Red Queen Coevolution on Fitness Landscapes

  • Ricard V. Solé
  • Josep Sardanyés
Part of the Emergence, Complexity and Computation book series (ECC, volume 6)


Species do not merely evolve, they also coevolve with other organisms. Coevolution is a major force driving interacting species to continuously evolve exploring their fitness landscapes. Coevolution involves the coupling of species fitness landscapes, linking species genetic changes with their inter-specific ecological interactions. Here we first introduce the Red Queen hypothesis of evolution commenting on some theoretical aspects and empirical evidences. As an introduction to the fitness landscape concept, we review key issues on evolution on simple and rugged fitness landscapes. Then we present key modeling examples of coevolution on different fitness landscapes at different scales, from RNA viruses to complex ecosystems and macroevolution.


Cellular Automaton Sequence Space Cellular Automaton Vesicular Stomatitis Virus Fitness Landscape 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agrawal, A.F., Lively, C.M.: Parasites and the evolution of self-fertilization. Evolution 55(5), 869–879 (2001)CrossRefGoogle Scholar
  2. 2.
    Agrawal, A.F., Lively, C.M.: Infection genetics: gene-for-gene versus matching-alleles models and all points in between. Evol. Ecol. Res. 4, 79–90 (2002)Google Scholar
  3. 3.
    Bak, P., Flyvjerg, H., Lautrup, B.: Coevolution in a rugged fitness landscape. Phys. Rev. A 46, 6724–6730 (1992)CrossRefGoogle Scholar
  4. 4.
    Benton, M.J.: Red Queen hypothesis. In: Briggs, D.E.G., Growther, P.R. (eds.) Paleobiology, Blackwell, Oxford (1995)Google Scholar
  5. 5.
    Berryman, A.A., Millstein, J.A.: Are ecological systems chaotic - and if not, why not? Trends Ecol. Evol. 4, 17–28 (1986)Google Scholar
  6. 6.
    Case, T.J.: An Illustrated Guide to Theoretical Ecology. Oxford University Press, Oxford (2000)Google Scholar
  7. 7.
    Chen, Z.Q., Benton, M.J.: The timing and pattern of biotic recovery following the end-Permian mass extinction. Nat. Geosci. 5, 375–383 (2012)CrossRefGoogle Scholar
  8. 8.
    Clarke, D.K., Duarte, E.A., Elena, S.F., Moya, A., Domingo, E., Holland, J.J.: The Red Queen reigns in the kingdom of RNA viruses. Proc. Natl. Acad. Sci. U.S.A. 91, 4821–4824 (1994)CrossRefGoogle Scholar
  9. 9.
    Darwin, C.: On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. John Murray, London (1859)Google Scholar
  10. 10.
    Decaestecker, E., Gaba, S., Raeymaekers, J.A.M., Stoks, R., van Kerckhoven, L., Ebert, D., de Meester, L.: Host-parasite ‘Red Queen’ dynamics archived in pond sediment. Nature 450, 870–873 (2007)CrossRefGoogle Scholar
  11. 11.
    Dercole, F., Ferriere, R., Rinaldi, S.: Chaotic Red Queen coevolution in a three species food chain. Proc. Roy. Soc. B 277, 2321–2330 (2012)CrossRefGoogle Scholar
  12. 12.
    de Visser, J.A.G.M., Elena, S.F.: The evolution of sex: empirical insights into the roles of epistasis and drift. Nat. Rev. Genetics 8, 139–149 (2007)CrossRefGoogle Scholar
  13. 13.
    Dieckmann, U., Marrow, P., Law, R.: Evolutionary cycling in predator-prey interactions: Population dynamics and the Red Queen. J. Theor. Biol. 176, 91–92 (1995)CrossRefGoogle Scholar
  14. 14.
    Dobzhansky, T.: Genetics and the Origin of Species, 3rd edn. Columbia University Press, New York (1951)Google Scholar
  15. 15.
    Drossel, B.: Biological evolution and statistical physics. Adv. Phys. 50, 209–295 (2001)CrossRefGoogle Scholar
  16. 16.
    Ehrlich, P.R., Raven, P.H.: Butterflies and plants: A study in coevolution. Evolution 18, 586–608 (1964)CrossRefGoogle Scholar
  17. 17.
    Eigen, M.: Selforganization of matter and evolution of biological macromolecules. Naturwiss 58, 465–523 (1971)CrossRefGoogle Scholar
  18. 18.
    Elena, S.F., Solé, R.V., Sardanyés, J.: Simple genomes, complex interactions: Epistasis in RNA virus. Chaos 20, 26106 (2010)CrossRefGoogle Scholar
  19. 19.
    Ferrière, R., Fox, G.A.: Chaos and evolution. Trends Ecol. E 10, 480–485 (1995)CrossRefGoogle Scholar
  20. 20.
    Flor, H.H.: The complementary genetic systems in flax and flax rust. Adv. Genetics 8, 29–54 (1956)CrossRefGoogle Scholar
  21. 21.
    Freund, H., Wolter, R.: Evolution of bit strings: some preliminary results. Complex Systems 5, 279–298 (1991)zbMATHGoogle Scholar
  22. 22.
    Gould, S.J.: The Structure of Evolutionary Theory. Harvard University Press, Cambridge (2003)Google Scholar
  23. 23.
    Grosberg, R.K., Hart, M.W.: Mate selection and the evolution of highly polymorphic self/nonself recognition genes. Science 289, 2111–2114 (2000)CrossRefGoogle Scholar
  24. 24.
    Haken, H.: Advanced Synergetics. Springer Series in Synergetics. Springer, New York (1983)CrossRefzbMATHGoogle Scholar
  25. 25.
    Haldane, J.B.S.: The Causes of Evolution. Longmans and Green, London (1932)Google Scholar
  26. 26.
    Hamilton, W.D.: Sex vs. non-sex vs. parasite. Oikos 35, 282–290 (1980)CrossRefGoogle Scholar
  27. 27.
    Hamilton, W.D., Axelrod, A., Tanese, R.: Sexual reproduction as an adaptation to resist parasites (a review). Proc. Natl. Acad. Sci. U.S.A. 87, 3566–3573 (1990)CrossRefGoogle Scholar
  28. 28.
    Hastings, A., Powell, T.: Chaos in a three-species food chain. Ecology 72(3), 896–903 (1991)CrossRefGoogle Scholar
  29. 29.
    Hoffman, A.: Testing the Red Queen hypothesis. J. Evol. Biol. 4, 1–7 (1991)CrossRefGoogle Scholar
  30. 30.
    Howard, R.S., Lively, C.M.: Parasitism, mutation accumulation and the maintenance of sex. Nature 367, 554–557 (1994)CrossRefGoogle Scholar
  31. 31.
    Ikegami, T., Kaneko, K.: Evolution of host-parasitoid network through homeochaotic dynamics. Chaos 2, 397–407 (1992)CrossRefGoogle Scholar
  32. 32.
    Ilachinsky, A.: Cellular Automata. A Discrete Universe. World Scientific, Singapore (2000)Google Scholar
  33. 33.
    Jacob, F.: Evolution and tinkering. Science 196, 1161 (1977)CrossRefGoogle Scholar
  34. 34.
    Jacob, F.: Molecular tinkering in evolution. In: Rondall, D.S. (ed.) Evolution from Molecules to Men. Cambridge University Press, Cambridge (1983)Google Scholar
  35. 35.
    Jaenike, J.: An hypothesis to account for the maintenance of sex in populations. Evol. Theor. 3, 191–194 (1978)Google Scholar
  36. 36.
    Kaneko, K., Ikegami, T.: Homeochaos: dynamic stability of a symbiotic network with population dynamics and evolving mutation rates. Physica D 56, 406–429 (1992)CrossRefzbMATHGoogle Scholar
  37. 37.
    Kauffman, S.A., Johnsen, J.: Coevolution on the edge of chaos: Coupled fitness landscapes, poised states and coevolutionary avalanches. J. Theor. Biol. 149, 467–505 (1991)CrossRefGoogle Scholar
  38. 38.
    Kauffman, S.A.: The Origins of Order. Oxford University Press, New York (1993)Google Scholar
  39. 39.
    Kerr, A.: The impact of molecular genetics of plant pathology. Annu. Rev. Phytopathol. 25, 87–110 (1987)CrossRefGoogle Scholar
  40. 40.
    King, K.C., Delph, L.F., Jokela, J., Lively, C.M.: The geographic mosaic of sex and the Red Queen. Curr. Biol. 19, 1438–1441 (2009)CrossRefGoogle Scholar
  41. 41.
    Lafforgue, G., Martínez, F., Sardanyés, J., de la Iglesia, F., Shi-Shun, L., Qi-Wen, N., Solé, R.V., Chua, N.H., Darós, J.-A., Elena, S.F.: Tempo and mode of plant RNA virus escape from RNA interference-mediated resistance. J. Virol. 85(19), 9686–9695 (2011)CrossRefGoogle Scholar
  42. 42.
    Li, W.H., Graur, D.: Fundamentals of Molecular Evolution. Sinauer Associates, Sunderland (1991)Google Scholar
  43. 43.
    Lively, C.M.: Evidence from a New Zealand snail for the maintenance of sex by parasitism. Nature 328, 519–521 (1987)CrossRefGoogle Scholar
  44. 44.
    Manrubia, S.C., Paczuski, M.: A simple model of large-scale organization in Evolution. Int. J. Mod. Phys. C 9, 1025–1032 (1998)CrossRefGoogle Scholar
  45. 45.
    May, R.M., Anderson, R.M.: Epidemiology and genetics in the coevolution of parasites and hosts. Proc. R. Soc. Lond. B 219, 281–313 (1983)CrossRefzbMATHGoogle Scholar
  46. 46.
    McCaskill, J.S., Altemeyer, S.: Error threshold for spatially resolved evolution in the quasispecies model. Phys. Rev. Lett. 86, 5819 (2001)CrossRefGoogle Scholar
  47. 47.
    Mode, D.J.: A mathematical model for the co-evolution of obligate parasites and their hosts. Evolution 12, 158–165 (1958)CrossRefGoogle Scholar
  48. 48.
    Montoya, J.M., Pim, S., Solé, R.V.: Ecological networks and their fragility. Nature 442, 259–264 (2006)CrossRefGoogle Scholar
  49. 49.
    Morran, L.T., Schmidt, O.G., Gelarden, I.A., Parrish II, R.C., Lively, C.M.: Running with the Red Queen: Host-parasite coevolution selects for biparental sex. Science 333, 216–218 (2011)CrossRefGoogle Scholar
  50. 50.
    Newman, M.E.J., Palmer, R.G.: Modeling Extinction. Oxford University Press, New York (2003)Google Scholar
  51. 51.
    Nicolis, G., Prigogine, I.: Self-Organization in Non-Equilibrium Systems. Wiley-Interscience, New York (1977)Google Scholar
  52. 52.
    Parker, M.A.: Pathogens and sex in plants. Evol. Ecol. 8, 560–584 (1994)CrossRefGoogle Scholar
  53. 53.
    Pascual, M.: Diffusion-induced chaos in a spatial predator-prey system. Proc. Roy. Soc. London B 251, 1–7 (1993)CrossRefGoogle Scholar
  54. 54.
    Molecular evolution on rugged landscapes: proteins, RNA and the immune system. In: Perelson, A.S., Kauffman, S. (eds.) SFI Studies in the Sciences of Complexity, vol. IX. Addison-Wesley, Redwood (1991)Google Scholar
  55. 55.
    Quer, J., Huerta, R., Novella, I.S., Tsimring, L., Domingo, E., Holland, J.J.: Reproducible nonlinear population dynamics and critical points during replicative competitions of RNA virus quasispecies. J. Mol. Biol. 264, 465–471 (1996)CrossRefGoogle Scholar
  56. 56.
    Raup, D.M.: Biological extinction and Earth history. Science 231, 1528–1533 (1986)CrossRefGoogle Scholar
  57. 57.
    Raup, D.M.: A kill curve for phanerozoic marine species. Paleobiology 17, 37–48 (1991)Google Scholar
  58. 58.
    Roopnarine, P.D.: Extinction cascades and catastrophe in ancient food webs. Paleobiology 32(1), 1 (2006)Google Scholar
  59. 59.
    Sardanyés, J., Solé, R.V.: Chaotic stability in spatially-resovled host-parasite replicators: The Red Queen on a lattice. Int. J. Bif. and Chaos 17(2), 589–606 (2007)CrossRefzbMATHGoogle Scholar
  60. 60.
    Sardanyés, J.: Low dimensional homeochaos in coevolving host-parasotoid dimorphic populations: Extinction thresholds under local noise. Commun. Nonlinear Sci. Numer. Simul. 16, 3896–3903 (2011)CrossRefzbMATHGoogle Scholar
  61. 61.
    Sardanyés, J., Solé, R.V.: Matching allele dynamics and coevolution in a minimal predator-prey replicator model. Phys. Lett. A 372, 341–350 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  62. 62.
    Sardanyés, J., Solé, R.V.: Red Queen strange attractors in host-parasite replicator gene-for-gene coevolution. Chaos, Solitons and Fractals 32(5), 1666–1678 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  63. 63.
    Sardanyés, J., Elena, S.F.: Error threshold in RNA quasispecies models with complementation. J. Theor. Biol. 265, 278–286 (2010)CrossRefGoogle Scholar
  64. 64.
    Sardanyés, J., Elena, S.F.: Quasispecies spatial models for RNA viruses with different replication modes and infection strategies. PLoS One 6(9), e24884 (2011)Google Scholar
  65. 65.
    Sardanyés, J., Solé, R.V., Elena, S.F.: Replication mode and landscape topology differentially affect RNA virus mutational load and robustness. J. Virol. 83(23), 12579–12589 (2009)CrossRefGoogle Scholar
  66. 66.
    Sardanyés, J., Elena, S.F., Solé, R.V.: Simple quasispecies models for the survival-of-the-flattest effect: The role of space. J. Theor. Biol. 250, 560–568 (2008)CrossRefGoogle Scholar
  67. 67.
    Seger, J.: Evolution of exploiter-victim relationships. In: Crawley, M.J. (ed.) Natural Enemies: the Population Biology of Predators, Parasites and Diseases, pp. 3–25. Blackwell, Oxford (1992)Google Scholar
  68. 68.
    Solé, R.V., Sardanyés, J., Díez, J., Mas, A.: Information catastrophe in RNA viruses through replication thresholds. J. Theor. Biol. 240, 353–359 (2006)CrossRefGoogle Scholar
  69. 69.
    Solé, R.V.: Phase transitions in unstable cancer cell populations. Europ. Phys. Journal 35(1), 117–124 (2003)CrossRefGoogle Scholar
  70. 70.
    Solé, R.V., Ferrer, R., González-García, Q.J., Domingo, E.: Red Queen dynamics, competition and critical points in a model of RNA virus quasispecies. J. Theor. Biol. 198, 47–59 (1999)CrossRefGoogle Scholar
  71. 71.
    Solé, R.V., Bascopmte, J.: Self-organization in Complex Ecosystems. Princeton University Press, Princeton (2006)Google Scholar
  72. 72.
    Solé, R.V.: On macroevolution, extinctions and critical phenomena. Complexity 1, 40–46 (1996)CrossRefGoogle Scholar
  73. 73.
    Solé, R.V., Bascompte, J., Manrubia, S.C.: Extinction: bad genes or weak chaos? Proc. Roy. Soc. B 263, 161–168 (1996)CrossRefGoogle Scholar
  74. 74.
    Solé, R.V., Manrubia, S.C.: Extinction and self-organized criticality in a model of large-scale evolution. Phys. Rev. E 51, 6250–6253 (1996)CrossRefGoogle Scholar
  75. 75.
    Solé, R.V., Manrubia, S.C.: Criticality and unpredictability in macroevolution. Phys. Rev. E 55, 4500–4508 (1997)CrossRefGoogle Scholar
  76. 76.
    Solé, R.V., Montoya, J., Erwin, D.H.: Recovery after mass extinction: evolutionary assembly in large-scale biosphere dynamics. Phil. Trans. Roy. Soc. B-Biol. Sci. 357, 697–707 (2002)CrossRefGoogle Scholar
  77. 77.
    Solé, R.V., Saldaña, J., Montoya, J.M., Erwin, D.H.: Simple model of recovery dynamics after mass extinction. J. Theor. Biol. 267, 193–200 (2010)CrossRefGoogle Scholar
  78. 78.
    Solé, R.V., Manrubia, S.C., Mercader, J.P., Benton, M., Bak, P.: Long-range correlations in the fossil record and the fractal nature of macroevolution. Adv. Compl. Syst. 1, 255–266 (1998)CrossRefGoogle Scholar
  79. 79.
    Stenseth, N.C., Maynard Smith, J.: Coevolution in ecosystems: Red Queen evolution or stasis? Evolution 38, 870–880 (1984)CrossRefGoogle Scholar
  80. 80.
    Tegmark, M.: An icosahedron-based method for pixelizing the celestial sphere. The Astrophys. J. 470, L81–L84 (1996)Google Scholar
  81. 81.
    Thompson, J.N.: Interaction and coevolution. Wiley, New York (1982)Google Scholar
  82. 82.
    Thompson, J.N.: Concepts of coevolution. Trends Ecol. Evol. 4, 179–183 (1989)CrossRefGoogle Scholar
  83. 83.
    Thompson, J.N.: Coevolution and the evolutionary genetics of interactions among plants and insects and pathogens. In: Burdon, J.J., Leather, S.R. (eds.) Pests, Pathogens and Plant Communities, pp. 249–271. Blackwell, Oxford (1990)Google Scholar
  84. 84.
    Thompson, J.N., Burdon, J.J.: Gene-for-gene coevolution between plants and parasites. Nature 360, 121–125 (1992)CrossRefGoogle Scholar
  85. 85.
    Van Valen, L.: Energy and evolution. Evol. Theory 1, 179–229 (1976)Google Scholar
  86. 86.
    Van Valen, L.: Evolution as a zero-sum game for energy. Evol. Theory 4, 129–142 (1980)Google Scholar
  87. 87.
    Van Valen, L.: A new evolutionary law. Evol. Theory 1, 1–30 (1973)Google Scholar
  88. 88.
    Vidal, C., Pacault, A. (eds.): Non-Equilibrium Dynamics in Chemical Systems. Springer Series in Synergetics. Springer, New York (1984)zbMATHGoogle Scholar
  89. 89.
    Weltz, J.S., Levin, S.: Size and scaling of predator-prey dynamics. Ecol. Lett. 9, 548–557 (2006)CrossRefGoogle Scholar
  90. 90.
    Wright, S.: Evolution in Mendelian populations. Genetics 16, 97 (1931)Google Scholar
  91. 91.
    Wright, S.: The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proceedings of the Sixth International Congress on Genetics 1, 356 (1932)Google Scholar
  92. 92.
    Yip, K.Y., Patel, P., Kim, P.M., Engelman, D.M., McDermott, D., Gerstein, M.: An integrated system for studying residue coevolution in proteins. Bioinformatics 24, 290–292 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ricard V. Solé
    • 1
    • 2
    • 3
  • Josep Sardanyés
    • 1
    • 2
  1. 1.ICREA-Complex Systems LabUniversitat Pompeu FabraBarcelonaSpain
  2. 2.Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra)BarcelonaSpain
  3. 3.Santa Fe InstituteSanta FeUSA

Personalised recommendations