Skip to main content

Adaptive Landscape with Singularity in Evolutionary Processes

  • Chapter
  • First Online:
Nonlinear Dynamics and Complexity

Part of the book series: Nonlinear Systems and Complexity ((NSCH,volume 8))

  • 1451 Accesses

Abstract

Adaptive landscape, proposed by Sewall Wright, has been used to find optimized solutions of a system. The optimized solution of an evolutionary system is when evolution maximizes or minimizes the value of some function of the trait under consideration, thus providing an absolute measure of fixation for a biological process in a probabilistic sense. We survey the role of adaptive landscape and give some general results concerning the question of infinite potential escaping. The results presented include complex dynamical behaviors manifested by adaptive landscape with singularity in all parameters regimes. In addition, both metaphoric and quantitative description of many complex biological phenomena is provided by adaptive landscape, such as the rare event of transition between different stable states.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wright S (1932) The role of mutation, inbreeding, crossbreeding and selection in evolution. Proc Int Congr Genet 1:356–366

    Google Scholar 

  2. Lande R (1976) Natural selection and random genetic drift in phenotypic evolution. Evolution 30:314–334

    Article  Google Scholar 

  3. Arnold SJ, Pfrender ME, Jones AG (2001) The adaptive landscape as a conceptual bridge between micro and macroevolution. Genetica 112–113: 9–32

    Article  Google Scholar 

  4. Wright S (1988) Surfaces of selective value revisited. Am Nat 131:115–123

    Article  Google Scholar 

  5. Wright S (1967) Surfaces of selective value. Proc Natl Acad Sci 131:165–172

    Article  Google Scholar 

  6. Provine WB (1986) Sewall Wright and evolutionary biology. University of Chicago Press, Chicago, IL

    Google Scholar 

  7. Weinreich DM, Sindi S, Watson RA (2013) Finding the boundary between evolutionary basins of attraction, and implications for wrights fitness landscape analogy. J Stat Mech Theor Exp 01:P01001

    MathSciNet  Google Scholar 

  8. Gyllenberg M, Metz JAJ, Service R (2011) When do optimisation arguments make evolutionary sense? In: Fabio ACC Chalub, Jos Francisco Rodrigues (eds) The mathematics of Darwin’s legacy. Springer, Basel, pp 233–288

    Google Scholar 

  9. Ao P (2009) Global view of bionetwork dynamics: adaptive landscape. J Genet Genom 36:63–73

    Article  Google Scholar 

  10. Kaplan J (2008) The end of the adaptive landscape metaphor? Biol Philos 23:625–638

    Article  Google Scholar 

  11. Gavrilets S (1997) Evolution and speciation on holey adaptive landscapes. Trends Ecol Evol 12:307–312

    Article  Google Scholar 

  12. Ao P (2008) Emerging of stochastic dynamical equalities and steady state thermodynamics from Darwinian dynamics. Comm Theor Phys 49:1073–1090

    Article  MathSciNet  Google Scholar 

  13. Ao P (2005) Laws in Darwinian evolutionary theory. Phys Life Rev 2:117–156

    Article  Google Scholar 

  14. Pigliucci M, Kaplan J (2006) Making sense of evolution: the conceptual foundations of evolutionary thoery. University of Chicago Press, Chicago, IL

    Book  Google Scholar 

  15. de Vladar HP, Barton NH (2009) Statistical mechanics and the evolution of polygenic quantitative traits. Genetics 181:997–1011

    Article  Google Scholar 

  16. Coe JB, Barton NH (2009) On the application of statistical physics to evolutionary biology. J Theor Biol 259:317–324

    Article  MathSciNet  Google Scholar 

  17. Assaf M, Mobilia M (2011) Fixation of deleterious allele under mutation pressure and finite selection intensity. J Theor Biol 275:93–103

    Article  MathSciNet  Google Scholar 

  18. Bharucha-Reid AT (1960) Elements of the theory of Markov processes and their applications. McGraw-Hill, New York

    MATH  Google Scholar 

  19. Feller W (1954) Diffusion processes in one dimension. Trans Am Math Soc 77:1–31

    Article  MathSciNet  MATH  Google Scholar 

  20. Kimura M (1964) Diffusion models in population genetics. J Appl Prob 1:177–232

    Article  MATH  Google Scholar 

  21. Ewens WJ (2004) Mathematical population genetics. Springer, New York

    Book  MATH  Google Scholar 

  22. Ao P (2004) Potential in stochatic differential equation: novel construction. J Phys Math Gen 37:25–30

    Article  MathSciNet  Google Scholar 

  23. Fisher RA (1930) The genetical theory of natural selection. Clarendon Press, Oxford

    MATH  Google Scholar 

  24. Wright S (1931) Evolution in Mendelian populations. Genetics 16:97–159

    Google Scholar 

  25. Blythe RA, McKane AJ (2007) Stochastic models of evolution in genetics, ecology and linguistics. J Stat Mech Theor Exp 2007:P07018

    Article  Google Scholar 

  26. Waxman D, Loewe L (2010) A stochastic model for a single click of Muller’s ratchet. J Theor Biol 264:1120–1132

    Article  MathSciNet  Google Scholar 

  27. Van Nimwegen E, Crutchfield JP, Huynen M (1999) Neutral evolution of mutational robustness. Proc Natl Acad Sci 96:9716–9720

    Article  Google Scholar 

  28. Krakauer DC, Plotkin JB (2002) Redundancy, antiredundancy, and the robustness of genomes. Proc Natl Acad Sci 99:1405–1409

    Article  Google Scholar 

  29. Waxman D (2007) Singular solutions of the diffusion equation of population genetics. J Theor Biol 247:849–858

    Article  MathSciNet  Google Scholar 

  30. Gillespie JH (2004) Population genetics: a concise guide. The Johns Hopkins University Press, Baltimore

    Google Scholar 

  31. Kramers HA (1940) Brownian motion in a field of force and the diffusion model of chemical reactions. Physica 7:284–304

    Article  MathSciNet  MATH  Google Scholar 

  32. Xu S, Jiao SY, Jiang PY, Yuan B, Ao P (2012) Escape from infinite adaptive peak. In: Proceedings of Sixth International Conference on System Biology, 268–273, Xi’an, 18–20 August (2012)

    Google Scholar 

  33. Muller HJ (1964) The relation of recombination to mutational advance. Mutat Res Fund Mol Mech Mutagen 1:2–9

    Article  Google Scholar 

  34. Maynard Smith J (1978) The evolution of sex. Cambridge University Press, England

    Google Scholar 

  35. Etheridge A, Pfaffelhuber P, Wakolbinger A (2009) How often does the ratchet click? Facts, heuristics, asymptotics. In: Bath J, Mörters P, Scheutzow M (eds) Trends in stochastic analysis. Springer, Basel, pp 233–288

    Google Scholar 

  36. Jiao SY, Ao P (2012) Absorbing phenomena and escaping time for Muller’s ratchet in adaptive landscape. BMC Syst Biol S1:S10

    Article  Google Scholar 

  37. Van Kampen NG (1992) Stochatic processes in physics and chemistry. North Holland, Amsterdam

    Google Scholar 

  38. Ø ksendal B (2003) Stochatic differential equations: an introduction with applications. Springer, Berlin

    Google Scholar 

  39. Zhou D, Qian H (2011) Redundancy, antiredundancy, and the robustness of genomes. J Theor Biol 99:1405–1409

    Google Scholar 

Download references

Acknowledgements

The critical discussion with Prof. Zhu Xiaomei is appreciated. We also thank Jiang Pengyao, Wang Yanbo, and other members in the lab for their constructive comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ping Ao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Jiao, S., Xu, S., Ao, P. (2014). Adaptive Landscape with Singularity in Evolutionary Processes. In: Afraimovich, V., Luo, A., Fu, X. (eds) Nonlinear Dynamics and Complexity. Nonlinear Systems and Complexity, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-02353-3_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-02353-3_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02352-6

  • Online ISBN: 978-3-319-02353-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics