niche_overlap_index: Index of habitat niche overalp

Description Usage Arguments Details Value Author(s) Examples

View source: R/niche_overlap_index.R

Description

Derive an index (0: complete separation, 1: complete overlap) from a kselect object to estimate a degree of habitat niche overlap between species/indviduals

Usage

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niche_overlap_index(X, kernel = "gaussian", bw = "nrd0")

Arguments

X

a kselect (adehabitatHS) object

kernel

a character string giving the smoothing kernel to be used. Default is "gaussian". See density()

bw

the smoothing bandwidth to be used to compute the kernel density. Default is "nrd0". See density()

permutations

logical, if permutations should be computed or not

nb.permutations

number of permutations to compute

hypothesis

the H0 to be tested: c("segregation","overlap")

Details

Uses scores obtained for each individual on each dimension of the ecological space of the Kselect and compute a non-parametric kernel estimation. Area of overlap between distribution of the two indviduals is calculated. Eigen values of the kslect are then used to calculated an overlap weihgted index.

O_{ij} = \int_{b}^{a} ≤ft [ f(x) - g(x) \right ]dx

\bar{O_{ij}} = \frac{∑_{e}^{n} O_{ij_{e}} λ _{e}}{∑_{e}^{n} λ _{e}}

i and j are the two individuals to be compared, f(x) and f(x) the two probability functions of indviduals i and j and e each of the axes.

Value

A list of paired matrices with an overlap index between each individuals calculated on each axis and a Weighted (based on eigen values of the kselect) overlap index calculated on all axes

Author(s)

Cyril Milleret

Examples

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library(adehabitatHS)
data(puechabonsp)

locs <- puechabonsp$relocs
map <- puechabonsp$map

## compute the home range of animals (e.g. using the minimum convex polygon)
 
pc <- mcp(locs[,"Name"])
hr <- hr.rast(pc, map)

## Compute the number of relocation in each pixel of the map
cp <- count.points(locs[,"Name"], map)

## prepares the data for the kselect analysis
x <- prepksel(map, hr, cp)
tab <- x$t

## We call a new graphic window
## A K-select analysis
acp <- dudi.pca(tab, scannf = FALSE, nf = 4)
kn <- kselect(acp, x$factor, x$weight,
              scannf = FALSE, nf = 4)

# compute habitat niche overlap 
niche_overlap_index(kn, kernel = "gaussian", bw = "nrd0",permutations=TRUE,nb.permutations=100,hypothesis="segregation")

cyrilmi/myfunctions documentation built on May 12, 2017, 2:26 p.m.