dist_fun2: Distance function with segmented attenuation

In bSims: Bird Point Count Simulator

Description

Distance function with segmented attenuation crossing a number of boundaries of strata with different attenuation characteristics following results in Yip et al. (2017).

Usage

dist_fun2(d, tau, dist_fun, breaks = numeric(0), ...)

Arguments

d	distance from observer.
tau	a parameter passed to the the distance function. Length of tau must equal length(b) + 1 referring to distance function parameters in the different strata (a stratum is defined by an interval surrounded by 1 or 2 boundaries).
dist_fun	distance function taking two arguments: distance, and tau, see examples.
breaks	distance breakpoints, must be length(tau) - 1 in length. These breakpoints represent the boundaries between the intervals characterized by homogeneous attenuation characteristics.
...	other arguments passed to dist_fun

Value

Probability of detection given the distance, stratum specific parameters and the arrangement of breakpoints.

Author(s)

Peter Solymos

References

Yip, D. A., Bayne, E. M., Solymos, P., Campbell, J., and Proppe, J. D., 2017. Sound attenuation in forested and roadside environments: implications for avian point count surveys. Condor, 119: 73–84. <doi:10.1650/CONDOR-16-93.1>

Examples

tau <- c(1, 2, 3, 2, 1)
d <- seq(0, 4, 0.01)
dist_fun <- function(d, tau) exp(-(d/tau)^2) # half normal
#dist_fun <- function(d, tau) exp(-d/tau) # exponential
#dist_fun <- function(d, tau) 1-exp(-(d/tau)^-2) # hazard rate

b <- c(0.5, 1, 1.5, 2) #  boundaries

op <- par(mfrow=c(2, 1))
plot(d, dist_fun2(d, tau[1], dist_fun), type="n",
  ylab="P(detection)", xlab="Distance", axes=FALSE,
  main="Sound travels from left to right")
axis(1)
axis(2)
for (i in seq_len(length(b)+1)) {
  x1 <- c(0, b, 4)[i]
  x2 <- c(0, b, 4)[i+1]
  polygon(c(0, b, 4)[c(i, i, i+1, i+1)], c(0, 1, 1, 0),
    border=NA,
    col=c("darkolivegreen1", "burlywood1", "lightgrey",
    "burlywood1", "darkolivegreen1")[i])
}
lines(d, dist_fun2(d, tau[1], dist_fun))
lines(d, dist_fun2(d, tau[2], dist_fun))
lines(d, dist_fun2(d, tau[3], dist_fun))
lines(d, dist_fun2(d, tau, dist_fun, b), col=2, lwd=3)

plot(rev(d), dist_fun2(d, tau[1], dist_fun), type="n",
  ylab="P(detection)", xlab="Distance", axes=FALSE,
  main="Sound travels from right to left")
axis(1)
axis(2)
for (i in seq_len(length(b)+1)) {
  x1 <- c(0, b, 4)[i]
  x2 <- c(0, b, 4)[i+1]
  polygon(c(0, b, 4)[c(i, i, i+1, i+1)], c(0, 1, 1, 0),
    border=NA,
    col=c("darkolivegreen1", "burlywood1", "lightgrey",
    "burlywood1", "darkolivegreen1")[i])
}
lines(rev(d), dist_fun2(d, tau[1], dist_fun))
lines(rev(d), dist_fun2(d, tau[2], dist_fun))
lines(rev(d), dist_fun2(d, tau[3], dist_fun))
lines(rev(d), dist_fun2(d, tau, dist_fun, rev(4-b)), col=2, lwd=3)
par(op)

bSims documentation built on Oct. 7, 2021, 9:13 a.m.