genotype by environment interactions gx e and climate change
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Genotype by environment interactions (GxE)
and climate change Jacob van Etten Alberto Labarga
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G x E
P = G + E + G*E
P = Production G = Genotype E = Environment
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In other words...
Suppose we have a continuous environmental variable two different genotypes i = {1,2}
Now the regression equation becomes:
P = (β0 +) β1Gi + β2E + β3GiE (+ e)
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Purely genetic difference
P = β1Gi + β2E + β3GiE β1 ≠ 0 β2 = 0 β3 = 0
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Purely additive interaction
P = β1Gi + β2E + β3GiE β1 ≠ 0 β2 ≠ 0 β3 = 0
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Non-additive interaction
P = β1Gi + β2E + β3GiE β1 ≠ 0 β2 ≠ 0 β3 ≠ 0
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Cross-over: When does another variety take over?
climate change →
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Lobell et al. (2011) study Weather variables
Yield
Ecophysiological variables
Weather variables
Yield
Ecophysiological variables
+ 1 °C
Estimate statistical
model Calculate
Recalculate Predict using
estimated model
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Lobell et al. (2011)
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Climate change impact maps
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GxE: OPV vs hybrid
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GxE: duration
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What breeders usually do: AMMI
Additive Main Effects and Multiplicative Interaction
Production = G + E + residuals Then do a PCA on residuals to visualize the GxE interactions. (An alternative is to only remove G – known as GGE.)
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Example of AMMI Biplot
Stress
Normal
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RDA: adding environmental variables
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Variety adaptation zones
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Final remarks
Statistical models complement mechanistic models Use real data for places where mechanistic models have not been calibrated Get an estimate of the error Link to daily plant breeding practice!
Package weatherData to get weather data for trial locations and derive ecophysiological variables