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, ...)list of SpatRaster layer objects with the same spatial extent and resolution.
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)
the grain size of the grid cells in decimal degrees (default).
if specified, the vector polygon of grid cells with a column labeled “grids”.
Further arguments passed to or from other methods.
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.
mapproject for conversion of
latitude and longitude into projected coordinates system.
long2sparse for conversion of community data.
# \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]])
#> 6 x 8 sparse Matrix of class "dgCMatrix"
#> Chytranthus_gilletii Commelina_ramulosa Cymbopogon_caesius
#> v100 . . .
#> v101 . . .
#> v102 . . .
#> v103 . . .
#> v104 . . .
#> v105 . . .
#> Dalechampia_ipomoeifolia Grewia_barombiensis Indigofera_berhautiana
#> v100 1 . .
#> v101 1 . .
#> v102 1 . .
#> v103 1 . .
#> v104 1 . .
#> v105 1 . .
#> Indigofera_erecta Indigofera_oubanguiensis
#> v100 . .
#> v101 . .
#> v102 . .
#> v103 . .
#> v104 . .
#> v105 . .
# }
# \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]])
#> 6 x 5 sparse Matrix of class "dgCMatrix"
#> species1 species2 species3 species4 species5
#> v10 . 1 . 1 .
#> v100 1 1 . 1 .
#> v1000 1 . 1 1 .
#> v1001 1 . . 1 .
#> v1002 1 . . 1 .
#> v1003 1 . . 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]])
#> 6 x 100 sparse Matrix of class "dgCMatrix"
#> [[ suppressing 100 column names ‘sp1’, ‘sp10’, ‘sp100’ ... ]]
#>
#> v100 . . . . . . . 1 . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . .
#> v101 . 1 . . . . . . . . . . . . . . . 1 . . . . . . . . . . . 1 . . . . . . .
#> v102 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v103 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v105 . . . . . . . . 1 . 1 . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v106 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#>
#> v100 . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v101 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . .
#> v102 . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v103 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v105 1 . . . . . . . 1 . 1 . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v106 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#>
#> v100 . 1 . . . . . . . . . . . . . . . . . . . . . . . .
#> v101 . . 1 . . . . . . . . . . . . . . . . . . . . . . .
#> v102 . . . . . . . . . . . . . . . . . . . . . . . . . .
#> v103 . . . . . . . . 1 . . 1 . . . . . . . . . . . . . 1
#> v105 . . . . . 1 . . . . . . . . . 1 . . . . . . . . . .
#> v106 . . . . . . . . . . . . . . . . . . . 1 . . . . . .