spatialEco (version 2.0-2)

dispersion: Dispersion (H-prime)

Description

Calculates the dispersion ("rarity") of targets associated with planning units

Usage

dispersion(x)

Value

data.frame with columns H values for each target, H , sH, sHmax

Arguments

x

data.frame object of target values

Author

Jeffrey S. Evans <[e-mail]>

Details

The dispersion index (H-prime) is calculated H = sum( sqrt(p) / sqrt(a) ) where; P = (sum of target in planning unit / sum of target across all planning units) and a = (count of planning units containing target / number of planning units)

References

Evans, J.S., S.R. Schill, G.T. Raber (2015) A Systematic Framework for Spatial Conservation Planning and Ecological Priority Design in St. Lucia, Eastern Caribbean. Chapter 26 in Central American Biodiversity : Conservation, Ecology and a Sustainable Future. F. Huettman (eds). Springer, NY.

Examples

# \donttest{ 
 library(sf)
   data(pu)
  
 d <- dispersion(st_drop_geometry(pu[,2:ncol(pu)]))  
   p <- d[,"H"]
 clr <- c("#3288BD", "#99D594", "#E6F598", "#FEE08B", 
          "#FC8D59", "#D53E4F")      
 clrs <- ifelse(p < 0.5524462, clr[1], 
           ifelse(p >= 0.5524462 & p < 1.223523, clr[2],
             ifelse(p >= 1.223523 & p < 2.465613, clr[3],
 	          ifelse(p >= 2.465613 & p < 4.76429, clr[4],
 	            ifelse(p >= 4.76429 & p < 8.817699, clr[5],
 	              ifelse(p >= 8.817699, clr[6], NA))))))
 plot(st_geometry(pu), col=clrs, border=NA)
   legend("bottomleft", legend=rev(c("Very Rare","Rare","Moderately Rare",
          "Somewhat Common","Common","Over Dispersed")),
          fill=clr, cex=0.6, bty="n") 
   box()
# }