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Vocal similarity in long-distance and short-distance vocalizations in raven pairs (Corvus corax) in captivity
Behavioural Processes 142 (2017) 1–7
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Vocal similarity in long-distance and short-distance vocalizations in raven pairs (Corvus corax) in captivity
MARK
⁎
Eva Maria Luefa, , Andries Ter Maatb, Simone Pikac,d a
Seoul National University, College of Education, Department of Foreign Languages, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea Max Planck Institute for Ornithology, Department of Behavioural Neurobiology, Eberhard-Gwinner-Strasse 6, 82319 Seewiesen, Germany c Max Planck Institute for Ornithology, Humboldt Research Group ‘Evolution of Communication’, Virtual Geesehouse, Eberhard-Gwinner-Strasse 6, 82319 Seewiesen, Germany d Max Planck Institute for the Sciences of Human History, Humboldt Research Group, Virtual Geesehouse, 07743 Jena, Germany b
A R T I C L E I N F O
A B S T R A C T
Keywords: Common long-distance calls Communication Long-distance calls Raven (Corvus corax) Raven communication Short-distance calls Short-distance calls vocal similarity Vocalizations Vocal similarity
Vocal interactions in many birds are characterized by imitation or the matching of vocalizations whereby one individual makes its vocalizations more similar to those of a conspecific. This behaviour is aided by vocal learning, which allows birds to change the vocalizations already in their repertoires, or to add new ones. The majority of studies on vocal similarity have been focussing on the songs of birds rather than their calls, with evidence for vocal similarity in calls being rather scarce. Here, we investigated whether ravens make their calls acoustically similar to one another by analysing the extent to which short- and long-distance calls of their vocal repertoires exhibited vocal similarity. Our results showed that long-distance calls, but not short-distance calls, are highly similar between pair partners. This effect may be explained by the different functions underlying short- and long-distance communication in ravens, with vocal similarity possibly being scaffolded by specific social matrices such as pair-bonds and/or strong social relationships.
1. Introduction Vocal interactions in many birds are characterized by imitating or matching the vocalizations of another bird, whereby one individual makes its vocalizations more similar to those of a conspecific (Beecher et al., 2000; Mundinger, 1970; Scarl and Bradbury, 2009; Vehrencamp, 2001; Zann, 1990). This process is aided by vocal learning, which enables birds to make adaptations to their vocal repertoires. For instance, they can change previously learned vocalizations or add completely new ones (Janik and Slater, 1997; Tyack, 2008). Producing vocalizations similar to those of another individual is a common phenomenon in many species of birds (as well as in humans: Giles, 2008) and serves a variety of functions in social interactions among conspecifics (see, e.g. Farabaugh et al., 1994; Mundinger, 1979). There are many ways how vocal similarity in birds can arise. Vocal convergence, for instance, describes the process whereby two individuals (or whole groups) attune the acoustical features of their vocal utterances to one another to achieve the production of an identical vocalization (Scarl and Bradbury, 2009). The matching of vocalizations can be driven by one individual imitating the call of another, or by all interactants in a group creating a new vocalization together. The extent to which similarity is exhibited may differ between species depending ⁎
Corresponding author. E-mail addresses: [email protected], [email protected] (E.M. Luef).
http://dx.doi.org/10.1016/j.beproc.2017.05.013 Received 18 May 2016; Received in revised form 6 May 2017; Accepted 16 May 2017 Available online 20 May 2017 0376-6357/ © 2017 Elsevier B.V. All rights reserved.
on the function of the vocalization. For example, orange-fronted conures (Aratinga canicularis) are able to match their calls after one short vocal interaction with another individual (Balsby and Scarl, 2008). In contrast, in black-capped chickadees (Poecile atricapillus) the acoustic matching of calls takes longer and the effort required may represent a kind of investment which ensures an individual’s allegiance to a particular flock (Mammen and Nowicki, 1981; Nowicki, 1989). The majority of studies on vocal similarity to date have been focussing on the songs of birds rather than their calls (Kondo and Watanabe, 2009; Kroodsma, 1982; Marler, 2004; Vehrencamp, 2001). Songs and calls can be distinguished from one another based on several factors. In general, songs have been defined as longer and more complex vocalizations produced by males during breeding seasons. Calls are shorter and simpler, and may be produced by both sexes throughout the year (see Catchpole and Slater, 1995). This definition is, however, not unproblematic as female song has been shown to be a common phenomenon (see, e.g. Odom et al., 2014). There is a predictable stereotypy to song production concerning when and how it is produced; call production, on the other hand, is more unpredictable and context-specific as it is highly dependent on the social circumstances a bird experiences (Marler, 2004). In addition, functional differences between songs and calls also play a role, with the
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Table 1 The table shows the individuals observed in this study, their names, sex, age (in years), location, origin, year of pairing and breeding success (yes or no) with their respective pair partner. Pair
Name
Sex
Age (in years)
Location
Origin
Time of pairing with current partner
Breeding success with current partner
1 1 2 2 3 3 4 4 5 5
Anton Elen Jakob H Biene Jakob S Lena Jakob M Munin Rudi Hexe
Male Female Male Female Male Female Male Female Male Female
1 1 6 2 1 1 9 23 14 12
Seewiesen Seewiesen Klein-Auheim Klein-Auheim Seewiesen Seewiesen Munich Munich Kronberg Kronberg
Haidlhof, Austria Haidlhof, Austria Wiesbaden, Germany Bielefeld, Germany Haidlhof, Austria Haidlhof, Austria Prague, Czech Republic Metelen, Germany Wuppertal, Germany Pri (Czech Republic)
2012 2012 2012 2012 2012 2012 2005 2005 2001 2001
No No No No Yes Yes No No Yes Yes
whether raven pairs acoustically match their calls by analysing the extent to which calls in their short-distance and long-distance repertoires exhibit vocal similarity. Since it has been observed that raven pair partners copy each other’s sounds for immediate recognition at a distance and also to enhance their social bond (Goodwin, 1976; Gwinner, 1964), we expected to find high degrees of vocal similarity within paired partners. Previous studies have shown that many birds − including ravens − use two main call categories: short-distance calls − so-called ‘soft calls’ − and long-distance calls − also referred to as ‘loud calls’ (see, e.g. Naguib and Wiley, 2001; Reichard and Anderson, 2015; ter Maat et al., 2014; Titus, 1998; Zollinger and Brumm, 2015). In ravens, soft calls are used for affiliative expressions between paired or strongly-bonded individuals whereas loud calls can facilitate communication over longer distances (Gwinner, 1964). Our research question therefore concerned whether vocal similarities can be found in the soft and/or the loud calls of paired partners. To answer this question, we analysed soft and loud calls separately with a special focus on the degree of shared acoustical parameters within and between different pairs. Since soft calls may be used to strengthen the pair bond and loud calls to promote group cohesion with the pair partner (Gwinner, 1964), we predicted to find a high degree vocal similarity in both call categories.
maintenance of social coherence, alarm calling and food calling being important social contexts for call production. Songs are most frequently used for courtship and territorial defense purposes (see Marler, 2004). While vocal similarity between conspecifics has frequently been demonstrated in bird song (see, e.g. Catchpole and Slater, 1995; Mundinger, 1982; Nelson and Poesel, 2009; Payne, 1983; Payne and Payne, 1993; Vehrencamp, 2001; Zann, 1990), evidence for vocal similarity in calls is limited (Hile et al., 2005; Mammen and Nowicki, 1981; Tyack, 2008). In particular, the similarity of calls within pairbonded individuals is an understudied phenomenon. There is some evidence for vocal convergence within pair-bonded individuals in budgerigar males (Melopsittacus undulatus), which learn the contact call of the females they are courting (Hile et al., 2005). However, after the mating season, they revert back to their “own“ call, suggesting that vocal convergence in this species may represent only a temporary feature during courtship (Moravec et al., 2006). In red crossbills (Loxia curvirostra), pair partners create acoustically novel calls that are then shared exclusively between the pair (Groth, 1993; Mundinger, 1979; Sewall, 2009), suggesting that both partners converge acoustically. Chaffinches (Fringilla coelebs), chickadees (Poecile atricapillus), goldfinches (Spinus tristis) and siskins (Spinus pinus) are also prone to vocal convergence once they are exposed to the calls of other conspecifics (see Mammen and Nowicki, 1981; Marler and Mundinger, 1971; Mundinger, 1970; Nowicki, 1989). In addition, anecdotal evidence for the vocal convergence of calls stems from members of the corvid family – common ravens (Corvus corax) – who ‘lure their missed and desired pair partner’ (Gwinner and Kneutgen, 1962), by using calls which are normally exclusively and preferably used by the pair partner itself. Common ravens belong to the Passeriformes, and are renowned for their imitative vocal skills (Gwinner, 1964). Ravens living in captive environments have been reported to imitate their human caregivers, artificial sounds as well as sounds of other species (Gwinner and Kneutgen, 1962; Heinrich, 1989; Lorenz, 1931). Both sexes of this bird species engage in vocal imitation but the degree of pair-distinctive call sharing in raven communication is still unknown. Some degree of vocal convergence has been described for wild ravens in contexts of long-distance calling and among neighbouring same-sex individuals (Enggist-Düblin and Pfister, 2002). Ravens rely heavily on cooperation between pair partners, with whom they form enduring, lifelong monogamous relationships (Gwinner, 1964; Heinrich, 1999). So far, research on the vocal similarity of bird calls has mainly been focussing on selected calls of a particular study species as opposed to the entire call repertoire (see, e.g. Mammen and Nowicki, 1981; Nowicki, 1989). Often, these selected calls include contact calls (Barnardius zonarius: Baker, 2000; Aratinga canicularis: Bradbury et al., 2001; see, e.g. Fringilla coelebs: Detert and Bergmann, 1984; Molothrus ater: Rothstein and Fleischer, 1987; Amazona auropalliata: Wright, 1996). Comparative investigations of vocal similarity including the entire call repertoire of individual birds are rare and have not been conducted on any member of the corvid family. Here, we investigated
2. Methods 2.1. Subjects and study sites Our study species was the common raven (Corvus corax), whose vocal repertoire has previously been described by Gwinner (1964) and Enggist-Düblin and Pfister (2002). Audio-recordings of captive birds’ vocalizations were captured from five pairs living at and originating from different locations in Europe (see Table 1). 2.2. Data collection Data recordings started in January 2013 and were carried out until July 2013 (before, during, and after the breeding season). Communicative vocal interactions between the pairs were recorded for approximately 1.5 h per day using a Sennheiser microphone (ME67) situated outside their aviaries that was connected to a digital audio recorder (Zoom H4n). Calls were sampled at 44.1 kHz with a 16-bit depth. All applicable international, national, and institutional guidelines for the care and use of animals were followed. The recording procedure included 30-min of focal animal sampling per day followed by 30 min of group protocols (Lehner, 2002; Martin and Bateson, 1994). In addition, video recordings were made of the birds’ behaviour during these communicative interactions. Each pair was recorded for an average of 19.2 h (SD = 5.07) over a four-month period. Recordings ended when the recording of new call types had reached an asymptote, meaning no new vocalizations were heard for seven consecutive days. 2
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individual raven, and hence, one cell per dyad. Into the first matrix we entered the dyad class (pair partner, same-sex, neither nor) of the specific dyad, the second matrix contained the average similarity scores between calls of the two individuals of the dyad. The mean for each class of dyad was then calculated and squared deviations of these means from the mean of the whole matrix were determined as the test statistic. Subsequently, we permuted one matrix with a Mantel-like permutation procedure (i.e. rows and columns were permuted simultaneously, Sokal and Rohlf, 1995) and calculated the test statistics as for the original data but based on the permuted matrices. Note that each permutation (i.e., randomization) creates a data set for which the null-hypothesis is, by definition, true since the data are randomized. Note also that the permutation procedure retains the non-independence of the data through randomizing entire rows and columns, whereby applying the same random reordering to both rows and columns also keeps values on the diagonal (similarity of individuals with themselves) which are not relevant for the question addressed here. We conducted a total of 1000 permutations into which we included the original data as one permutation. We then determined the P-value as the proportion of test statistics that were at least as large as that of the original data. We conducted one overall significance test for each call type and post-hoc pairwise comparisons of the dyad types (as part of the same permutation procedure). The test was repeated twice, once for soft calls and once for loud calls and conducted with a function written in R (R Team, 2015) by Roger Mundry. A detailed description of the whole procedure (including a figure) can be found in Sokal and Rohlf (1995, p. 818–819). Note that with ten individuals the sample is clearly large enough to enable significance; however, the power of the test will certainly be limited.
2.3. Data analyses Vocalizations were extracted from the recorded sound files manually. Only those vocalizations which did not show temporal overlap with the partner’s calls or other background noises were selected for acoustic analysis. To analyse the acoustic parameters of the vocalizations, the vocalizations produced by the animals were classified and time-stamped using segmentation followed by sorting of calls into clusters (ter Maat et al., 2014). Vocalizations were extracted from the sound files using a trigger level set by the user which were then converted into sonograms assembled from 512 point fast Fourier transforms (FFT; Intel MLK library). Calls were sampled at a rate of 22050 samples per second at an 11025 Hz range. The bitmap pictures of call spectrograms show 0–9991 Hz (232 vertical pixels of the 256 that were actually used for the calculations). A 512 point FFT (covering 23 ms) was calculated every 8 msec, which gives an overlap of about 66%. The source code of the program is freely available at https:// github.com/ornith. The relevant code (written in Pascal) that was used to calculate the acoustic parameters is called “wav_count.PAS”. From the recorded vocalizations the average frequency, the modal frequency, the first peak, Wiener entropy, the locations of the positive and negative peaks of the signal's amplitude envelope, the duration, and their standard deviations were calculated (see Supplementary material for descriptions of the measured parameters). Subsequently, the sounds were clustered (see supplementary Fig. S1a for exemplary results of the program clusters). Sorting of calls was done using a k-means clustering algorithm (Hartigan, 1975) starting with two clusters and splitting new clusters off, one at a time. After a final check of all sounds to sort out mistakes, the recordings were analysed using custom software written in Delphi Pascal for Windows and C++ on Apple Macintosh (ter Maat et al., 2014). This procedure produced a table of all acoustic parameters that were measured for a particular call. From these data distance matrices (Euclidian distances) were determined which were then used to calculate the degree of difference in the calls of all individuals in the sample. These distance scores will henceforth be referred to as “similarity scores”. These similarity scores indicate that calls are more similar if the score approaches “0” and becomes more dissimilar as the score increases. All statistical operations were carried out using JMP10 or R (R Team, 2015). We investigated all soft calls and all loud calls that were recorded from the subjects. The distinction between short-distance (soft calls) and long-distance (loud calls) vocalizations was primarily based on the context of call occurrences. Soft calls were produced when the animals were situated in close proximity to each other (so-called contact sit), and were uttered during courtship and affiliative behaviours; loud calls were produced when the animals were farther apart from each other, and engaged in behaviours such as advertising their territories or interacting with other animals, including other ravens (Dabelsteen et al., 1998; Gwinner, 1964). So-called “self-assertive displays” (Gwinner, 1964; Heinrich, 1999) were only recorded when they occurred in the context of territorial advertisement or defense, such as when wild ravens or humans approached the aviaries. Either or both individuals in a raven pair could be involved in calling and these cases were counted as loud calls since they were directed towards outsiders. To determine the extent to which these vocalizations exhibited similarity, soft and loud calls were analysed separately between the following dyads: (a) pair partners, (b) same-sex individuals, and (c) non-pair members. To test whether similarity scores differed between different classes of dyads (paired partner, same-sex, neither nor), we used a permutation test (Adams and Anthony, 1996; Manly, 1997). The permutation test we carried out was similar to an ANOVA; however, to account for the nonindependence of the similarity scores (arising from the fact that each individual provided similarity scores with all others), we determined the P-value based on repeated reshuffling of the data. More specifically, we first created two matrices with one row and one column per
2.4. Ethics statement Data collection was carried out in accordance with the U.K. Animals (Scientific Procedures) Act, 1986 and associated guidelines, EU Directive 2010/63/EU for animal experiments and the National Institutes of Health guide for the care and use of Laboratory animals (NIH Publications No- 8023, revised 1978). 3. Results 3.1. Repertoire size Overall, we recorded a total of 1299 vocalizations (soft calls: 402, loud calls: 897) from ten paired individuals. Each individual produced an average of 40.2 (SD = 35.6) soft and 89.7 (SD = 59.3) loud calls. Cluster analysis (see Fig. 1 and Figs. S1a and S1b in the supplementary materials) yielded a total of eight different types of soft calls and 32 different types of loud calls (see Figs. 2 and 3 and supplementary Figs. S2–S5 for examples of call types). The females produced on average 5.2 different soft call types and 6 loud call types. The males uttered on average 3.8 different soft call types and 8.4 loud call types. An overview of the acoustic measurements of all soft and loud calls can be found in the supplementary material (Tables S1 and S2). On average, each pair produced 5.6 soft call types and 8.8 loud call types during the study period. Each pair shared between zero and seven of the soft call types and between two and nine of the loud call types. Table 2 provides an overview of the vocal repertoires of the individual subjects and pairs. 3.2. Soft and loud call similarity To investigate whether paired ravens produce similar vocalizations within the pair, we compared similarity scores between pair-partners with those of non-pair members. The mean similarity score between pair-partners was 3.27 (SD = 0.91) whereas the mean similarity score between non-pair members was 3.84 (SD = 0.28). 3
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Fig. 1. Illustration of cluster discrimination by Sound Explorer. Shown are loud call clusters 9, 10, 11, 26, and 32, which are clearly separable even based on two or three (out of 12) parameters. The clusters were chosen because of their similar number of calls in order to achieve a clear picture.
Fig. 3. Example of a series of loud calls. Loud calls were not filtered and the sonograms were produced with a gain of 36 dB and a range of 22 dB. FFT size was 256, and a Hanning window was applied.
Fig. 2. Example of a soft call. The soft call recordings were amplified by 18 dB, then filtered (100 or 384 Hz high pass filter). The sonograms were produced with a gain of 40 dB and a range at 22 dB.
similarity scores than paired individuals (mean similarity score for same-sex partners = 3.63 SD = 0.24). See Fig. 5. To exclude the possibility that the similarity scores were influenced by the fact that four birds grew up at the same location (Haidlhof, see Tables 1 and 3), we contrasted similarity scores between birds that had the same place of origin with those which did not across the three dyad types (pair partners/same-sex partners/non-pair members, see Table 3). The vocal repertoires (soft and loud calls) of the ravens from the same place of origin were not more similar to one another than to the mean of the whole study population.
The analysis of the soft calls did not reveal differences in similarity scores across the three dyad types (permutation test, overall comparison: test statistic = 0.0029, p = 0.952). See Fig. 4. The analysis of the loud calls revealed that the overall similarity between pair-partners was significant (permutation test, overall comparison: test statistic = 0.0203, p = 0.002). More specifically, the comparison of pair partners and non-pair members showed differences between the two (permutation test: p = 0.001), with pair partners displaying a higher degree of similarity than non-pair members (mean similarity score for pair partners = 3.44, SD = 0.27; mean similarity score for non-pair members = 3.63, SD = 0.31). Additionally, the comparison of pair-partners and same-sex partners revealed a significant result (p = 0.005) whereby same-sex partners showed lower
4. Discussion The aim of this study was to investigate whether raven pairs 4
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Table 2 Different call types as used by each individual: short-distance (soft) and long-distance (loud) vocalizations.
Site 1 (SW I) Site 2 (SW II) Site 3 (M) Site 4 (KlA) Site 5 (K)
Total number of call types
Soft call types
Nr. of soft call types shared
Loud call types
Nr. of loud call types shared
♂
13
6
6
7
5
♀ ♂
13 12
8 7
7
5 5
2
♀ ♂ ♀ ♂
9 12 9 10
7 2 0 1
♀ ♂ ♀
12 14 13
4 3 7
0 1
3
2 10 9 9 8 11 6
9 8
6
Fig. 5. Loud calls similarity scores across the three dyad types: Other (each individual with every other individual excluding the pair-partner and individuals of the same sex), same-sex (all individuals of the same sex), and partner (pair-partner). Points show the average per individual and dyad type, and points connected by a dashed line represent data from the same individual. Also see table S4b for detailed similarity scores.
Table 3 Vocal similarity scores among Seewiesen ravens (from same juvenile group). Seewiesen individuals (place of origin: Haidlhof, Austria)
Soft calls
Mean across entire sample
Loud calls
Mean across entire sample
Pair partners Same sex Non-pair members
4.22 4.2 4.23
3.1 4.1 4.1
4.45 3.56 3.75
3.44 3.62 3.63
between populations or differences in social structure that, in turn, lead to differences in the usage of vocalizations. In addition, environmental influences may also have an impact (see Catchpole and Slater, 1995; for a review). However, concerning the results of our study these factors alone are not sufficient to explain the present findings. If genetic differences between the studied raven pairs could explain our results, the soft call repertoires would have been equally affected and thus different between individuals and pairs. The social environment of all animals in the present study was very similar as we only studied cohoused, mated pair partners. The environmental surroundings in which the investigated pairs lived were also similar, with all of them being held in comparable captive housing conditions. A hypothesis that could explain our results is that soft calls are largely determined by genetic factors in ravens, whereas loud calls are influenced by learning processes. Vocal plasticity has most commonly been described for the songs of songbirds but not for their calls (Kondo and Watanabe, 2009). In general, calls are often described as being largely genetically determined whereas songs are usually learned (see Marler, 2004; for a review). This difference is likely due to the function that calls fulfill within the birds’ repertoires. For instance, contact calls are used to maintain the coherence of a social group, alarm calls warn conspecifics of a specific source of danger, and food calls are used to attract others to a food source (see Marler, 2004). In these instances the recognition of calls by conspecifics is important, and variation in the acoustic structure of calls should be relatively small to be correctly interpreted by their targeted receivers. On the other hand, Heinrich (1989, 1999) showed that ravens acquire and develop their diverse call types during their time in non-breeding groups characterized by fissionfusion dynamics. Ravens also are able to use these calls to attract mates. Individual call types can vary to a great extent between individuals but
Fig. 4. Soft call similarity scores across the three dyad types: Other (each individual with every other individual excluding the pair-partner and individuals of the same sex), samesex (all individuals of the same sex), and partner (pair-partner). Points show the average per individual and dyad type, and points connected by a dashed line represent data from the same individual. Also see Table S4a for detailed similarity scores.
acoustically match their vocal repertoires. To do so, we studied the vocal behaviour of captive ravens and compared the acoustic similarities of both their short-distance (soft) call and their long-distance (loud) call repertoires. We addressed the question of whether vocal similarity occurs primarily in soft and/or in loud calls. We found that the size of call repertoires ranged from twelve to 18 different vocalization types per pair, with a minimum of two soft calls, a maximum of seven soft calls, a minimum of two loud calls and a maximum of nine loud calls per pair. Subsequent analyses revealed that similarity scores differed between soft and loud calls. The analysis of soft calls did not provide any differences between unfamiliar same-sex individuals, non-pair individuals and pair partners. The soft call repertoires of all individuals were found to be similar, and vocal similarity was not higher in individuals of the same sex or pair partners. In contrast, pair-partners showed a higher degree of acoustic similarity than other investigated dyads (same-sex, non-pair individuals) in their loud call repertoires. These results suggest that vocal similarity is high in ravens’ long-range vocalizations, but not in their close-range vocal repertoire. It has been argued that similarities in vocalizations need not be the result of learning processes (Catchpole and Slater, 1995; Janik and Slater, 1997). They can, for instance, be a result of genetic differences 5
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tion, immediate location of the pair partner, or joint territorial defense (Brown and Farabaugh, 1997; Gwinner and Kneutgen, 1962), the main function of soft calling is the affiliative exchange between highly familiar individuals in a relatively “private” setting (Gwinner, 1964). It seems, therefore, that call types differ in the degree of genetic conservation, with loud calls being more prone to vocal adjustment than soft calls. Our analyses of different call categories (short- and long-distance) showed clear differences concerning the degrees of shared acoustic parameters in ravens. However, there are some limitations to our study. Due to the fact that we recorded a smaller number of soft calls (8 in total) than loud calls (32 in total), it may be that the probability of finding shared acoustic characteristics differs between the two samples. In addition, one female did not contribute to the soft call analysis as she was never heard to utter these calls. This female and her partner had not reproduced in the past decade, and also did not engage in affiliative behaviours (e.g. preening and contact-sit) during our study periods. Hence, the lack of a strong social bond may explain the absence of soft calling in this particular female. Furthermore, the small sample size of the present study warrants some caution in the generalization of the results while the exact mechanisms of call matching remain elusive. Vocal similarity could arise from imitation on the part of one individual, creation of a (new) vocalization on the part of both individuals, or a combination of both factors. We hope that our results will inspire future studies that will be able to shed more light on these fascinating topics. To summarise, the present study adds a new facet to the research on call learning in songbirds by providing the first evidence that vocal similarity is unequally distributed in short-distance and long-distance calls of ravens. Functional differences between soft and loud calls in ravens may well be the driving forces behind the observed phenomenon. Future studies — whose focus lies on determining specific functions or meanings of calls — may ultimately be able to explain the role of vocal similarity in raven calls. In addition, the study adds to the growing body of work emphasizing the role specific social matrices such as pair-bonds and strong social relationships play in the development of sophisticated communicative skills (Pika and Bugnyar, 2011).
still remain effective as contact calls for social behaviours (Boeckle et al., 2012). Detailed future studies of the function of soft calls in ravens are thus important to draw definite conclusions as to why the soft call repertoire is less variable than the loud call repertoire. Some degree of call learning has been described for a small number of birds (reviewed by Farabaugh et al., 1994; Marler, 2004) and often song-learning birds also learn at least some of their calls (Farabaugh et al., 1994; Güttinger, 1974; Mundinger, 1970, 1979; Nicolai, 1959; Nowicki, 1989). Learning of calls in songbirds may be confined to only one sex, such as the contact call (or loud call) in zebra finches (Taeniopygia guttata, see Simpson and Vicario, 1990; Zann, 1990). Furthermore, while in some species learning is an open-ended process continuing into adulthood (Loxia curvirostra: Mundinger, 1979), in other species it may be confined to certain sensitive periods during early ontogeny (see Marler, 2004). Even though evidence for it may be scarcer, dialectal variation does not only occur in bird song but can also be found in the calls of songbirds such as common chaffinches (Fringilla coelebs: Sick, 1939), brown-headed cowbirds (Molothrus ater: Rothstein et al., 1986), or black-capped chickadees (Poecile atricapillus: Miyasato and Baker, 1999). Our findings of similar raven calls within the pair bond thus extent the previous literature on call learning in songbirds by further specifying that not all call types uniformly display a learned component. With regard to the calls investigated in this study, the reason that soft calls appear to have a largely genetic basis while loud calls seem to be largely learned may lie in the different functions that these two types of vocalization serve. Soft calls are predominantly used for the expression of affiliation and to maintain and strengthen the pair bond (Gwinner, 1964). They thus may need to be ‘universal’ across larger raven populations enabling the birds to migrate and also still be able to communicate successfully with potential partners. Vocalizations upon which crucial aspects of survival depend, are prime candidates for being more genetically determined and the soft calls of ravens may fall into this category. Loud calls, on the other hand, seem to serve functions that require collective communicative efforts, such as territorial defence, location of the partner, and vocal recognition (Gwinner, 1964). They thus may require more adaptability on the part of each individual raven. In particular, the location and recognition of the partner over longer distances and when out of sight may be facilitated by call similarity. Recent studies showed that ravens recognize and remember other conspecifics based on their long-distance calls, and can also recall the relationships they had with these individuals in the past (Boeckle and Bugnyar, 2012; Massen et al., 2014). These studies suggest that an important aspect of loud calls is to convey individuality. Long-distance calling faces the additional challenge of sound transmission through the environment. An alternative hypothesis for vocal similarity in raven loud calls may be that the environment exerts some influence over vocal production and ravens counter problems with sound transmission over longer distances through vocal similarity. This does not necessarily preclude the notion of individuality or adaptation to the pair partner playing a role in shaping the vocal repertoire as all three may, to some degree, influence vocality. Complex vocal repertoires (such as those of songbirds or humans, for instance) are prone to influence from a gamut of factors related to sociality, individuality, as well as environmental events. Overall, the male ravens in our sample displayed a larger repertoire of loud calls than females, whereas females displayed a larger soft call repertoire than males. This finding could be explained by size differences between the sexes. Males, being the larger sex, may take the lead in territorial disputes, thereby requiring a larger loud call repertoire than females. In a study of the vocal perception patterns of loud calls, male ravens seemed more interested in changes to the call patterns of potential rivals than females (Reber et al., 2016). Vocal recognition of conspecifics might thus play a larger role in the social life and interactions of male ravens. While loud, long-distance calling mainly concerns vocal recogni-
Acknowledgements This work was made possible by a Sofja Kovalevskaja-Award of the Alexander von Humboldt-Foundationx (Germany) awarded to SP. The funding agency had no involvement in the preparation of the study. The authors have no conflict of interest to declare with their sponsors. We are grateful to the following people and institutions for their help and support for our research: M. Ebel at Fasanerie Klein Auheim, S. Sprenzel at Zoo Munich, and J. Beckmann at Opel-Zoo Kronberg. We thank two reviewers and J. Beckmann for valuable comments on the manuscript. Furthermore, we are indebted to R. Mundry for statistical help and advice, and W. Wickler for stimulating discussions of vocal learning in songbirds. In addition, we thank M. Krug for steady, administrative support and Katharina Piehler and Frank Lehman for their valuable help with the ravens. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.beproc.2017.05.013. References Adams, D.C., Anthony, C.D., 1996. Using randomization techniques to analyse behavioural data. Anim. Behav. 51, 733–738. Baker, M.C., 2000. Cultural diversification in the flight call of the ringneck parrot in Western Australia. Condor 102, 905–910. Balsby, J.S., Scarl, J.C., 2008. Sex-specific responses to vocal convergence and divergence of contact calls in orange-fronted conures (Aratinga canicularis). Proc. Biol. Sci. 275,
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Miyasato, L.E., Baker, M.C., 1999. Black-capped chickadee call dialects along a continuous habitat corridor. Anim. Behav. 57, 1311–1318. Moravec, M.L., Striedtler, G.F., Burley, N.T., 2006. Assortative pairing based on contact call similarity in budgerigars, Melopsittacus undulatus. Ethology 112, 1108–1116. Mundinger, P.C., 1970. Vocal imitation and individual recognition of finch calls. Science 168, 480–482. Call learning in the Carduelinae: ethological and systematic considerations. Syst. Zool. 28, 270–283. Microgeographic and macrogeographic variation in the acquired vocalizations of birds. In: Kroodsma, D.E., Miller, E.H. (Eds.), Acoustic Communication in Birds. Academic Press, New York, pp. 147–208. Naguib, M., Wiley, R.H., 2001. Estimating the distance to a source of sound: mechanisms and adaptations for long-range communication. Anim. Behav. 62, 825–837. Nelson, D.A., Poesel, A., 2009. Does learning produce song conformity or novelty in white-crowned sparrows, Zonotrichia leucophrys. Anim. Behav. 78, 433–440. Nicolai, J., 1959. Familientradition in der gesangsentwicklung des gimpels (Pyrrhula pyrrhula L.). J. Ornithol. 100, 39–46. Nowicki, S., 1989. Vocal plasticity in captive black-capped chickadees: the acoustic basis and rate of call convergence. Anim. Behav. 37. Odom, K.J., Hall, M.L., Riebel, K., Omland, K.E., Langmore, N.E., 2014. Female song is widespread and ancestral in songbirds. Nat. Commun. 5, 1–6. Payne, R.B., Payne, L.L., 1993. Song copying and cultural transmission in indigo buntings. Anim. Behav. 46, 1045–1065. Payne, R.B., 1983. The social context of song mimicry: song matching dialects in Indigo Buntings (Passerina cyanea). Anim. Behav. 31, 788–805. Pika, S., Bugnyar, T., 2011. The use of referential gestures in ravens (Corvus corax) in the wild. Nat. Commun. 2, 560. R Team, D.C., 2015. R: A Language and Environment for Statistical Computing. Vienna, Austria. Reber, S.A., Boeckle, M., Szipl, G., Janisch, J., Bugnyar, T., Fitch, W.T., 2016. Territorial ravens pairs are sensitive to structural changes in simulated acoustic displays of conspecifics. Anim. Behav. 116, 153–162. Reichard, D.G., Anderson, R.C., 2015. Why signal softly? The structure, function and evolutionary significance of low-amplitude signals. Anim. Behav. 105, 253–265. Rothstein, S.I., Fleischer, R.C., 1987. Vocal dialects and their possible relation to honest status signalling in the brown-headed cowbird. Condor 89, 1–23. Rothstein, S.I., Yokel, D.A., Fleischer, R.C., 1986. Social dominance, mating and spacing systems, female fecundity, and vocal dialects in captive and free-ranging brownheaded cowbirds. In: Johnston, R.F. (Ed.), Current Ornithology. Plenum Press, New York, pp. 127–185. Scarl, J.C., Bradbury, J.W., 2009. Rapid vocal convergence in an Australian cockatoo, the galah Eolophus roseicapillus. Anim. Behav. 77, 1019–1026. Sewall, K.B., 2009. Limited adult vocal learning maintains call dialects but permits pairdistinctive calls in red crossbills. Anim. Behav. 77, 1303–1311. Sick, H., 1939. Über die dialektbildung beim regenruf des buchfinken. J. Ornithol. 87, 568–592. Simpson, H.B., Vicario, D.S., 1990. Brain pathways for learned and unlearned vocalizations differ in zebra finches. J. Neurosci. 10, 1541–1556. Sokal, R.R., Rohlf, F.J., 1995. Biometry: The Principles and Practice of Statistics in Biological Research. Freeman & Co., New York. ter Maat, A., Sagunsky, H., Seltmann, S., Gahr, M., 2014. Zebra finch mates use their forebrain song system in unlearned call communication. PLoS One 9, e109334. Titus, R.C., 1998. Short-range and long-range songs: use of two acoustically distinct song classes by dark-eyed juncos. Auk 115, 386–393. Tyack, P.L., 2008. Convergence of calls as animals form social bonds, active compensation for noisy communication channels, and the evolution of vocal learning in mammals. J. Comp. Psychol. 122, 319–331. Vehrencamp, S.L., 2001. Is song-type matching a conventional signal of aggressive intentions? Proc. Biol. Sci. 268, 1637–1642. Wright, T.F., 1996. Regional dialects in the contact call of a parrot. Proc. Biol. Sci. 263, 867–872. Zann, R., 1990. Song and call learning in wild zebra finches in south-east Australia. Anim. Behav. 40, 811–828. Zollinger, S.A., Brumm, H., 2015. Why birds sing loud songs and why they sometimes don't. Anim. Behav. 105, 289–295.
2147–2154. Beecher, M.D., Campbell, S.E., Burt, J.M., Hill, C.E., Nordby, J.C., 2000. Song-type matching between neighbouring song sparrows. Anim. Behav. 59, 21–27. Boeckle, M., Bugnyar, T., 2012. Long-term memory for affiliates in ravens. Curr. Biol. 22, 801–806. Boeckle, M., Szipl, G., Bugnyar, T., 2012. Who wants food? Individual characteristics in raven yells. Anim. Behav. 84, 1123–1130. Bradbury, J.W., Cortopassi, K.A., Clemmons, J.R., 2001. Geographical variation in the contact calls of orange-fronted parakeets. Auk 118, 958–972. Brown, E.D., Farabaugh, S.M., 1997. What birds with complex social relationships can tell us about vocal learning: vocal sharing in avian groups. In: Snowdon, C.T., Hausberger, M. (Eds.), Social Influences on Vocal Development. Cambridge University Press, Cambridge, UK, pp. 98–127. Catchpole, C.D., Slater, P.L.B., 1995. Bird Song: Themes and Variations. Cambridge University Press, New York. Dabelsteen, T., McGregor, P.K., Lampe, H.M., Langmore, N.E., Holland, J., 1998. Quiet song in birds: an overlooked phenomenon. Bioacoustics 9, 80–105. Detert, H., Bergmann, H.-H., 1984. Regenrufdialekte von Buchfinken (Fringilla coelebs L.): Untersuchungen an einer Population von Mischrufern. Ökologie der Vögel 6, 101–118. Enggist-Düblin, P., Pfister, U., 2002. Cultural transmission of vocalizations in ravens, Corvus corax. Anim. Behav. 64, 831–841. Farabaugh, S.M., Linzenbold, A., Dooling, R.J., 1994. Vocal plasticity in budgerigars (Melopsittacus undulatus): evidence for social factors in the learning of contact calls. J. Comp. Psychol. 108, 81–92. Güttinger, H.R., 1974. Gesang des Grünlings (Chloris chloris): Lokale Unterschiede und Entwicklung bei Schallisolation. J. Ornithol. 115, 321–337. Giles, H., 2008. Communication accommodation theory. In: Baxter, L.A., Braithewaite, D.O. (Eds.), Engaging Theories in Interpersonal Communication: Multiple Perspectives. Sage, Thousand Oaks, CA, pp. 161–173. Goodwin, D., 1976. Crows of the World. Cornell University Press, New York. Groth, J.G., 1993. Call matching and positive assortative mating in red crossbills. Auk 110, 398–401. Gwinner, E., Kneutgen, J., 1962. Über die biologische Bedeutung der zweckdienlichen Anwendung erlernter Laute bei Vögeln. Z. Tierpsychol. 19, 692–696. Gwinner, E., 1964. Untersuchungen über das ausdrucks- und sozialverhalten des kolkraben (Corvus corax). Z. Tierpsychol. 21, 145–178. Hartigan, J.A., 1975. Clustering Algorithms. John Wiley & Sons Inc, Hoboken NJ. Heinrich, B., 1989. Ravens in Winter. Simon & Schuster, New York. Heinrich, B., 1999. Mind of the Raven. Harper Collins, New York. Hile, A.G., Burley, N.T., Coopersmith, C.B., Foster, V., Striedtler, G.F., 2005. Effects of male vocal learning on female behavior in the budgerigar, Melopsittacus undulatus. Ethology 111, 901–923. Janik, V.M., Slater, P.J.B., 1997. Vocal learning in mammals. Adv. Stud. Behav. 26, 59–99. Kondo, N., Watanabe, S., 2009. Contact calls: information and social function. Jpn. Psychol. Res. 51, 197–208. Kroodsma, D.E., 1982. Learning and the ontogeny of sound signals in birds. In: Kroodsma, D.E., Miller, E.H. (Eds.), Acoustic Communication in Birds. Academic Press, New York, pp. 11–23. Lehner, P.N., 2002. Handbook of Ethological Methods. Cambridge University Press, Cambridge, UK. Lorenz, K., 1931. Beiträge zur Ethologie sozialer Corviden. J. Ornithol. 79, 67–120. Mammen, D.L., Nowicki, S., 1981. Individual differences and within-flock convergence in chickadee calls. Behav. Ecol. Sociobiol. 9, 179–186. Manly, B.F.J., 1997. Randomization, Bootstrap and Monte Carlo Methods in Biology. Chapman & Hall, London. Marler, P., Mundinger, P., 1971. Vocal learning in birds. In: Moltz, H. (Ed.), Ontogeny of Vertebrate Behavior. Academic Press, New York, pp. 389–450. Marler, P., 2004. Bird calls: their potential for behavioral neurobiology. Ann. N. Y. Acad. Sci. 1016, 31–44. Martin, P., Bateson, P., 1994. Measuring Behaviour: An Introductory Guide. Cambridge University Press, London. Massen, J.J.M., Pasukonis, A., Schmidt, J., Bugnyar, T., 2014. Ravens notice dominance reversals among conspecifics within and outside their social group. Nat. Commun. 5, 3679.
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Vocal similarity in long-distance and short-distance vocalizations in raven pairs (Corvus corax) in captivity
MARK
⁎
Eva Maria Luefa, , Andries Ter Maatb, Simone Pikac,d a
Seoul National University, College of Education, Department of Foreign Languages, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea Max Planck Institute for Ornithology, Department of Behavioural Neurobiology, Eberhard-Gwinner-Strasse 6, 82319 Seewiesen, Germany c Max Planck Institute for Ornithology, Humboldt Research Group ‘Evolution of Communication’, Virtual Geesehouse, Eberhard-Gwinner-Strasse 6, 82319 Seewiesen, Germany d Max Planck Institute for the Sciences of Human History, Humboldt Research Group, Virtual Geesehouse, 07743 Jena, Germany b
A R T I C L E I N F O
A B S T R A C T
Keywords: Common long-distance calls Communication Long-distance calls Raven (Corvus corax) Raven communication Short-distance calls Short-distance calls vocal similarity Vocalizations Vocal similarity
Vocal interactions in many birds are characterized by imitation or the matching of vocalizations whereby one individual makes its vocalizations more similar to those of a conspecific. This behaviour is aided by vocal learning, which allows birds to change the vocalizations already in their repertoires, or to add new ones. The majority of studies on vocal similarity have been focussing on the songs of birds rather than their calls, with evidence for vocal similarity in calls being rather scarce. Here, we investigated whether ravens make their calls acoustically similar to one another by analysing the extent to which short- and long-distance calls of their vocal repertoires exhibited vocal similarity. Our results showed that long-distance calls, but not short-distance calls, are highly similar between pair partners. This effect may be explained by the different functions underlying short- and long-distance communication in ravens, with vocal similarity possibly being scaffolded by specific social matrices such as pair-bonds and/or strong social relationships.
1. Introduction Vocal interactions in many birds are characterized by imitating or matching the vocalizations of another bird, whereby one individual makes its vocalizations more similar to those of a conspecific (Beecher et al., 2000; Mundinger, 1970; Scarl and Bradbury, 2009; Vehrencamp, 2001; Zann, 1990). This process is aided by vocal learning, which enables birds to make adaptations to their vocal repertoires. For instance, they can change previously learned vocalizations or add completely new ones (Janik and Slater, 1997; Tyack, 2008). Producing vocalizations similar to those of another individual is a common phenomenon in many species of birds (as well as in humans: Giles, 2008) and serves a variety of functions in social interactions among conspecifics (see, e.g. Farabaugh et al., 1994; Mundinger, 1979). There are many ways how vocal similarity in birds can arise. Vocal convergence, for instance, describes the process whereby two individuals (or whole groups) attune the acoustical features of their vocal utterances to one another to achieve the production of an identical vocalization (Scarl and Bradbury, 2009). The matching of vocalizations can be driven by one individual imitating the call of another, or by all interactants in a group creating a new vocalization together. The extent to which similarity is exhibited may differ between species depending ⁎
Corresponding author. E-mail addresses: [email protected], [email protected] (E.M. Luef).
http://dx.doi.org/10.1016/j.beproc.2017.05.013 Received 18 May 2016; Received in revised form 6 May 2017; Accepted 16 May 2017 Available online 20 May 2017 0376-6357/ © 2017 Elsevier B.V. All rights reserved.
on the function of the vocalization. For example, orange-fronted conures (Aratinga canicularis) are able to match their calls after one short vocal interaction with another individual (Balsby and Scarl, 2008). In contrast, in black-capped chickadees (Poecile atricapillus) the acoustic matching of calls takes longer and the effort required may represent a kind of investment which ensures an individual’s allegiance to a particular flock (Mammen and Nowicki, 1981; Nowicki, 1989). The majority of studies on vocal similarity to date have been focussing on the songs of birds rather than their calls (Kondo and Watanabe, 2009; Kroodsma, 1982; Marler, 2004; Vehrencamp, 2001). Songs and calls can be distinguished from one another based on several factors. In general, songs have been defined as longer and more complex vocalizations produced by males during breeding seasons. Calls are shorter and simpler, and may be produced by both sexes throughout the year (see Catchpole and Slater, 1995). This definition is, however, not unproblematic as female song has been shown to be a common phenomenon (see, e.g. Odom et al., 2014). There is a predictable stereotypy to song production concerning when and how it is produced; call production, on the other hand, is more unpredictable and context-specific as it is highly dependent on the social circumstances a bird experiences (Marler, 2004). In addition, functional differences between songs and calls also play a role, with the
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Table 1 The table shows the individuals observed in this study, their names, sex, age (in years), location, origin, year of pairing and breeding success (yes or no) with their respective pair partner. Pair
Name
Sex
Age (in years)
Location
Origin
Time of pairing with current partner
Breeding success with current partner
1 1 2 2 3 3 4 4 5 5
Anton Elen Jakob H Biene Jakob S Lena Jakob M Munin Rudi Hexe
Male Female Male Female Male Female Male Female Male Female
1 1 6 2 1 1 9 23 14 12
Seewiesen Seewiesen Klein-Auheim Klein-Auheim Seewiesen Seewiesen Munich Munich Kronberg Kronberg
Haidlhof, Austria Haidlhof, Austria Wiesbaden, Germany Bielefeld, Germany Haidlhof, Austria Haidlhof, Austria Prague, Czech Republic Metelen, Germany Wuppertal, Germany Pri (Czech Republic)
2012 2012 2012 2012 2012 2012 2005 2005 2001 2001
No No No No Yes Yes No No Yes Yes
whether raven pairs acoustically match their calls by analysing the extent to which calls in their short-distance and long-distance repertoires exhibit vocal similarity. Since it has been observed that raven pair partners copy each other’s sounds for immediate recognition at a distance and also to enhance their social bond (Goodwin, 1976; Gwinner, 1964), we expected to find high degrees of vocal similarity within paired partners. Previous studies have shown that many birds − including ravens − use two main call categories: short-distance calls − so-called ‘soft calls’ − and long-distance calls − also referred to as ‘loud calls’ (see, e.g. Naguib and Wiley, 2001; Reichard and Anderson, 2015; ter Maat et al., 2014; Titus, 1998; Zollinger and Brumm, 2015). In ravens, soft calls are used for affiliative expressions between paired or strongly-bonded individuals whereas loud calls can facilitate communication over longer distances (Gwinner, 1964). Our research question therefore concerned whether vocal similarities can be found in the soft and/or the loud calls of paired partners. To answer this question, we analysed soft and loud calls separately with a special focus on the degree of shared acoustical parameters within and between different pairs. Since soft calls may be used to strengthen the pair bond and loud calls to promote group cohesion with the pair partner (Gwinner, 1964), we predicted to find a high degree vocal similarity in both call categories.
maintenance of social coherence, alarm calling and food calling being important social contexts for call production. Songs are most frequently used for courtship and territorial defense purposes (see Marler, 2004). While vocal similarity between conspecifics has frequently been demonstrated in bird song (see, e.g. Catchpole and Slater, 1995; Mundinger, 1982; Nelson and Poesel, 2009; Payne, 1983; Payne and Payne, 1993; Vehrencamp, 2001; Zann, 1990), evidence for vocal similarity in calls is limited (Hile et al., 2005; Mammen and Nowicki, 1981; Tyack, 2008). In particular, the similarity of calls within pairbonded individuals is an understudied phenomenon. There is some evidence for vocal convergence within pair-bonded individuals in budgerigar males (Melopsittacus undulatus), which learn the contact call of the females they are courting (Hile et al., 2005). However, after the mating season, they revert back to their “own“ call, suggesting that vocal convergence in this species may represent only a temporary feature during courtship (Moravec et al., 2006). In red crossbills (Loxia curvirostra), pair partners create acoustically novel calls that are then shared exclusively between the pair (Groth, 1993; Mundinger, 1979; Sewall, 2009), suggesting that both partners converge acoustically. Chaffinches (Fringilla coelebs), chickadees (Poecile atricapillus), goldfinches (Spinus tristis) and siskins (Spinus pinus) are also prone to vocal convergence once they are exposed to the calls of other conspecifics (see Mammen and Nowicki, 1981; Marler and Mundinger, 1971; Mundinger, 1970; Nowicki, 1989). In addition, anecdotal evidence for the vocal convergence of calls stems from members of the corvid family – common ravens (Corvus corax) – who ‘lure their missed and desired pair partner’ (Gwinner and Kneutgen, 1962), by using calls which are normally exclusively and preferably used by the pair partner itself. Common ravens belong to the Passeriformes, and are renowned for their imitative vocal skills (Gwinner, 1964). Ravens living in captive environments have been reported to imitate their human caregivers, artificial sounds as well as sounds of other species (Gwinner and Kneutgen, 1962; Heinrich, 1989; Lorenz, 1931). Both sexes of this bird species engage in vocal imitation but the degree of pair-distinctive call sharing in raven communication is still unknown. Some degree of vocal convergence has been described for wild ravens in contexts of long-distance calling and among neighbouring same-sex individuals (Enggist-Düblin and Pfister, 2002). Ravens rely heavily on cooperation between pair partners, with whom they form enduring, lifelong monogamous relationships (Gwinner, 1964; Heinrich, 1999). So far, research on the vocal similarity of bird calls has mainly been focussing on selected calls of a particular study species as opposed to the entire call repertoire (see, e.g. Mammen and Nowicki, 1981; Nowicki, 1989). Often, these selected calls include contact calls (Barnardius zonarius: Baker, 2000; Aratinga canicularis: Bradbury et al., 2001; see, e.g. Fringilla coelebs: Detert and Bergmann, 1984; Molothrus ater: Rothstein and Fleischer, 1987; Amazona auropalliata: Wright, 1996). Comparative investigations of vocal similarity including the entire call repertoire of individual birds are rare and have not been conducted on any member of the corvid family. Here, we investigated
2. Methods 2.1. Subjects and study sites Our study species was the common raven (Corvus corax), whose vocal repertoire has previously been described by Gwinner (1964) and Enggist-Düblin and Pfister (2002). Audio-recordings of captive birds’ vocalizations were captured from five pairs living at and originating from different locations in Europe (see Table 1). 2.2. Data collection Data recordings started in January 2013 and were carried out until July 2013 (before, during, and after the breeding season). Communicative vocal interactions between the pairs were recorded for approximately 1.5 h per day using a Sennheiser microphone (ME67) situated outside their aviaries that was connected to a digital audio recorder (Zoom H4n). Calls were sampled at 44.1 kHz with a 16-bit depth. All applicable international, national, and institutional guidelines for the care and use of animals were followed. The recording procedure included 30-min of focal animal sampling per day followed by 30 min of group protocols (Lehner, 2002; Martin and Bateson, 1994). In addition, video recordings were made of the birds’ behaviour during these communicative interactions. Each pair was recorded for an average of 19.2 h (SD = 5.07) over a four-month period. Recordings ended when the recording of new call types had reached an asymptote, meaning no new vocalizations were heard for seven consecutive days. 2
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individual raven, and hence, one cell per dyad. Into the first matrix we entered the dyad class (pair partner, same-sex, neither nor) of the specific dyad, the second matrix contained the average similarity scores between calls of the two individuals of the dyad. The mean for each class of dyad was then calculated and squared deviations of these means from the mean of the whole matrix were determined as the test statistic. Subsequently, we permuted one matrix with a Mantel-like permutation procedure (i.e. rows and columns were permuted simultaneously, Sokal and Rohlf, 1995) and calculated the test statistics as for the original data but based on the permuted matrices. Note that each permutation (i.e., randomization) creates a data set for which the null-hypothesis is, by definition, true since the data are randomized. Note also that the permutation procedure retains the non-independence of the data through randomizing entire rows and columns, whereby applying the same random reordering to both rows and columns also keeps values on the diagonal (similarity of individuals with themselves) which are not relevant for the question addressed here. We conducted a total of 1000 permutations into which we included the original data as one permutation. We then determined the P-value as the proportion of test statistics that were at least as large as that of the original data. We conducted one overall significance test for each call type and post-hoc pairwise comparisons of the dyad types (as part of the same permutation procedure). The test was repeated twice, once for soft calls and once for loud calls and conducted with a function written in R (R Team, 2015) by Roger Mundry. A detailed description of the whole procedure (including a figure) can be found in Sokal and Rohlf (1995, p. 818–819). Note that with ten individuals the sample is clearly large enough to enable significance; however, the power of the test will certainly be limited.
2.3. Data analyses Vocalizations were extracted from the recorded sound files manually. Only those vocalizations which did not show temporal overlap with the partner’s calls or other background noises were selected for acoustic analysis. To analyse the acoustic parameters of the vocalizations, the vocalizations produced by the animals were classified and time-stamped using segmentation followed by sorting of calls into clusters (ter Maat et al., 2014). Vocalizations were extracted from the sound files using a trigger level set by the user which were then converted into sonograms assembled from 512 point fast Fourier transforms (FFT; Intel MLK library). Calls were sampled at a rate of 22050 samples per second at an 11025 Hz range. The bitmap pictures of call spectrograms show 0–9991 Hz (232 vertical pixels of the 256 that were actually used for the calculations). A 512 point FFT (covering 23 ms) was calculated every 8 msec, which gives an overlap of about 66%. The source code of the program is freely available at https:// github.com/ornith. The relevant code (written in Pascal) that was used to calculate the acoustic parameters is called “wav_count.PAS”. From the recorded vocalizations the average frequency, the modal frequency, the first peak, Wiener entropy, the locations of the positive and negative peaks of the signal's amplitude envelope, the duration, and their standard deviations were calculated (see Supplementary material for descriptions of the measured parameters). Subsequently, the sounds were clustered (see supplementary Fig. S1a for exemplary results of the program clusters). Sorting of calls was done using a k-means clustering algorithm (Hartigan, 1975) starting with two clusters and splitting new clusters off, one at a time. After a final check of all sounds to sort out mistakes, the recordings were analysed using custom software written in Delphi Pascal for Windows and C++ on Apple Macintosh (ter Maat et al., 2014). This procedure produced a table of all acoustic parameters that were measured for a particular call. From these data distance matrices (Euclidian distances) were determined which were then used to calculate the degree of difference in the calls of all individuals in the sample. These distance scores will henceforth be referred to as “similarity scores”. These similarity scores indicate that calls are more similar if the score approaches “0” and becomes more dissimilar as the score increases. All statistical operations were carried out using JMP10 or R (R Team, 2015). We investigated all soft calls and all loud calls that were recorded from the subjects. The distinction between short-distance (soft calls) and long-distance (loud calls) vocalizations was primarily based on the context of call occurrences. Soft calls were produced when the animals were situated in close proximity to each other (so-called contact sit), and were uttered during courtship and affiliative behaviours; loud calls were produced when the animals were farther apart from each other, and engaged in behaviours such as advertising their territories or interacting with other animals, including other ravens (Dabelsteen et al., 1998; Gwinner, 1964). So-called “self-assertive displays” (Gwinner, 1964; Heinrich, 1999) were only recorded when they occurred in the context of territorial advertisement or defense, such as when wild ravens or humans approached the aviaries. Either or both individuals in a raven pair could be involved in calling and these cases were counted as loud calls since they were directed towards outsiders. To determine the extent to which these vocalizations exhibited similarity, soft and loud calls were analysed separately between the following dyads: (a) pair partners, (b) same-sex individuals, and (c) non-pair members. To test whether similarity scores differed between different classes of dyads (paired partner, same-sex, neither nor), we used a permutation test (Adams and Anthony, 1996; Manly, 1997). The permutation test we carried out was similar to an ANOVA; however, to account for the nonindependence of the similarity scores (arising from the fact that each individual provided similarity scores with all others), we determined the P-value based on repeated reshuffling of the data. More specifically, we first created two matrices with one row and one column per
2.4. Ethics statement Data collection was carried out in accordance with the U.K. Animals (Scientific Procedures) Act, 1986 and associated guidelines, EU Directive 2010/63/EU for animal experiments and the National Institutes of Health guide for the care and use of Laboratory animals (NIH Publications No- 8023, revised 1978). 3. Results 3.1. Repertoire size Overall, we recorded a total of 1299 vocalizations (soft calls: 402, loud calls: 897) from ten paired individuals. Each individual produced an average of 40.2 (SD = 35.6) soft and 89.7 (SD = 59.3) loud calls. Cluster analysis (see Fig. 1 and Figs. S1a and S1b in the supplementary materials) yielded a total of eight different types of soft calls and 32 different types of loud calls (see Figs. 2 and 3 and supplementary Figs. S2–S5 for examples of call types). The females produced on average 5.2 different soft call types and 6 loud call types. The males uttered on average 3.8 different soft call types and 8.4 loud call types. An overview of the acoustic measurements of all soft and loud calls can be found in the supplementary material (Tables S1 and S2). On average, each pair produced 5.6 soft call types and 8.8 loud call types during the study period. Each pair shared between zero and seven of the soft call types and between two and nine of the loud call types. Table 2 provides an overview of the vocal repertoires of the individual subjects and pairs. 3.2. Soft and loud call similarity To investigate whether paired ravens produce similar vocalizations within the pair, we compared similarity scores between pair-partners with those of non-pair members. The mean similarity score between pair-partners was 3.27 (SD = 0.91) whereas the mean similarity score between non-pair members was 3.84 (SD = 0.28). 3
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Fig. 1. Illustration of cluster discrimination by Sound Explorer. Shown are loud call clusters 9, 10, 11, 26, and 32, which are clearly separable even based on two or three (out of 12) parameters. The clusters were chosen because of their similar number of calls in order to achieve a clear picture.
Fig. 3. Example of a series of loud calls. Loud calls were not filtered and the sonograms were produced with a gain of 36 dB and a range of 22 dB. FFT size was 256, and a Hanning window was applied.
Fig. 2. Example of a soft call. The soft call recordings were amplified by 18 dB, then filtered (100 or 384 Hz high pass filter). The sonograms were produced with a gain of 40 dB and a range at 22 dB.
similarity scores than paired individuals (mean similarity score for same-sex partners = 3.63 SD = 0.24). See Fig. 5. To exclude the possibility that the similarity scores were influenced by the fact that four birds grew up at the same location (Haidlhof, see Tables 1 and 3), we contrasted similarity scores between birds that had the same place of origin with those which did not across the three dyad types (pair partners/same-sex partners/non-pair members, see Table 3). The vocal repertoires (soft and loud calls) of the ravens from the same place of origin were not more similar to one another than to the mean of the whole study population.
The analysis of the soft calls did not reveal differences in similarity scores across the three dyad types (permutation test, overall comparison: test statistic = 0.0029, p = 0.952). See Fig. 4. The analysis of the loud calls revealed that the overall similarity between pair-partners was significant (permutation test, overall comparison: test statistic = 0.0203, p = 0.002). More specifically, the comparison of pair partners and non-pair members showed differences between the two (permutation test: p = 0.001), with pair partners displaying a higher degree of similarity than non-pair members (mean similarity score for pair partners = 3.44, SD = 0.27; mean similarity score for non-pair members = 3.63, SD = 0.31). Additionally, the comparison of pair-partners and same-sex partners revealed a significant result (p = 0.005) whereby same-sex partners showed lower
4. Discussion The aim of this study was to investigate whether raven pairs 4
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Table 2 Different call types as used by each individual: short-distance (soft) and long-distance (loud) vocalizations.
Site 1 (SW I) Site 2 (SW II) Site 3 (M) Site 4 (KlA) Site 5 (K)
Total number of call types
Soft call types
Nr. of soft call types shared
Loud call types
Nr. of loud call types shared
♂
13
6
6
7
5
♀ ♂
13 12
8 7
7
5 5
2
♀ ♂ ♀ ♂
9 12 9 10
7 2 0 1
♀ ♂ ♀
12 14 13
4 3 7
0 1
3
2 10 9 9 8 11 6
9 8
6
Fig. 5. Loud calls similarity scores across the three dyad types: Other (each individual with every other individual excluding the pair-partner and individuals of the same sex), same-sex (all individuals of the same sex), and partner (pair-partner). Points show the average per individual and dyad type, and points connected by a dashed line represent data from the same individual. Also see table S4b for detailed similarity scores.
Table 3 Vocal similarity scores among Seewiesen ravens (from same juvenile group). Seewiesen individuals (place of origin: Haidlhof, Austria)
Soft calls
Mean across entire sample
Loud calls
Mean across entire sample
Pair partners Same sex Non-pair members
4.22 4.2 4.23
3.1 4.1 4.1
4.45 3.56 3.75
3.44 3.62 3.63
between populations or differences in social structure that, in turn, lead to differences in the usage of vocalizations. In addition, environmental influences may also have an impact (see Catchpole and Slater, 1995; for a review). However, concerning the results of our study these factors alone are not sufficient to explain the present findings. If genetic differences between the studied raven pairs could explain our results, the soft call repertoires would have been equally affected and thus different between individuals and pairs. The social environment of all animals in the present study was very similar as we only studied cohoused, mated pair partners. The environmental surroundings in which the investigated pairs lived were also similar, with all of them being held in comparable captive housing conditions. A hypothesis that could explain our results is that soft calls are largely determined by genetic factors in ravens, whereas loud calls are influenced by learning processes. Vocal plasticity has most commonly been described for the songs of songbirds but not for their calls (Kondo and Watanabe, 2009). In general, calls are often described as being largely genetically determined whereas songs are usually learned (see Marler, 2004; for a review). This difference is likely due to the function that calls fulfill within the birds’ repertoires. For instance, contact calls are used to maintain the coherence of a social group, alarm calls warn conspecifics of a specific source of danger, and food calls are used to attract others to a food source (see Marler, 2004). In these instances the recognition of calls by conspecifics is important, and variation in the acoustic structure of calls should be relatively small to be correctly interpreted by their targeted receivers. On the other hand, Heinrich (1989, 1999) showed that ravens acquire and develop their diverse call types during their time in non-breeding groups characterized by fissionfusion dynamics. Ravens also are able to use these calls to attract mates. Individual call types can vary to a great extent between individuals but
Fig. 4. Soft call similarity scores across the three dyad types: Other (each individual with every other individual excluding the pair-partner and individuals of the same sex), samesex (all individuals of the same sex), and partner (pair-partner). Points show the average per individual and dyad type, and points connected by a dashed line represent data from the same individual. Also see Table S4a for detailed similarity scores.
acoustically match their vocal repertoires. To do so, we studied the vocal behaviour of captive ravens and compared the acoustic similarities of both their short-distance (soft) call and their long-distance (loud) call repertoires. We addressed the question of whether vocal similarity occurs primarily in soft and/or in loud calls. We found that the size of call repertoires ranged from twelve to 18 different vocalization types per pair, with a minimum of two soft calls, a maximum of seven soft calls, a minimum of two loud calls and a maximum of nine loud calls per pair. Subsequent analyses revealed that similarity scores differed between soft and loud calls. The analysis of soft calls did not provide any differences between unfamiliar same-sex individuals, non-pair individuals and pair partners. The soft call repertoires of all individuals were found to be similar, and vocal similarity was not higher in individuals of the same sex or pair partners. In contrast, pair-partners showed a higher degree of acoustic similarity than other investigated dyads (same-sex, non-pair individuals) in their loud call repertoires. These results suggest that vocal similarity is high in ravens’ long-range vocalizations, but not in their close-range vocal repertoire. It has been argued that similarities in vocalizations need not be the result of learning processes (Catchpole and Slater, 1995; Janik and Slater, 1997). They can, for instance, be a result of genetic differences 5
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tion, immediate location of the pair partner, or joint territorial defense (Brown and Farabaugh, 1997; Gwinner and Kneutgen, 1962), the main function of soft calling is the affiliative exchange between highly familiar individuals in a relatively “private” setting (Gwinner, 1964). It seems, therefore, that call types differ in the degree of genetic conservation, with loud calls being more prone to vocal adjustment than soft calls. Our analyses of different call categories (short- and long-distance) showed clear differences concerning the degrees of shared acoustic parameters in ravens. However, there are some limitations to our study. Due to the fact that we recorded a smaller number of soft calls (8 in total) than loud calls (32 in total), it may be that the probability of finding shared acoustic characteristics differs between the two samples. In addition, one female did not contribute to the soft call analysis as she was never heard to utter these calls. This female and her partner had not reproduced in the past decade, and also did not engage in affiliative behaviours (e.g. preening and contact-sit) during our study periods. Hence, the lack of a strong social bond may explain the absence of soft calling in this particular female. Furthermore, the small sample size of the present study warrants some caution in the generalization of the results while the exact mechanisms of call matching remain elusive. Vocal similarity could arise from imitation on the part of one individual, creation of a (new) vocalization on the part of both individuals, or a combination of both factors. We hope that our results will inspire future studies that will be able to shed more light on these fascinating topics. To summarise, the present study adds a new facet to the research on call learning in songbirds by providing the first evidence that vocal similarity is unequally distributed in short-distance and long-distance calls of ravens. Functional differences between soft and loud calls in ravens may well be the driving forces behind the observed phenomenon. Future studies — whose focus lies on determining specific functions or meanings of calls — may ultimately be able to explain the role of vocal similarity in raven calls. In addition, the study adds to the growing body of work emphasizing the role specific social matrices such as pair-bonds and strong social relationships play in the development of sophisticated communicative skills (Pika and Bugnyar, 2011).
still remain effective as contact calls for social behaviours (Boeckle et al., 2012). Detailed future studies of the function of soft calls in ravens are thus important to draw definite conclusions as to why the soft call repertoire is less variable than the loud call repertoire. Some degree of call learning has been described for a small number of birds (reviewed by Farabaugh et al., 1994; Marler, 2004) and often song-learning birds also learn at least some of their calls (Farabaugh et al., 1994; Güttinger, 1974; Mundinger, 1970, 1979; Nicolai, 1959; Nowicki, 1989). Learning of calls in songbirds may be confined to only one sex, such as the contact call (or loud call) in zebra finches (Taeniopygia guttata, see Simpson and Vicario, 1990; Zann, 1990). Furthermore, while in some species learning is an open-ended process continuing into adulthood (Loxia curvirostra: Mundinger, 1979), in other species it may be confined to certain sensitive periods during early ontogeny (see Marler, 2004). Even though evidence for it may be scarcer, dialectal variation does not only occur in bird song but can also be found in the calls of songbirds such as common chaffinches (Fringilla coelebs: Sick, 1939), brown-headed cowbirds (Molothrus ater: Rothstein et al., 1986), or black-capped chickadees (Poecile atricapillus: Miyasato and Baker, 1999). Our findings of similar raven calls within the pair bond thus extent the previous literature on call learning in songbirds by further specifying that not all call types uniformly display a learned component. With regard to the calls investigated in this study, the reason that soft calls appear to have a largely genetic basis while loud calls seem to be largely learned may lie in the different functions that these two types of vocalization serve. Soft calls are predominantly used for the expression of affiliation and to maintain and strengthen the pair bond (Gwinner, 1964). They thus may need to be ‘universal’ across larger raven populations enabling the birds to migrate and also still be able to communicate successfully with potential partners. Vocalizations upon which crucial aspects of survival depend, are prime candidates for being more genetically determined and the soft calls of ravens may fall into this category. Loud calls, on the other hand, seem to serve functions that require collective communicative efforts, such as territorial defence, location of the partner, and vocal recognition (Gwinner, 1964). They thus may require more adaptability on the part of each individual raven. In particular, the location and recognition of the partner over longer distances and when out of sight may be facilitated by call similarity. Recent studies showed that ravens recognize and remember other conspecifics based on their long-distance calls, and can also recall the relationships they had with these individuals in the past (Boeckle and Bugnyar, 2012; Massen et al., 2014). These studies suggest that an important aspect of loud calls is to convey individuality. Long-distance calling faces the additional challenge of sound transmission through the environment. An alternative hypothesis for vocal similarity in raven loud calls may be that the environment exerts some influence over vocal production and ravens counter problems with sound transmission over longer distances through vocal similarity. This does not necessarily preclude the notion of individuality or adaptation to the pair partner playing a role in shaping the vocal repertoire as all three may, to some degree, influence vocality. Complex vocal repertoires (such as those of songbirds or humans, for instance) are prone to influence from a gamut of factors related to sociality, individuality, as well as environmental events. Overall, the male ravens in our sample displayed a larger repertoire of loud calls than females, whereas females displayed a larger soft call repertoire than males. This finding could be explained by size differences between the sexes. Males, being the larger sex, may take the lead in territorial disputes, thereby requiring a larger loud call repertoire than females. In a study of the vocal perception patterns of loud calls, male ravens seemed more interested in changes to the call patterns of potential rivals than females (Reber et al., 2016). Vocal recognition of conspecifics might thus play a larger role in the social life and interactions of male ravens. While loud, long-distance calling mainly concerns vocal recogni-
Acknowledgements This work was made possible by a Sofja Kovalevskaja-Award of the Alexander von Humboldt-Foundationx (Germany) awarded to SP. The funding agency had no involvement in the preparation of the study. The authors have no conflict of interest to declare with their sponsors. We are grateful to the following people and institutions for their help and support for our research: M. Ebel at Fasanerie Klein Auheim, S. Sprenzel at Zoo Munich, and J. Beckmann at Opel-Zoo Kronberg. We thank two reviewers and J. Beckmann for valuable comments on the manuscript. Furthermore, we are indebted to R. Mundry for statistical help and advice, and W. Wickler for stimulating discussions of vocal learning in songbirds. In addition, we thank M. Krug for steady, administrative support and Katharina Piehler and Frank Lehman for their valuable help with the ravens. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.beproc.2017.05.013. References Adams, D.C., Anthony, C.D., 1996. Using randomization techniques to analyse behavioural data. Anim. Behav. 51, 733–738. Baker, M.C., 2000. Cultural diversification in the flight call of the ringneck parrot in Western Australia. Condor 102, 905–910. Balsby, J.S., Scarl, J.C., 2008. Sex-specific responses to vocal convergence and divergence of contact calls in orange-fronted conures (Aratinga canicularis). Proc. Biol. Sci. 275,
6
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Miyasato, L.E., Baker, M.C., 1999. Black-capped chickadee call dialects along a continuous habitat corridor. Anim. Behav. 57, 1311–1318. Moravec, M.L., Striedtler, G.F., Burley, N.T., 2006. Assortative pairing based on contact call similarity in budgerigars, Melopsittacus undulatus. Ethology 112, 1108–1116. Mundinger, P.C., 1970. Vocal imitation and individual recognition of finch calls. Science 168, 480–482. Call learning in the Carduelinae: ethological and systematic considerations. Syst. Zool. 28, 270–283. Microgeographic and macrogeographic variation in the acquired vocalizations of birds. In: Kroodsma, D.E., Miller, E.H. (Eds.), Acoustic Communication in Birds. Academic Press, New York, pp. 147–208. Naguib, M., Wiley, R.H., 2001. Estimating the distance to a source of sound: mechanisms and adaptations for long-range communication. Anim. Behav. 62, 825–837. Nelson, D.A., Poesel, A., 2009. Does learning produce song conformity or novelty in white-crowned sparrows, Zonotrichia leucophrys. Anim. Behav. 78, 433–440. Nicolai, J., 1959. Familientradition in der gesangsentwicklung des gimpels (Pyrrhula pyrrhula L.). J. Ornithol. 100, 39–46. Nowicki, S., 1989. Vocal plasticity in captive black-capped chickadees: the acoustic basis and rate of call convergence. Anim. Behav. 37. Odom, K.J., Hall, M.L., Riebel, K., Omland, K.E., Langmore, N.E., 2014. Female song is widespread and ancestral in songbirds. Nat. Commun. 5, 1–6. Payne, R.B., Payne, L.L., 1993. Song copying and cultural transmission in indigo buntings. Anim. Behav. 46, 1045–1065. Payne, R.B., 1983. The social context of song mimicry: song matching dialects in Indigo Buntings (Passerina cyanea). Anim. Behav. 31, 788–805. Pika, S., Bugnyar, T., 2011. The use of referential gestures in ravens (Corvus corax) in the wild. Nat. Commun. 2, 560. R Team, D.C., 2015. R: A Language and Environment for Statistical Computing. Vienna, Austria. Reber, S.A., Boeckle, M., Szipl, G., Janisch, J., Bugnyar, T., Fitch, W.T., 2016. Territorial ravens pairs are sensitive to structural changes in simulated acoustic displays of conspecifics. Anim. Behav. 116, 153–162. Reichard, D.G., Anderson, R.C., 2015. Why signal softly? The structure, function and evolutionary significance of low-amplitude signals. Anim. Behav. 105, 253–265. Rothstein, S.I., Fleischer, R.C., 1987. Vocal dialects and their possible relation to honest status signalling in the brown-headed cowbird. Condor 89, 1–23. Rothstein, S.I., Yokel, D.A., Fleischer, R.C., 1986. Social dominance, mating and spacing systems, female fecundity, and vocal dialects in captive and free-ranging brownheaded cowbirds. In: Johnston, R.F. (Ed.), Current Ornithology. Plenum Press, New York, pp. 127–185. Scarl, J.C., Bradbury, J.W., 2009. Rapid vocal convergence in an Australian cockatoo, the galah Eolophus roseicapillus. Anim. Behav. 77, 1019–1026. Sewall, K.B., 2009. Limited adult vocal learning maintains call dialects but permits pairdistinctive calls in red crossbills. Anim. Behav. 77, 1303–1311. Sick, H., 1939. Über die dialektbildung beim regenruf des buchfinken. J. Ornithol. 87, 568–592. Simpson, H.B., Vicario, D.S., 1990. Brain pathways for learned and unlearned vocalizations differ in zebra finches. J. Neurosci. 10, 1541–1556. Sokal, R.R., Rohlf, F.J., 1995. Biometry: The Principles and Practice of Statistics in Biological Research. Freeman & Co., New York. ter Maat, A., Sagunsky, H., Seltmann, S., Gahr, M., 2014. Zebra finch mates use their forebrain song system in unlearned call communication. PLoS One 9, e109334. Titus, R.C., 1998. Short-range and long-range songs: use of two acoustically distinct song classes by dark-eyed juncos. Auk 115, 386–393. Tyack, P.L., 2008. Convergence of calls as animals form social bonds, active compensation for noisy communication channels, and the evolution of vocal learning in mammals. J. Comp. Psychol. 122, 319–331. Vehrencamp, S.L., 2001. Is song-type matching a conventional signal of aggressive intentions? Proc. Biol. Sci. 268, 1637–1642. Wright, T.F., 1996. Regional dialects in the contact call of a parrot. Proc. Biol. Sci. 263, 867–872. Zann, R., 1990. Song and call learning in wild zebra finches in south-east Australia. Anim. Behav. 40, 811–828. Zollinger, S.A., Brumm, H., 2015. Why birds sing loud songs and why they sometimes don't. Anim. Behav. 105, 289–295.
2147–2154. Beecher, M.D., Campbell, S.E., Burt, J.M., Hill, C.E., Nordby, J.C., 2000. Song-type matching between neighbouring song sparrows. Anim. Behav. 59, 21–27. Boeckle, M., Bugnyar, T., 2012. Long-term memory for affiliates in ravens. Curr. Biol. 22, 801–806. Boeckle, M., Szipl, G., Bugnyar, T., 2012. Who wants food? Individual characteristics in raven yells. Anim. Behav. 84, 1123–1130. Bradbury, J.W., Cortopassi, K.A., Clemmons, J.R., 2001. Geographical variation in the contact calls of orange-fronted parakeets. Auk 118, 958–972. Brown, E.D., Farabaugh, S.M., 1997. What birds with complex social relationships can tell us about vocal learning: vocal sharing in avian groups. In: Snowdon, C.T., Hausberger, M. (Eds.), Social Influences on Vocal Development. Cambridge University Press, Cambridge, UK, pp. 98–127. Catchpole, C.D., Slater, P.L.B., 1995. Bird Song: Themes and Variations. Cambridge University Press, New York. Dabelsteen, T., McGregor, P.K., Lampe, H.M., Langmore, N.E., Holland, J., 1998. Quiet song in birds: an overlooked phenomenon. Bioacoustics 9, 80–105. Detert, H., Bergmann, H.-H., 1984. Regenrufdialekte von Buchfinken (Fringilla coelebs L.): Untersuchungen an einer Population von Mischrufern. Ökologie der Vögel 6, 101–118. Enggist-Düblin, P., Pfister, U., 2002. Cultural transmission of vocalizations in ravens, Corvus corax. Anim. Behav. 64, 831–841. Farabaugh, S.M., Linzenbold, A., Dooling, R.J., 1994. Vocal plasticity in budgerigars (Melopsittacus undulatus): evidence for social factors in the learning of contact calls. J. Comp. Psychol. 108, 81–92. Güttinger, H.R., 1974. Gesang des Grünlings (Chloris chloris): Lokale Unterschiede und Entwicklung bei Schallisolation. J. Ornithol. 115, 321–337. Giles, H., 2008. Communication accommodation theory. In: Baxter, L.A., Braithewaite, D.O. (Eds.), Engaging Theories in Interpersonal Communication: Multiple Perspectives. Sage, Thousand Oaks, CA, pp. 161–173. Goodwin, D., 1976. Crows of the World. Cornell University Press, New York. Groth, J.G., 1993. Call matching and positive assortative mating in red crossbills. Auk 110, 398–401. Gwinner, E., Kneutgen, J., 1962. Über die biologische Bedeutung der zweckdienlichen Anwendung erlernter Laute bei Vögeln. Z. Tierpsychol. 19, 692–696. Gwinner, E., 1964. Untersuchungen über das ausdrucks- und sozialverhalten des kolkraben (Corvus corax). Z. Tierpsychol. 21, 145–178. Hartigan, J.A., 1975. Clustering Algorithms. John Wiley & Sons Inc, Hoboken NJ. Heinrich, B., 1989. Ravens in Winter. Simon & Schuster, New York. Heinrich, B., 1999. Mind of the Raven. Harper Collins, New York. Hile, A.G., Burley, N.T., Coopersmith, C.B., Foster, V., Striedtler, G.F., 2005. Effects of male vocal learning on female behavior in the budgerigar, Melopsittacus undulatus. Ethology 111, 901–923. Janik, V.M., Slater, P.J.B., 1997. Vocal learning in mammals. Adv. Stud. Behav. 26, 59–99. Kondo, N., Watanabe, S., 2009. Contact calls: information and social function. Jpn. Psychol. Res. 51, 197–208. Kroodsma, D.E., 1982. Learning and the ontogeny of sound signals in birds. In: Kroodsma, D.E., Miller, E.H. (Eds.), Acoustic Communication in Birds. Academic Press, New York, pp. 11–23. Lehner, P.N., 2002. Handbook of Ethological Methods. Cambridge University Press, Cambridge, UK. Lorenz, K., 1931. Beiträge zur Ethologie sozialer Corviden. J. Ornithol. 79, 67–120. Mammen, D.L., Nowicki, S., 1981. Individual differences and within-flock convergence in chickadee calls. Behav. Ecol. Sociobiol. 9, 179–186. Manly, B.F.J., 1997. Randomization, Bootstrap and Monte Carlo Methods in Biology. Chapman & Hall, London. Marler, P., Mundinger, P., 1971. Vocal learning in birds. In: Moltz, H. (Ed.), Ontogeny of Vertebrate Behavior. Academic Press, New York, pp. 389–450. Marler, P., 2004. Bird calls: their potential for behavioral neurobiology. Ann. N. Y. Acad. Sci. 1016, 31–44. Martin, P., Bateson, P., 1994. Measuring Behaviour: An Introductory Guide. Cambridge University Press, London. Massen, J.J.M., Pasukonis, A., Schmidt, J., Bugnyar, T., 2014. Ravens notice dominance reversals among conspecifics within and outside their social group. Nat. Commun. 5, 3679.
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