epm (version 1.1.4)

betadiv_taxonomic: Map turnover in species communities

Description

Multisite taxonomic community dissimilarity is calculated for each cell within a circular moving window of neighboring cells. To implement a custom function, see customBetaDiv.

Usage

betadiv_taxonomic(
  x,
  radius,
  component = "full",
  focalCoord = NULL,
  slow = FALSE,
  nThreads = 1
)

Value

Returns a grid with multi-site community dissimilarity for each cell.

Arguments

x

object of class epmGrid.

radius

Radius of the moving window in map units.

component

which component of beta diversity to use, can be "turnover", "nestedness" or "full"

focalCoord

vector of x and y coordinate, see details

slow

if TRUE, use an alternate implementation that has a smaller memory footprint but that is likely to be much slower. Most useful for high spatial resolution.

nThreads

number of threads for parallelization

Author

Pascal Title

Details

For each cell, multisite dissimilarity is calculated from the focal cell and its neighbors. If focalCoord is specified, then instead of multisite dissimilarity within a moving window of gridcells, pairwise dissimilarity is calculated from the cell at the focal coordinates, to all other cells.

All metrics are based on Sorensen dissimilarity and range from 0 to 1.
For each metric, the following components can be specified. These components are additive, such that the full metric = turnover + nestedness.

• turnover: species turnover without the influence of richness differences

• nestedness: species turnover due to differences in richness richness and pure turnover

If the R package spdep is installed, this function should run more quickly.

References

Baselga, A. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography 21 (2012): 1223–1232.

Examples

# \donttest{
tamiasEPM

tamiasEPM <- addPhylo(tamiasEPM, tamiasTree)
tamiasEPM <- addTraits(tamiasEPM, tamiasTraits)

# taxonomic turnover
beta_taxonomic_turnover <- betadiv_taxonomic(tamiasEPM, radius = 70000,
		component = 'turnover')
beta_taxonomic_nestedness <- betadiv_taxonomic(tamiasEPM, radius = 70000,
		component = 'nestedness')
beta_taxonomic_full <- betadiv_taxonomic(tamiasEPM, radius = 70000,
		component = 'full')



oldpar <- par(mfrow = c(1, 3))
plot(beta_taxonomic_turnover, reset = FALSE, key.pos = NULL)
plot(beta_taxonomic_nestedness, reset = FALSE, key.pos = NULL)
plot(beta_taxonomic_full, reset = FALSE, key.pos = NULL)



# using square grid epmGrid
tamiasEPM2 <- createEPMgrid(tamiasPolyList, resolution = 50000,
	cellType = 'square', method = 'centroid')

beta_taxonomic_full <- betadiv_taxonomic(tamiasEPM2, radius = 70000,
		component = 'full')
beta_taxonomic_full_slow <- betadiv_taxonomic(tamiasEPM2, radius = 70000,
		component = 'full', slow = TRUE)

par(mfrow=c(1,2))
terra::plot(beta_taxonomic_full, col = sf::sf.colors(100))
terra::plot(beta_taxonomic_full_slow, col = sf::sf.colors(100))

# dissimilarity from a focal cell
focalBeta <- betadiv_taxonomic(tamiasEPM, radius = 70000,
		component = 'full', focalCoord = c(-1413764, 573610.8))
plot(focalBeta, reset = FALSE)
points(-1413764, 573610.8, pch = 3, col = 'white')

par(oldpar)
# }