Compute the set of indices based on number of species in Functional Entities
Source:R/FE_multidim_ind_computation.R
alpha.fd.fe.RdThis function computes the set of indices based on number of species in Functional Entities (FEs) following Mouillot et al. (2014).
Usage
alpha.fd.fe(
asb_sp_occ,
sp_to_fe,
ind_nm = c("fred", "fored", "fvuln"),
check_input = TRUE,
details_returned = TRUE
)Arguments
- asb_sp_occ
a matrix linking occurrences (coded as 0/1) of species (columns) in a set of assemblages (rows). Warning: An assemblage must contain at least one species.
- sp_to_fe
a list with details of species clustering into FE from
sp.to.fe.- ind_nm
a vector of character strings with the names of functional diversity indices to compute among 'fred', 'fored' and 'fvuln'. Indices names must be written in lower case letters. Default: all the indices are computed.
- check_input
a logical value indicating whether key features the inputs are checked (e.g. class and/or mode of objects, names of rows and/or columns, missing values). If an error is detected, a detailed message is returned. Default:
check.input = TRUE.- details_returned
a logical value indicating whether details about indices computation should be returned. These details are required by
alpha.fd.fe.plotto plot FEs indices.
Value
A list with:
asb_fdfe a matrix containing for each assemblage (rows), values of functional diversity indices (same names than in 'ind_nm') as well as the number of species ('nb_sp') and the number of FE (nb_fe);
if details_returned is
TRUE,details_fdfe a list with asb_fe_nbsp a matrix with number of species per FE in each assemblage.
References
Mouillot et al. (2014) Functional over-redundancy and high functional vulnerability in global fish faunas on tropical reefs. PNAS, 38, 13757-13762.
Examples
# Load Species*Traits dataframe:
data('fruits_traits', package = 'mFD')
# Load Traits categories dataframe:
data('fruits_traits_cat', package = 'mFD')
# Load Assemblages*Species matrix:
data('baskets_fruits_weights', package = 'mFD')
# Remove continuous trait:
fruits_traits <- fruits_traits[, -5]
fruits_traits_cat <- fruits_traits_cat[-5, ]
# Compute gathering species into FEs:
sp_to_fe_fruits <- mFD::sp.to.fe(sp_tr = fruits_traits,
tr_cat = fruits_traits_cat,
fe_nm_type = 'fe_rank', check_input = TRUE)
#> Warning: All Functional Entities have a single species.
# Get the occurrence dataframe:
asb_sp_fruits_summ <- mFD::asb.sp.summary(asb_sp_w = baskets_fruits_weights)
asb_sp_fruits_occ <- asb_sp_fruits_summ$'asb_sp_occ'
# Compute alpha fd indices:
alpha.fd.fe(
asb_sp_occ = asb_sp_fruits_occ,
sp_to_fe = sp_to_fe_fruits,
ind_nm = c('fred', 'fored', 'fvuln'),
check_input = TRUE,
details_returned = TRUE)
#> $asb_fdfe
#> nb_sp nb_fe fred fored fvuln
#> basket_1 8 8 1 0 1
#> basket_2 8 8 1 0 1
#> basket_3 8 8 1 0 1
#> basket_4 8 8 1 0 1
#> basket_5 8 8 1 0 1
#> basket_6 8 8 1 0 1
#> basket_7 8 8 1 0 1
#> basket_8 8 8 1 0 1
#> basket_9 8 8 1 0 1
#> basket_10 8 8 1 0 1
#>
#> $details_fdfe
#> $details_fdfe$asb_fe_nbsp
#> fe_1 fe_2 fe_3 fe_4 fe_5 fe_6 fe_7 fe_8 fe_9 fe_10 fe_11 fe_12 fe_13
#> basket_1 1 0 1 0 0 0 1 0 0 0 1 0 0
#> basket_2 1 0 1 0 0 0 1 0 0 0 1 0 0
#> basket_3 1 0 1 0 0 0 1 0 0 0 1 0 0
#> basket_4 1 0 0 0 0 0 0 0 0 1 1 0 0
#> basket_5 1 0 0 0 0 0 0 0 0 1 1 0 0
#> basket_6 1 0 1 0 0 0 0 0 0 0 0 1 1
#> basket_7 1 0 1 0 0 0 0 0 0 0 0 1 1
#> basket_8 0 0 0 1 1 1 1 1 0 0 1 0 0
#> basket_9 0 0 0 1 1 1 1 1 0 0 1 0 0
#> basket_10 1 1 0 0 0 0 0 1 1 0 0 0 0
#> fe_14 fe_15 fe_16 fe_17 fe_18 fe_19 fe_20 fe_21 fe_22 fe_23 fe_24
#> basket_1 0 1 0 1 0 1 0 0 0 1 0
#> basket_2 0 1 0 1 0 1 0 0 0 1 0
#> basket_3 0 1 0 1 0 1 0 0 0 1 0
#> basket_4 0 0 1 0 1 1 0 1 0 0 1
#> basket_5 0 0 1 0 1 1 0 1 0 0 1
#> basket_6 1 0 1 0 0 0 1 0 0 0 0
#> basket_7 1 0 1 0 0 0 1 0 0 0 0
#> basket_8 0 0 0 0 0 0 0 0 1 1 0
#> basket_9 0 0 0 0 0 0 0 0 1 1 0
#> basket_10 0 1 0 0 0 1 0 1 0 1 0
#> fe_25
#> basket_1 0
#> basket_2 0
#> basket_3 0
#> basket_4 0
#> basket_5 0
#> basket_6 1
#> basket_7 1
#> basket_8 0
#> basket_9 0
#> basket_10 0
#>
#>