contour {secr}

R Documentation

Contour Detection Probability

Description

Display contours of the net probability of detection p.(X), or the area within a specified distance of detectors. bufferContour adds a conventional ‘boundary strip’ to a detector (trap) array, where buffer equals the strip width.

Usage

pdotContour(traps, border = NULL, nx = 64, detectfn = 0,
    detectpar = list(g0 = 0.2, sigma = 25, z = 1), noccasions = NULL,
    binomN = NULL, levels = seq(0.1, 0.9, 0.1), poly =
    NULL, poly.habitat = TRUE, plt = TRUE, add = FALSE, fill = NULL, ...)

bufferContour(traps, buffer, nx = 64, convex = FALSE, ntheta = 100,
     plt = TRUE, add = FALSE, poly = NULL, poly.habitat = TRUE, 
     fill = NULL, ...)

Arguments

traps	traps object (or mask for bufferContour)
border	width of blank margin around the outermost detectors
nx	dimension of interpolation grid in x-direction
detectfn	integer code or character string for shape of detection function 0 = halfnormal etc. – see detectfn
detectpar	list of values for named parameters of detection function
noccasions	number of sampling occasions
binomN	integer code for discrete distribution (see secr.fit)
levels	vector of levels for p.(X)
poly	matrix of two columns, the x and y coordinates of a bounding polygon (optional)
poly.habitat	logical as in make.mask
plt	logical to plot contours
add	logical to add contour(s) to an existing plot
fill	vector of colours to fill contours (optional)
...	other arguments to pass to contour
buffer	vector of buffer widths
convex	logical, if TRUE the plotted contour(s) will be convex
ntheta	integer value for smoothness of convex contours

Details

pdotContour constructs a rectangular mask and applies pdot to compute the p.(X) at each mask point.

If convex = FALSE, bufferContour constructs a mask and contours the points on the basis of distance to the nearest detector at the levels given in buffer.

If convex = TRUE, bufferContour constructs a set of potential vertices by adding points on a circle of radius = buffer to each detector location; the desired contour is the convex hull of these points (this algorithm derives from Efford, 2012).

If traps has a usage attribute then noccasions is set accordingly; otherwise it must be provided.

If traps is for multiple sessions then detectpar should be a list of the same length, one component per session, and noccasions may be a numeric vector of the same length.

Increase nx for smoother lines, at the expense of speed.

Value

Coordinates of the plotted contours are returned as a list with one component per polygon. The list is returned invisibly if plt = TRUE.

For multi-session input (traps) the value is a list of such lists, one per session.

Note

The precision (smoothness) of the fitted line in bufferContour is controlled by ntheta rather than nx when convex = TRUE.

To suppress contour labels, include the argument drawlabels = FALSE (this will be passed via ... to contour). Other useful arguments of contour are col (colour of contour lines) and lwd (line width).

You may wish to consider function st_buffer in package sf as an alternative to bufferContour.

bufferContour failed with multi-session traps before secr 2.8.0.

References

Efford, M. G. (2012) DENSITY 5.0: software for spatially explicit capture–recapture. Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand https://www.otago.ac.nz/density/.

See Also

pdot, make.mask

Examples

possumtraps <- traps(possumCH)

## convex and concave buffers
plot(possumtraps, border = 270)
bufferContour(possumtraps, buffer = 100, add = TRUE, col = "blue")
bufferContour(possumtraps, buffer = 100, convex = TRUE, add = TRUE)

## areas
buff.concave <- bufferContour(possumtraps, buffer = 100,
    plt = FALSE)
buff.convex  <- bufferContour(possumtraps, buffer = 100,
    plt = FALSE, convex = TRUE)
sum (sapply(buff.concave, polyarea)) ## sum over parts
sapply(buff.convex, polyarea)

## effect of nx on area
buff.concave2 <- bufferContour(possumtraps, buffer = 100,
    nx = 128, plt = FALSE)
sum (sapply(buff.concave2, polyarea))

## Not run: 

plot(possumtraps, border = 270)
pdotContour(possumtraps, detectfn = 0, nx = 128, detectpar =
    detectpar(possum.model.0), levels = c(0.1, 0.01, 0.001),
    noccasions = 5, add = TRUE)

## clipping to polygon
olddir <- setwd(system.file("extdata", package = "secr"))
possumtraps <- traps(possumCH)
possumarea <- read.table("possumarea.txt", header = TRUE)
par(xpd = TRUE, mar = c(1,6,6,6))
plot(possumtraps, border = 400, gridlines = FALSE)
pdotContour(possumtraps, detectfn = 0, nx = 256, detectpar =
    detectpar(possum.model.0), levels = c(0.1, 0.01, 0.001),
    noccasions = 5, add = TRUE, poly = possumarea, col = "blue")
lines(possumarea)
setwd(olddir)
par(xpd = FALSE, mar = c(5,4,4,2) + 0.1)    ## reset to default


## End(Not run)

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