spatialEco (version 2.0-2)

breeding.density: Breeding density areas (aka, core habitat areas)

Description

Calculates breeding density areas base on population counts and spatial point density.

Usage

breeding.density(x, pop, p = 0.75, bw = 6400, b = 8500, self = TRUE)

Value

A list object with:

• pop.pts sf POINT object with points identified within the specified p

• pop.area sf POLYGON object of buffered points specified by parameter b

• bandwidth Specified distance bandwidth used in identifying neighbor counts

• buffer Specified buffer distance used in buffering points for pop.area

• p Specified population percent

Arguments

x

sf POINT object

pop

Population count/density column in x

p

Target percent of population

bw

Bandwidth distance for the kernel estimate (default 8500)

b

Buffer distance (default 8500)

self

(TRUE/FALSE) Should source observations be included in density (default TRUE)

Author

Jeffrey S. Evans <[e-mail]>

Details

The breeding density areas model identifies the Nth-percent population exhibiting the highest spatial density and counts/frequency. It then buffers these points by a specified distance to produce breeding area polygons. If you would like to recreate the results in Doherty et al., (2010), then define bw = 6400m and b[if p < 0.75 b = 6400m, | p >= 0.75 b = 8500m]

References

Doherty, K.E., J.D. Tack, J.S. Evans, D.E. Naugle (2010) Mapping breeding densities of greater sage-grouse: A tool for range-wide conservation planning. Bureau of Land Management. Number L10PG00911

Examples

library(sf)

n=1500
bb <- rbind(c(-1281299,-761876.5),c(1915337,2566433.5))
bb.mat <- round(cbind(c(bb[1,1], bb[1,2], bb[1,2], bb[1,1]),
                  c(bb[2,1], bb[2,1], bb[2,2], bb[2,2])),2)
 bbp <- st_sfc(st_polygon(list(rbind(bb.mat, bb.mat[1,]))))
   pop <- st_as_sf(st_sample(bbp, n, type = "random"))
  st_geometry(pop) <- "geometry"
     pop$ID <- 1:nrow(pop)
  pop$counts <- round(runif(nrow(pop), 1,250),0)
   
    bd75 <- breeding.density(pop, pop='counts', p=0.75, b=8500, bw=6400)	 
      plot(st_geometry(bd75$pop.area), border = NA,  
        main='75% breeding density areas', col="grey")
         plot(st_geometry(pop), pch=20, col='black', add=TRUE)
         plot(st_geometry(bd75$pop.pts), pch=20, col='red', add=TRUE)
      legend("bottomright", legend=c("selected areas","selected sites", "all sites"),
             bg="white", fill=c("grey","red", "black"), pt.cex = 2)