Simulate Animals on Lines

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Description

This function is a simple substitute for the secr function sim.popn() for the case of a linear habitat.

Usage

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sim.linearpopn(mask, D, N, Ndist = c('poisson', 'fixed'), ...)

Arguments

mask

linearmask object

D

numeric density animals / km

N

number of individuals

Ndist

character string for distribution of total number of individuals

...

other arguments passed to sim.popn

Details

The linearmask input represents a discretized line - essentially a chain of line segments. By default, each segment is populated with a Poisson number of individuals. The user may specify D or N.

D may be a vector with one density per mask pixel, or a single number that will be applied across all pixels.

If Ndist = 'fixed' then a constant number of individuals N are simulated in each trial; otherwise N has a Poisson distribution across trials. N = sum(D) x mask length if D is specified.

This is a simplified wrapper for sim.popn called with model2D = "linear".

Value

Object of class c(‘linearpopn’, ‘popn’, ‘data.frame’).

Note

The population output from sim.linearpopn may be used unchanged with secr functions such as sim.capthist. However, to be faithful to the linear network you should set the ‘userdist’ argument of sim.capthist to networkdistance.

See Also

linearpopn, sim.popn

Examples

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x <- seq(0, 4*pi, length = 200)
xy <- data.frame(x = x*100, y = sin(x)*300)
mask <- read.linearmask(data = xy, spacing = 10)
trps <- make.line(mask, n = 15, startbuffer = 1000, by = 30)

newmask <- clipmask(mask, trps, buffer = 200)

linpop <- sim.linearpopn(newmask, 200)
CH <- sim.capthist(trps, linpop, userdist = networkdistance)
plot(newmask)
plot(CH, add = TRUE)

secr.fit(CH, mask = mask, details = list(userdist = networkdistance))