Istat: I Similarity Statistic for Quantifying Niche Overlap

In SDMTools: Species Distribution Modelling Tools: Tools for processing data associated with species distribution modelling exercises

Description

Istat computes the I similarity statistic of Warren et al. 2008. It is a method for defining niche overlap from predictions of species' distributions.

NOTE: it is assumed the input data are of the same extent and cellsize, and all values are positive.

Usage

Istat(x, y, old = FALSE)

Arguments

x	a vector or matrix of data; the matrix can be a raster of class 'asc' (adehabitat package), 'RasterLayer' (raster package) or 'SpatialGridDataFrame' (sp package)
y	a vector or matrix of data with the same dimensions and class of 'x'
old	a boolean identifying if "old" equation is to be used (see description). This was kept for legacy issues.

Details

The I similarity statistic sums the pair-wise differences between two predictions to create a single value representing the similarity of the two distributions. The I similarity statistic ranges from a value of 0, where two distributions have no overlap, to 1 where two distributions are identical (Warren et al., 2008).

NOTE: updated to correct equation but not to worry about old... see explanation at http://enmtools.blogspot.com.au/2010_09_01_archive.html.

Value

A single value that is the I similarity statistic

Author(s)

Jeremy VanDerWal [e-mail]

References

Warren, D. L., R. E. Glor, M. Turelli, and D. Funk. 2008. Environmental Niche Equivalency versus Conservatism: Quantitative Approaches to Niche Evolution. Evolution 62:2868-2883.

Examples

#create some simple objects of class 'asc'
tasc = as.asc(matrix(1:50,nr=50,nc=50)); print(tasc)
#modify the asc objects so that they are slightly different
tasc1 = tasc + runif(n = 2500, min = -1, max = 1)
tasc2 = tasc + rnorm(n = 2500, mean = 1, sd = 1)

#ensure all data is positive
tasc1 = abs(tasc1)
tasc2 = abs(tasc2)

#calculate the I similarity statistic
I = Istat(tasc1,tasc2)
print(I) #high niche overlap

#using a more variable map
tasc2 = tasc + rnorm(n = 2500, mean = 25, sd = 15);tasc2 = abs(tasc2)
I = Istat(tasc1,tasc2)
print(I) #lower niche overlap

Example output

Raster map of class "asc":
Cell size:  1 
Number of rows:  50 
Number of columns:  50 
Type:  numeric 
[1] 0.9993098
[1] 0.9719067

SDMTools documentation built on Jan. 11, 2020, 9:23 a.m.