| mask {secr} | R Documentation |
Encapsulate a habitat mask for spatially explicit capture–recapture.
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 = ~cover.
In relation to the first purpose, the definition of 'negligible' is fluid. Any probability less than 0.01 seems OK in the sense of not causing noticeable bias in density estimates, but extent of the mask affects the binomial sampling variance of density derived from conditional likelihood estimates of the detection function (M. Efford unpubl. results).
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 –
| type | 'traprect', 'trapbuffer', 'pdot', 'polygon' (see make.mask) or 'user' |
| polygon | vertices of polygon defining habitat boundary, for type = 'polygon' |
| pdotmin | threshold of p.(X) for type = 'pdot' |
| covariates | dataframe of site-specific covariates |
| meanSD | data frame with centroid (mean and SD) of x and y coordinates |
| area | area (ha) of the grid cell associated with each point |
| spacing | nominal spacing (metres) between adjacent points |
| boundingbox | data 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 habitat mask is needed by secr.fit, but one will be generated automatically if none is provided. You should be aware of this and check that the default settings (e.g. buffer) are appropriate.
Murray Efford murray.efford@otago.ac.nz
make.mask, read.mask, secr.fit, secr density models