This tutorial was rendered using Rdistance version 4.5.0.
Abundance via line-transect distance-sampling when detection depends on covariates.
Loading required package: units
udunits database from C:/Users/trent/AppData/Local/R/win-library/4.6/units/share/udunits/udunits2.xml
data(sparrowDf)
oneHectare <- units::set_units(1, "ha")
whi <- set_units(200, "m")
dfuncFit <- sparrowDf |>
dfuncEstim(dist ~ bare + groupsize(groupsize)
, likelihood = "hazrate"
, w.hi = whi) |>
abundEstim(area = oneHectare
, ci = NULL)
summary(dfuncFit)
Call: dfuncEstim(data = sparrowDf, dist ~ bare + groupsize(groupsize),
likelihood = "hazrate", w.hi = whi)
Coefficients:
Estimate SE z p(>|z|)
(Intercept) 3.22867307 0.230688774 13.995796 1.653672e-44
bare 0.01214628 0.003512742 3.457778 5.446505e-04
k 3.15551173 0.411046996 7.676766 1.631547e-14
Message: Success; Asymptotic SE's
Function: HAZRATE
Strip: 0 [m] to 200 [m]
Average effective strip width (ESW): 66.26362 [m] (range 48.15407 [m] to 86.61745 [m])
Average probability of detection: 0.3313181 (range 0.2407703 to 0.4330873)
Scaling: g(0 [m]) = 1
Log likelihood: -1641.974
AICc: 3290.016
Surveyed Units: 36000 [m]
Individuals seen: 372 in 354 groups
Average group size: 1.050847
Group size range: 1 to 3
Density in sampled area: 8.023898e-05 [1/m^2]
Abundance in 10000 [m^2] study area: 0.8023898
plot(dfuncFit
, newdata = data.frame(bare = c(30, 40, 50))
, lty = 1
, nbins = 30
, border = NA
, col = "grey75")
