Wrapper for `cluster::daisy()`

function in `cluster`

package,
to compute distance matrix of trait between each pair of species present in
given `traits_table`

, each row represents a species and each column
a trait. To be able to compute other metrics `traits_table`

must have
species name as row names.

```
compute_dist_matrix(
traits_table,
metric = "gower",
center = FALSE,
scale = FALSE
)
```

- traits_table
a data.frame of traits with species in row and traits in columns,

**row names**should be**species names**,- metric
character vector in list

`'gower'`

,`'manhattan'`

,`'euclidean'`

defining the type of distance to use (see`cluster::daisy()`

), see Details section,- center
logical that defines if traits should be centered (only in the case of

`'euclidean'`

distance)- scale
logical that defines if traits should be scaled (only in the case of

`'euclidean'`

distance)

A functional distance matrix, **column** and **row** names follow
**species name** from `traits_table`

row names.

The functional distance matrix can be computed using any type of
distance metric. When traits are both quantitative and qualitative Gower's
(Gower, 1971; Podani, 1999) distance can be used. Otherwise, any other
distance metric (Euclidean, Manhattan, Minkowski) can be used - as long
as the rows and the columns are named following the species. When using
mixed data consider also Gower's distance extension by Pavoine et al.
(2009). **IMPORTANT NOTE**: in order to get functional rarity indices
between 0 and 1, the distance metric has to be scaled between 0 and 1.

```
Gower, J.C. (1971) A general coefficient of similarity and some of its
properties. Biometrics, 857–871.
Podani, J. (1999) Extending Gower’s general coefficient of similarity
to ordinal characters. Taxon, 331–340.
Pavoine, S., Vallet, J., Dufour, A.-B., Gachet, S., & Daniel, H. (2009)
On the challenge of treating various types of variables: application for
improving the measurement of functional diversity. Oikos, 118, 391–402.
```

`cluster::daisy()`

which this function wraps, base `stats::dist()`

or `ade4::dist.ktab()`

for Pavoine et al. (2009) extension of Gower's
distance.