Calculate Relative Functional Distinctiveness (FD) from Trait Data

Computes relative functional distinctiveness for species based on multiple traits. Traits are median-centered before computing pairwise Euclidean distances, and FD is calculated as the mean distance of each species to all others.

Usage

fun_dist(data_frame, trait_columns, species_col = "species")

Arguments

data_frame: A data frame containing species data with a column of species names.
trait_columns: Character vector specifying the names of numeric trait columns to use for FD calculation. Must contain at least two traits.
species_col: Character string specifying the column in data_frame that contains species names. Default is "species".

Value

A data.frame with one row per species containing:

species_col — species name.
fun_dist — functional distinctiveness value.

Details

Functional distinctiveness (FD) for each species is calculated as the mean of its distances to all other species in the dataset. This is a relative measure — a species can be functionally distinct within a subset of species but not necessarily across all species globally.

Examples


# Create a dataframe of maple species with trait data (SLA, height, seed mass)
maple_data <- data.frame(species_name = c("Acer campestre", "Acer monspessulanum", "Acer negundo", "Acer opalus", "Acer platanoides", "Acer pseudoplatanus", "Acer saccharinum"), SLA = c(5, 15, 6, 11, 23.5, 52, 4), height = c(50, 65, 28, 70, 68, 43, 55), seed_mass = c(1.2, 0.57, 2, 8.5, 0.54, 2.3, 1.9))

FD_results <- fun_dist(data_frame = maple_data, trait_columns = c("SLA", "height", "seed_mass"))
#> Error in dplyr::rename(., species_name = !!species_sym): Can't rename columns that don't exist.
#> ✖ Column `species` doesn't exist.

print(FD_results)
#> Error: object 'FD_results' not found