lets.presab: Create a presence-absence matrix of species' geographic...
In letsR: Data Handling and Analysis in Macroecology

Description Usage Arguments Details Value Author(s) See Also Examples

Convert species' ranges (in shapefile format) into a presence-absence matrix based on a user-defined grid system

lets.presab(
  shapes,
  xmn = -180,
  xmx = 180,
  ymn = -90,
  ymx = 90,
  resol = 1,
  remove.cells = TRUE,
  remove.sp = TRUE,
  show.matrix = FALSE,
  crs = CRS("+proj=longlat +datum=WGS84"),
  crs.grid = crs,
  cover = 0,
  presence = NULL,
  origin = NULL,
  seasonal = NULL,
  count = FALSE
)

`shapes`	Object of class `SpatialPolygonsDataFrame` (see function `readShapePoly` to open these files) containing the distribution of one or more species. Species names should be in a column (within the .DBF table of the shapefile) called BINOMIAL/binomial or SCINAME/sciname.
`xmn`	Minimun longitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest)
`xmx`	Maximun longitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest)
`ymn`	Minimun latitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest)
`ymx`	Maximun latitude used to construct the grid in which the matrix will be based (i.e. the [gridded] geographic domain of interest)
`resol`	Numeric vector of length 1 or 2 to set the grid resolution.
`remove.cells`	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).
`remove.sp`	Logical, if `TRUE` the final matrix will not contain species that do not match any cell in the grid.
`show.matrix`	Logical, if `TRUE` only the presence-absence matrix will be returned.
`crs`	Character representign the PROJ.4 type description of a Coordinate Reference System (map projection) of the polygons.
`crs.grid`	Character representign 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.
`cover`	Porcentage of the cell covered by the shapefile that will be considered for presence (values between 0 and 1).
`presence`	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).
`origin`	A vector with the code numbers for the origin type to be considered in the process (for IUCN spatial data).
`seasonal`	A vector with the code numbers for the seasonal type to be considered in the process (for IUCN spatial data).
`count`	Logical, if `TRUE` a counting window will open.

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).

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.

Bruno Vilela & Fabricio Villalobos

plot.PresenceAbsence

lets.presab.birds

lets.shFilter

## Not run: 
# Spatial distribution polygons of south american frogs 
# of genus Phyllomedusa. 
data(Phyllomedusa)
PAM <- lets.presab(Phyllomedusa, xmn = -93, xmx = -29,
                   ymn = -57, ymx = 15)
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")

## End(Not run)