feve.plot {mFD}

Plot FEve index

Description

This function plots FEve index for a given pair of functional axes and one or several assemblages. It adds Minimum Spanning Tree (MST) of a given assemblage on the background plot.

Usage

feve.plot(
  ggplot_bg,
  asb_sp_coord2D,
  asb_sp_relatw,
  asb_mst,
  plot_sp = TRUE,
  shape_sp,
  color_sp,
  fill_sp,
  color_mst,
  width_mst,
  linetype_mst
)

Arguments

ggplot_bg

a ggplot object of the plot background retrieved through the background.plot function.

asb_sp_coord2D

a list of matrix (ncol = 2) with coordinates of species present in each assemblage for a given pair of functional axes.

asb_sp_relatw

a list of vector gathering species relative weight in each assemblage. It can be retrieved through the alpha.fd.multidim.

asb_mst

a list (with names as in asb_sp_coord2D) of vectors with names of species linked in the MST of the studied assemblage.

plot_sp

a logical value indicating whether species of each assemblage should be plotted or not. Default: plot_sp = TRUE

shape_sp

a numeric value referring to the shape of the symbol used for species plotting if one assemblage to plot or a vector numeric values if several assemblages to plot. If more than one assemblage to plot, the vector should be formatted as: c(asb1 = "firstRshape", asb2 = "secondRshape", ...).

color_sp

a R color name or an hexadecimal code referring to the color of species if one assemblage to plot or a vector of R color names or hexadecimal codes if several assemblages to plot. If more than one assemblage to plot, the vector should be formatted as: c(asb1 = "firstRcolorname", asb2 = "secondRcolorname", ...).

fill_sp

a R color name or an hexadecimal code referring to the color of species symbol filling (if shape_sp > 20) if one assemblage to plot or a vector of R color names or hexadecimal codes if several assemblages to plot. If more than one assemblage to plot, the vector should be formatted as: c(asb1 = "firstRcolorname", asb2 = "secondRcolorname", ...).

color_mst

a R color name or an hexadecimal code referring to the color the MST if one assemblage to plot or a vector of R color names or hexadecimal codes if several assemblages to plot. If more than one assemblage to plot, the vector should be formatted as: c(asb1 = "firstRcolorname", asb2 = "secondRcolorname", ...).

width_mst

a numeric value referring to the width of segments of the MST if one assemblage to plot or a vector numeric values if several assemblages to plot. If more than one assemblage to plot, the vector should be formatted as: c(asb1 = "firstRsize", asb2 = "secondRsize", ...).

linetype_mst

a numeric value referring to the linetype of the segments representing the MST if one assemblage to plot or a vector numeric values if several assemblages to plot. If more than one assemblage to plot, the vector should be formatted as: c(asb1 = "firstRlinetype", asb2 = "secondRlinetype", ...).

Value

A ggplot object showing FEve index on the background plot.

Author(s)

Camille Magneville and Sebastien Villeger

Examples

# Load Species*Traits dataframe:
data("fruits_traits", package = "mFD")

# Load Assemblages*Species dataframe:      
data("baskets_fruits_weights", package = "mFD") 

# Load Traits categories dataframe:
data("fruits_traits_cat", package = "mFD") 
 
# Compute functional distance 
sp_dist_fruits <- mFD::funct.dist(sp_tr         = fruits_traits,
                                  tr_cat        = fruits_traits_cat,
                                  metric        = "gower",
                                  scale_euclid  = "scale_center",
                                  ordinal_var   = "classic",
                                  weight_type   = "equal",
                                  stop_if_NA    = TRUE)
  
# Compute functional spaces quality to retrieve species coordinates matrix:
fspaces_quality_fruits <- mFD::quality.fspaces(sp_dist = sp_dist_fruits, 
 maxdim_pcoa         = 10,
 deviation_weighting = "absolute",
 fdist_scaling       = FALSE,
 fdendro             = "average")
 
# Retrieve species coordinates matrix:
sp_faxes_coord_fruits <- fspaces_quality_fruits$details_fspaces$sp_pc_coord

# Set faxes limits:
# set range of axes if c(NA, NA):
 range_sp_coord_fruits  <- range(sp_faxes_coord_fruits)
 range_faxes_lim <- range_sp_coord_fruits + 
 c(-1, 1)*(range_sp_coord_fruits[2] - 
 range_sp_coord_fruits[1]) * 0.05
 
 # Retrieve the background plot:
 ggplot_bg_fruits <- mFD::background.plot(
                               range_faxes = range_faxes_lim, 
                               faxes_nm    = c("PC 1", "PC 2"), 
                               color_bg    = "grey90") 
                               
 # Retrieve the matrix of species coordinates for "basket_1" and PC1 and PC2
 sp_filter <- mFD::sp.filter(asb_nm          = "basket_1", 
                             sp_faxes_coord = sp_faxes_coord_fruits, 
                             asb_sp_w       = baskets_fruits_weights)
 fruits_asb_sp_coord_b1 <- sp_filter$`species coordinates`
 fruits_asb_sp_coord2D_b1 <- fruits_asb_sp_coord_b1[, c("PC1", "PC2")]
                               
 # Use alpha.fd.multidim() function to get inputs to plot FIde:
 alpha_fd_indices_fruits <- mFD::alpha.fd.multidim(
  sp_faxes_coord   = sp_faxes_coord_fruits[, c("PC1", "PC2", "PC3", "PC4")],
  asb_sp_w         = baskets_fruits_weights,
  ind_vect         = c("feve"),
  scaling          = TRUE,
  check_input      = TRUE,
  details_returned = TRUE)
  
 # Retrieve fide values through alpha.fd.multidim outputs:
 fruits_asb_mst_b1 <- 
         alpha_fd_indices_fruits$details$asb_mst["basket_1"]
 fruits_asb_sp_coord_b1 <- sp_filter$`species coordinates`
 fruits_asb_sp_coord2D_b1 <- fruits_asb_sp_coord_b1[, c("PC1", "PC2")]
 fruits_asb_sp_relatw_b1 <- 
         alpha_fd_indices_fruits$details$asb_sp_relatw["basket_1", ]
         
 # Retrieve FEve plot:
 feve_plot <- feve.plot(ggplot_bg = ggplot_bg_fruits,
           asb_sp_coord2D = list(basket_1 = fruits_asb_sp_coord2D_b1),
           asb_sp_relatw = list(basket_1 = fruits_asb_sp_relatw_b1),
           asb_mst = fruits_asb_mst_b1,
           plot_sp = TRUE,
           shape_sp = 16,
           color_sp = "red",
           fill_sp = "red",
           color_mst = list(basket_1 = "blue"),
           width_mst = list(basket_1 = 1),
           linetype_mst = list(basket_1 = "solid"))
           
 feve_plot