Anne Duputié | MEE 2013 | Modelling range shifts in dynamic environments – How can evolution enter the stage?

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Anne Duputié | MEE 2013 | Modelling range shifts in dynamic environments – How can evolution enter the stage?

  1. 1. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Modelling range shifts in dynamic environments – How can evolution enter the stage? Anne Duputié CEFE, Montpellier
  2. 2. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Parmesan et al. Nature 1999 Tircis 1940-69 1970-97 1915-39 - Migration Responses to environmental changes (& lack thereof) 65% of 35 non migrating butterflies have shifted their range northwards in <100 y
  3. 3. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Zhu et al. GCB 2012 Northward shift Southward shift Expansion Contraction - Migration (or not) Northernboundarychange(deglatitude) Southern boundary change (deg latitude) Responses to environmental changes (& lack thereof) only 20% of 92 North American tree species show a northward range shift (59%: contraction)
  4. 4. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Bradshaw & Holzapfel PNAS 2001 1940-69 1970-97 Latitude (corrected for altitude) Wyeomyia smithii (photo S Gray) - Migration (or not) - Adaptation Criticalphotoperiod(h) Responses to environmental changes (& lack thereof) Evolution of critical photoperiod for entering into diapause (heritable trait, h²=15-70%) within 25 years
  5. 5. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 - Migration (or not) - Adaptation (or not) . generation time . no standing variance left Responses to environmental changes (& lack thereof) Drosphila birchii Fragmented populations; no available genetic variance to respond to stress Hoffmann et al Science 2003
  6. 6. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits Distribution of Chamaechrista fasciculata Responses to environmental changes (& lack thereof)
  7. 7. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 precocity number of leaves Responses to environmental changes (& lack thereof) Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits Distribution of Chamaechrista fasciculata
  8. 8. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum climate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits
  9. 9. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum migrationclimate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits
  10. 10. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum migration Adaptation (no migration) climate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits
  11. 11. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum climate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits Phenotype distribution
  12. 12. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum climate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits Phenotype distribution
  13. 13. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum climate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits Phenotype distribution
  14. 14. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Etterson & Shaw Science 2001 Future optimum climate shift by 2035 Responses to environmental changes (& lack thereof) precocity number of leaves Chamaechrista fasciculata Distribution of Chamaechrista fasciculata - Migration (or not) - Adaptation (or not) . generation time . no standing variance left . correlations among traits Phenotype distribution Correlations among traits slow down evolution
  15. 15. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Modelling species distributions Observed occurrences Observed/inferred density Probability of occurrence Habitat suitability
  16. 16. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Modelling species distributions Observed occurrences Observed/inferred density Probability of occurrence Habitat suitability
  17. 17. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Modelling species distributions Example: Fagus sylvatica, European beech
  18. 18. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Modelling species distributions Example: Fagus sylvatica, European beech
  19. 19. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Environment Probability of occurrence Tmax Tmin Prec GDD … Modelling species distributions ?
  20. 20. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 “Phenomenological” Environment Probability of occurrence Tmax Tmin Prec GDD … Modelling species distributionsP(occurrence) environment “
  21. 21. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 “Phenomenological” “Process-based” Environment Probability of occurrence Traits: reaction norms Growth/ Survival… (Fitness) Tmax Tmin Prec GDD … Modelling species distributionsP(occurrence) environment Trait environment
  22. 22. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 “Phenomenological” “Process-based” Environment Probability of occurrence Traits: reaction norms Growth/ Survival… (Fitness) “Conceptual” Traits: realised vs optimum Fitness Tmax Tmin Prec GDD … Modelling species distributionsP(occurrence) environment Trait environment Fitness Matching trait/optimum
  23. 23. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 “Phenomenological” “Process-based” Environment Probability of occurrence Traits: reaction norms Growth/ Survival… (Fitness) “Conceptual” Traits: realised vs optimum Fitness Ease of calibration Understanding Tmax Tmin Prec GDD … Modelling species distributionsP(occurrence) environment Trait environment Fitness Matching trait/optimum Trait evolution
  24. 24. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Genetic adaptation and distribution ranges 1. Constraints to adaptation ? a conceptual model of trait adaptation on a shifting gradient 2. Evolution of trait reaction norms a process-based model of tree distribution ranges
  25. 25. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Factors limiting distribution ranges: Topography Biotic interactions Demography Adaptation Migration 1. Responses to environmental changes: existing conceptual models Brown AmNat 1974 Grinnell Auk 1917 Mimura & Aitken JEB 2009 « Fundamental » niche Realised niche Svenning & Skov EcolLett 2007
  26. 26. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Factors limiting distribution ranges: Topography Biotic interactions Demography Adaptation Migration 1. Responses to environmental changes: existing conceptual models Brown AmNat 1974 Grinnell Auk 1917 Mimura & Aitken JEB 2009 « Fundamental » niche Realised niche Svenning & Skov EcolLett 2007
  27. 27. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Breeder’s equation: R=h² S Available genetic variance Selection strength 1. Responses to environmental changes: existing conceptual models Fitness (intrinsicgrowthrater) Mean trait z Selection gradient Model: - One species - Quantitative trait evolves
  28. 28. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Fitness (intrinsicgrowthrater) Mean trait z Selection gradient Model: - One species - Quantitative trait evolves - Environmental gradient Fitness r 1. Responses to environmental changes: existing conceptual models
  29. 29. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Model: - One species - Quantitative trait evolves - Environmental gradient - Variable population density Fitness r Space Density Coupling demography/adaptation 1. Responses to environmental changes: existing conceptual models Coupling demography/adaptation
  30. 30. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Model: - One species - Quantitative trait evolves - Environmental gradient - Variable population density Fitness r Space Density Coupling demography/adaptation 1. Responses to environmental changes: existing conceptual models
  31. 31. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Some results of this type of models: - No spatial heterogeneity: Maximal speed of environmental change (Lynch & Lande 1993) - Can be generalised to several traits (Gomulkiewicz & Houle AmNat 2009) 0 2 1 2 2 2 G G c S e S V V k k r V N V     too little genetic variance or too weak selection low fecundity small population Extinction if: 1. Responses to environmental changes: existing conceptual models
  32. 32. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Some results of this type of models: - No spatial heterogeneity - Spatial heterogeneity only (Kirkpatrick & Barton AmNat 1997) 1. Responses to environmental changes: existing conceptual models Adaptation depends on VG and migration Meantrait optimum realised Space
  33. 33. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 1. Responses to environmental changes: existing conceptual models Adaptation depends on VG and migration Wider distribution for intermediate migration rates Space MeantraitDensity optimum realised Space Some results of this type of models: - No spatial heterogeneity - Spatial heterogeneity only (Kirkpatrick & Barton AmNat 1997)
  34. 34. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Some results of this type of models: - No spatial heterogeneity - Spatial heterogeneity only - Spatial and temporal heterogeneity (Pease et al Ecology 1989) 1. Responses to environmental changes: existing conceptual models Space MeantraitDensity optimum realised Space
  35. 35. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Some results of this type of models: - No spatial heterogeneity - Spatial heterogeneity only - Spatial and temporal heterogeneity (Pease et al Ecology 1989) 1. Responses to environmental changes: existing conceptual models Space MeantraitDensity optimum realised Space Clines move as the environment changes. If persisting, the species shifts its range at the speed of the environmental change, with a lag.
  36. 36. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Some results of this type of models: - No spatial heterogeneity - Spatial heterogeneity only - Spatial and temporal heterogeneity  what about genetic constraints in heterogeneous environments? 1. Responses to environmental changes: existing conceptual models
  37. 37. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 1. Genetic correlations and range shifts: model ingredients - One species - Fitness depends on several traits under stabilizing selection: S Trait1 Trait 2 Adaptive landscape S
  38. 38. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 1. Genetic correlations and range shifts: model ingredients - One species - Fitness depends on several traits under stabilizing selection: S - Genetic variance: G Trait1 Trait 2 Adaptive landscape S G
  39. 39. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 1. Genetic correlations and range shifts: model ingredients - One species - Fitness depends on several traits under stabilizing selection: S - Genetic variance: G - Environmental gradient, slope b Trait1 Trait 2 Adaptive landscape S G b Space optimum 1 optimum 2 Traitmean
  40. 40. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 - One species - Fitness depends on several traits under stabilizing selection: S - Genetic variance: G - Environmental gradient, slope b - Shifting at speed v Trait1 Trait 2 Adaptive landscape S G b Space optimum 1 optimum 2 Traitmean 1. Genetic correlations and range shifts: model ingredients
  41. 41. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 - One species - Fitness depends on several traits under stabilizing selection: S - Genetic variance: G - Environmental gradient, slope b - Shifting at speed v - Migration: density-dependent diffusion, σ Trait1 Trait 2 Adaptive landscape S G bσ Space Density Space optimum 1 optimum 2 Traitmean 1. Genetic correlations and range shifts: model ingredients
  42. 42. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 - One species - Fitness depends on several traits under stabilizing selection: S - Genetic variance: G - Environmental gradient, slope b - Shifting at speed v - Migration: density-dependent diffusion, σ - Spatial selection gradient Sb Trait1 Trait 2 Adaptive landscape S G b Sb σ Space optimum 1 optimum 2 Traitmean Space Density 1. Genetic correlations and range shifts: model ingredients
  43. 43. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 - One species - Fitness depends on several traits under stabilizing selection: S - Genetic variance: G - Environmental gradient, slope b - Shifting at speed v - Migration: density-dependent diffusion, σ - Spatial selection gradient Sb - G, S, b assumed constant Trait1 Trait 2 Adaptive landscape S G b Sb σ Space optimum 1 optimum 2 TraitmeanDensity Space 1. Genetic correlations and range shifts: model ingredients
  44. 44. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Space trait z optima 1. Genetic correlations and range shifts: results
  45. 45. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Traits develop clines Clines often flatter than optima Space trait z optima realised 1. Genetic correlations and range shifts: results
  46. 46. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Traits develop clines Clines often flatter than optima Population density is gaussian Space trait z optima fitness r Space Space density n realised 1. Genetic correlations and range shifts: results
  47. 47. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Traits develop clines, shifting across time Clines often flatter than optima Population density is gaussian Population shifts Space trait z optima fitness r Space Space density n realised 1. Genetic correlations and range shifts: results
  48. 48. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Traits develop clines, shifting across time Clines often flatter than optima Population density is gaussian Population shifts, with constant lag Space trait z optima fitness r Space Space density n realised Ln 1. Genetic correlations and range shifts: results
  49. 49. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Traits develop clines, shifting across time Clines often flatter than optima Population density is gaussian Population shifts, with constant lag Space trait z optima fitness r Space Space density n realised Ln ρ 1. Genetic correlations and range shifts: results
  50. 50. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb σ Traits develop clines, shifting across time Clines often flatter than optima Population density is gaussian Population shifts, with constant lag Range width constant Space trait z optima fitness r Space Space density n realised Ln ρ Vn 1. Genetic correlations and range shifts: results
  51. 51. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S G b Sb Traits develop clines, shifting across time Clines often flatter than optima Population density is gaussian Population shifts, with constant lag Range width constant Analytical expressions for adaptation & demography. Increase when: Maximal adaptability A = bTS G Sb G aligned with Sb Minimal spatial fitness gradient B = bT S b b aligned with S 1. Genetic correlations and range shifts: results
  52. 52. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Trait1 Trait 2 Adaptive landscape S b Traits develop clines, shifting across time Clines often flatter than optima Population density is gaussian Population shifts, with constant lag Range width constant Analytical expressions for adaptation & demography. Increase when: Maximal adaptability A = bTS G Sb G aligned with Sb Minimal spatial fitness gradient B = bT S b b aligned with S 1. Genetic correlations and range shifts: results
  53. 53. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 0 2 2 2 c B A v r B      Extinction if change faster than: Low fecundity Maladapted migrants Not enough adaptation Slow migration Tolerance to change: 1. Genetic correlations and range shifts: results
  54. 54. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 1. Genetic correlations and range shifts: results Hinders adaptation Widens range diffusion σ Rangewidth diffusion σ Criticalspeed ofchange Migration: diffusion σ Clineslopes Maximal tolerance for intermediate dispersal + = 0 2 2 2 c B A v r B      Extinction if change faster than: Low fecundity Maladapted migrants Not enough adaptation Slow migration Tolerance to change:
  55. 55. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. EcolLett. 2012 Adaptation to change easier when - genetic variance available in the direction of the (spatial) selection gradient - optimum changes in a direction under weak stabilising selection. Counter gradients may appear due to genetic correlations/correlational selection The more traits, the more persistence is threatened. 1. Genetic correlations and range shifts: wrap-up
  56. 56. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Fixed genetic variance Fixed, diffusive dispersal Constrained fitness function No phenotypic plasticity Linear gradients shifting at constant speed 1. BUT…
  57. 57. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Fixed genetic variance Fixed, diffusive dispersal Constrained fitness function No phenotypic plasticity Linear gradients shifting at constant speed Burrows et al. Science 2011 Williams et al PNAS 2007 Non-analogous climates, B2 scenario Projected temperature changes (°C/decade) Spatial gradient (°C/km) 1. BUT…
  58. 58. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Fixed genetic variance Fixed, diffusive dispersal Constrained fitness function No phenotypic plasticity Linear gradients shifting at constant speed use a process-based model to: - evaluate selective pressures - take phenotypic plasticity into account - explicitly model spatial heterogeneity 1. BUT…
  59. 59. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Genetic adaptation and distribution ranges 1. Constraints to adaptation ? a conceptual model of trait adaptation on a shifting gradient 2. Evolution of trait reaction norms a process-based model of tree distribution ranges
  60. 60. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Fitness Local climate Phenological traits ReproductionSurvival Resistance traits
  61. 61. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Bud dormancy Fitness ReproductionSurvival
  62. 62. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Bud dormancy Leafing Flowering Fitness ReproductionSurvival
  63. 63. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Bud dormancy Leafing Flowering Fruit maturation Fitness ReproductionSurvival
  64. 64. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Bud dormancy Leafing Flowering Fruit maturation Leaf senescence Fitness ReproductionSurvival
  65. 65. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT FrostBud dormancy Leafing Flowering Fruit maturation Leaf senescence Fitness ReproductionSurvival
  66. 66. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Frost Drought Bud dormancy Leafing Flowering Fruit maturation Leaf senescence Fitness ReproductionSurvival
  67. 67. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Chuine & Beaubien EcolLett. 2001 2. Evolution of trait reaction norms: the model PHENOFIT Frost Drought Bud dormancy Leafing Flowering Fruit maturation Leaf senescence Fitness ReproductionSurvival
  68. 68. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: calibrating the model fructification leafing + senescence Using time series: phenology & climate Leafingdate observed modelled Year Example: sessile oak Quercus petraea
  69. 69. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: validating the model Presence / absence Observed distribution Fitness simulated by PHENOFIT (1980-2000) Using observed distribution ranges Example: sessile oak Quercus petraea
  70. 70. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: model extrapolations 1950-2000 50-year fecundity, simulated by PHENOFIT Under scenario A1Fi (“business as usual”) Example: sessile oak Quercus petraea
  71. 71. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 1990-2040 2. Evolution of trait reaction norms: model extrapolations 50-year fecundity, simulated by PHENOFIT Under scenario A1Fi (“business as usual”) Example: sessile oak Quercus petraea
  72. 72. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2010-2060 2. Evolution of trait reaction norms: model extrapolations 50-year fecundity, simulated by PHENOFIT Under scenario A1Fi (“business as usual”) Example: sessile oak Quercus petraea
  73. 73. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2030-2080 2. Evolution of trait reaction norms: model extrapolations 50-year fecundity, simulated by PHENOFIT Under scenario A1Fi (“business as usual”) Example: sessile oak Quercus petraea
  74. 74. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2050-2100 2. Evolution of trait reaction norms: model extrapolations 50-year fecundity, simulated by PHENOFIT Under scenario A1Fi (“business as usual”) Example: sessile oak Quercus petraea
  75. 75. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients « plastic » date d=165 d=125 d=102 Method: impose event dates – e.g. leafing date.
  76. 76. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients « plastic » date d=165 d=125 d=102 d=166 d=126 d=103 d=164 d=124 d=101 1plasticd d  1plasticd d  Method: impose event dates – e.g. leafing date.
  77. 77. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients « plastic » date d=165 d=125 d=102 d=166 d=126 d=103 d=164 d=124 d=101 Fecundity 1plasticd d  1plasticd d  Method: impose event dates – e.g. leafing date.
  78. 78. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients « plastic » date d=165 d=125 d=102 d=166 d=126 d=103 d=164 d=124 d=101 Fecundity 1plasticd d  1plasticd d   log fecundity trait   Method: impose event dates – e.g. leafing date.
  79. 79. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients Sessile oak Quercus petraea European beech Fagus sylvatica Fecundity Selection gradient 2000 Fecundity: high low Budburst selected to occur: later earlier
  80. 80. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2020 Sessile oak Quercus petraea European beech Fagus sylvatica Fecundity: high low Budburst selected to occur: later earlier Fecundity Selection gradient 2. Evolution of trait reaction norms: determine selection gradients
  81. 81. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients 2040 Sessile oak Quercus petraea European beech Fagus sylvatica Fecundity Selection gradient Fecundity: high low Budburst selected to occur: later earlier
  82. 82. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients 2060 Sessile oak Quercus petraea European beech Fagus sylvatica Fecundity Selection gradient Fecundity: high low Budburst selected to occur: later earlier
  83. 83. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients 2080 Sessile oak Quercus petraea European beech Fagus sylvatica Fecundity Selection gradient Fecundity: high low Budburst selected to occur: later earlier
  84. 84. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients Sessile oak Quercus petraea European beech Fagus sylvatica Fecundity Selection gradient Fecundity: high low Budburst selected to occur: later earlier 2100
  85. 85. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep 2. Evolution of trait reaction norms: determine selection gradients Temperature Precipitations Temperature Selection for later budburst: western (warmer) part of the range Sessile oak Quercus petraea European beech Fagus sylvatica Budburst selected to occur: later earlier In the climatic (niche) space:
  86. 86. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep Budburst date (imposed) Fecundity Sessile oak Quercus petraea Jan 30 Mar 30 Jun 20 2. Evolution of trait reaction norms: why these patterns?
  87. 87. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep Budburst date (imposed) Fecundity Sessile oak Quercus petraea Jan 30 Mar 30 Jun 20 frost damage 2. Evolution of trait reaction norms: why these patterns?
  88. 88. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Duputié et al. in prep insufficient time to reach maturation Budburst date (imposed) Fecundity Sessile oak Quercus petraea Jan 30 Mar 30 Jun 20 frost damage 2. Evolution of trait reaction norms: why these patterns?
  89. 89. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep Method: suppress reaction norm phenology/local climate Treatments: plastic population d=165 d=125 d=102 d=152 d=120 d=96 year1 year 2 200 160 120 80 Resistance Fitness Climate Phenology 2. Evolution of trait reaction norms: where is plasticity beneficial?
  90. 90. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep 2. Evolution of trait reaction norms: where is plasticity beneficial? Method: suppress reaction norm phenology/local climate Treatments: plastic population no interannual plasticity J=165 J=125 J=102 J=152 J=120 J=96 year1 year 2 200 160 120 80 d=145 d=125 d=102 d=145 d=125 d=102 Resistance Fitness Climate Phenology
  91. 91. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep 2. Evolution of trait reaction norms: where is plasticity beneficial? advantageous burdensome interannual plasticity precipitations temperature
  92. 92. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep Précipitations Température 2. Evolution of trait reaction norms: where is plasticity beneficial? advantageous burdensome interannual plasticity imposed budburst date fecundity
  93. 93. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep Précipitations Température 2. Evolution of trait reaction norms: where is plasticity beneficial? advantageous burdensome interannual plasticity imposed budburst date fecundity
  94. 94. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep Précipitations Température 2. Evolution of trait reaction norms: where is plasticity beneficial? advantageous burdensome interannual plasticity imposed budburst date fecundity
  95. 95. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Rutschmann et al. in prep Précipitations Température 2. Evolution of trait reaction norms: where is plasticity beneficial? advantageous burdensome interannual plasticity imposed budburst date fecundity
  96. 96. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Wrap-up Phenotypic plasticity may translate constraints Interannual variability on budburst/senescence dates weakly impacts fitness + long-distance gene flow e.g. Kremer et al. 2012 -> reaction norms selected at the scale of the range? … except at range/niche margins e.g. Pichancourt & van Klinken 2012
  97. 97. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Perspectives Selection gradients vary over space/time  weak response to climatic change? Can the evolution of phenology mitigate projections of range shifts in temperate trees? Optimal reaction norm Simulated fitness, t=later
  98. 98. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Perspectives Selection gradients vary over space/time  weak response to climatic change? Can the evolution of phenology mitigate projections of range shifts in temperate trees? Optimal reaction norm Simulated fitness, t=later PhD project, O. Ronce/I. Chuine, ED SIBAGHE response  Gβ
  99. 99. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Perspectives Selection gradients vary over space/time  weak response to climatic change? Can the evolution of phenology mitigate projections of range shifts in temperate trees? Optimal reaction norm realised reaction norm Simulated fitness, t=later PhD project, O. Ronce/I. Chuine, ED SIBAGHE response  Gβ
  100. 100. Anne Duputié – Models in Evolutionary Ecology – May 23rd, 2013 Thanks! Isabelle Chuine François Massol Ophélie Ronce Alexis Rutschmann Mark Kirkpatrick

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