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Genecology and Adaptation of Douglas-Fir to Climate Change

Genecology and Adaptation of Douglas-Fir to Climate Change. Brad St.Clair 1 , Ken Vance-Borland 2 and Nancy Mandel 1 1 USDA Forest Service, Pacific Northwest Research Station 2 Oregon State University Corvallis, Oregon. Objectives.

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Genecology and Adaptation of Douglas-Fir to Climate Change

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  1. Genecology and Adaptation of Douglas-Fir to Climate Change Brad St.Clair1, Ken Vance-Borland2 and Nancy Mandel1 1USDA Forest Service, Pacific Northwest Research Station 2Oregon State University Corvallis, Oregon

  2. Objectives • To explore geographic genetic structure and the relationship between genetic variation and climate • To evaluate the effects of changing climates on adaptation of current populations • To consider the locations of populations that might be expected to be best adapted to future climates

  3. Genecology • Definition: the study of intra-specific genetic variation of plants in relation to environments (Turesson 1923) • Consistent correlations between genotypes and environments suggest natural selection and adaptation of populations to their environments (Endler 1986) • Methods for exploring genecology and geographic structure – common garden studies • Classical provenance tests • Campbell approach • intensive sampling scheme • particularly advantageous in the highly heterogeneous environments in mountains

  4. Objective 1: Geographic structure and relationship between genetic variation and climate Douglas-fir common garden study Distribution of parent trees and elevation Raised beds

  5. Analysis • Canonical correlation analysis • Determines pairs of linear combinations from two sets of original variables such that the correlations between canonical variables are maximized • Trait variables • emergence, growth, bud phenology, and partitioning • Climate variables • modeled by PRISM • annual and monthly precipitation, minimum and maximum temperatures, seasonal ratios • Use GIS to display results

  6. Results from CCA First component accounted for much of the variation. First component may be called vigor – correlated with large size (r=0.65), late bud-set (r=0.94), high shoot:root ratio (r=0.60), and fast emergence rate (r=0.71).

  7. Results from CCA Model: trait1=-0.08+0.38*decmin –0.25*janmin+0.09*febmax +0.13*marmin-0.12*augmin+0.02*augpre

  8. Dec Minimum Temperature CV 1 for Traits Geographic genetic variation in first canonical variable for traits

  9. Objective 2: Effects of changing climates on adaptation of current populations Methods • Develop model of the relationship between genetic variation and environment using climate variables. • Given model, determine set of genotypes that may be expected to be best adapted to future climate. • Given climate change, determine degree of maladaptation of current population to changed climate as determined by the mismatch between current population and best adapted population.

  10. Step 2: Given model, determine set of genotypes that may be expected to be best adapted to future climate • Some assumptions: • A population is better adapted to its place of origin than any other populations. • The map of adaptive genetic variation is also a map of the environmental complex that is active in natural selection. • Thus, the map of the future climate is also a map of the genotypes that may be expected to be best adapted to that climate.

  11. Climate change predictions • Two models: • Canadian Center for Climate Modeling and Analysis • Hadley Center for Climate Prediction and Research • We assumed no geographic variation in climate change

  12. Climate change predictions

  13. Present 2030 2095 Geographic genetic variation that may be expected to be best adapted to present and future climates

  14. Step 3: Given climate change, determine degree of maladaptation of current population to changed climate as determined by the mismatch between current population and best adapted population to the future climate (risk index as proposed by Campbell 1986) current population future environmental complex Degree of mismatch a function of: difference = 0.5 additive genetic variance a= 0.52 percentage mismatch = 37 %

  15. Present 2030 2095 Maladaptation from climate change

  16. Summary of Objective 2: Effects of changing climates on adaptation of current populations • 40% risk of maladaptation within acceptable limits of seed transfer (Campbell, Sorensen). • 71-84% risk is somewhat high. • Enough genetic variation present to allow evolution through natural selection or migration. • Maladaptation does not necessarily mean mortality. Trees may actually grow better, but below the optimum possible with the best adapted populations.

  17. present 2030 2095 Objective 3. To consider the locations of populations that might be expected to be best adapted to future climates Focal Point Seed Zones

  18. How far down in elevation do we go to find populations adapted to future climates? r = -0.69

  19. Conclusions • Douglas-fir has considerable geographic genetic structure in vigor, most strongly associated with winter minimum temperatures. • Climate change results in some risk of maladaptation, but current populations appear to have enough genetic variation that they may be expected to evolve to a new optimum through natural selection or migration. • Populations that may be expected to be best adapted to future climates will come from much lower elevations, and, perhaps, further south. • Forest managers should consider mixing seed from local populations with populations that may be expected to be adapted to future climates.

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