adehabitatHR (version 0.4.22)

LoCoH: Estimating LoCoH home ranges

Description

The functions computes the home range of one or several animals using the LoCoH family of methods.

The functions LoCoH.k, LoCoH.r, and LoCoH.a implement the k-LoCoH, r-LoCoH, and a-LoCoH respectively (Getz et al. 2007).

The functions LoCoH.k.area, LoCoH.r.area, and LoCoH.a.area compute the curve showing the relationships between the home-range size (computed to a specified percent) and the k, r or a parameters respectively.

Usage

LoCoH.k(xy, k=5, unin = c("m", "km"),
        unout = c("ha", "m2", "km2"),
        duplicates=c("random","remove"), amount = NULL)
LoCoH.r(xy, r, unin = c("m", "km"),
        unout = c("ha", "m2", "km2"),
        duplicates=c("random","remove"), amount = NULL)
LoCoH.a(xy, a, unin = c("m", "km"),
        unout = c("ha", "m2", "km2"),
        duplicates=c("random","remove"), amount = NULL)
LoCoH.k.area(xy, krange, percent=100, unin = c("m", "km"),
             unout = c("ha", "m2", "km2"),
             duplicates=c("random","remove"), amount = NULL)
LoCoH.r.area(xy, rrange, percent=100, unin = c("m", "km"),
             unout = c("ha", "m2", "km2"),
             duplicates=c("random","remove"), amount = NULL)
LoCoH.a.area(xy, arange, percent=100, unin = c("m", "km"),
             unout = c("ha", "m2", "km2"),
             duplicates=c("random","remove"), amount = NULL)

Value

The functions LoCoH.* return either objects of class

SpatialPolygonsDataFrame (if the relocations of only one animals are passed as the xy argument) or a list of

SpatialPolygonsDataFrame (if the relocations of several animals are passed as the xy argument).

The functions LoCoH.*.area return invisibly either a vector (if the relocations of only one animals are passed as the xy

argument) or a data frame containing the home-range sizes for various values of k, r (rows) for the different animals (columns).

Arguments

xy

An object inheriting the class SpatialPoints containing the x and y relocations of the animal. If xy inherits the class SpatialPointsDataFrame, it should contain only one column (a factor) corresponding to the identity of the animals for each relocation.

k

numeric. The number of nearest neighbors minus one out of which to create convex hulls

r

numeric. The convex hulls are created out of all points within r distance from the root points

a

numeric. Create convex hulls from the maximum number of nearest neighbors such that the sum of their distances is less than or equal to this parameter

unin

the units of the relocations coordinates. Either "m" for meters or "km" for kilometers

unout

the units of the output areas. Either "m2" for square meters, "km2" for square kilometers or "ha" for hectares

duplicates

a setting to determine how duplicated points are handled. If "random" the duplicated points are slightly moved randomly. If "remove" the duplicated points are removed.

amount

if duplicates == random, this parameter controls the amount of noise added to the data (see the help page of jitter for additional information on this parameter).

krange

a vector containing the values of k for which the home range size is to be estimated.

arange

a vector containing the values of k for which the home range size is to be estimated.

rrange

a vector containing the values of k for which the home range size is to be estimated.

percent

the percentage level of the home range. For the function plot.LoCoH, this value could also be the character string "all", indicating that all the polygons are to be displayed.

Author

Clement Calenge
with contributions from Scott Fortmann-Roe

References

Getz, W.M. & Wilmers, C.C. (2004). A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography, 27, 489--505.

Getz, W.M., Fortmann-Roe, S.B, Lyons, A., Ryan, S., Cross, P. (2007). LoCoH methods for the construction of home ranges and utilization distributions. PLoS ONE, 2: 1--11.

See Also

MCHu, getverticeshr.

Examples

if (FALSE) {

## Load the data
data(puechabonsp)

## The relocations:
locs <- puechabonsp$relocs
locsdf <- as.data.frame(locs)
head(locsdf)

## Shows the relocations
plot(locs, col=as.numeric(locsdf[,1]))


## Examinates the changes in home-range size for various values of k
## Be patient! the algorithm can be very long
ar <- LoCoH.k.area(locs[,1], k=c(8:13))

## 12 points seems to be a good choice (rough asymptote for all animals)
## the k-LoCoH method:
nn <- LoCoH.k(locs[,1], k=12)

## Graphical display of the results
plot(nn, border=NA)

## the object nn is a list of objects of class
## SpatialPolygonsDataFrame
length(nn)
names(nn)
class(nn[[1]])

## shows the content of the object for the first animal
as.data.frame(nn[[1]])

## The 95% home range is the smallest area for which the
## proportion of relocations included is larger or equal
## to 95% In this case, it is the 22th row of the
## SpatialPolygonsDataFrame.
## The area covered by the home range is for this first animal
## equal to 22.87 ha.

## shows this area:
plot(nn[[1]][11,])


## rasterization of the home ranges:
## use the map of the area:
image(puechabonsp$map)
ras <- MCHu.rast(nn, puechabonsp$map, percent=100)  
opar <- par(mfrow=c(2,2))
lapply(1:4, function(i) { image(ras,i); box()})
par(opar)


## r-LoCoH and a-LoCoH can be applied similarly

}