Evolutionary Biology

, Volume 44, Issue 1, pp 43–55 | Cite as

Multivariate Phenotypic Evolution: Divergent Acoustic Signals and Sexual Selection in Gryllus Field Crickets

  • Thomas Blankers
  • David A. Gray
  • R. Matthias Hennig
Research Article

Abstract

Predicting the response to selection is at the core of evolutionary biology. Presently, thorough understanding of the effects of selection on the multivariate phenotype is lacking, in particular for behavioral traits. Here, we compared multivariate acoustic mating signals among seven field cricket species contrasting two selection regimes: (1) species producing songs with long trains of pulses for which preference functions for acoustic energy (chirp duty cycle) are linear and likely exert strong directional selection (‘trillers’); (2) species producing songs consisting of short chirps and for which preference functions for chirp duty cycle are concave and directional selection is likely weak or absent (‘chirpers’). We compared the phenotypic variance–covariance matrix (P) among species and uncovered two main patterns: First, surprisingly, pulse rate and chirp rate were positively correlated in six of seven species thus suggesting phenotypic coupling of timescales. Second, chirp rate and chirp duty cycle also covaried, but the direction of covariation differed between chirpers (positive) and trillers (negative). Multi-population Bayesian methods for matrix comparisons, Krzanowski’s subspace comparison and tensor analysis, revealed significant variation in P unrelated to phylogenetic distance, but strongly contrasting chirpers and trillers. We also found differences in the predicted selection response between chirpers and trillers. We thus report that variation in P is higher between than within selection regimes. Although effects from drift and shared ancestry cannot be fully excluded, these findings highlight a role for sexual selection in shaping patterns of phenotypic covariation that can ultimately affect the evolutionary trajectory of a multivariate mating signal.

Keywords

P matrix Sexual selection Acoustic communication Gryllus Bayesian 

Notes

Acknowledgments

The manuscript strongly benefitted from comments by Emma Berdan, Jonas Finck, and Michael Reichert and peer review by Derek A. Roff, Katherine Willmore, and four anonymous reviewers. The performed experiments comply with the “Principles of animal care”, publication No. 86-23, revised 1985 of the National Institute of Health, and also with the current laws of Germany. The authors declare no conflict of interest. Data will be deposited in the Dryad Digital Repository. This study is part of the GENART project funded by the Leibniz Association (SAW-2012-MfN-3).

Compliance with Ethical Standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

11692_2016_9388_MOESM1_ESM.docx (43 kb)
Supplementary material 1 (DOCX 42 kb)

References

  1. Aguirre, J. D., Hine, E., McGuigan, K., & Blows, M. W. (2014). Comparing G: Multivariate analysis of genetic variation in multiple populations. Heredity, 112(1), 21–29.CrossRefPubMedGoogle Scholar
  2. Alexander, R. (1962). Evolutionary change in cricket acoustical communication. Evolution, 16, 443–467.CrossRefGoogle Scholar
  3. Arnold, S. J., Bürger, R., Hohenlohe, P. A., Ajie, B. C., & Jones, A. G. (2008). Understanding the evolution and stability of the G-matrix. Evolution, 62(10), 2451–2461.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Bégin, M., & Roff, D. A. (2004). From micro- to macroevolution through quantitative genetic variation: Positive evidence from field crickets. Evolution, 58(10), 2287–2304.CrossRefPubMedGoogle Scholar
  5. Bentsen, C. L., Hunt, J., Jennions, M. D., & Brooks, R. (2006). Complex multivariate sexual selection on male acoustic signaling in a wild population of Teleogryllus commodus. The American Naturalist, 167(4), E102–E116.CrossRefPubMedGoogle Scholar
  6. Berner, D., Stutz, W. E., & Bolnick, D. I. (2010). Foraging trait (co)variances in stickleback evolve deterministically and do not predict trajectories of adaptive diversification. Evolution, 64(8), 2265–2277.PubMedGoogle Scholar
  7. Bertram, S. M., Fitzsimmons, L. P., McAuley, E. M., Rundle, H. D., & Gorelick, R. (2012). Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species. Ecology and Evolution, 2(1), 181–195.CrossRefPubMedPubMedCentralGoogle Scholar
  8. Blankers, T., Hennig, R. M., & Gray, D. A. (2015). Conservation of multivariate female preference functions and preference mechanisms in three species of trilling field crickets. Journal of Evolutionary Biology, 28(3), 630–641.CrossRefPubMedGoogle Scholar
  9. Blows, M. W., Chenoweth, S. F., & Hine, E. (2004). Orientation of the genetic variance–covariance matrix and the fitness surface for multiple male sexually selected traits. American Naturalist, 163, 329–340.CrossRefPubMedGoogle Scholar
  10. Blows, M. W., & Higgie, M. (2003). Genetic constraints on the evolution of mate recognition under natural selection. American Naturalist, 161, 240–253.CrossRefPubMedGoogle Scholar
  11. Broughton, R. E., & Harrison, R. G. (2003). Nuclear gene genealogies reveal historical, demographic and selective factors associated with speciation in field crickets. Genetics, 163(4), 1389–1401.PubMedPubMedCentralGoogle Scholar
  12. Cheverud, J. M. (1988). A comparison of genetic and phenotypic correlations. Evolution: International Journal of Organic Evolution, 42(5), 958–968.CrossRefGoogle Scholar
  13. Clemens, J., & Hennig, R. M. (2013). Computational principles underlying the recognition of acoustic signals in insects. Journal of Computational Neuroscience, 35, 75–85.CrossRefPubMedGoogle Scholar
  14. Flury, B. (1988). Common principal components and related multivariate models. New York: Wiley.Google Scholar
  15. Gerhardt, H. C., & Brooks, R. (2009). Experimental analysis of multivariate female choice in gray treefrogs (Hyla versicolor): Evidence for directional and stabilizing selection. Evolution, 63, 2504–2512.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Gerhardt, H. C., & Huber, F. (2002). Acoustic communication in insects and anurans. Chicago: The University of Chicago Press.Google Scholar
  17. Gray, D. A., & Cade, W. H. (2000). Sexual selection and speciation in field crickets. Proceedings of the National Academy of Sciences, 97, 14449–14454.CrossRefGoogle Scholar
  18. Gray, D. A., Gabel, E., Blankers, T., & Hennig, R. M. (2016a). Multivariate female preference tests reveal latent perceptual biases. Proc R Soc B (in review)Google Scholar
  19. Gray, D. A., Gutierrez, N. J., Chen, T. O. M. L., Weissman, D. B., & Cole, J. A. (2016b). Species divergence in field crickets: Genetics, song, ecomorphology, and pre- and postzygotic isolation. Biological Journal of the Linnean Society, 117(2), 192–205.CrossRefGoogle Scholar
  20. Gray, D. A., Huang, H., & Knowles, L. L. (2008). Molecular evidence of a peripatric origin for two sympatric species of field crickets (Gryllus rubens and G. texensis) revealed from coalescent simulations and population genetic tests. Molecular Ecology, 17, 3836–3855.CrossRefPubMedGoogle Scholar
  21. Grobe, B., Rothbart, M. M., Hanschke, A., & Hennig, R. M. (2012). Auditory processing at two time scales by the cricket Gryllus bimaculatus. The Journal of experimental biology, 215, 1681–1690.CrossRefPubMedGoogle Scholar
  22. Haber, A. (2014). The evolution of morphological integration in the ruminant skull. Evolutionary Biology, 42(1), 99–114.CrossRefGoogle Scholar
  23. Hadfield, J. D. (2010). MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software, 33, 1–22.CrossRefGoogle Scholar
  24. Hansen, T. F., & Houle, D. (2008). Measuring and comparing evolvability and constraint in multivariate characters. Journal of Evolutionary Biology, 21, 1201–1219.CrossRefPubMedGoogle Scholar
  25. Hazel, L. N., Dickerson, G. E., & Freeman, A. E. (1994). The selection index—Then, now, and for the future. Journal of Dairy Science, 77(10), 3236–3251.CrossRefPubMedGoogle Scholar
  26. Hedwig, B. (2000). Control of cricket stridulation by a command neuron: Efficacy depends on the behavioral state. Journal of Neurophysiology, 83, 712–722.PubMedGoogle Scholar
  27. Heiberger, R. M., & Holland, B. (2004). Statistical analysis and data display: An intermediate course with examples in S-plus, R, and SAS., Springer texts in statistics New York: Springer.CrossRefGoogle Scholar
  28. Hennig, M. R., Blankers, T., & Gray, D. A. (2016). Divergence in male cricket song and multivariate female preference functions in three allopatric sister species. Journal of Comparative Physiology A, 202, 347–360.CrossRefGoogle Scholar
  29. Hennig, R. M., Heller, K.-G., & Clemens, J. (2014). Time and timing in the acoustic recognition system of crickets. Frontiers in Physiology, 5, 286. doi:10.3389/fphys.2014.00286.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Hine, E., Chenoweth, S. F., Rundle, H. D., & Blows, M. W. (2009). Characterizing the evolution of genetic variance using genetic covariance tensors. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1523), 1567–1578.CrossRefGoogle Scholar
  31. Hoback, W. W., & Wagner, W. E., Jr. (1997). The energetic cost of calling in the variable field cricket, Gryllus lineaticeps. Physiological Entomology, 22, 286–290.CrossRefGoogle Scholar
  32. Houle, D., Pelabon, C., Wagner, G. P., & Hansen, T. F. (2011). Measurement and meaning in biology. The Quarterly Review of Biology, 86(1), 3–34.CrossRefPubMedGoogle Scholar
  33. Huang, Y., Ortí, G., Sutherlin, M., Duhachek, A., & Zera, A. (2000). Phylogenetic relationships of North American field crickets inferred from mitochondrial DNA data. Molecular Phylogenetics and Evolution, 17(1), 48–57.CrossRefPubMedGoogle Scholar
  34. Jones, A. G., Arnold, S. J., & Bürger, R. (2003). Stability of the G-matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift. Evolution, 57(8), 1747–1760.CrossRefPubMedGoogle Scholar
  35. Kolbe, J. J., Revell, L. J., Szekely, B., Brodie, E. D., III, & Losos, J. B. (2011). Convergent evolution of phenotypic integration and its alignment with morphological diversification in caribbean Anolis ecomorphs. Evolution, 65(12), 3608–3624.CrossRefPubMedGoogle Scholar
  36. Krzanowski, W. J. (1979). Between groups comparison of principal components. Journal of American Statistical Association, 74, 703–707.CrossRefGoogle Scholar
  37. Lande, R. (1979). Quantitative genetic analysis of multivariate evolution, applied to brain: Body size allometry. Evolution: International Journal of Organic Evolution, 33, 402–416.CrossRefGoogle Scholar
  38. Lande, R., & Arnold, S. J. (1983). The measurement of selection on correlated characters. Evolution, 37(6), 1210–1226.CrossRefGoogle Scholar
  39. Laughlin, D. C., & Messier, J. (2015). Fitness of multidimensional phenotypes in dynamic adaptive landscapes. Trends in Ecology & Evolution, 30(8), 1–10.CrossRefGoogle Scholar
  40. Lynch, M., & Walsh, B. (1998). Genetics and analysis of quantitative Traits. Sunderland, MA: Sinauer.Google Scholar
  41. Melo, D., & Marroig, G. (2014). Directional selection can drive the evolution of modularity in complex traits. Proceedings of the National Academy of Sciences, 112(2), 470–475.CrossRefGoogle Scholar
  42. Otte, D. (1992). Evolution of cricket songs. Journal of Orthoptera Research, 1, 25–49.CrossRefGoogle Scholar
  43. Phillips, P. C., & Arnold, S. J. (1989). Visualizing multivariate selection. Evolution, 43(6), 1209–1222.CrossRefGoogle Scholar
  44. R Development Core Team, R. (2015). R: A language and environment for statistical computing. In R. D. C. Team (Ed.), R foundation for statistical computing. R Foundation for Statistical Computing.Google Scholar
  45. Ritchie, M. G. (2007). Sexual selection and speciation. Annual Review of Ecology Evolution and Systematics, 38(1), 79–102.CrossRefGoogle Scholar
  46. Rodríguez, R. L., Hallett, A. C., Kilmer, J. T., & Fowler-Finn, K. D. (2013). Curves as traits: Genetic and environmental variation in mate preference functions. Journal of Evolutionary Biology, 26, 434–442.CrossRefPubMedGoogle Scholar
  47. Roff, D. (2000). The evolution of the G matrix: Selection or drift? Heredity, 84, 135–142.CrossRefPubMedGoogle Scholar
  48. Roff, D. A., & Fairbairn, D. J. (2012). The evolution of trade-offs under directional and correlational selection. Evolution, 66(8), 2461–2474.CrossRefPubMedGoogle Scholar
  49. Roff, D., Mousseau, T., & Howard, D. (1999). Variation in genetic architecture of calling song among populations of Allonemobius socius, A. fasciatus, and a hybrid population: Drift or selection? Evolution, 53(1), 216–224.CrossRefGoogle Scholar
  50. Rothbart, M. M., & Hennig, R. M. (2012). Calling song signals and temporal preference functions in the cricket Teleogryllus leo. Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology, 198(11), 817–825.CrossRefPubMedGoogle Scholar
  51. Sakaguchi, K. M., & Gray, D. A. (2011). Host song selection by an acoustically orienting parasitoid fly exploiting a multispecies assemblage of cricket hosts. Animal Behaviour, 81(4), 851–858.CrossRefGoogle Scholar
  52. Schöneich, S., & Hedwig, B. (2012). Cellular basis for singing motor pattern generation in the field cricket (Gryllus bimaculatus DeGeer). Brain and Behavior, 2(6), 707–725.CrossRefPubMedPubMedCentralGoogle Scholar
  53. Schoneich, S., Kostarakos, K., & Hedwig, B. (2015). An auditory feature detection circuit for sound pattern recognition. Science Advances, 1(8), e1500325.CrossRefPubMedPubMedCentralGoogle Scholar
  54. Steppan, S. J. (1997). Phylogenetic analysis of phenotypic covariance structure. I. Contrasting results from matrix correlation and common principal component analysis. Evolution, 51(2), 571–586.CrossRefGoogle Scholar
  55. Steppan, S. J., Phillips, P. C., & Houle, D. (2002). Comparative quantitative genetics: Evolution of the G matrix. Trends in Ecology & Evolution, 17(7), 320–327.CrossRefGoogle Scholar
  56. Swenson, N. G. (2014). Functional and phylogenetic ecology in R. New York, NY: Springer.CrossRefGoogle Scholar
  57. Turelli, M. (1988). Phenotypic evolution, constant covariances, and the maintenance of additive variance. Evolution, 42(6), 1342–1347.CrossRefGoogle Scholar
  58. Venables, W. N., & Ripley, B. D. (2002). Modern applied statistics with S. Statistics and computing. New York: Springer-Verlag.CrossRefGoogle Scholar
  59. Wagner, W. E., & Basolo, A. L. (2007). The relative importance of different direct benefits in the mate choices of a field cricket. Evolution, 61(3), 617–622.CrossRefPubMedGoogle Scholar
  60. Walker, T. J. (2015). Crickets. In Singing insects of North America. http://entnemdept.ifas.ufl.edu/walker/Buzz/crickets.htm.
  61. Willis, J. H., Coyne, J. A., & Kirkpatrick, M. (1991). Can one predict the evolution of quantitative characters without genetics. Evolution, 45(2), 441–444.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Behavioural Physiology, Department of BiologyHumboldt-Universität zu BerlinBerlinGermany
  2. 2.Museum für Naturkunde Berlin, Leibniz Institute for Evolution and Biodiversity ScienceBerlinGermany
  3. 3.Department of BiologyCalifornia State University NorthridgeNorthridgeUSA
  4. 4.Department of Neurobiology and BehaviorCornell UniversityIthacaUSA

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