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Adaptive dynamics Virginie Ravigné UMR BGPI, Montpellier Séminaire « Modèles en Ecologie Evolutive » 31 mai – 2 juin 2010 CEFE-CNRS Monpellier
Frequency-dependent selection ,[object Object],[object Object],[object Object],[object Object],Trait 1 Trait 2 Fitness ,[object Object]
Frequency-dependent selection ,[object Object],[object Object],[object Object],[object Object],Side-blotched lizards ( Uta stansburiana )  play a rock-paper-scissors game
Modelling frequency-dependent selection ,[object Object],[object Object],[object Object],[object Object]
How it works – “the mutation-limited toolbox” Chaque individu se caractérise par sa stratégie Trait 1 Trait 2 ... Au sein d’une  grande population monomorphe , dite  résidente , un  mutant  de phénotype proche apparaît. En supposant que chaque individu donne naissance à des individus de même stratégie que lui-même, et en se basant sur le cycle de vie de l’espèce étudiée, on peut calculer la dynamique de la population mutante au sein de la population résidente  La capacité d’un  mutant  à envahir le  résident  définit sa fitness. 3 cas sont alors possibles : - le type d’origine gagne  - le type mutant envahit  - les deux types coexistent En répétant cette démarche, on peut alors calculer quel(s) type(s) sera (seront) présent(s) à long terme. 1 stratégie  = 1  ensemble de traits
How it works – “the mutation-limited toolbox” ,[object Object],[object Object],[object Object],[object Object],[object Object],A finite number of well-known assumptions: Mutant frequency Time
How it works – “the mutation-limited toolbox” ,[object Object],[object Object],[object Object],La fonction d’invasion, une mesure de fitness En temps discret: Elle intègre la complexité écologique sous forme d’une  dynamique de population (d’invasion) Mutant population size Time 0 s x   (  y  ) x y
How it works – “the mutation-limited toolbox” Studying the shape of the invasion function allows to determine  the outcome of evolution Mathematical + graphical tools 0 s x  (  y  ) Resident Mutant Pairwise invasibility plot y = x y s x  (  y  ) Mutant  y Adaptive landscape
Singular strategies Le gradient de sélection donne la direction de la sélection s x  (  y  ) y = x y s x  (  y  ) y = x y gradient négatif gradient positif Singular strategies are those where the selection gradient vanishes s x*  (  y  ) y = x* y y y = x* s x*  (  y  )
Convergence stability Une stratégie ne peut être atteinte par petites mutations que si elle est stable par convergence Une stratégie stable par convergence est un attracteur évolutif x 1 (ex  y 0 ) x y x* x*   n’est pas stable par convergence x y x* x*   est stable par convergence x 0 y 0 x 0
Evolutionary stability Une stratégie singulière est stable par évolution si aucune autre stratégie ne peut l’envahir.  x*   est stable par évolution x*   n’est pas stable par évolution x* x y x y x*
La capacité d’invasion x*  ne peut jamais envahir quand elle est initialement rare x*  peut envahir quand elle est initialement rare x y x* x y x*
Mutual invasibility Deux stratégies  et  peuvent s’envahir mutuellement et éventuellement donner naissance à du polymorphisme si  s x   (  y  ) > 0 et  s y  (  x  ) > 0 x y x* x 1 x 2 x 1 x 2
A simple classification of singular strategies Geritz et al. 1998 Figures from Doebeli et al. 2004 Science Repellors  Trait value Time
A simple classification of singular strategies Geritz et al. 1998 Figures from Doebeli et al. 2004 Science Evolutionary end-points  Trait value Time
A simple classification of singular strategies Geritz et al. 1998 Figures from Doebeli et al. 2004 Science Branching points  Trait value Time
Branching points ,[object Object],[object Object],[object Object],[object Object],x y x* Trait value Time
Favorite topics of adaptive dynamics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
An famous example – DD99 Abondance d’une ressource Trait Dieckmann, U., and M. Doebeli (1999)  On the origin of species by sympatric speciation .  Nature  400 : 354-357. y Intensity of competition between mutant and resident x Efficiency of ressource use y Very simple conclusion :  Branching Evolutionary end-point where resource is maximal
An famous example – DD99
An famous example – DD99 “ Our results extend and contrast previous insights by showing that competition for unimodal resources can initiate sympatric speciation even if assortative mating depends on an ecologically neutral marker trait. […] Evidence is accumulating that ecology is important for speciation, and our theory may provide an integrative framework for understanding otherwise puzzling evidence for monophyletic origins of many sympatric species including cichlids, sticklebacks, snails, giant senecios, and anolis lizards. In all these cases it is likely that frequency-dependent mechanisms are important determinants of the species' ecologies.” Sic !
What’s wrong with adaptive dynamics? 2005 JEB’s target review is about adaptive dynamics  D. WAXMAN, S. GAVRILETS 20 Questions on Adaptive Dynamics H. KOKKO Useful ways of being wrong S. A. H. GERITZ, M. GYLLENBERG Seven answers from adaptive dynamics  J. A. J. METZ Eight personal rules for doing science U. DIECKMANN, M. DOEBELI Pluralism in evolutionary theory Abrams  “Waxman and Gavrilets’ […] are probably correct in arguing that Adaptive Dynamics is insufficient to predict when sympatric speciation will occur” Barton & Polechova  “adaptive dynamics is not plausible as an actual model of evolution under mutation and selection” Gourbière & Mallet  “Has adaptive dynamics contributed to the understanding of adaptive and sympatric speciation?”
What’s wrong with adaptive dynamics? Although the basic assumptions of AD are well-established, their impact on the predictions still has to be evaluated Example : small mutation effects c 1 c 1 Host 1 Host 2 s Ravigné et al. 2009 s 0 Random distribution between habitats Matching habitat choice 0.5 1 0.5 1 0.5 1 0 0 Any inverse trade-off strength   0.5 1 0.5 1 Random distribution between habitats Evolving habitat choice 0 0 W 1 W 2 p Local fitness
Links between AD and empirical research Barton & Polechova “Adaptive dynamics is a useful technique for understanding the qualitative behaviour of an evolving population”. = Souce of inspiration rather than predictive models
Evolution of Adaptive Dynamics Already feasible… - models with (very simple) sexual reproduction (Geritz & Kisdi 1999) - non-equilibrium resident population dynamics - accounting for traits population-level variances and covariances (Leimar 2009) - plasticity Ravigné et al. 2009 Habitat-choice trait,  h 1 0 No covariance 1 0 Local-adaptation trait,  p A 1 0 Strong positive covariance Local-adaptation trait,  p B
Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Merci de votre attention

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Virginie Ravigné - Dynamique adaptative

  • 1. Adaptive dynamics Virginie Ravigné UMR BGPI, Montpellier Séminaire « Modèles en Ecologie Evolutive » 31 mai – 2 juin 2010 CEFE-CNRS Monpellier
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  • 5. How it works – “the mutation-limited toolbox” Chaque individu se caractérise par sa stratégie Trait 1 Trait 2 ... Au sein d’une grande population monomorphe , dite résidente , un mutant de phénotype proche apparaît. En supposant que chaque individu donne naissance à des individus de même stratégie que lui-même, et en se basant sur le cycle de vie de l’espèce étudiée, on peut calculer la dynamique de la population mutante au sein de la population résidente La capacité d’un mutant à envahir le résident définit sa fitness. 3 cas sont alors possibles : - le type d’origine gagne - le type mutant envahit - les deux types coexistent En répétant cette démarche, on peut alors calculer quel(s) type(s) sera (seront) présent(s) à long terme. 1 stratégie = 1 ensemble de traits
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  • 8. How it works – “the mutation-limited toolbox” Studying the shape of the invasion function allows to determine the outcome of evolution Mathematical + graphical tools 0 s x ( y ) Resident Mutant Pairwise invasibility plot y = x y s x ( y ) Mutant y Adaptive landscape
  • 9. Singular strategies Le gradient de sélection donne la direction de la sélection s x ( y ) y = x y s x ( y ) y = x y gradient négatif gradient positif Singular strategies are those where the selection gradient vanishes s x* ( y ) y = x* y y y = x* s x* ( y )
  • 10. Convergence stability Une stratégie ne peut être atteinte par petites mutations que si elle est stable par convergence Une stratégie stable par convergence est un attracteur évolutif x 1 (ex y 0 ) x y x* x* n’est pas stable par convergence x y x* x* est stable par convergence x 0 y 0 x 0
  • 11. Evolutionary stability Une stratégie singulière est stable par évolution si aucune autre stratégie ne peut l’envahir. x* est stable par évolution x* n’est pas stable par évolution x* x y x y x*
  • 12. La capacité d’invasion x* ne peut jamais envahir quand elle est initialement rare x* peut envahir quand elle est initialement rare x y x* x y x*
  • 13. Mutual invasibility Deux stratégies et peuvent s’envahir mutuellement et éventuellement donner naissance à du polymorphisme si s x ( y ) > 0 et s y ( x ) > 0 x y x* x 1 x 2 x 1 x 2
  • 14. A simple classification of singular strategies Geritz et al. 1998 Figures from Doebeli et al. 2004 Science Repellors Trait value Time
  • 15. A simple classification of singular strategies Geritz et al. 1998 Figures from Doebeli et al. 2004 Science Evolutionary end-points Trait value Time
  • 16. A simple classification of singular strategies Geritz et al. 1998 Figures from Doebeli et al. 2004 Science Branching points Trait value Time
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  • 19. An famous example – DD99 Abondance d’une ressource Trait Dieckmann, U., and M. Doebeli (1999) On the origin of species by sympatric speciation . Nature 400 : 354-357. y Intensity of competition between mutant and resident x Efficiency of ressource use y Very simple conclusion : Branching Evolutionary end-point where resource is maximal
  • 20. An famous example – DD99
  • 21. An famous example – DD99 “ Our results extend and contrast previous insights by showing that competition for unimodal resources can initiate sympatric speciation even if assortative mating depends on an ecologically neutral marker trait. […] Evidence is accumulating that ecology is important for speciation, and our theory may provide an integrative framework for understanding otherwise puzzling evidence for monophyletic origins of many sympatric species including cichlids, sticklebacks, snails, giant senecios, and anolis lizards. In all these cases it is likely that frequency-dependent mechanisms are important determinants of the species' ecologies.” Sic !
  • 22. What’s wrong with adaptive dynamics? 2005 JEB’s target review is about adaptive dynamics D. WAXMAN, S. GAVRILETS 20 Questions on Adaptive Dynamics H. KOKKO Useful ways of being wrong S. A. H. GERITZ, M. GYLLENBERG Seven answers from adaptive dynamics J. A. J. METZ Eight personal rules for doing science U. DIECKMANN, M. DOEBELI Pluralism in evolutionary theory Abrams “Waxman and Gavrilets’ […] are probably correct in arguing that Adaptive Dynamics is insufficient to predict when sympatric speciation will occur” Barton & Polechova “adaptive dynamics is not plausible as an actual model of evolution under mutation and selection” Gourbière & Mallet “Has adaptive dynamics contributed to the understanding of adaptive and sympatric speciation?”
  • 23. What’s wrong with adaptive dynamics? Although the basic assumptions of AD are well-established, their impact on the predictions still has to be evaluated Example : small mutation effects c 1 c 1 Host 1 Host 2 s Ravigné et al. 2009 s 0 Random distribution between habitats Matching habitat choice 0.5 1 0.5 1 0.5 1 0 0 Any inverse trade-off strength  0.5 1 0.5 1 Random distribution between habitats Evolving habitat choice 0 0 W 1 W 2 p Local fitness
  • 24. Links between AD and empirical research Barton & Polechova “Adaptive dynamics is a useful technique for understanding the qualitative behaviour of an evolving population”. = Souce of inspiration rather than predictive models
  • 25. Evolution of Adaptive Dynamics Already feasible… - models with (very simple) sexual reproduction (Geritz & Kisdi 1999) - non-equilibrium resident population dynamics - accounting for traits population-level variances and covariances (Leimar 2009) - plasticity Ravigné et al. 2009 Habitat-choice trait, h 1 0 No covariance 1 0 Local-adaptation trait, p A 1 0 Strong positive covariance Local-adaptation trait, p B
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  • 27. Merci de votre attention