Convert the data frame of FEs coordinates to a species coordinates one

Usage

from.fecoord.to.spcoord(fe_faxes_coord, asb_sp_w, sp_to_fe)

Arguments

fe_faxes_coord: the data frame gathering FEs coordinates along functional axes, with columns representing axes and rows representing FEs.
asb_sp_w: the data frame gathering species*assemblages, with species in columns and assemblages in rows.
sp_to_fe: the output of the mFD::sp.to.fe() function.

Value

a data frame gathering species coordinates, with axes being columns and species being rows. Note: Works for up to 10 PC.

Author

Camille Magneville

Examples

# Load species traits data:
 data("fruits_traits", package = "mFD")

# Transform species traits data:
# Only keep the first 4 traits to illustrate FEs:
 fruits_traits <- fruits_traits[ , c(1:4)]   

# Load trait types data:
 data("fruits_traits_cat", package = "mFD")

# Transform the trait types data to only keep traits 1 - 4:
 fruits_traits_cat <- fruits_traits_cat[c(1:4), -3]
 
 # Load Assemblages*Species matrix:
data('baskets_fruits_weights', package = 'mFD')

# Gather species into FEs:
## gathering species into FEs (FEs named according to the decreasing...
## ...  number of species they gather):
 sp_FEs_fruits <- mFD::sp.to.fe(
      sp_tr      = fruits_traits, 
      tr_cat     = fruits_traits_cat, 
      fe_nm_type = "fe_rank")
      
# Compute the functional distance between FEs:
fe_dist_fruits <- mFD::funct.dist(sp_tr         = sp_FEs_fruits$fe_tr,
                                  tr_cat        = fruits_traits_cat,
                                  metric        = "gower",
                                  scale_euclid  = "scale_center",
                                  ordinal_var   = "classic",
                                  weight_type   = "equal",
                                  stop_if_NA    = TRUE)
 
 # Compute the quality of functional spaces:
 fspaces_quality_fruits <- mFD::quality.fspaces(
                                          sp_dist = fe_dist_fruits,
                                          maxdim_pcoa = 10,
                                          deviation_weighting = "absolute",
                                          fdist_scaling       = FALSE,
                                          fdendro             = "average")
 fspaces_quality_fruits$quality_fspaces
#>                     mad
#> pcoa_1d      0.15334415
#> pcoa_2d      0.06766273
#> pcoa_3d      0.05468598
#> pcoa_4d      0.06133105
#> pcoa_5d      0.07202144
#> pcoa_6d      0.07567050
#> pcoa_7d      0.07813058
#> pcoa_8d      0.08013256
#> pcoa_9d      0.08145439
#> pcoa_10d     0.08205815
#> tree_average 0.10189380
 
 # Get coordinates of FEs in the 3D space:
 fe_faxes_coord_fruits <- fspaces_quality_fruits$details_fspaces$sp_pc_coord
 fe_faxes_coord_fruits <- fe_faxes_coord_fruits[, 1:3]
      
# Get the matrix of species coordinates, from the matrix of FEs coordinates:
sp_faxes_coord <- mFD::from.fecoord.to.spcoord(
                                      fe_faxes_coord = fe_faxes_coord_fruits,
                                      asb_sp_w = baskets_fruits_weights,
                                      sp_to_fe = sp_FEs_fruits)