phyloregion (version 1.0.8)

rast2comm: Convert raw input distribution data to community

Description

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.

Usage

rast2comm(files)
polys2comm(dat, res = 0.25, pol.grids = NULL, ...)
points2comm(dat, res = 0.25, pol.grids = NULL, ...)

Value

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.

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.

See Also

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

Examples

# \donttest{
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]])
# }

# \donttest{
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]])