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secr (version 4.6.10)

mask: Mask Object

Description

Encapsulate a habitat mask for spatially explicit capture--recapture. See also secr-habitatmasks.pdf.

Arguments

Details

A habitat mask serves four main purposes in spatially explicit capture--recapture. Firstly, it defines an outer limit to the area of integration; habitat beyond the mask may be occupied, but animals there should have negligible chance of being detected (see pdot and below). Secondly, it distinguishes sites in the vicinity of the detector array that are `habitat' (i.e. have the potential to be occupied) from `non-habitat'. Thirdly, it discretizes continuous habitat as a list of points. Each point is notionally associated with a cell (pixel) of uniform density. Discretization allows the SECR likelihood to be evaluated by summing over grid cells. Fourthly, the x-y coordinates of the mask and any habitat covariates may be used to build spatial models of density. For example, a continuous or categorical habitat covariate `cover' measured at each point on the mask might be used in a formula for density such as D \(\sim\)cover.

In relation to the first purpose, the definition of `negligible' is fluid. Any probability less than 0.001 seems OK in the sense of not causing noticeable bias in density estimates, but this depends on the shape of the detection function (fat-tailed functions such as `hazard rate' are problematic). New tools for evaluating masks appeared in secr 1.5 (mask.check, esa.plot), and suggest.buffer automates selection of a buffer width.

Mask points are stored in a data frame with columns `x' and `y'. The number of rows equals the number of points.

Possible mask attributes

AttributeDescription
type`traprect', `trapbuffer', `pdot', `polygon', `clusterrect', `clusterbuffer' (see make.mask) or `user'
polygonvertices of polygon defining habitat boundary, for type = `polygon'
pdotminthreshold of p.(X) for type = `pdot'
covariatesdataframe of site-specific covariates
meanSDdata frame with centroid (mean and SD) of x and y coordinates
areaarea (ha) of the grid cell associated with each point
spacingnominal spacing (metres) between adjacent points
boundingboxdata frame of 4 rows, the vertices of the bounding box of all grid cells in the mask

Attributes other than covariates are generated automatically by make.mask. Type `user' refers to masks input from a text file with read.mask.

A virtual S4 class `mask' is defined to allow the definition of a method for the generic function raster from the raster package.

See Also

make.mask, read.mask, mask.check, esa.plot, suggest.buffer, secr.fit