Convert species' ranges (in shapefile format) into a presence-absence matrix based on a user-defined grid system
lets.presab(
shapes,
xmn = NULL,
xmx = NULL,
ymn = NULL,
ymx = NULL,
resol = NULL,
remove.cells = TRUE,
remove.sp = TRUE,
show.matrix = FALSE,
crs = "+proj=longlat +datum=WGS84",
crs.grid = crs,
cover = 0,
presence = NULL,
origin = NULL,
seasonal = NULL,
count = FALSE
)
The result is a list object of class PresenceAbsence
with the following objects: Presence-Absence Matrix: A matrix of
species' presence(1) and absence(0) information. The first two columns
contain the longitude (x) and latitude (y) of the cells' centroid (from the
gridded domain used); Richness Raster: A raster containing species
richness data; Species name: A character vector with species' names
contained in the matrix.
*But see the optional argument show.matrix
.
Object of class SpatVect
or Spatial
(see packages
terra
and sf
to read these files) containing
the distribution of one or more species. Species names should be stored in
the object as BINOMIAL/binomial or SCINAME/sciname.
Minimun longitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest). If NULL, limits will be calculated based on the limits of the shapes object.
Maximun longitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest). If NULL, limits will be calculated based on the limits of the shapes object.
Minimun latitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest). If NULL, limits will be calculated based on the limits of the shapes object.
Maximun latitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest). If NULL, limits will be calculated based on the limits of the shapes object.
Numeric vector of length 1 or 2 to set the grid resolution. If NULL, resolution will be equivalent to 1 degree of latitude and longitude.
Logical, if TRUE
the final matrix will not contain
cells in the grid with a value of zero (i.e. sites with no species present).
Logical, if TRUE
the final matrix will not contain
species that do not match any cell in the grid.
Logical, if TRUE
only the presence-absence matrix
will be returned.
Character representing the PROJ.4 type description of a Coordinate Reference System (map projection) of the polygons.
Character representing the PROJ.4 type description of a Coordinate Reference System (map projection) for the grid. Note that when you change this options you may probably change the extent coordinates and the resolution.
Percentage of the cell covered by the shapefile that will be considered for presence (values between 0 and 1).
A vector with the code numbers for the presence type to be considered in the process (for IUCN spatial data https://www.iucnredlist.org/resources/spatial-data-download, see metadata).
A vector with the code numbers for the origin type to be considered in the process (for IUCN spatial data).
A vector with the code numbers for the seasonal type to be considered in the process (for IUCN spatial data).
Logical, if TRUE
a progress bar indicating the processing
progress will be shown.
Bruno Vilela & Fabricio Villalobos
The function creates the presence-absence matrix based on a raster
object. Depending on the cell size, extension used and number of species it
may require a lot of memory, and may take some time to process it. Thus,
during the process, if count
argument is set TRUE
, a counting
window will open so you can see the progress (i.e. in what polygon/shapefile
the function is working). Note that the number of polygons is not the same
as the number of species that you have (i.e. a species may have more than
one polygon/shapefiles).
plot.PresenceAbsence
lets.presab.birds
lets.shFilter
if (FALSE) {
# Spatial distribution polygons of south american frogs
# of genus Phyllomedusa.
data(Phyllomedusa)
PAM <- lets.presab(Phyllomedusa)
summary(PAM)
# Species richness map
plot(PAM, xlab = "Longitude", ylab = "Latitude",
main = "Phyllomedusa species richness")
# Map of the specific species
plot(PAM, name = "Phyllomedusa nordestina")
}
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