Compute the functional diversity indices and community weighted means.

Usage

fw_fdcompute(
  fwdata,
  sitesdata,
  species,
  sites = NULL,
  dist = 1000,
  abund = NULL,
  FD = TRUE,
  dummy = TRUE
)

Arguments

fwdata: list A list from the fw_fetchdata function is the only data type accepted.
sitesdata: dataframe Dataframe with sites for which functional diversity and community weighted means indices will be computed for.
species: string The species column in the sitesdata.
sites: string The sites column in the sitesdata. If the sites are not provided by the geometry column, then sites can be auto generated by clustering closely separated records into sites.
dist: integer The distance used to cluster points as sites. The default is 1000.
abund: string Column with abundance data. If not provided, then only functional richness can be computed.
FD: logical To indicate whether to compute functional richness or community weighted means. The default is TRUE.
dummy: logical To form fuzzy code for the categorical traits. Default is TRUE.

Value

dataframe

Examples


if (FALSE) { # \dontrun{

set.seed(1135)
data('speciesdata')
speciesdata$abundance <- rnorm(n = nrow(speciesdata), 4.3, 1.2)

spgeo1 <- speciesdata |>
 sf::st_as_sf(coords = c('decimalLongitude', 'decimalLatitude'), crs = sf::st_crs(4326))

sptraits <- fw_fetchdata(data = speciesdata,
                        ecoparams = c('rheophily habitat', 'spawning habitat',
                                      'feeding diet adult'),
                        taxonomic_column = 'scientificName',
                        organismgroup = 'fi')
#functional richness
testdata5 <- fw_fdcompute(fwdata = sptraits,
                         sitesdata = speciesdata,
                         sites = 'waterBody',
                         species = 'scientificName',
                         FD = TRUE)

} # }