BIOMOD.formated.data.PA: 'BIOMOD_FormatingData()' output object class (with...
In biomod2: Ensemble Platform for Species Distribution Modeling

BIOMOD.formated.data.PA

R Documentation

`BIOMOD_FormatingData()` output object class (with pseudo-absences)

Description

Class returned by BIOMOD_FormatingData, and used by BIOMOD_Tuning, bm_CrossValidation and BIOMOD_Modeling

Usage

## S4 method for signature 'numeric,data.frame'
BIOMOD.formated.data.PA(
  sp,
  env,
  xy = NULL,
  dir.name = ".",
  sp.name = NULL,
  eval.sp = NULL,
  eval.env = NULL,
  eval.xy = NULL,
  PA.nb.rep = 1,
  PA.strategy = "random",
  PA.nb.absences = NULL,
  PA.dist.min = 0,
  PA.dist.max = NULL,
  PA.sre.quant = 0.025,
  PA.user.table = NULL,
  na.rm = TRUE,
  filter.raster = FALSE
)

## S4 method for signature 'numeric,SpatRaster'
BIOMOD.formated.data.PA(
  sp,
  env,
  xy = NULL,
  dir.name = ".",
  sp.name = NULL,
  eval.sp = NULL,
  eval.env = NULL,
  eval.xy = NULL,
  PA.nb.rep = 1,
  PA.strategy = "random",
  PA.nb.absences = NULL,
  PA.dist.min = 0,
  PA.dist.max = NULL,
  PA.sre.quant = 0.025,
  PA.user.table = NULL,
  na.rm = TRUE,
  filter.raster = FALSE
)

Arguments

`sp`	A `vector`, a `SpatVector` without associated data (if presence-only), or a `SpatVector` object containing binary data (`0` : absence, `1` : presence, `NA` : indeterminate) for a single species that will be used to build the species distribution model(s) Note that old format from sp are still supported such as `SpatialPoints` (if presence-only) or `SpatialPointsDataFrame` object containing binary data.
`env`	a `matrix`, `data.frame`, `SpatVector` or `SpatRaster` object containing the explanatory variables (in columns or layers) that will be used to build the species distribution model(s). Note that old format from raster and sp are still supported such as `RasterStack` and `SpatialPointsDataFrame` objects.
`xy`	(optional, default `NULL`) If `resp.var` is a `vector`, a 2-columns `matrix` or `data.frame` containing the corresponding `X` and `Y` coordinates that will be used to build the species distribution model(s)
`dir.name`	a `character` corresponding to the modeling folder
`sp.name`	a `character` corresponding to the species name
`eval.sp`	(optional, default `NULL`) A `vector`, a `SpatVector` without associated data (if presence-only), or a `SpatVector` object containing binary data (`0` : absence, `1` : presence, `NA` : indeterminate) for a single species that will be used to evaluate the species distribution model(s) with independent data Note that old format from sp are still supported such as `SpatialPoints` (if presence-only) or `SpatialPointsDataFrame` object containing binary data.
`eval.env`	(optional, default `NULL`) A `matrix`, `data.frame`, `SpatVector` or `SpatRaster` object containing the explanatory variables (in columns or layers) that will be used to evaluate the species distribution model(s) with independent data Note that old format from raster and sp are still supported such as `RasterStack` and `SpatialPointsDataFrame` objects.
`eval.xy`	(optional, default `NULL`) If `resp.var` is a `vector`, a 2-columns `matrix` or `data.frame` containing the corresponding `X` and `Y` coordinates that will be used to evaluate the species distribution model(s) with independent data
`PA.nb.rep`	(optional, default `0`) If pseudo-absence selection, an `integer` corresponding to the number of sets (repetitions) of pseudo-absence points that will be drawn
`PA.strategy`	(optional, default `NULL`) If pseudo-absence selection, a `character` defining the strategy that will be used to select the pseudo-absence points. Must be `random`, `sre`, `disk` or `user.defined` (see Details)
`PA.nb.absences`	(optional, default `0`) If pseudo-absence selection, and `PA.strategy = 'random'` or `PA.strategy = 'sre'` or `PA.strategy = 'disk'`, an `integer` (or a `vector` of `integer` the same size as `PA.nb.rep`) corresponding to the number of pseudo-absence points that will be selected for each pseudo-absence repetition (true absences included)
`PA.dist.min`	(optional, default `0`) If pseudo-absence selection and `PA.strategy = 'disk'`, a `numeric` defining the minimal distance to presence points used to make the `disk` pseudo-absence selection (in meters, see Details)
`PA.dist.max`	(optional, default `0`) If pseudo-absence selection and `PA.strategy = 'disk'`, a `numeric` defining the maximal distance to presence points used to make the `disk` pseudo-absence selection (in meters, see Details)
`PA.sre.quant`	(optional, default `0`) If pseudo-absence selection and `PA.strategy = 'sre'`, a `numeric` between `0` and `0.5` defining the half-quantile used to make the `sre` pseudo-absence selection (see Details)
`PA.user.table`	(optional, default `NULL`) If pseudo-absence selection and `PA.strategy = 'user.defined'`, a `matrix` or `data.frame` with as many rows as `resp.var` values, as many columns as `PA.nb.rep`, and containing `TRUE` or `FALSE` values defining which points will be used to build the species distribution model(s) for each repetition (see Details)
`na.rm`	(optional, default `TRUE`) A `logical` value defining whether points having one or several missing values for explanatory variables should be removed from the analysis or not
`filter.raster`	(optional, default `FALSE`) If `env` is of raster type, a `logical` value defining whether `sp` is to be filtered when several points occur in the same raster cell

Slots

dir.name: a character corresponding to the modeling folder
sp.name: a character corresponding to the species name
coord: a 2-columns data.frame containing the corresponding X and Y coordinates
data.species: a vector containing the species observations (0, 1 or NA)
data.env.var: a data.frame containing explanatory variables
data.mask: a SpatRaster object containing the mask of the studied area
has.data.eval: a logical value defining whether evaluation data is given
eval.coord: (optional, default NULL)
A 2-columns data.frame containing the corresponding X and Y coordinates for evaluation data
eval.data.species: (optional, default NULL)
A vector containing the species observations (0, 1 or NA) for evaluation data
eval.data.env.var: (optional, default NULL)
A data.frame containing explanatory variables for evaluation data
PA.strategy: a character corresponding to the pseudo-absence selection strategy
PA.table: a data.frame containing the corresponding table of selected pseudo-absences (indicated by TRUE or FALSE) from the pa.tab list element returned by the bm_PseudoAbsences function

Author(s)

Damien Georges

Examples


showClass("BIOMOD.formated.data.PA")

## ----------------------------------------------------------------------- #
library(terra)

# Load species occurrences (6 species available)
data(DataSpecies)
head(DataSpecies)

# Select the name of the studied species
myRespName <- 'GuloGulo'

# Keep only presence informations
DataSpecies <- DataSpecies[which(DataSpecies[, myRespName] == 1), ]

# Get corresponding presence/absence data
myResp <- as.numeric(DataSpecies[, myRespName])

# Get corresponding XY coordinates
myRespXY <- DataSpecies[, c('X_WGS84', 'Y_WGS84')]

# Load environmental variables extracted from BIOCLIM (bio_3, bio_4, bio_7, bio_11 & bio_12)
data(bioclim_current)
myExpl <- terra::rast(bioclim_current)



## ----------------------------------------------------------------------- #
# Format Data with pseudo-absences : random method
myBiomodData <- BIOMOD_FormatingData(resp.var = myResp,
                                     expl.var = myExpl,
                                     resp.xy = myRespXY,
                                     resp.name = myRespName,
                                     PA.nb.rep = 4,
                                     PA.strategy = 'random',
                                     PA.nb.absences = 1000)
myBiomodData
plot(myBiomodData)

biomod2 documentation built on July 9, 2023, 6:05 p.m.