mFD (version 1.0.7)

sp.tr.summary: Summarize Species x Traits data frame

Description

This function computes a summary data helping to choose the type of analysis you can do with your data. For this function to work, there must be no NA in your sp_tr data frame.

Usage

sp.tr.summary(tr_cat, sp_tr, stop_if_NA = TRUE)

Value

If there is no fuzzy-coded trait, a three-elements list with:

tr_summary_list

a table summarizing for each trait the number of species per modality for non-continuous trait and min, max, mean, median, and quartiles for continuous traits.

tr_types

a list containing traits type.

mod_list

a list containing modalities for all traits.

If there is fuzzy-coded trait, a four-elements list with:

tr_summary_non_fuzzy_list

a table summarizing for each trait the number of species per modality for non-continuous trait and min, max, mean, median, and quartiles for continuous traits.

tr_summary_fuzzy_list

a table summarizing for each subtrait min, max, mean, median and quartiles

tr_types

a list containing traits type.

mod_list

a list containing modalities for non-continuous trait.

Arguments

tr_cat

a data frame containing three columns for each trait (rows):

• trait_name: the name of all traits as in sp_tr data frame;

• trait_type: the category code for each trait as followed: N for Nominal traits (factor variable), O for Ordinal traits (ordered variable), C for Circular traits (integer values)(circular traits can not be used in mFD function used to compute functional distance but ok for summary function and function to group species into Functional Entities), Q for quantitative traits (numeric values), and F for fuzzy traits (i.e. described with several values defined with several column);

• fuzzy_name: name of fuzzy-coded trait to which 'sub-trait' belongs (if trait is not fuzzy, ignored so could be trait name or NA).

• trait_weight: weights of each traits if the user wants to specify a weight for each trait.

sp_tr

a data frame of traits values (columns) for each species (rows). Note that species names must be specified in the row names.

stop_if_NA

a logical value indicating whether the process should stop if there is some NA in the sp_tr dataframe. If you continue with functional analysis, we remind you that functional measures, are sensitive to missing traits

Author

Camille Magneville and Sebastien Villeger

Examples

# Load Species x Traits data
data('fruits_traits', package = 'mFD')

# Load Traits x Categories data
data('fruits_traits_cat', package = 'mFD')

# Summarize Species x Traits data
mFD::sp.tr.summary(tr_cat = fruits_traits_cat, sp_tr = fruits_traits)