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Evolution of migration in a fluctuating environment François Blanquart and Sylvain Gandon June 1 st  2010 François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],François Blanquart – Séminaire MEE 01.06.10 W(home) W(away) W(away)
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],François Blanquart – Séminaire MEE 01.06.10 Siepielski et al.2009 years selection gradient
Introduction ,[object Object],[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10 A M selection A  and  a migration M  and  m 4   genotypes -> p A , p M , D
Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
[object Object],Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
Local adaptation in a fluctuating environment ,[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10
Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
Local adaptation in a fluctuating environment ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10 Fitness( A )>1 Fitness( a )<1 A a Fitness( A )<1 Fitness( a )>1 M many   Am many   am
Evolution of migration ,[object Object],[object Object],[object Object],[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10
Evolution of migration François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Evolution of migration ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Conclusion and perspectives ,[object Object],[object Object],François Blanquart – Séminaire MEE 01.06.10
Conclusion and perspectives ,[object Object],François Blanquart – Séminaire MEE 01.06.10 Sasaki et al. 2002
Conclusion and perspectives ,[object Object],François Blanquart – Séminaire MEE 01.06.10 Gandon & Otto 2007
Conclusion and perspectives ,[object Object],François Blanquart – Séminaire MEE 01.06.10
Thank you François Blanquart – Séminaire MEE 01.06.10

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François Blanquart - Evolution of migration in a fluctuating environment

  • 1. Evolution of migration in a fluctuating environment François Blanquart and Sylvain Gandon June 1 st 2010 François Blanquart – Séminaire MEE 01.06.10
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  • 11. Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
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  • 14. Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
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  • 16. Local adaptation in a fluctuating environment François Blanquart – Séminaire MEE 01.06.10
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  • 19. Evolution of migration François Blanquart – Séminaire MEE 01.06.10
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  • 30. Thank you François Blanquart – Séminaire MEE 01.06.10

Notes de l'éditeur

  1. Clutch=couvée
  2. Clutch=couvée
  3. Clutch=couvée
  4. Clutch=couvée
  5. Clutch=couvée
  6. Rajouter: 2 allèles * 2 loci, 4 génotypes,
  7. Dire direct le taux de migration (taux faible) Expliquer zones grises zones blanches Mettre en avant : le lag et la proportion de la population qui est adaptée…
  8. Plus faible migration: plus grand retard dans le tracking de la sélection, mais une plus forte proportion d’individus est localement adaptée Plus forte migration: plus faible retard dans le tracking de la sélection, mais une plus faible proportion d’individus est localement adaptée
  9. Conclure (c’est grosso modo la même chose) Dire que l’argument intuitif c’est que pour les séries de fourier le premier composant sinusoide est le plus gros contributeur à l’AL.
  10. Evolution of the modifier does not maximize local adaptation, because the two things are not directly related
  11. Evolution of the modifier does not maximize local adaptation, because the two things are not directly related
  12. Evolution of the modifier does not maximize local adaptation, because the two things are not directly related
  13. Mettre des flèches When recombination increases, the ESMR decreases because recombination also helps tracking selection
  14. When there is a cost the ESMR is maximal for an intermediate speed When no cost, the ESMR only depends on the sign of selection; if there is a cost it also depends on the strength of selection on the modifier ; and this strength is very weak when selection changes quickly.