lets.presab: Create a presence-absence matrix of species' geographic...

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

View source: R/lets_presab.R

Description

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

Usage

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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)

Arguments

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). This option is only available when the coordinates are in degrees (longitude/latitude).

presence

A vector with the code numbers for the presence type to be considered in the process (for IUCN spatial data http://www.iucnredlist.org/technical-documents/spatial-data, 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.

Details

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).

Value

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.

Author(s)

Bruno Vilela & Fabricio Villalobos

See Also

plot.PresenceAbsence

lets.presab.birds

lets.shFilter

Examples

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## 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)

letsR documentation built on June 20, 2017, 9:08 a.m.