saturation: Detector saturation

In secrdesign: Sampling Design for Spatially Explicit Capture-Recapture

Detector saturation

Description

Computes the expected proportion of successful detectors (i.e., ‘trap success’). The calculation does not allow for local variation in realised density (number of animals centred near each detector) and the predictions are therefore slightly higher than simulations with Poisson local density. The discrepancy is typically less than 1%.

Usage

saturation(traps, mask, detectpar, detectfn = 
    c("HHN", "HHR", "HEX", "HAN", "HCG", 'HN', 'HR', 'EX'), 
    D, plt = FALSE, add = FALSE, ...)

Arguments

traps	secr traps object
mask	secr mask object
detectpar	a named list giving a value for each parameter of detection function
detectfn	integer code or character string for shape of detection function – see detectfn
D	population density animals / hectare; may be scalar or vector of length nrow(mask)
plt	logical; if TRUE then a colour plot is produced
add	logical; if TRUE any plot is added to the existing plot
...	other arguments passed to plot.mask when plt = TRUE

Details

The calculation is based on an additive hazard model. If detectfn is not a hazard function (‘HHN’, ‘HEX’, ‘HHR’, ‘HAN’ and ‘HCG’) then an attempt is made to approximate one of the hazard functions (HN -> HHN, HR -> HHR, EX -> HEX). The default is ‘HHN’.

Computation is not possible for single-catch traps.

An empirical estimate of saturation is the total number of detectors visited divided by the total number of detectors used. These are outputs from the summary method for capthist objects. See Examples.

Value

A list with components

bydetector	expected saturation for each detector
mean	average over detectors

The list is returned invisibly if plt = TRUE.

See Also

Enrm

Examples

tr <- traps(captdata)
detector(tr) <- 'multi'
mask <- make.mask(tr, buffer = 100)
saturation(tr, mask, detectpar = list(lambda0 = 0.27, sigma = 29), 
    detectfn = 'HHN', D = 5.5, plt = TRUE)
plotMaskEdge(as.mask(tr), add = TRUE)  ## boundary line

# empirical - useful for extractfn argument of secrdesign::run.scenarios
satfn <- function(CH) { 
    sumCH <- summary(CH)$counts
    sumCH['detectors visited', 'Total'] /  sumCH['detectors used', 'Total']
}
satfn(captdata)

secrdesign documentation built on March 31, 2023, 10:25 p.m.