SAVE_FATE.step1_PFG: Save data to reproduce building of Plant Functional Groups
In MayaGueguen/RFate: Vegetation modelling with the FATE model

Description Usage Arguments Value Author(s) See Also Examples

This script is designed to gather all data and parameters used to build a set of Plant Functional Groups.

SAVE_FATE.step1_PFG(
  name.dataset,
  mat.observations,
  rules.selectDominant = c(doRuleA = NA, rule.A1 = NA, rule.A2_quantile = NA, doRuleB =
    NA, rule.B1_percentage = NA, rule.B1_number = NA, rule.B2 = NA, doRuleC = NA),
  mat.traits,
  mat.overlap = NA,
  rules.speciesDistance = c(opt.maxPercent.NA = NA, opt.maxPercent.similarSpecies = NA,
    opt.min.sd = NA),
  mat.species.DIST,
  clust.evaluation = NA,
  no.clusters,
  determ.all,
  mat.traits.PFG
)

`name.dataset`	a `string` corresponding to the name to give to archive folder
`mat.observations`	a `data.frame` with at least 3 columns : `sites`, `species`, `abund` (and optionally, `habitat`) (see `PRE_FATE.selectDominant`)
`rules.selectDominant`	(optional) default `NA`. A `vector` containing all the parameter values given to the `PRE_FATE.selectDominant` function, if used (`doRuleA`, `rule.A1`, `rule.A2_quantile`, `doRuleB`, `rule.B1_percentage`, `rule.B1_number`, `rule.B2`, `doRuleC`).
`mat.traits`	a `data.frame` with at least 3 columns : `species`, `GROUP`, `...` (one column for each functional trait) (see `PRE_FATE.speciesDistance`)
`mat.overlap`	(optional) default `NA`. Otherwise, two options : a `data.frame` with 2 columns : `species`, `raster` a dissimilarity structure representing the niche overlap between each pair of species. It can be a `dist` object, a `niolap` object, or simply a `matrix`. (see `PRE_FATE.speciesDistance`)
`rules.speciesDistance`	(optional) default `NA`. A `vector` containing all the parameter values given to the `PRE_FATE.speciesDistance` function, if used ( `opt.maxPercent.NA`, `opt.maxPercent.similarSpecies`, `opt.min.sd`).
`mat.species.DIST`	a `dist` object, or a `list` of `dist` objects (one for each `GROUP` value), corresponding to the distance between each pair of species. Such an object can be obtained with the `PRE_FATE.speciesDistance` function.
`clust.evaluation`	(optional) default `NA`. A `data.frame` with 4 columns : `GROUP`, `no.clusters`, `variable`, `value`. Such an object can be obtained with the `PRE_FATE.speciesClustering_step1` function.
`no.clusters`	an `integer`, or a `vector` of `integer` (one for each `GROUP` value), with the number of clusters to be kept (see `PRE_FATE.speciesClustering_step2`)
`determ.all`	a `data.frame` with 6 or 10 columns : `PFG`, `GROUP`, `ID.cluster`, `species`, `ID.species`, `DETERMINANT` (and optionally, `sp.mean.dist`, `allSp.mean`, `allSp.min`, `allSp.max`). Such an object can be obtained with the `PRE_FATE.speciesClustering_step2` function.
`mat.traits.PFG`	a `data.frame` with at least 3 columns : `PFG`, `no.species`, `...` (one column for each functional trait, computed as the `mean` (for numeric traits) or the `median` (for categorical traits) of the values of the determinant species of this PFG). Such an object can be obtained with the `PRE_FATE.speciesClustering_step3` function.

A list containing all the elements given to the function and checked :

name.dataset

name of the dataset

mat.observations

(see PRE_FATE.selectDominant)

sites: name of sampling site
(x, y): coordinates of sampling site
species: name of the concerned species
abund: abundance of the concerned species
(habitat): habitat of sampling site

rules.selectDominant

a vector containing values for the parameters doRuleA, rule.A1, rule.A2_quantile, doRuleB, rule.B1_percentage, rule.B1_number, rule.B2, doRuleC (see PRE_FATE.selectDominant)

mat.traits

(see PRE_FATE.speciesDistance)

species: name of the concerned species
GROUP: name of the concerned data subset
...: one column for each functional trait

mat.overlap

a dist object corresponding to the distance between each pair of species in terms of niche overlap (see PRE_FATE.speciesDistance)

rules.speciesDistance

a vector containing values for the parameters opt.maxPercent.NA, opt.maxPercent.similarSpecies, opt.min.sd (see PRE_FATE.speciesDistance)

mat.species.DIST

a dist object corresponding to the distance between each pair of species, or a list of dist objects, one for each GROUP value (see PRE_FATE.speciesDistance)

clust.evaluation

(see PRE_FATE.speciesClustering_step1)

GROUP: name of data subset
no.clusters: number of clusters used for the clustering
variable: evaluation metrics' name
value: value of evaluation metric

no.clusters

number of clusters to be kept for each data subset

determ.all

(see PRE_FATE.speciesClustering_step2)

PFG: ID of the plant functional group (GROUP + ID.cluster)
GROUP: name of data subset
ID.cluster: cluster number
species: name of species
ID.species: species number in each PFG
DETERMINANT: TRUE if determinant species, FALSE otherwise
(sp.mean.dist): species mean distance to other species of the same PFG
(allSp.mean): mean(\text{sp.mean.dist}) within the PFG
(allSp.min): mean(\text{sp.mean.dist}) - 1.64 * sd(\text{sp.mean.dist}) within the PFG
(allSp.max): mean(\text{sp.mean.dist}) + 1.64 * sd(\text{sp.mean.dist}) within the PFG

mat.traits.PFG