costing {secrdesign}

Cost of SECR design

Description

The cost of implementing a spatially explicit capture–recapture design depends on the detector layout, the number of detections and the various unit costs.

Usage

costing(traps, nr, noccasions, unitcost = list(), nrepeats = 1, routelength = NULL, 
    setupoccasion = TRUE)

Arguments

traps

traps object for detector array

nr

numeric vector with E(n) and E(r) as first two elements

noccasions

integer number of sampling occasions

unitcost

list with unit costs (see Details)

nrepeats

integer number of repeated arrays

routelength

numeric route length (km)

setupoccasion

logical; if TRUE then the cost of a setup visit is included (noccasions+1)

Details

nr is a vector with the expected sample sizes (numbers of individuals and recaptures), usually the output from Enrm.

unitcost should be a list with at least one of the components ‘perkm’, ‘perarray’, ‘perdetector’, ‘pervisit’ and ‘perdetection’.

The number of occasions (noccasions) is incremented by 1 if setupoccasion is TRUE.

Component	Unit cost	Costing
Arrays	perarray	perarray x nrepeats
Detectors	perdetector	perdetector x nrow(traps) x nrepeats
Travel	perkm	perkm x routelength x noccasions x nrepeats
Visits	pervisit	sum(pervisit x trapcost) x noccasions x nrepeats
Detections	perdetection	perdetection x total detections (E(n) + E(r))

‘Travel’ and ‘Visits’ are alternative ways to cost field time. The variable ‘routelength’ represents the length of a path followed to visit all detectors; if not specified it is approximated by the sum of the nearest-trap distances. The variable ‘trapcost’ is a vector of length equal to the number of detectors. By default it is a vector of 1's, but detector- specific values may be provided as trap covariate ‘costpervisit’. In the latter case the value of ‘pervisit’ should probably be 1.0.

‘Arrays’ and 'Detectors' represent one-off costs.

‘Detections’ includes costs such as handling time and laboratory DNA analysis.

See ../doc/secrdesign-tools.pdf for more.

Value

A named numeric vector

See Also

Enrm, scenarioSummary

Examples

tr <- make.grid(8, 8, spacing = 25)
msk <- make.mask(tr, buffer = 100, type = 'trapbuffer')
nrm <- Enrm(D = 5, tr, msk, list(lambda0 = 0.2, sigma = 20), 5)
costing (tr, nrm, 5, unitcost = list(pervisit = 5, perdetection = 15))