rast2comm function

Convert raw input distribution data to community

The functions points2comm, polys2comm, rast2comm

provide convenient interfaces to convert raw distribution data often available as point records, polygons and raster layers, respectively, to a community composition data frame at varying spatial grains and extents for downstream analyses.

rast2comm(files)

polys2comm(dat, res = 0.25, pol.grids = NULL, ...)

points2comm(dat, res = 0.25, pol.grids = NULL, ...)

Arguments

• files: list of SpatRaster layer objects with the same spatial extent and resolution.

• dat: layers of merged maps corresponding to species polygons for polys2comm; or point occurrence data frame for points2comm, with at least three columns:

  • Column 1: species (listing the taxon names)
  • Column 2: decimallongitude (corresponding to decimal longitude)
  • Column 3: decimallatitude (corresponding to decimal latitude)

• res: the grain size of the grid cells in decimal degrees (default).

• pol.grids: if specified, the vector polygon of grid cells with a column labeled grids .

• ...: Further arguments passed to or from other methods.

Returns

Each of these functions generate a list of two objects as follows:

• comm_dat: (sparse) community matrix
• map: vector or raster of grid cells with the values per cell for mapping.

Examples

fdir <- system.file("NGAplants", package="phyloregion")
files <- file.path(fdir, dir(fdir))
ras <- rast2comm(files) # Note, this function generates
     # a list of two objects
head(ras[[1]])


require(terra)
s <- vect(system.file("ex/nigeria.json", package="phyloregion"))
sp <- random_species(100, species=5, pol=s)
pol <- polys2comm(dat = sp)
head(pol[[1]])

library(terra)
s <- vect(system.file("ex/nigeria.json", package="phyloregion"))
set.seed(1)
m <- as.data.frame(spatSample(s, 1000, method = "random"),
                   geom = "XY")[-1]
names(m) <- c("lon", "lat")
species <- paste0("sp", sample(1:100))
m$taxon <- sample(species, size = nrow(m), replace = TRUE)

pt <- points2comm(dat = m, res = 0.5) # This generates a list of two objects
head(pt[[1]])

See Also

mapproject for conversion of latitude and longitude into projected coordinates system. long2sparse for conversion of community data.