International Journal of Primatology

, Volume 33, Issue 6, pp 1453–1466 | Cite as

Vocal Tract Morphology Determines Species-Specific Features in Vocal Signals of Lemurs (Eulemur)

Article

Abstract

The source-filter theory describes vocal production as a two-stage process involving the generation of a sound source, with its own spectral structure, which is then filtered by the resonant properties of the vocal tract. This theory has been successfully applied to the study of animal vocal signals since the 1990s. As an extension, models reproducing vocal tract resonance can be used to reproduce formant patterns and to understand the role of vocal tract filtering in nonhuman vocalizations. We studied three congeneric lemur species —Eulemur fulvus, E. macaco, E. rubriventer— using morphological measurements to build computational models of the vocal tract to estimate formants, and acoustic analysis to measure formants from natural calls. We focused on call types emitted through the nose, without apparent articulation. On the basis of anatomical measurements, we modeled the vocal tract of each species as a series of concatenated tubes, with a cross-sectional area that changed along the tract to approximate the morphology of the larynx, the nasopharyngeal cavity, the nasal chambers, and the nostrils. For each species, we calculated the resonance frequencies in 2500 randomly generated vocal tracts, in which we simulated intraspecific length and size variation. Formant location and spacing showed significant species-specific differences determined by the length of the vocal tract. We then measured formants of a set of nasal vocalizations (“grunts”) recorded from captive lemurs of the same species. We found species-specific differences in the natural calls. This is the first evidence that morphology of the vocal tract is relevant in generating filter-related acoustic cues that potentially provide receivers with information about the species of the emitter.

Keywords

Eulemur Formant Modeling Strepsirrhini Vocalization 

Notes

Acknowledgments

This research was supported by the Università degli Studi di Torino and by grants from the Parco Natura Viva—Centro Tutela Specie Minacciate. We thank Dr. Cesare Avesani Zaborra, Dr. Caterina Spiezio, Gilbert Rakotoarisoa, Jules Medard, Haingoson Randriamialison, Hajanirina Ramino, and Fanomezantsoa Andrianirina for their help and logistic support. We also thank two anonymous referees and the editor for their comments on earlier versions of this article.

References

  1. Altmann, J. (1974). Observational study of behavior: sampling methods. Behaviour, 49, 227–267.PubMedCrossRefGoogle Scholar
  2. Aubin, T., & Jouventin, P. (2002). How to identify vocally a kin in a crowd? The penguin model. Advances in the Study of Behavior, 31, 243–277.CrossRefGoogle Scholar
  3. Aubin, T., Mathevon, N., Staszewski, V., & Boulinier, T. (2007). Acoustic communication in the Kittiwake Rissa tridactyla: potential cues for sexual and individual signatures in long calls. Polar Biology, 30, 1027–1033.CrossRefGoogle Scholar
  4. Blumstein, D. T., & Munos, O. (2005). Individual, age and sex-specific information is contained in yellow-bellied marmot alarm calls. Animal Behavior, 69, 353–361.CrossRefGoogle Scholar
  5. Boersma, P. (2001). Praat, a system for doing phonetics by computer. Glot International, 5, 341–345.Google Scholar
  6. Colquhoun, I.C. (1997). A predictive socioecological study of the black lemur (Eulemur macaco macaco) in northwestern Madagascar. PhD Dissertation: Washington University.Google Scholar
  7. de Boer, B., & Fitch, W. T. (2010). Computer models of vocal tract evolution: an overview and critique. Adaptive Behavior, 18, 36–47.CrossRefGoogle Scholar
  8. Development Core Team, R. (2008). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
  9. Efremova, K. O., Volodin, I. A., Volodina, E. V., Frey, R., Lapshina, E. N., & Soldatova, N. V. (2011). Developmental changes of nasal and oral calls in the goitred gazelle Gazella subgutturosa, a nonhuman mammal with a sexually dimorphic and descended larynx. Naturwissenschaften, 98, 919–931.PubMedCrossRefGoogle Scholar
  10. Fant, G. (1960). Acoustic theory of speech production. The Hague: Mouton.Google Scholar
  11. Fitch, W. T. (1997). Vocal tract length and formant frequency dispersion correlate with body size in rhesus macaques. Journal of the Acoustical Society of America, 102, 1213–1222.PubMedCrossRefGoogle Scholar
  12. Fitch, W. T. (2000). The phonetic potential of nonhuman vocal tracts: comparative cineradiographic observations of vocalizing animals. Phonetica, 57, 205–218.PubMedCrossRefGoogle Scholar
  13. Fitch, W. T. (2006). Production of vocalizations in mammals. In K. Brown (Ed.), Encyclopedia of language and linguistics (pp. 115–121). Oxford: Elsevier.Google Scholar
  14. Fitch, W. T., & Fritz, J. B. (2006). Rhesus macaques spontaneously perceive formants in conspecific vocalizations. Journal of the Acoustical Society of America, 120, 2132–2141.PubMedCrossRefGoogle Scholar
  15. Frey, R., Volodin, I., & Volodina, E. (2007). A nose that roars: anatomical specializations and behavioural features of rutting male saiga. Journal of Anatomy, 211, 717–736.PubMedCrossRefGoogle Scholar
  16. Gamba, M. (2006). Evoluzione della comunicazione vocale nei lemuri del Madagascar. Ph.D., dissertation, University of Torino.Google Scholar
  17. Gamba, M., & Giacoma, C. (2005). Key issues in the study of primate acoustic signals. Journal of Anthropological Sciences, 83, 61–87.Google Scholar
  18. Gamba, M., & Giacoma, C. (2006). Vocal tract modeling in a prosimian primate: the black and white ruffed lemur. Acta Acustica united with Acustica, 92, 749–755.Google Scholar
  19. Gamba, M., & Giacoma, C. (2007). Quantitative acoustic analysis of the vocal repertoire of the crowned lemur. Ethology Ecology Evolution, 19, 323–343.CrossRefGoogle Scholar
  20. Gamba, M., & Giacoma, C. (2008). Subspecific divergence in the black lemur’s low-pitched vocalizations. The Open Acoustic Journal. doi:10.2174/1874837600801010049.
  21. Gamba, M., Colombo, C., & Giacoma, C. (2012). Acoustic cues to caller identity in lemurs: a case study. Journal of Ethology, 30, 191–196.CrossRefGoogle Scholar
  22. Gautier, J.-P. (1971). Étude morphologique et fonctionelle des annexes extra-laryngées des Cercopithecinae: liaison avec les cris d'espacement. Biologia Gabonica, 7, 229–267.Google Scholar
  23. Gautier, J.-P., & Gautier-Hion, A. (1982). Vocal communication within a group of monkeys: Analysis by biotelemetry. In C. T. Snowdon, C. H. Brown, & M. Petersen (Eds.), Primate communication (pp. 5–29). New York: Cambridge University Press.Google Scholar
  24. Ghazanfar, A. A., Turesson, H. J., Maier, J. X., van Dinther, R., Patterson, R. D., & Logothetis, N. K. (2007). Vocal tract resonances as indexical cues in rhesus monkeys. Current Biology, 17, 425–430.PubMedCrossRefGoogle Scholar
  25. Glander, K. E., Wright, P. C., Daniels, P. S., & Merenlender, A. M. (1992). Morphometrics and testicle size of rainforest lemur species from southeastern Madagascar. Journal of Human Evolution, 22, 1–17.CrossRefGoogle Scholar
  26. Gosset, D., Fornasieri, I., & Roeder, J.-J. (2001). Acoustic structure and contexts of emission of vocal signals by black lemurs. Evolution of Communication, 4, 225–251.CrossRefGoogle Scholar
  27. Harrison, D. F. N. (1995). The anatomy and physiology of the mammalian larynx. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  28. Kewley-Port, D., & Watson, C. S. (1994). Formant-frequency discrimination for isolated English vowels. Journal of the Acoustical Society of America, 95, 485–496.PubMedCrossRefGoogle Scholar
  29. Lieberman, P., Klatt, D. H., & Wilson, W. H. (1969). Vocal tract limitations on the vowel repertoires of rhesus monkey and other nonhuman primates. Science, 164, 1185–1187.PubMedCrossRefGoogle Scholar
  30. Macedonia, J. M., & Stanger, K. F. (1994). Phylogeny of the lemuridae revisited: evidence from communication signals. Folia Primatologica, 63, 1–43.CrossRefGoogle Scholar
  31. Markel, J. D., & Gray, A. H. (1976). Linear prediction of speech. Berlin: Springer-Verlag.CrossRefGoogle Scholar
  32. Mitchell, C., Gillette, R., Vernon, J., & Herman, P. (1970). Pure-tone auditory behavioral thresholds in three species of lemurs. Journal of the Acoustical Society of America, 48, 531–535.PubMedCrossRefGoogle Scholar
  33. Mittermeier, R. A., Louis, E. E., Jr., Richardson, M., Schwitzer, C., Langrand, O., Rylands, A. B., et al. (2010). Lemurs of Madagascar (3rd ed.). Washington, DC: Conservation International.Google Scholar
  34. Nicastro, N. (2004). Perceptual and acoustic evidence for species-level differences in meow vocalizations by domestic cats (Felis catus) and African wild cats (Felis silvestris lybica). Journal of Comparative Psychology, 118, 287–296.PubMedCrossRefGoogle Scholar
  35. Reby, D., & McComb, K. (2003). Anatomical constraints generate honesty: acoustic cues to age and weight in the roars of red deer stags. Animal Behavior, 65, 519–530.CrossRefGoogle Scholar
  36. Riede, T., & Fitch, W. T. (1999). Vocal tract length and acoustics of vocalization in the domestic dog Canis familiaris. Journal of Experimental Biology, 202, 2859–2867.PubMedGoogle Scholar
  37. Riede, T., Bronson, E., Hatzikirou, H., & Zuberbuhler, K. (2005). Vocal production in a non-human primate: morphological data and a model. Journal of Human Evolution, 48, 85–96.PubMedCrossRefGoogle Scholar
  38. Riede, T., Suthers, R. A., Fletcher, N. H., & Blevins, W. E. (2006). Songbirds tune their vocal tract to the fundamental frequency of their song. Proceedings of the National Academy of Sciences of the USA, 103, 5543–5548.PubMedCrossRefGoogle Scholar
  39. Rousseeuw, P. J. (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65.Google Scholar
  40. Shipley, C., Carterette, E. C., & Buchwald, J. S. (1991). The effect of articulation on the acoustical structure of feline vocalization. Journal of Acoustical Society America, 89, 902–909.CrossRefGoogle Scholar
  41. Sokal, R. R., & Rohlf, F. J. (1995). Biometry: the principles and practice of statistics in biological research (3rd ed.) New York: W.H. Freeman.Google Scholar
  42. Taylor, A. M., & Reby, D. (2010). Contribution of the source-filter theory to the study of mammal vocal communication. Journal of Zoology, 280, 221–236.CrossRefGoogle Scholar
  43. Terranova, C. J., & Coffman, B. S. (1997). Body weights of wild and captive lemurs. Zoo Biology, 16, 17–30.CrossRefGoogle Scholar
  44. Titze, I. R. (1994). Principles of voice production. Englewood Cliffs: Prentice Hall.Google Scholar
  45. Volodin, I. A., Lapshina, E. N., Volodina, E. V., Frey, R., & Soldatova, N. V. (2011). Nasal and oral calls in juvenile goitred gazelles (Gazella subgutturosa) and their potential to encode sex and identity. Ethology, 117, 294–308.CrossRefGoogle Scholar
  46. Xue, S. A., & Hao, J. G. (2006). Normative standards for vocal tract dimensions by race as measured by acoustic pharyngometry. Journal of Voice, 20, 391–400.PubMedCrossRefGoogle Scholar
  47. Zhang, Z., & Espy-Wilson, C. (2004). A vocal tract model of American English /l/. Journal of the Acoustical Society of America, 115, 1274–1280.PubMedCrossRefGoogle Scholar
  48. Zhao, Y., & Karypis, G. (2001) Criterion functions for document clustering: experiments and analysis. Technical Report TR 01-40, University of Minnesota.Google Scholar
  49. Zhou, X., Zhang, Z., & Espy-Wilson, C. (2004). VTAR: a Matlab-based computer program for vocal tract acoustic modeling. Journal of the Acoustical Society of America, 115, 2543–2543.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Life Sciences and Systems BiologyUniversity of TorinoTorinoItaly
  2. 2.Centre for Molecular Systems BiologyUniversity of TorinoTorinoItaly

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