J Ornithol (2015) 156:533–542 DOI 10.1007/s10336-014-1153-6

ORIGINAL ARTICLE

Geographic variation in the calls of the Common Cuckoo (Cuculus canorus): isolation by distance and divergence among subspecies

Chentao Wei • Chenxi Jia • Lu Dong • Daiping Wang • Canwei Xia • Yanyun Zhang • Wei Liang

Received: 3 June 2014 / Revised: 8 November 2014 / Accepted: 19 December 2014 / Published online: 13 January 2015 Ó Dt. Ornithologen-Gesellschaft e.V. 2015

Abstract Studies on the pattern of geographic variation distance and environmental differences on call differenti- in bird vocalizations can facilitate the understanding of the ation. The results showed there to be significant differences evolutionary history of species and species differentiation. in the calls of different subspecies of the Common Cuckoo. The Common Cuckoo (Cuculus canorus) is a non-passer- Discriminant function analysis was able to correctly iden- ine widely distributed in Eurasia, and its calls are not tify 81.7 % of individuals to their original subspecies, and acquired through learning. Revealing the geographic pat- 98 % of individuals of subspecies subtelephonus were tern of Common Cuckoo calls may help our understanding correctly assigned. Differences in calls both within and of the relationship between environment, genetic differ- between subspecies were found to be significantly corre- entiation, and vocal differentiation. In the present study, lated with geographic distance, while environmental dif- geographic variation in the calls of the Common Cuckoo ferences have no important effect. Our study stressed the was investigated throughout Eurasia for the first time. Calls effect of isolation by distance on geographic variation of of different subspecies of the Common Cuckoo were non-passerine vocalization, and we infer that the great compared, and the correlations between differences in divergence in calls between different Common Cuckoo calls, geographic distance, climatic differences, and alti- subspecies may be a hint of cryptic species. tude differences were determined in order to evaluate the influence of subspecies differentiation, isolation by Keywords Common Cuckoo Á Cuculus canorus Á Eurasia Á Call variation Á Subspecies Á Isolation by distance Communicated by F. Bairlein. Zusammenfassung Electronic supplementary material The online version of this article (doi:10.1007/s10336-014-1153-6) contains supplementary Geographische Variation in den Rufen des Kuckucks material, which is available to authorized users. (Cuculus canorus): Isolation durch Entfernung und C. Wei Á L. Dong Á D. Wang Á C. Xia Á Y. Zhang Unterschiede zwischen Unterarten Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Studien u¨ber die geographischen Verteilungsmuster von College of Life Sciences, Beijing Normal University, 100875 Beijing, China Lauta¨ußerungen der Vo¨gel ko¨nnen das Versta¨ndnis der evolutiona¨ren Geschichte von Arten erleichtern. Der Ku- C. Wei Á W. Liang (&) ckuck (Cuculus canorus) ist ein in Eurasien weit verbre- Ministry of Education Key Laboratory for Tropical Animal and iteter Nichtsperlingsvogel, dessen Rufe nicht erlernt Plant Ecology, College of Life Sciences, Hainan Normal University, 571158 Haikou, China werden. Die geographische Verteilung der Kuckucksrufe e-mail: [email protected] darzustellen ko¨nnte helfen den Zusammenhang zwischen Umwelt, genetischer Differenzierung und stimmlicher C. Jia Differenzierung zu verdeutlichen. In dieser Studie wurden Key Laboratory of the Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, erstmals die geographischen Unterschiede zwischen den 100101 Beijing, China Rufen des Kuckucks in Eurasien untersucht. Die Rufe 123 534 J Ornithol (2015) 156:533–542 verschiedener Unterarten wurden verglichen und die Kor- Vocal divergence also occurs in populations that expe- relationen zwischen Unterschieden im Ruf, geographischer rience prolonged isolation (Koetz et al. 2007; Robin et al. Entfernung, klimatischer Unterschiede und Ho¨henunters- 2011; Parker et al. 2012). Genetic and cultural drift can chieden berechnet, um die Einflu¨sse von Unterartendiffer- lead to vocal differentiation, and geographic isolation can enzierung, Isolation durch Entfernung und Umweltfaktoren facilitate the accumulation of these differences in different auf Rufe zu ermitteln. Es zeigten sich signifikante Unter- populations. Subspecies differentiation represents histori- schiede in den Rufen verschiedener Unterarten des Ku- cal isolation between populations, therefore relatively large ckucks. Eine Diskriminanzanalyse war in der Lage, 81,7 % vocal differences are also prone to occur (Dingle et al. der Individuen ihrer Unterart richtig zuzuordnen und 98 % 2008; Turcokova et al. 2010). der Individuen der Unterart subtelephonus wurden richtig The Common Cuckoo (Cuculus canorus) is a migratory zugeordnet. Unterschiede in Rufen sowohl in derselben brood parasite. It breeds extensively in Eurasia and a few Unterart als auch zwischen Unterarten waren signifikant places in North Africa and winters in Africa and southern mit der geographischen Entfernung korreliert, wa¨hrend Asia. There are four Common Cuckoo subspecies, canorus, Umweltfaktoren keinen Einfluss hatten. Unsere Studie subtelphonus, bakeri, and bangsi. They differ notably in betont den Effekt der Isolation durch Entfernung auf die plumage color (Payne 2005). The Common Cuckoo is a geographischen Unterschiede in den Lauta¨ußerungen von non-passerine bird and during the breeding season, the Nichtsperlingsvo¨geln und wir schließen aus der großen males emit loud, characteristic ‘‘cu-coo’’ calls. It is gen- Variation in Rufen zwischen verschiedenen Unterarten des erally considered that its call does not vary very much Kuckucks, dass es sich um eine kryptische Art handeln across the entire distribution (Payne 2005). However, ko¨nnte. studies on the variation of Common Cuckoo calls have been either on a small-scale (Fuisz and de Kort 2007; Jung et al. 2014) or limited by a small sample size (Lei et al. 2005). There has been no investigation on the pattern of Introduction geographic variation in the calls of the Common Cuckoo over a large geographic area, and none of the previous Vocal cues play an important role in species recognition and studies discussed vocal divergence between subspecies. mate choice in birds (Marler and Slabbekoorn 2004; Catch- This species is widely distributed in Eurasia, where envi- pole and Slater 2008). Differences in vocalization among ronments can differ greatly. In addition, this cuckoo may different geographic populations can sometimes lead to be the only non-passerine species with a distribution which reproductive isolation, thereby promoting the formation of extends from sea level (in Europe and on the east coast of new species (Irwin 2000). Consequently, studies on geo- China) to high altitudes (up to 4,000 m) in the Himalayas graphic variation in songs and calls of birds are of significant and southwest China. The acoustic adaptation hypothesis importance in understanding the relationship between mating predicts that call properties are adapted to different envi- signal evolution and species differentiation. ronments. If so, Common Cuckoo calls may show rela- The song divergence of many songbirds can be tively large differences between environments and may described using the isolation by distance model (Irwin have a close correlation with environmental variables. 2000; Rivera-Gutierrez et al. 2010; Xing et al. 2013). It is According to the isolation by distance model, large dis- generally believed that these patterns are caused by cul- tances reduce the likelihood of gene flow between popu- tural drift and that differences in songs increase with lations (Wright 1943). Because the Common Cuckoo is a distance due to inaccuracies in the learning process. non-passerine, its call is affected more by genetic factors However, studies examining whether the differentiation in than by other factors such as the learning process, while the calls of suboscine and non-passerine fit the isolation genetic differentiation caused by isolation by distance may by distance model have been rare (Pe´rez-Mena and Mora also lead to vocal divergence between remote places. 2011; Lovell and Lein 2013). Non-learned calls may also Meanwhile, subspecies differentiation represents a past fit the isolation by distance model. For example, a study history of vicariance events, and differences in plumage on the calls of the Greenish Warbler (Phylloscopus tro- color indicate relatively large genetic differences between chiloides) showed that the call differentiation is correlated different Common Cuckoo subspecies, so it is also quite with geographic and genetic differences (Irwin et al. possible that there will be large vocal divergences among 2008). The calls of non-passerines are not acquired them. It has been suggested that, within the Common through learning and are therefore not subject to cultural Cuckoo species, there may exist several genetically drift. Whether the differentiation of their calls can still be divergent gentes (Gibbs et al. 2000; Fossøy et al. 2011). A described by the isolation by distance model is worth study showed there to be significant differences in the calls exploring. of the Common Cuckoo in different habitats where they 123 J Ornithol (2015) 156:533–542 535 parasitise different hosts (Fuisz and de Kort 2007). To fully Collection of climate and altitude data understand the geographic variation in Common Cuckoo calls, the ‘‘cu-coo’’ calls of Common Cuckoos were col- To test the acoustic adaptation hypothesis, climate and lected from most of their breeding area in Eurasia, and the altitude data were collected and used as indicators of the call features were compared across subspecies and habitats. environmental selective pressure. Climate data were We also analyzed the correlation between geographic dis- downloaded from http://worldclim.org (Hijmans et al. tance, climatic and attitude differences, and differences in 2005). This database integrates mean climate data collected calls. By these means, we want (1) to reveal the full geo- from 1950 to 2000 in global climate databases. Data were graphic variation pattern of cuckoo calls across the Eurasia, extracted at a resolution of approximately 1 km2 using and figure out the factors that play major roles in shaping ArcGIS (Esri, USA) according to the GPS coordinates of the pattern, and (2) to bring new insights into divergence the recording sites. For each individual, 19 bioclim vari- among cuckoo populations and subspecies. ables were obtained (Table 1). IBM SPSS20.0 (IBM, Ar- monk, NY, USA) was used for principal component analysis of the 19 variables for dimensionality reduction, Methods and principal components with eigenvalues greater than 1 were subjected to further analysis. The altitude information Collection of call samples came from the databases of the recordings, or where this information was missing, we obtained the altitudes via In 2012 and 2013, the calls of male Common Cuckoos Google Earth (Google) according to the recording localities. were recorded in the field using a TASCAM HD-P2 digital recorder, TASCAM DR100MKII digital recorder Call measurements (TASCAM, Japan) or Marantz PMD670 digital recorder (Marantz, Japan) with external Sennheiser MKH416 P48 Avisoft-SASLab Pro (Avisoft Bioacoustics, Germany) was or ME66 (Sennheiser Electronic, Germany) directional used for re-sampling of the recording files at a sampling microphones. During all recording processes, the distance frequency of 8,000 Hz and to generate the spectrograms of between the microphone and the target individual was the calls. The methods used to measure the Common kept within 30 m, and when we took the recordings we Cuckoo calls were similar to those described by Fuisz and only recorded those birds that we were sure of being de Kort (2007). For each recording, a ‘‘cu-coo’’ call that was different individuals, by observing that they were singing clear with relatively little background noise was selected; simultaneously in different sites, or by walking for a long and 9 variables were measured (Fig. 2). Then, four addi- distance to record the next bird. The habitat information tional variables were derived, giving a total of 13 variables of the recording sites was logged. The geographic loca- (Table 2). When measuring the frequency variables, the tion and altitude information were recorded using Garmin spectrogram parameters were set as follows: FFT GPS map 60CSx handset (Garmin, USA), or obtained via length = 512, Hamming window, frequency band- Google Earth (Google, USA). To ensure that the sam- width = 20 Hz, time resolution = 32 ms. And when mea- pling sites covered all the main distribution regions of suring the time variables, the spectrogram parameters were the species, we also downloaded recordings of the set as follows: FFT length = 128, Hamming window, fre- Common Cuckoo from online databases http://www. quency bandwidth = 81 Hz, time resolution = 8 ms. The xeno-canto.org and http://www.avocet.zoology.msu.edu, automatic parameter measurements of Avisoft-SASLab Pro and obtained some recordings from two other researchers were implied to avoid any artificial bias. A three-hreshold J. Li and X. Zhang. For recordings downloaded from model was used and all were set at -25 dB for element online databases, we only chose recordings that were separation, and the peak frequency option was selected for most probably of different birds, based on the recording spectrum-based parameters. For each individual, the mean time and the locality of the recordings. Locality infor- values of each parameter were calculated and used in the mation of the recordings given by the databases was following analysis. IBM SPSS 20.0 was used for principal used. Figure 1 shows the distribution of all the sampling component analysis (PCA) of the above-mentioned vari- sites used in the present study. The subspecies of each ables, and principal components with eigenvalues greater individual was assigned based on their recording locality, than 1 were reserved for subsequent analysis. the boundaries of four subspecies being determined according to published ornithological books (Payne 2005; Statistical analysis MacKinnon and Phillipps 1999; Aye´ et al. 2012). The sound recordings have been archived (Electronic Sup- To examine the effect of subspecies differentiation on call plementary Material). differentiation, multivariate analysis of variance 123 536 J Ornithol (2015) 156:533–542

Fig. 1 Sampling sites for Common Cuckoo (Cuculus canorus) calls which were recorded. Breeding ranges of different subspecies were shown in different colors. C. c. bangsi in red, C. c. canorus in blue, C. c. subtelephonus in green, and C. c. bakeri in yellow (colour figure online)

Table 1 Climate variables Variable Meaning

BIO1 Average annual temperature BIO2 Range of changes in daily average of the temperature pause BIO3 Isothermality T1 T2 BIO4 Seasonality of the temperature F1H PF1 BIO5 Maximum temperature in the warmest month F1L F2H F2L BIO6 Minimum temperature in the coldest month PF2 BIO7 Amplitude of annual temperature change BIO8 Average temperature in the wettest season BIO9 Average temperature in the driest season Fig. 2 Schematic used to measure the features of cuckoo calls BIO10 Average temperature in the warmest season BIO11 Average temperature in the coldest season BIO12 Annual precipitation (MANOVA) was performed to determine whether there BIO13 Precipitation in the wettest month were any significant differences in calls between different BIO14 Precipitation in the driest month Common Cuckoo subspecies. We set subspecies as fixed BIO15 Seasonality of the precipitation factor and the principal component of calls as the dependent BIO16 Precipitation in the wettest season variable. The Kolmogorov–Smirnov test was performed to determine whether the data were normally distributed BIO17 Precipitation in the driest season before MANOVA. Because the first principal component BIO18 Precipitation in the warmest season (PCcall1) of the call did not fit the normal distribution, it BIO19 Precipitation in the coldest season was transformed as follows: ln(PCcall1 ?3). The PC scores

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Table 2 Measured acoustic traits (variables) in Common Cuckoo test and partial Mantel test were performed to assess the (Cuculus canorus) calls correlation between geographic distance, climatic and Variable Meaning altitude differences, and the differences in calls. For the principal component of acoustic variables and climate PF1 Frequency at which the energy of the first note is the variables, the average values were calculated by sampling highest locality. Based on this, the Euclidean distance matrices of F1L Lowest frequency of the first note call variables and climate variables were calculated F1H Highest frequency of the first note between each pair of sampling locations. The field package PF2 Frequency at which the energy of the second note is the highest was used to calculate the great circle distance matrix F2L Lowest frequency of the second note between each pair of sampling locations (Furrer et al. 2010). The following three types of analyses were per- F2H Highest frequency of the second note formed to show the effect of geographic distance and cli- DF1 Frequency bandwidth of the first note matic differences on calls: (1) comparison of the acoustic DF2 Frequency bandwidth of the second note difference matrix with the geographic distance matrix; (2) DPF Difference between PF1 and PF2 comparison of the acoustic difference matrix with the cli- T1 Duration of the first note mate difference matrix; and (3) comparison of the acoustic T2 Duration of the second note difference matrix with the climate difference matrix while Pause Interval between the two notes controlling the geographic distance matrix to examine the Duration Duration of the call impact of differences in climate on acoustic differentiation with the effect of geographic distance excluded. Because calls may vary considerably between different subspecies, differed significantly between subspecies, and in order to it was considered necessary to exclude the impact of sub- better understand the acoustic divergence between subspe- species differentiation. Because there were few sampling cies, we then examined the effect of subspecies on the sites for subspecies subtelephonus, bakeri, and bangsi, data original acoustic variables that these PC scores stand for. from the subspecies canorus alone were used to repeat the The Kolmogorov–Smirnov test was used to check normality above analyses. To discover the effect of altitude on call of the data and Levene’s test was conducted to test the divergence, the mean values of altitude were calculated by homogeneity of variance of the data. A non-parametric sampling locality, and a Euclidean distance matrix of Kruskal–Wallis test followed by a multiple comparisons altitude was generated. We then compared the acoustic test was used because the acoustic variables did not fit the distance matrix to the altitude matrix, and these two assumption of a parametric test. The critical p value was matrices were also compared when the geographic distance adjusted with the Bonferroni correction. To confirm whe- matrix was controlled for. The Mantel test and partial ther the subspecies of each individual could be identified Mantel test were both performed using the vegan package based on their calls, discriminant function analysis (DFA) (Oksanen et al. 2007) in R 3.0.2 (R Core Team 2013). In was performed on individuals using the principal compo- each analysis, the number of matrix permutations was set nents of the calls, and subspecies was set as grouping var- to 9,999. iable. Data of subspecies bangsi were excluded from the above-mentioned analysis, because of its small sample size (only three individuals). All the analysis above was per- Results formed using IBM SPSS 20.0. A reasonable numbers of recordings of calls from both Subspecies and call divergence forests and wetland habitats were only obtained in central China (Dongzhai in Henan Province, Wuhan City and the A total of 221 recordings of Common Cuckoo calls were Caidian District in Hubei Province). To determine whether obtained, covering 4 subspecies, 105 locations, and 178 Common Cuckoo calls also differ across habitats, MA- male individuals (Electronic Supplementary Material Table NOVA was performed to compare calls from central S1). Via principal component analysis of acoustic vari- China. Kolmogorov–Smirnov testing was performed to ables, four principal components were obtained: PCcall1, determine whether the data fit normal distribution, and PCcall2, PCcall3, and PCcall4. These components Levene’s test was performed to assess the homogeneity of explained 84.7 % of the variation in the original variables variance of the data. The above analysis was also per- (Table 3). MANOVA results showed that there was sig- formed using IBM SPSS 20.0. nificant differentiation in calls between subspecies (Pillai’s To examine the impact of geographic distance and Trace = 0.619, F = 19.05, P \ 0.01). There were signifi- environmental difference on call differentiation, the Mantel cant differences in PCcall1 (F = 87.76, P \ 0.01) and 123 538 J Ornithol (2015) 156:533–542

PCcall4 (F = 7.34, P \ 0.01) across subspecies, but there Call differentiation between habitats were no significant differences in PCcall2 (F = 1.29, P = 0.278) or PCcall3 (F = 1.46, P = 0.234) across Analysis of the Common Cuckoo calls in central China subspecies. These results indicated that the calls of dif- revealed there to be significant differences in the calls in ferent subspecies differ mainly in their frequency param- different habitats (MANOVA, Pillai’s Trace = 0.471, eters (Fig. 3). Because PF1, F1L, F1H, PF2, F2L, F2H and F = 4.46, P \ 0.01). Tests of between-subject effect DPF had the strongest factor loadings on PCcall1 and showed the Common Cuckoo calls to differ significantly in PCcall4, these variables were subject to the Kruskal–Wallis PCcall3 between forests and wetlands (F = 9.69, test, which conformed there to be significant differences P \ 0.01), suggesting that, in these two habitats, Common between subspecies in these parameters (Table 4). Multiple Cuckoo calls differed mainly in the bandwidth of the sec- comparisons found that acoustic parameters of subteleph- ond note. onus were significantly higher than canorus and bakeri in PF1, F1L, F1H, PF2, F2L, and F2H, while there was no Geographic distance, climatic differences, altitude significant difference between canorus and bakeri in these differences and call differentiation variables (Fig. 4a–f). DPF in subtelephonus was signifi- cantly greater than canorus, while there was no significant Four principal components, namely PCclim1, PCclim2, difference between subtelephonus and bakeri, as well as PCclim3, and PCclim4, were obtained from component canorus and bakeri (Fig. 4g). analysis of the climate data. These together explained With discriminant function analysis, the subspecies of 92.9 % of the variation in the original variable (Table 6). 81.7 % of the individuals examined were correctly identi- Mantel test and partial Mantel test results showed signifi- fied (Table 5). This included 75.2 % of the individuals of cant correlations between differences in calls and geo- subspecies canorus, 76.5 % of the individuals of subspe- graphic distance (Mantel test, r = 0.224, P \ 0.01). No cies bakeri, and 98 % of the individuals of subspecies significant correlation was found between differences in subtelephonus, suggesting that subtelephonus had notable calls and in climate (Mantel test, r = 0.066, P = 0.150), call differentiation from the other two subspecies. Some and no significant correlation was found between differ- 13.8 % of the individuals belonging to subspecies canorus ences in calls and in climate when the impact of geographic were incorrectly identified as subspecies bakeri, and 11 % distance was excluded (partial Mantel test, r =-0.050, canorus individuals were incorrectly assigned to subspe- P = 0.783). To rule out the effect of subspecies differen- cies subtelephonus, while 11.8 % of bakeri individuals tiation, analysis of subspecies canorus alone revealed sig- were incorrectly classified as canorus, and 11.8 % of nificant correlations between differences in calls and bakeri were incorrectly classified as subtelephonus. geographic distance (Mantel test, r = 0.269, P \ 0.01). No significant correlation was found between differences in calls and in climate (Mantel test, r = 0.110, P = 0.087), Table 3 Principal components of cuckoo calls and no significant correlation was found between differ- PCcall1 PCcall2 PCcall3 PCcall4 ences in calls and in climate when the impact of geographic Eigen values 6.733 1.861 1.285 1.129 distance was excluded (partial Mantel test, r =-0.051, % Total variance explained 51.794 14.318 9.885 8.687 P = 0.728). In addition, there was no significant correla- Component matrix tion to be found between differences in calls and in alti- PF1 0.952 0.183 -0.007 -0.151 tudes (Mantel test, r =-0.094, P = 0.944), and no significant correlation was found even when the impact of F1L 0.911 0.027 -0.179 0.179 geographic distance was excluded (partial Mantel test, F1H 0.953 0.178 0.137 -0.082 r =-0.187, P = 0.999). PF2 0.946 0.032 0.052 0.233 F2L 0.944 0.048 -0.031 0.148 F2H 0.947 0.043 0.102 0.251 Discussion DF1 0.523 0.292 0.494 -0.394 DF2 0.189 -0.014 0.600 0.501 Call differentiation between subspecies DPF 0.562 0.313 -0.084 20.614 T1 -0.567 0.229 0.502 0.102 Our results showed remarkable differentiation in call traits T2 -0.500 0.481 0.342 -0.140 between different subspecies of the Common Cuckoo. We Pause -0.060 0.753 -0.487 0.292 found that the calls of subtelephonus birds differed greatly Duration -0.454 0.870 -0.052 0.173 from both canorus and bakeri birds and have significantly Significant differences in bold higher frequency traits. The majority (98 %) of individuals 123 J Ornithol (2015) 156:533–542 539

Fig. 3 Geographical variation of Common Cuckoo calls. The subspecies and the sampling sites are shown on the right

Table 4 Descriptive statistics of acoustic varibles of different Common Cuckoo subspecies and the results of Kruskal–Wallis testing Variable (Hz) canorus (n = 109) subtelephonus (n = 49) bakeri (n = 17) HP Mean SE Mean SE Mean SE

PF1 694 7 850 7 725 12 84.1 <0.001 F1L 614 6 747 5 658 12 94.2 <0.001 F1H 713 9 874 6 730 11 77.8 <0.001 PF2 562 5 681 4 579 6 91.2 <0.001 F2L 548 5 660 4 561 7 86.3 <0.001 F2H 568 5 687 4 590 6 90.7 <0.001 DPF 131 4 169 9 146 9 15.9 <0.001 The meanings of the variables are given in Table 2 SE standard error of the mean P values in bold indicate significance after Bonferroni correction (a, 0.0071) in subspecies subtelephonus were correctly identified with which indicates that the calls of canorus and bakeri are discriminant function analysis on calls, suggesting that more variable and may overlap with other subspecies. subtelephonus can be easily distinguished from subspecies Differentiation in vocal features between different sub- canorus and subspecies bakeri by their calls, and that the species or lineages of the same species is relatively com- call features within subspecies subtelephonus are relatively mon. For example, the different subspecies of Grey- consistent. Although we did not find significant differences breasted Wood-wren (Henicorhina leucophrys) can be in acoustic traits between birds of canorus and bakeri, their completely discriminated via their songs (Dingle et al. ratios of classification success in the discriminant function 2008), and Rufous-naped wren (Campylorhynchus rufinu- analysis were still relatively high (75.2 and 76.5 %), and cha) songs differ significantly between genetic groups the ratios of misclassification to each other were relatively (Sosa-Lo´pez et al. 2013). It is generally believed that the low (13.8 and 11.8 %). These indicate that there still exists songs of songbirds are greatly influenced by the learning divergence in calls between the two subspecies to a certain process (Catchpole and Slater 2008). Because the forma- degree. It was possible that the nonparametric tests were tion of different subspecies typically indicates vicariance not powerful enough to detect the differences. Both can- events, cultural drift may lead to relatively large differ- orus and bakeri have some portions (24.8 and 23.5 %) of ences in songs among populations that have experienced individuals being wrongly assigned to other subspecies, vicariance, and the impact of such differentiation may

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Fig. 4 Boxplots of acoustic variables of different cuckoo subspecies, 1 canorus, 2 subtelephonus, 3 bakeri. Subspecies that did not differ significantly from each other are shown with the same letter, and those are significantly different at p \ 0.05 are labeled with different letters according to the multiple comparison test

Table 5 Discriminant function analysis of Common Cuckoo indi- subspecies have already differentiated into different spe- viduals, grouped by subspecies (cross-validation) cies. Furthermore, as acoustic cues play important roles in Original group Group predicted by calls species recognition and mate choice in birds, it is highly possible that assertive mating will happen if female cuck- Canorus Subtelephonus Bakeri Total oos prefer males with call features of their own subspecies, Canorus 82 (75.2 %) 12 (11 %) 15 (13.8 %) 109 and this may hinder the gene flow between different sub- Subtelephonus 0(0%) 48 (98 %) 1 (2 %) 49 species and accelerate the process of speciation. These Bakeri 2 (11.8 %) 2 (11.8 %) 13 (76.5 %)17 need to be tested in future studies using both ethological and molecular methods. Numbers and the percentage of individuals of each subspecies clas- sified by discriminant function analysis; results in bold indicate classification success Impact of habitat

A significant difference in the call features between the continue through learning between individuals (Koetz et al. Common Cuckoos in two habitats was found. This is 2007). The Common Cuckoo is a non-passerine, and its consistent with the findings of a previous study on the call is regulated primarily by genetic factors, not learning differences in Common Cuckoo calls between different (Fuisz and de Kort 2007). For this reason, differences in habitats in Europe (Fuisz and de Kort 2007). However, this calls between its subspecies may reflect relatively large previous study suggested that the calls of the Common genetic differences. Differences in Common Cuckoo calls Cuckoo from different habitats differed primarily in the were also found between different habitats. However, dis- highest, lowest, and maximum energy frequencies of the criminant function analysis was still able to discriminate second note, whereas the present study found that the calls the calls between different subspecies relatively well, of the Common Cuckoo from different habitats mainly suggesting that the differences in Common Cuckoo calls differed in the bandwidth of the second note. Studies of the between subspecies are far more pronounced than between genetic differentiation in female Common Cuckoos have calls from different habitats. The large difference in calls suggested that the females show host specificity (Gibbs found in the present study may indicate that different et al. 2000). However, a study by Teuschl et al. (1998)

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Table 6 Climate principal component 1975). Based on this hypothesis, it can be predicted that PCclim1 PCclim2 PCclim3 PCclim4 calls in different environments possess acoustic features Eigenvalues 7.537 5.694 2.554 1.869 adapted to those habitats, and the same species may have % Total variance 39.667 29.969 13.440 9.839 similar calls in similar environments. However, the results explained of the present study suggested that, on a large scale, the Component matrix calls of the Common Cuckoo are not closely correlated bio1 0.743 0.547 -0.158 -0.341 with environmental factors. As a result, the acoustic bio2 20.646 0.222 0.468 -0.326 adaptation hypothesis cannot be used to explain the geo- bio3 0.090 -0.209 0.813 -0.452 graphic variation in Common Cuckoo calls. Differences in bio4 20.670 0.472 -0.497 0.216 calls were found to be closely correlated with geographic distance, indicating that the calls fit the isolation by dis- bio5 0.265 0.765 -0.449 -0.302 tance model. Because the calls of Common Cuckoos are bio6 0.945 0.045 -0.027 -0.287 mainly affected by genetic factors rather than obtained bio7 20.785 0.472 -0.276 0.088 through learning, the correlations between differences in bio8 0.104 0.842 -0.356 -0.078 calls and geographic distance may reflect the influence of bio9 0.844 -0.037 0.036 -0.391 genetic differentiation caused by geographic distance. bio10 0.377 0.771 -0.449 -0.215 bio11 0.905 0.169 0.098 -0.363 Acknowledgments We would like to thank Prof. Franz Bairlein and bio12 0.781 0.344 0.211 0.433 two anonymous reviewers who provided helpful comments, which bio13 0.407 0.729 0.384 0.376 helped us greatly improve this manuscript. The recordists from www. xeno-canto.org and www.avocet.zoology.msu.edu used in this study bio14 0.683 -0.539 -0.232 0.290 were much appreciated. We thank Kuankuoshui, Dongzhai and bio15 -0.492 0.698 0.362 0.032 Zhalong National Nature Reserves for support and permission to carry bio16 0.466 0.676 0.414 0.382 out this study, Longwu Wang, Tongping Su, Juan Huo for assistance bio17 0.742 -0.461 -0.236 0.288 with fieldwork, Yajing Chang for assistance with climate data extraction, and Jiangqiang Li, Xiaofeng Zhang for offering four of bio18 0.348 0.727 0.393 0.394 their recordings. This work was funded by the National Natural bio19 0.687 -0.556 -0.160 0.283 Science Foundation of China (Nos. 31272328 and 31472013 to WL, 31172098 to YZ and 31272300 to CJ). Significant differences in bold Ethical standard The experiments comply with the current laws of revealed that both male and female Common Cuckoos China in which they were performed. exhibited imprinting on the habitats into which they were born. In this way, after sexual maturity, Cuculus canorus are more likely to return to places in the same or similar References habitats than to other places to mate. As a consequence, male Cuculus canorus born in similar habitats on a small Aye´ R, Schweizer M, Roth T (2012) Birds of Central Asia: spatial scale are likely to have close genetic relationships. Kazakhstan, Turkmenistan, Uzbekistan, Kyrgyzstan, Tajikistan, Recent studies on the genetic differentiation of the Com- and Afghanistan. Princeton University Press, Princeton mon Cuckoo in Europe has supported this view (Fossøy Catchpole CK, Slater PJB (2008) Bird Song: biological themes and variations, 2nd edn. Cambridge University Press, Cambridge et al. 2011). In the present study, differentiation in calls Dingle C, Halfwerk W, Slabbekoorn H (2008) Habitat-dependent between different habitats on a small spatial scale might song divergence at subspecies level in the grey-breasted wood- come from the genetic differentiation attributable to the wren. J Evol Biol 21:1079–1089 relative rarity of gene flow between populations in different Fossøy F, Antonov A, Moksnes A, Røskaft E, Vikan JR, Møller AP, Shykoff JA, Stokke BG (2011) Genetic differentiation among habitats. sympatric cuckoo host races: males matter. Proc R Soc Lond B 278:1639–1645 Impact of geographic distance and environmental Fuisz TI, de Kort SR (2007) Habitat-dependent call divergence in the differences common cuckoo: is it a potential signal for assortative mating? Proc R Soc Lond B 274:2093–2097 Furrer R, Nychka D, Sain S (2010) Fields: tools for spatial data. http:// The present results suggest that the differences in calls and cran.r-project.org/package=fields geographic distance are closely correlated, and that dif- Gibbs HL, Sorenson MD, Marchetti K, Brooke M de L, Davies NB, ferences in climate and altitude do not significantly affect Nakamura H (2000) Genetic evidence for female host-specific races of the common cuckoo. Nature 407:183–186 call differentiation. According to the acoustic adaptation Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very hypothesis, calls that can propagate effectively and be high resolution interpolated climate surfaces for global land identified in the local environment will be selected (Morton areas. Int J Clim 25:1965–1978

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Irwin DE (2000) Song variation in an avian ring species. Evolution Payne RB (2005) The cuckoos. Oxford University Press, Oxford 54:998–1010 Pe´rez-Mena EE, Mora EC (2011) Geographic song variation in the Irwin DE, Thimgan MP, Irwin JH (2008) Call divergence is correlated non-passerine Cuban tody (Todus multicolor). Wilson J Ornithol with geographic and genetic distance in greenish warblers 123:76–84 (Phylloscopus trochiloides): a strong role for stochasticity in R Core Team (2013) R: a language and environment for statistical signal evolution? J Evol Biol 21:435–448 computing. R Foundation for Statistical Computing, Vienna, Jung W-J, Lee J-W, Yoo J-C (2014) ‘‘cu-coo’’: Can you recognize my Austria. http://www.R-project.org/ stepparents?: a study of host-specific male call divergence in the Rivera-Gutierrez HF, Matthysen E, Adriaensen F, Slabbekoorn H common cuckoo. PLoS ONE 9:e90468 (2010) Repertoire sharing and song similarity between great tit Koetz AH, Westcott DA, Congdon BC (2007) Geographical variation males decline with distance between forest fragments. Ethology in song frequency and structure: the effects of vicariant isolation, 116:951–960 habitat type and body size. Anim Behav 74:1573–1583 Robin VV, Katti M, Purushotham C, Sancheti A, Sinha A (2011) Lei F, Zhao H, Wang A, Yin Z, Payne RB (2005) Vocalizations of the Singing in the sky: song variation in an endemic bird on the sky common cuckoo Cuculus canorus in China. Acta Zool Sin islands of southern India. Anim Behav 82:513–520 51:31–37 Sosa-Lo´pez JR, Mennill DJ, Navarro-Sigu¨enza AG (2013) Geo- Lovell SF, Lein MR (2013) Geographical variation in songs of a graphic variation and the evolution of song in Mesoamerican suboscine Passerine, the alder flycatcher (Empidonax alnorum). rufous-naped wrens Campylorhynchus rufinucha. J Avian Biol Wilson J Ornithol 125:15–23 44:027–038 MacKinnon J, Phillipps K (1999) A field guide to the birds of China. Teuschl Y, Taborsky B, Taborsky M (1998) How do cuckoos find Oxford University Press, Oxford their hosts? The role of habitat imprinting. Anim Behav Marler P, Slabbekoorn H (2004) Nature’s music: the science of 56:1425–1433 birdsong. Elsevier, San Diego Turcokova L, Osiejuk TS, Pavel V, Glapan J, Petruskova´ T (2010) Morton ES (1975) Ecological sources of selection on avian sounds. Song divergence of two bluethroat subspecies (Luscinia s. Am Nat 109:17–34 svecica and cyanecula). Ornis Fenn 87:168–179 Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens MHH, Oksanen Wright S (1943) Isolation by distance. Genetics 28:114 MJ, Suggests M (2007) The vegan package. Community Xing X, Alstro¨m P, Yang X, Lei F (2013) Recent northward range Ecology Package expansion promotes song evolution in a passerine bird, the light- Parker KA, Anderson MJ, Jenkins PF, Brunton DH (2012) The effects vented bulbul. J Evol Biol 26:867–877 of translocation-induced isolation and fragmentation on the cultural evolution of bird song. Ecol Lett 15:778–785

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