed 3 methods of extracting additional ecological detail from acoustic data that are applicable to a broad range of acoustically active species. We conducted landscape‐scale passive acoustic surveys of a declining owl species and an invasive congeneric competitor in California. We then used sex‐specific vocalization frequency to inform multistate occupancy models; call rates at occupied sites to characterize interactions with interspecific competitors and assess habitat quality; and a flexible multivariate approach to differentiate individuals based on vocal characteristics. The multistate occupancy models yielded novel estimates of breeding status occupancy rates that were more robust to false detections and captured known habitat associations more consistently than single‐state occupancy models agnostic to sex. Call rate was related to the presence of a competitor but not habitat quality and thus could constitute a useful behavioral metric for interactions that are challenging to detect in an occupancy framework. Quantifying multivariate distance between groups of vocalizations provided a novel quantitative means of discriminating individuals with ≥20 vocalizations and a flexible tool for balancing type I and II errors. Therefore, it appears possible to estimate site turnover and demographic rates, rather than just occupancy metrics, in PAM programs. Our methods can be applied individually or in concert and are likely generalizable to many acoustically active species. As such, they are opportunities to improve inferences from PAM data and thus benefit conservation. Article Impact Statement: Animal sounds are signals, and studying them as such can improve conservation outcomes in passive acoustic monitoring programs. [ABSTRACT FROM AUTHOR]

Only a few bird species are known to produce low-frequency vocalizations. We analyzed the display vocalizations of Western Capercaillie males kept in breeding centers and identified harmonically structured signals with a fundamental frequency of 28.7 ± 1.2 Hz (25.6–31.6 Hz). These low-frequency components temporally overlap with the Whetting phase (96% of its duration) and they significantly contribute to the distinct vocal expression between individuals. The resulting model of discrimination analysis classified 67.6% vocalizations (63%, cross-validated result) correctly to the specific individual in comparison to the probability by chance of 12.5%. We discuss a possible function of low-frequency components that remains unclear. The occurrence of such low frequencies is surprising as this grouse is substantially smaller than cassowaries (Southern cassowary Casuarius casuarius and Dwarf cassowary Casuarius bennetti) , the species that produces similarly low frequencies. Because these low frequency components temporarily overlap with the Whetting phase, they are hardly audible from a distance larger than several meters.

Non-vocal, or unvoiced, signals surprisingly have received very little attention until recently especially when compared to other acoustic signals. Some sounds made by terrestrial vertebrates are produced not only by the larynx but also by the syrinx. Furthermore, some birds are known to produce several types of non-syrinx sounds. Besides mechanical sounds produced by feathers, bills and/or wings, sounds can be also produced by constriction, anywhere along the pathway from the lungs to the lips or nostrils (in mammals), or to the bill (in birds), resulting in turbulent, aerodynamic sounds. These noises often emulate whispering, snorting or hissing. Even though hissing sounds have been studied in mammals and reptiles, only a few studies have analyzed hissing sounds in birds. Presently, only the hissing of small, nesting passerines as a defense against their respective predators have been studied. We studied hissing in domestic goose. This bird represents a ground nesting non-passerine bird which frequently produces hissing out of the nest in comparison to passerines producing hissing during nesting in holes e.g., parids. Compared to vocally produced alarm calls, almost nothing is known about how non-vocal hissing sounds potentially encode information about a caller's identity. Therefore, we aimed to test whether non-vocal air expirations can encode an individual's identity similar to those sounds generated by the syrinx or the larynx. We analyzed 217 hissing sounds from 22 individual geese. We calculated the Potential for Individual Coding (PIC) comparing the coefficient of variation both within and among individuals. In addition, we conducted a series of 15 a stepwise discriminant function analysis (DFA) models. All 16 acoustic variables showed a higher coefficient of variation among individuals. Twelve DFA models revealed 51.2- 54.4% classification result (cross-validated output) and all 15 models showed 60.868.2% classification output based on conventional DFA in comparison to a 4.5% success rate when classification by chance. This indicates the stability of the DFA results even when using different combinations of variables. Our findings showed that an individual's identity could be encoded with respect to the energy distribution at the beginning of a signal and the lowest frequencies. Body weight did not influence an individual's sound expression. Recognition of hissing mates in dangerous situations could increase the probability of their surviving via a more efficient anti-predator response. [ABSTRACT FROM AUTHOR]

Only a few bird species are known to produce low-frequency vocalizations. Weanalyzed the display vocalizations of Western Capercaillie males kept in breeding centers and identified harmonically structured signals with a fundamental frequency of 28.7 1.2 Hz (25.6 31.6 Hz). These low-frequency components temporally overlap with the Whetting phase (96% of its duration) and they significantly contribute to the distinct vocal expression between individuals. The resulting model of discrimination analysis classified 67.6% vocalizations (63%, cross-validated result) correctly to the specific individual in comparison to the probability by chance of 12.5%. We discuss a possible function of low-frequency components that remains unclear. The occurrence of such low frequencies is surprising as this grouse is substantially smaller than cassowaries (Southern cassowary Casuarius casuarius and Dwarf cassowary Casuarius bennetti), the species that produces similarly low frequencies. Because these low frequency components temporarily overlap with the Whetting phase, they are hardly audible from a distance larger than several meters. [ABSTRACT FROM AUTHOR]

Acoustic monitoring of birds is developing rapidly as equipment, methods and analyses improve. However, most population monitoring studies still utilise traditional techniques like mark-recapture or line transects. Previous researchers used vocal recordings of male European nightjars, Caprimulgus europaeus, to identify individuals, finding that four acoustic parameters correctly assigned 98.5% of calls to individuals. We tested their methods on a population of European nightjars recorded over two successive breeding seasons and found that percentage of males correctly classified within a season reached a maximum of 73.5%, rising to 75% if full-length calls and 13 acoustic parameters were used. We tested whether males could be re-identified over a two-year period and found that only 20% of calls were assigned to the same putative territorial individuals, despite separate ringing data showing that males can maintain site fidelity for up to eight years. Our results indicate that the characteristics of male nightjar vocalisations may alter over time. We therefore recommend that vocal discrimination be used in conjunction with existing monitoring techniques when surveying for population monitoring, that as many call parameters as possible are used and that recording for automated presence/absence surveys takes place over a short time-frame. [ABSTRACT FROM AUTHOR]

Duetting, or the stereotypical, repeated and often coordinated vocalizations between 2 individuals arose independently multiple times in the Order Primates. Across primate species, there exists substantial variation in terms of timing, degree of overlap, and sex-specificity of duet contributions. There is increasing evidence that primates can modify the timing of their duet contributions relative to their partner, and this vocal flexibility may have been an important precursor to the evolution of human language. Here, we present the results of a fine-scale analysis of Gursky's spectral tarsier Tarsius spectrumgurskyae duet phrases recorded in North Sulawesi, Indonesia. Specifically, we aimed to investigate individual-level variation in the female and male contributions to the duet, quantify individual- and pair-level differences in duet timing, and measure temporal precision of duetting individuals relative to their partner. We were able to classify female duet phrases to the correct individual with an 80% accuracy using support vector machines, whereas our classification accuracy for males was lower at 64%. Females were more variable than males in terms of timing between notes. All tarsier phrases exhibited some degree of overlap between callers, and tarsiers exhibited high temporal precision in their note output relative to their partners. We provide evidence that duetting tarsier individuals can modify their note output relative to their duetting partner, and these results support the idea that flexibility in vocal exchanges—a precursor to human language—evolved early in the primate lineage and long before the emergence of modern humans. [ABSTRACT FROM AUTHOR]

Invasive trapping and radio-collaring techniques are currently used by conservation biologists to study the population dynamics of gray wolves (Canis lupus). Previous research has found wolf howls can be used to determine individual identity on high quality recordings from captive animals, offering an opportunity for non-invasive monitoring of packs. We recorded wild wolves in Central Wisconsin to determine the effectiveness of these features in determining individuality in low quality recordings. The wolf howls analyzed were from two adult individuals from separate packs. Using a principle component analysis, maximum frequency and end frequency of the calls were determined to be most individualistic. Using these features in a discriminant function analysis, howls were able to be identified from individuals with 100% accuracy. Gray wolves play an important role in ecosystem maintenance, however, the current monitoring techniques are costly and invasive. The creation of an easily accessible, noninvasive technique that can be used by individuals with a variety of technical backgrounds is necessary to address concerns faced by conservation efforts. To address these issues, all analyses performed used free or low-cost software, making this method of individual identification a useful alternative for conservation biologists. [ABSTRACT FROM AUTHOR]

Abstract Background Individuality in vocalizations may provide an effective tool for surveying populations of the Common Cuckoo (Cuculus canorus) but there remains few data on which technique to use to identify individuality. In this research, we compared the within- and between-individual variation in cuckoo calls using two different analytical methods, and discuss the feasibility of using call individuality to count male cuckoos within a population. Methods We recorded vocalization from 13 males, and measured 15 spectro-temporal variables for each call. The majority of these call variables (n = 12) have greater variation between individuals than within individual. We first calculated the similarity (Pearson’s R) for each paired calls in order to find a threshold that could distinguish calls emitted from the same or different males, and then counted the number of males based on this distinction. Second, we used the more widely accepted technique of discriminant function analysis (DFA) to identify individual male cuckoos, and compared the correct rate of classifying individuals between the two analytical methods. Results Similarity of paired calls from the same male was significantly higher than from different males. Under a relatively broad threshold interval, we achieved a high (>90%) correct rate to distinguish calls and an accurate estimate of male numbers. Based on banded males (n = 3), we found the similarity of paired calls from different days was lower when compared with paired calls from the same day, but this change did not obscure individual identification, as similarity values of paired calls from different days were still larger than the threshold used to distinguish calls from the same or different males. DFA also yielded a high rate (91.9%) of correct classification of individuals. Conclusions Our study suggests that identifying individual vocalizations can form the basis of an appropriate survey method for counting male cuckoos within a population, provided the performance of different analytical techniques are compared.

Identity signals have been studied for over 50 years but, and somewhat remarkably, there is no consensus as to how to quantify individuality in animal signals. While there is a variety of different metrics to quantify individuality, these methods remain un‐validated and the relationships between them unclear.We contrasted three univariate and four multivariate identity metrics (and their different computational variants) and evaluated their performance on simulated and empirical datasets.Of the metrics examined, Beecher's information statistic (HS) performed closest to theoretical expectations and requirements for an ideal identity metric. It could be also easily and reliably converted into the commonly used discrimination score (and vice versa). Although Beecher's information statistic is not entirely independent of study sampling, this problem can be considerably lessened by reducing the number of parameters or by increasing the number of individuals in the analysis.Because it is easily calculated, has superior performance, can be used to quantify identity information in single variable or in a complete signal and because it indicates the number of individuals who can be discriminated given a set of measurements, we recommend that individuality should be quantified using Beecher's information statistic in future studies. Consistent use of Beecher's information statistic could enable meaningful comparisons and integration of results across different studies of individual identity signals. [ABSTRACT FROM AUTHOR]

Vocal individuality has been used as a monitoring tool, and two criteria are a prerequisite: high variation among individuals and low variation within individuals, and vocal consistency within and across seasons. We examined individual variation in the territorial hoot calls of the tawny owl (Strix aluco) to discriminate between males and to assess a possible conservation technique that would allow for monitoring individuals within a study area. The territorial calls were recorded from five males in the Naejang Mountain National Park in South Korea during the breeding season in 2015 and 2016 and analyzed both quantitatively and qualitatively to determine the amount of variation within and between individuals. Our results showed that the territorial calls were specific to individuals within a population and that the acoustic distances between males living in the same territory during the two years were the smallest for the four nesting sites. Our results suggest that territorial calls of the tawny owls are individually identifiable over two years and that this acoustic technique can be useful for monitoring individual site fidelity. [ABSTRACT FROM AUTHOR]

Numerous studies have identified individually distinctive vocal characteristics and call consistency in different bird species. If these vocal characteristics are to be utilised as non-invasive markers for monitoring purposes, then they must remain stable over time. Three recent studies have shown that it is possible to identify individual male Common Cuckoos (Cuculus canorus) based on vocal characteristics, but whether these characteristics are stable over the duration of a breeding season remains unknown. We recorded 1032 syllables from 30 male Common Cuckoos in a Northeast Asian population. We banded six of these males and made repeated recordings of their cu-coo advertisement call across a 19-day period of the breeding season in China. We used three methods to identify individuals: discriminant function analyses (DFA), correlation analysis (CA) and spectrographic cross-correlation (SPCC). We also used repeatability analysis to test whether call consistency (the number of syllables in each calling bout) was repeatable within individuals. Based on the same-day recordings, calls from the same male were more similar in their characteristics than compared to those of different males, and yielded correct rates of classifying individuals of 93.6% (SPCC), 90.8% (DFA), and 71.5% (CA). However, these rates declined to 40.5% (SPCC), 40.7% (DFA) and 27% (CA) when using recordings over the 19-day period. Call consistency was repeatable within individuals across two successive calling bouts, but this individual repeatability disappeared when several (more than two) calling bouts from the same day or bouts from the different days of the study were included in the analyses. Declines in the correct rate of identifying individual male cuckoos and call consistency in this study raise concerns that individual male cuckoo calls may be more variable than previously thought. [ABSTRACT FROM AUTHOR]

Vocal individuality is a prerequisite for individual recognition, especially when visual and chemical cues are not available or effective. Vocalizations encoding information of individual identity have been reported in many social animals and should be particularly adaptive for species living in large and complexly organized societies. Here, we examined the individuality in coo calls of adult male golden snub-nosed monkeys (Rhinopithecus roxellana) living in a large and multilevel society. Coo calls are one of the most frequently occurring call types in R. roxellana and likely serve as the signals for contact maintenance or advertisement in various contexts including group movement, foraging, and resting. From April to October 2016, April to July 2017, and September to October 2017, we recorded a total of 721 coo calls from six adult males in a provisioned, free-ranging group and one adult male in captivity in Shennongjia National Park, China. We selected 162 high-quality recordings to extract 14 acoustic parameters based on the source-filter theory. Results showed that each of all parameters significantly differed among individuals, while pairwise comparisons failed to detect any parameter that was different between all pairs. Furthermore, a discriminant function analysis indicated that the correct assignment rate was 80.2% (cross-validation: 67.3%), greater than expected by chance (14.3%). In conclusion, we found evidence that coo calls of adult male R. roxellana allowed the reliable accuracy of individual discrimination complementarily enhanced by multiple acoustic parameters. The results of our study point to the selective pressures acting on individual discrimination via vocal signals in a highly gregarious forest-living primate. [ABSTRACT FROM AUTHOR]

Abstract: Individualistic contact calls facilitate mother‐offspring reunion after separation. However, in many mammals, both the acoustic structure and individuality of contact calls differ between mother and young. In contrast, in Siberian wapiti Cervus elaphus sibiricus, contact calls are similar in the acoustics between mother and young, whereas effects of this similarity on vocal individuality were not investigated. In this study, we analyzed acoustic differences between closed‐mouth (nasal) and open‐mouth (oral) contact calls and examined individuality of the most usual oral calls of 19 Siberian wapiti (9 hinds and 10 5–6‐month adolescents) emitted in response to mother‐offspring separation. In the oral calls, the values of frequency and power variables were higher than in the nasal calls. Calls of hinds and adolescents did not differ by the maximum fundamental frequency and duration, whereas the peak frequency was higher in the young. Discriminant function analysis (DFA) based on 11 acoustic variables of oral calls accurately classified to individual 92.5% of hind calls and 96.9% of adolescent calls (chi‐square test for differences between hinds and adolescents, p = 0.19). Variables mainly contributing to vocal identity (duration, start, and maximum fundamental frequency) were the same in calls of mothers and adolescents. We conclude that similarities in the acoustics calls of mothers and adolescents mean that they do not differ in their potential for encoding individual identity, suggesting a mutual process of mother‐offspring vocal recognition in Siberian wapiti. [ABSTRACT FROM AUTHOR]

The risk of overestimating the number of nocturnal owls during a census is substantial when the territory density is high and no individual signature is available. The tawny owl voice was demonstrated to be individual, but no statistical technique evaluated to date is suitable for a census of this species. To overcome the problem, the combination of two methods is suggested in this study: (1) the Visual Spectrographic Comparison (VSC), a bioacoustics tool which tries to separate owls’ voices classifying the spectrograms of their calls based on their visual characteristics, and (2) the extensively used technique of Mapping Method (MM). The technique was applied to a dense population of tawny owls living in an isolated deciduous wood of northern Italy. Fourteen territorial males were individuated in the area, resulting a density of 6.0 pairs/km2. Most of the home ranges seem to overlap substantially, an evidence not in step with the common idea of high territoriality of the species. Since the technique is believed to be exhaustive, a future monitoring of this population could be precise, cheap and very informative. This technique could be easily extended to other elusive species that show individual vocal cues. [ABSTRACT FROM AUTHOR]

Censusing nocturnal species such as the Tawny Owl (Strix aluco) living in a dense population can lead to an overestimate if individual signatures are not available. A technique that separates the individualistic call of the Tawny Owl could be a useful tool for an exhaustive census. Six Tawny Owl males were followed for nine months; 654 vocalizations were analysed. Three methods - Spectrographic Cross Correlation (SPCC), Acoustic Space (AS) and Visual Spectrogram Comparison (VSC) - were tested to assess their ability to classify the typical male call. For SPCC, 10 randomly selected hoots for each male were compared: the distributions of correlation coefficients differed in only 26.7% of the cases when intra and inter individual variability are compared. For AS, all the spectrograms were measured through 13 parameters and intra and inter individual distances were compared: the interval containing 95.4% of intra-individual measures also contained 95.9% of inter-individual comparisons. Both SPCC and AS are considered not to be able to adequately separate subjects. For VSC, 31 randomly selected hoots were visually compared by 5 helpers; their classifications were compared pairwise and with the real situation; operators correctly identified a male in 70% of cases (mean = 70.4 SD = 5.4). If we integrate VSC with information coming from field notes, we have a more powerful tool than the mapping method. It is plausible that this technique can be useful for an exhaustive census of Tawny Owl populations living at high densities. [ABSTRACT FROM AUTHOR]

All four nightjar species resident in Peninsular Malaysia are vocally distinct, yet they remain little studied. Conventional field methods based on visual cues to study diurnal species may be impractical for nightjars. Alternatively, aural survey can potentially be applied on nightjars provided that individuality in their vocalisations can be proven. Our study aimed to determine the vocal individuality of the common, large-tailed nightjar (Caprimulgus macrurus) in oil palm smallholdings and an isolated forest patch located in Selangor, Peninsular Malaysia. From the call recordings obtained from 22 individuals, results of the Kruskal-Wallis analysis revealed significant differences in all the nine vocal parameters (call length, interquartile range bandwidth, low, high, average, centre and peak frequencies as well as first and third quartile frequencies) measured among individual nightjars (p < 0.001) regardless of study sites. Discriminant Function Analysis showed that more than 94.5% of original grouped cases were correctly classified. This implied that the majority of vocalizations can be assigned to individual birds based on the parameters measured. This study demonstrated the occurrence of vocal individuality in the large-tailed nightjar and such a finding pertaining to distinct vocalisations at the individual level will compensate for the limited access to visual cues in field surveys, as with the case for all nocturnal birds. [ABSTRACT FROM PUBLISHER]

The ability to identify individuals within a population is often essential for a detailed understanding of the ecology and conservation of a species. However, some species, including large parrots, are notoriously difficult to catch and mark for individual identification. Palm cockatoos (Probosciger aterrimus) are a large, poorly understood species of parrot which are likely in severe decline within the eastern part – and possibly the western part – of their range on Cape York Peninsula, Australia. Here, we investigated whether three different palm cockatoo call types are sufficiently individually distinctive to function as a non-invasive “marker” for identifying individuals over time. Using Discriminant Function Analysis, overall identification accuracy among 12 putative individuals for all call types was 81% (i.e. 148 out of 183 calls were assigned to the correct individual) on the basis of multiple temporal, energy (amplitude) and frequency measurements on the spectrogram. For three different call types, individual identification accuracy among males and females ranged from 69 to 95%. However, based on a limited sample sizes of five putative individuals between years, our data suggest that individual call structure, as quantified by call parameters, was not stable between years. We discuss the applicability of these results for future studies of palm cockatoos and other parrot species. [ABSTRACT FROM AUTHOR]

The ability to discriminate between individuals on the basis of call features has proven to be a useful tool for monitoring rare, nocturnal and cryptic bird species. In this study, vocal individuality was assessed in a population of Great Spotted Kiwi (Apteryx haastii) in the Hawdon Valley, New Zealand. Acoustic recorders were installed near the nest-sites of seven pairs between November 2012 and March 2013. Recorders were again installed at the new nesting sites for three of these same pairs in the following season (September-December 2013). Temporal and spectral parameters of calls were measured and stepwise discriminant function analysis was used to determine whether these parameters were effective in discriminating between individuals. The analyses indicated that Great Spotted Kiwi vocalisations were highly individualised. Male individuals were classified with an accuracy of 95.7%, on the basis of seven parameters, and females with an accuracy of 90%, on the basis of five call parameters. Individuals could also be accurately identified between years, suggesting that the individual features of calls are temporally stable. These findings suggest that Great Spotted Kiwi vocalisations could be used for acoustic identification purposes. [ABSTRACT FROM PUBLISHER]

Like many owl species, Sunda Scops-Owls ( Otus lempiji) are difficult to monitor using traditional survey techniques, because of their nocturnal habits, secretive nature, and cryptic coloration. Individual variation in vocalizations could potentially be used to distinguish individuals of this owl species, as has been demonstrated for many bird species. The objectives of this study were to describe the territorial call of Sunda Scops-Owls, to determine whether the calls can be distinguished individually, and to examine whether the calls from the same individuals were stable over time. We analyzed 75 recordings collected from 12 owls from December 2014 to June 2015 in a lowland forest and oil palm smallholdings in Selangor State, Peninsular Malaysia. Using two temporal parameters and six frequency parameters derived from spectrogram, we employed ANOVA tests and found significant differences for all parameters among individual owls. Discriminant function analysis correctly classified 97.1% of the owl calls to the correct individuals. Based on the Wilcoxon signed-rank test, all vocal parameters did not vary significantly for the six birds that were vocally active over two predetermined survey sessions within the breeding period. Our results demonstrated that Sunda Scops-Owls can be identified individually by their vocalizations. This implies that assessing vocal individuality can be useful as a noninvasive method for surveying the Sunda Scops-Owls and the method should be further tested for other little-known owl species in the tropics. [ABSTRACT FROM AUTHOR]

Vocal individuality could be used to estimate numbers of individuals in species otherwise difficult to monitor. However, the usefulness of this technique in providing conservation information is little studied. The vocalisations of the Corncrake show a high level of individual distinctiveness. This fact was used to examine current counting methods and estimate movement patterns within one breeding season. Information on individual identity gained from vocalisations increased census estimates by 20–30% and showed that male Corncrakes called less frequently than previous studies had suggested. Males moved greater distances in areas with lower availability of suitable habitat. The conservation implications of these results are discussed.

Acoustically identifying individuals may be a helpful technique when it is necessary to monitor animal populations over space and time. Previous studies have largely focused on the theoretical exploitation of vocal individuality or have looked at a small number of individuals. Here, we examined whether vocal individuality can be used to track the movement of individuals within a population (in this case when the number of individuals is greater than 100) and unknown beforehand. As a model species, we used the Corncrake ( Crex crex)-a highly secretive bird whose calls are characterized by an individual-specific feature: pulse-to-pulse duration (PPD). When we performed classical discriminant function analyses on PPD, we correctly identified a high percentage of individuals (>98 %), even when sample size was larger than 100. However, a comparison of PPD similarity within and between individuals showed that, while birds can be correctly discriminated, unambiguous identification is impossible when the number of individuals is unknown beforehand. Therefore, we were only able to assess the probability that two calls belonged to the same individual. The results of this study show that acoustic identification in the Corncrake, and probably in other animal species, is mainly useful in detecting general behavioral patterns within populations. For instance, we discovered that more than 50 % of males change territories during the breeding season, probably to find females. Physical marking methods seem to be more reliable to tracking specific individuals. However, those methods usually consider limited numbers of individuals. Therefore, generalizing results to the population scale can also be misleading. [ABSTRACT FROM AUTHOR]

Movements of animals at large spatial scales are important in ecology and conservation biology, but current methods for monitoring long-distance movements (e.g. ringing or telemetry) are resource demanding and limit sample sizes. Many birds have individually characteristic calls and songs, and recordings may provide an alternative method for monitoring movements. Previous studies have shown that Corncrake Crex crex night-time calls are individually characteristic. We recorded and analysed Corncrake calls from 60 different territories (30 % of all known territories) in two widely separated areas of Norway in one breeding season to assess the potential of recordings to identify individuals that had moved. Due to extensive mowing of meadows, many territories were used for only a short time, and Corncrakes appeared in new places throughout the breeding season, suggesting movements. By using recordings from the same territory during different nights as a measure of variability within individuals, and recordings from different territories during the same night as a measure of variability between individuals, discriminant analyses indicated that 86 pairwise comparisons of calls from different territories had a high probability (≥0.80) of being from the same bird. Movements could be excluded for 20 of those pairs (23 %) because observations in the two territories overlapped in time. In another 26 cases (30 %), there was overlap in observation dates with other pairs that included the same recording. Thus, chance similarity between different individuals is a problem for individual recognition. Overlap in time decreased with increasing call similarity and, for pairs with very high call similarity (probability ≥0.95), only 5 % overlapped in time. Depending on degree of similarity in calls, the data suggested that 18-48 % of males made movements >10 km, and that the 60 recording sites only represented 31-45 different males. In conclusion, analyses of call recordings suggested that long-distance movements occurred, although positive identification of individual movements is difficult because the likelihood of chance similarity increases with the increasing number of birds recorded. [ABSTRACT FROM AUTHOR]

Individually stereotyped vocalizations often play an important role in relocation of offspring in gregarious breeders. In phocids, mothers often alternate between foraging at sea and attending their pup. Pup calls are individually distinctive in various phocid species. However, experimental evidence for maternal recognition is rare. In this study, we recorded Weddell seal ( Leptonychotes weddellii) pup vocalizations at two whelping patches in Atka Bay, Antarctica, and explored individual vocal variation based on eight vocal parameters. Overall, 58% of calls were correctly classified according to individual. For males ( n= 12) and females ( n= 9), respectively, nine and seven individuals were correctly identified based on vocal parameters. To investigate whether mothers respond differently to calls of familiar vs. unfamiliar pups, we conducted playback experiments with 21 mothers. Maternal responses did not differ between playbacks of own, familiar, and unfamiliar pup calls. We suggest that Weddell seal pup calls may need to contain only a critical amount of individually distinct information because mothers and pups use a combination of sensory modalities for identification. However, it cannot be excluded that pup developmental factors and differing environmental factors between colonies affect pup acoustic behavior and the role of acoustic cues in the relocation process. [ABSTRACT FROM AUTHOR]

Abstract: Frequent mother–pup separations and reunions occurring in the South American sea lion Otaria flavescens require a well-developed individual recognition system. Individuality in mothers’ and pups’ calls of this species has been found in Península Valdés (PV), Argentina (with individuality rates of 95% and 89%, respectively). In order to test the hypotheses of ecological constraints (i.e., population density, habitat) and geographic variation affecting the characteristics and/or the individuality of vocalizations, we studied another population at Isla de Lobos (IL), Uruguay, separated by approx. 1200km from PV. DFAs showed classification rates of 63.2% in mothers and 53.3% in pups. This lower degree of individuality can be explained by differences in population density. Differences in acoustic characteristics were also found: at IL mother and pup calls tended to be shorter in duration and mother calls lower-pitched. This can be explained by an adaptation to the local environment: at IL sea lions breed in sympatry with South American fur seals in an obstructed habitat whereas PV sea lions are the unique species in the colony constituted by an open habitat. Finally, the acoustic differences can also be a consequence of the genetic isolation that has been found between these two colonies of O. flavescens. [Copyright &y& Elsevier]

The article presents a study that examines the structure and individual variation of songs of Brownish-flanked Bush Warbler in Southwestern China. The study analyses frequency and temporal characteristics of the birds' recorded songs and reveals uniqueness of its repertoire that is predominantly composed by two song types that are alternately delivered. A discriminant analysis reveals distinctiveness of the songs and that 98% of it have two notes and 99% of it have three notes.

Vocal individuality varies between species and/or ontogenesis stages depending on needs in the vocal recognition, but also estimation of individual differences depends on the method of analysis. We studied pair-specific differences of duets elicited by mating pairs of Siberian crane Grus leucogeranus. We quantitatively described the duet structure and compared visual and statistical classification methods of pair identification by duet. Three methods were used: discriminant analysis, method of classification trees and visual classification of spectrogram. We found significant interpair differences. The pairs differ by duet structure that is by the ratio of male- and female-initiated duets and by the ratio of the number of male to female calls; temporal-frequency duet characteristics are pair-specific, too. All methods showed high interpair differences, which exceeded random values significantly. Discriminant analysis stepwise procedure based on 11 parameters resulted in 97.3% of correctly assigned duets. Human observers correctly assigned 80.7% of spectrograms. Our data provide a basis for remote monitoring of this endangered species with a wild population of only 3,000 birds. [ABSTRACT FROM AUTHOR]

The article discusses results of a study that explores the variation in pup vocalizations of Weddell seal Leptonychotes weddellii at two whelping patches in Atka Bay, Antarctica. The study showed that 58 percent of all calls were correctly classified according to individual while 75 percent for males and 78 percent for females were correctly identified based on their vocal parameters. Based on results of playback experiments with 21 mothers, maternal behavior did not differ between playbacks of own, familiar and unfamiliar pup calls. It concludes that Weddell seal pup calls do not need to be individually distinctive because mothers rely primarily on spatial and/or olfactorial cues to relocate their pups.

This study compares the ability of four classification methods to distinguish between songs of individual Mexican Antthrush Formicarius moniliger: self-organizing maps (SOMs), discriminant function analysis, fuzzy logic and hidden Markov models. Recordings were made under field conditions in a Mexican rainforest. Two types of data were analysed - recordings from birds that had been ringed and identified to sex, and recordings from birds that had been identified based on their recording location and song timing. An event detector extracted song features and SOMs were used to confirm the number of individuals recorded. The SOM separated all five ringed birds successfully, and also differentiated two other birds that were not identified while vocalising. The three supervised learning methods correctly classified over 97% of songs to individual from the set of identified recordings. Tests with songs for predicted, rather than known, individuals yielded more variable results across methods, with results ranging from 77.8% to 93.9% correctly identified. The respective merits of the three supervised classification procedures are discussed for automated recording, detection and classification. [ABSTRACT FROM AUTHOR]

The cryptic plumage and nocturnal nature of the great gray owl (Strix nebulosa) make it difficult to study in its densely forested habitat. We investigated whether the vocalizations of individual great gray owls could be distinguished and used as a tool for population survey and monitoring. We recorded 312 territorial calls produced by 14 male and 11 female great gray owls between March and July 2006 and 2007 in the Sierra Nevada range of California, USA. We recorded 19 owls on multiple occasions within a season and 8 owls between seasons. We extracted 17 frequency and 15 temporal variables from the sonograms of each call. Discriminant analysis selected 9 variables and classified 92.8% of calls to the correct individual within a season; 71.4% of calls were classified to the correct individual between seasons. Our results indicate that territorial calls could be used to monitor individual great gray owls for both short- and long-term studies. Vocal individuality could be useful as a noninvasive method to improve census estimates and yield information on site fidelity, turnover rates, seasonal movements, and behavioral traits of great gray owls. [ABSTRACT FROM AUTHOR]

The article discusses research on the variations in vocalizations of the endangered southwestern willow flycatcher or Empidonax traillii extimus. The researchers used discriminant function analysis and trained artificial neural networks to determine the vocal individuality of the species. The researchers found population-level vocal variations in three different populations, including Roosevelt Lake and San Pedro River in Arizona and in Kern River, California.

The Woodcock Scolopax rusticola is a difficult species to survey in the breeding season because of its cryptic plumage and, with the exception of courtship flights, secretive behaviour. Sparse data from general bird surveys prohibit reliable estimation of population sizes and trends, and a new species-specific method to provide baseline information on population status and to enable reliable future monitoring is required. Counts of displaying, or ‘roding’, males at dawn or dusk potentially provide such a method but their value is unclear because it is impossible for an observer to distinguish different birds. We examined the vocal individuality of 39 roding males and were able to attribute calls to individuals correctly in 95% of cases on the basis of five parameters measured from spectrograms. Using calls, we determined the number of individual males at 43 sites. Roding activity differed between males at one site, with the two most active birds accounting for, on average, 55 and 27% of passes. There was no evidence of sequential roding by different males. We quantified the relationship between numbers of males and numbers of passes of roding birds during a 1-h period at dusk. This relationship was not affected by region, month, habitat or woodland size class. We conclude that counts of roding males provide a suitable index for monitoring populations of this species. [ABSTRACT FROM AUTHOR]

The focus of this study was to determine whether individual vocal identification of Scops Owls Otus scops was possible and if there was a stability of the hoot-calls over a short time period in the same individuals. Spontaneous vocalizations of 13 owls were recorded in 2004 in Southern Tuscany, Italy. Visual analysis of spectrograms and quantitative multivariate analysis of six vocal features showed marked individual differences. In some owls a repertoire of two different hoot types was found. In 2005, 10 Scops owls were recorded three times in the same breeding season (2 hours and 10 days after the first session). Statistical analysis of data showed that 60% of owls did not change call features over time. However a slight but significant variability between successive vocal performances of the same owl was found in 40% of cases. This variability may decrease the recognition power by acoustic analysis. To overcome this obstacle I suggest a multi step qualitative/quantitative approach. A Difference Index (DI) was calculated to set a threshold between the slight intra-individual and the very high inter-individual variability. This method allowed the recognition of calls of each owl recorded over time in 2005. [ABSTRACT FROM AUTHOR]