# NOT RUN {
# 1. Compute the TPDs of three different species:
traits_iris <- iris[, c("Sepal.Length", "Sepal.Width")]
sp_iris <- iris$Species
TPDs_iris <- TPDs(species = sp_iris, traits_iris)
#2. Compute the TPDc of three different communities:
abundances_comm_iris <- matrix(c(c(0.9, 0.1, 0), #I. setosa dominates
c(0.0, 0.9, 0.1 ), #I. Versic. dominates; setosa absent
c(0.0, 0.1, 0.9 )), #I. virg. dominates; setosa absent
ncol = 3, byrow = TRUE, dimnames = list(paste0("Comm.",1:3),
unique(iris$Species)))
TPDc_iris <- TPDc(TPDs = TPDs_iris, sampUnit = abundances_comm_iris)
#3. Estimate functional dissimilarity
example_dissimilarity_comm <- dissim (TPDc_iris)
example_dissimilarity_sps <- dissim (TPDs_iris)
# }
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