EC_effect {mppR}

Determine EC effects

Description

Determine the effect of environmental covariates (EC) on the mean of a trait across environments and the time range where this effect is the strongest. The procedure was originally proposed by Li et al. (2018).

Usage

EC_effect(
  trait_env_mean,
  crop_duration,
  EC_list,
  type,
  min_win = 20,
  sel_criteria = "global",
  plot = TRUE,
  plot_dir = NULL,
  p_title = "EC_plot",
  env_nm = NULL
)

Arguments

trait_env_mean

vector of trait mean over environment.

crop_duration

numerical value indicating the crop duration.

EC_list

list EC parameter matrix. one per environment. The order of the environment must be the same as the one of the trait mean.

type

character string vector indicating the type of statistic that correspond to the EC. Either the cumulated sum ('sum') or the average ('mean').

min_win

Numerical value indicating the minimum size of the range between start and end day when the EC values are measured. Default = 20

sel_criteria

Character specifying the selection criteria. Default = 'global'

plot

Logical value indicating if a plot of the EC effects over time should be returned. Default = FALSE,

plot_dir

Directory where the plot should be returned. Default = NULL

p_title

Title of the plot. Default = 'EC_plot'

env_nm

Optional vector of environment name. Default = NULL.

Value

Return:

data.frame that contains the following elements for each EC (line). The first line is the value of the EC in the different environments:

1. Start and end date of the optimal window

2. R2 of correlation between trait and EC

3. Direction of the correlation

4. Average R2 value over all tested windows

5. EC value in the different environments for the optimal time window

Author(s)

Vincent Garin

References

Li, X., Guo, T., Mu, Q., Li, X., & Yu, J. (2018). Genomic and environmental determinants and their interplay underlying phenotypic plasticity. Proceedings of the National Academy of Sciences, 115(26), 6679-6684.