Function for nonparametric bootstrap resampling to calculate community weighted trait mean and higher moments.
trait_np_bootstrap(filled_traits, nrep = 100, sample_size = 200, raw = FALSE)output from the trait_fill function.
number of bootstrap replicates
bootstrap size
logical; argument to extract the raw data of the trait
distributions.
The default is raw = FALSE. If raw = TRUE, nrep is restricted to 1 to
avoid memory issues.
a tibble with columns for each grouping variable of filled_traits
(usually the elements of scale_hierarchy and the traits column), and the moments mean, variance, skewness, and kurtosis.
The observed traits are re-sampled in proportion to their weights,
e.g. the abundance of a species or the biomass.
Values across all individuals
in a community are resampled sample_size times to incorporate the full
spectrum of trait variation, generating nrep trait distributions.
From these distributions the function estimates the mean and the higher
moments including variance, skewness and kurtosis.
#' The output of trait_np_bootstrap() can be summarized using
trait_summarize_boot_moments().
library(dplyr)
data(community)
data(trait)
# Filter community data to make example faster
community <- community |>
filter(
PlotID %in% c("A", "B"),
Site == 1
)
filled_traits <- trait_fill(
comm = community,
traits = trait,
scale_hierarchy = c("Site", "PlotID"),
taxon_col = "Taxon", value_col = "Value",
trait_col = "Trait", abundance_col = "Cover"
)
boot_traits <- trait_np_bootstrap(filled_traits,
nrep = 20,
sample_size = 200
)