jbar calculates average Jaccard similarity among sites (columns)
in your landscape as the expected ratio of the intersection between two
sites to to their union:
J.Bar = mean(intersection/union)
jstar gives an approximation of this value from species
occupancy rates (row sums) as the ratio of the expected intersection
between two randomly chosen sites to the expected union:
J.Star = mean(intersection)/mean(union)
pstar gives the "effective occupancy" of a landscape, defined in
Harris et al. (2011). A landscape composed entirely of species with this
occupancy rate would have the same J.Star value as the input landscape.
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The number of sites in your landscape. Only needed for
David Jay Harris
Harris, D. J., K. G. Smith, and P. J. Hanly. 2011. "Occupancy is nine-tenths of the law: Occupancy rates determine the homogenizing and differentiating effects of exotic species." The American Naturalist.
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data(PLANTS) # Calculate key values for Wyoming from raw data landscape = PLANTS[["WY native table"]] jbar(landscape) jstar(landscape) pstar(landscape) # jstar and pstar also work if given row means and landscape sizes. # jbar requires spatial information that is lost during this averaging. occupancy = rowMeans(landscape) nsites = ncol(landscape) jstar(occupancy, nsites) pstar(occupancy, nsites)
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