Istat {SDMTools} | R Documentation |
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.
Istat(x, y, old = FALSE)
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. |
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.
A single value that is the I similarity statistic
Jeremy VanDerWal jjvanderwal@gmail.com
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.
#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