Calculate phylogenetic community metrics and their standardized effect sizes for raster data

Calculates the standardized effect size for phylogenetic community metrics. See Details for more information.

Usage

geo.phylo.ses(
  x,
  tree,
  inv.R,
  edge.path,
  branch.length,
  n.descen,
  spat_alg = "bootspat_str",
  spat_alg_args = list(rprob = NULL, rich = NULL, fr_prob = NULL),
  random = c("tip", "spat")[2],
  aleats = 10,
  cores = 1,
  filename = "",
  ...
)

Arguments

x: SpatRaster. A SpatRaster containing presence-absence data (0 or 1) for a set of species. The layers (species) will be sorted according to the tree order. See the phylo.pres function.
tree: phylo. A dated tree.
inv.R: SpatRaster. Inverse of range size. See inv.range
edge.path: matrix representing the paths through the tree from root to each tip. See phylo.pres
branch.length: numeric. A Named numeric vector of branch length for each species. See phylo.pres
n.descen: numeric. A Named numeric vector of number of descendants for each branch. See phylo.pres
spat_alg: A function with the algorithm implementing the desired randomization method. It must work with SpatRaster objects. See examples. Example of functions that work are: bootspat_naive, bootspat_str, bootspat_ff.
spat_alg_args: List of arguments passed to the randomization method chosen in 'spat_alg'. See bootspat_naive, bootspat_str, bootspat_ff
random: character. A character indicating the type of randomization. The currently available randomization methods are "tip", "site", "species" or "both" (site and species).
aleats: positive integer. A positive integer indicating how many times the calculation should be repeated.
cores: positive integer. If cores > 1, a 'parallel' package cluster with that many cores is created and used. You can also supply a cluster object. Ignored for functions that are implemented by terra in C++ (see under fun)
filename: character. Output filename
...: additional arguments passed for terra::app

Value

SpatRaster

Details

The spatial randomization (spat) keeps the richness exact and samples species presences proportionally to their observed frequency (i.e. number of occupied pixels). The randomization will not assign values to cells with nodata.

References

Williams, P.H., Humphries, C.J., Forey, P.L., Humphries, C.J., VaneWright, R.I. (1994). Biodiversity, taxonomic relatedness, and endemism in conservation. In: Systematics and Conservation Evaluation (eds Forey PL, Humphries C.J., Vane-Wright RI), p. 438. Oxford University Press, Oxford.

Crisp, M., Laffan, S., Linder, H., Monro, A. (2001). Endemism in the Australian flora. Journal of Biogeography, 28, 183–198.

Author

Neander Marcel Heming

Examples

# \donttest{
library(terra)
library(phyloraster)
require("SESraster")
#> Loading required package: SESraster
#> This is SESraster 0.7.0
#> If you use SESraster, please cite in your publications. See:
#>   citation("SESraster")
x <- terra::rast(system.file("extdata", "rast.presab.tif",
package="phyloraster"))
tree <- ape::read.tree(system.file("extdata", "tree.nex",
package="phyloraster"))
tses <- geo.phylo.ses(x = x,
                     tree = tree,
                      # FUN_args = list(range.BL=area.branch$range.BL,
                      # inv.R=area.branch$inv.R,
                      # branch.length=data$branch.length,
                      # n.descen = data$n.descendants),
                      spat_alg = "bootspat_str",
                      spat_alg_args = list(rprob = NULL,
                                           rich = NULL,
                                           fr_prob = NULL),
                      aleats = 2)
terra::plot(tses)

# }