This simulated data set by Mazerolle (2015) is based on the biological
parameters for the Gopher Tortoise (Gopherus polyphemus) reported
by Smith et al. (2009). A half-normal distribution with a scale of 10
and without an adjustment factor was used to simulate the distance data
for a study area of 120 km^2. An effort of 500 m in 300 line
transects was deployed. A density of 72 individuals per km^2 was
used in the simulation using the approach outlined in Buckland et
al. (2001).
Usage
data(tortoise)
Format
A data frame with 410 observations on the following 5 variables.
Region.Label
a numeric identifier for the study area.
Area
a numeric variable for the surface area of the
study area in square meters.
Sample.Label
a numeric identifier for each line
transect relating each observation to its corresponding transect.
Effort
Effort in meters expended in each line transect.
distance
a numeric variable for the perpendicular
distances in meters relative to the transect line for each of the
individuals detected during the survey. Note that transects
without detections have a value of NA for this variable.
Details
This data set is used to illustrate classic distance sampling (Buckland
et al. 2001, Mazerolle 2015).
Source
Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L.,
Borchers, D. L., Thomas, L. (2001) Introduction to distance
sampling: estimating abundance of biological populations. Oxford
University Press: Oxford.
Mazerolle, M. J. (2015) Estimating detectability and biological
parameters of interest with the use of the R
environment. Journal of Herpetology49, 541–559.
Smith, L. L., Linehan, J. M., Stober, J. M., Elliott, M. J., Jensen,
J. B. (2009) An evaluation of distance sampling for large-scale gopher
tortoise surveys in Georgia, USA. Applied Herpetology6,
355–368.
Examples
data(tortoise)
str(tortoise)
##plot distance data to determine if truncation is required
##(Buckland et al. 2001, pp. 15--17)
hist(tortoise$distance)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(AICcmodavg)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AICcmodavg/tortoise.Rd_%03d_medium.png", width=480, height=480)
> ### Name: tortoise
> ### Title: Gopher Tortoise Distance Sampling Data
> ### Aliases: tortoise
> ### Keywords: datasets
>
> ### ** Examples
>
> data(tortoise)
> str(tortoise)
'data.frame': 410 obs. of 5 variables:
$ Region.Label: int 1 1 1 1 1 1 1 1 1 1 ...
$ Area : num 1.2e+08 1.2e+08 1.2e+08 1.2e+08 1.2e+08 1.2e+08 1.2e+08 1.2e+08 1.2e+08 1.2e+08 ...
$ Sample.Label: int 1 1 2 3 4 5 5 5 6 6 ...
$ Effort : int 500 500 500 500 500 500 500 500 500 500 ...
$ distance : num 5.1 9.4 1.2 NA 5.4 11.1 5.2 4.6 7.5 8.4 ...
>
> ##plot distance data to determine if truncation is required
> ##(Buckland et al. 2001, pp. 15--17)
> hist(tortoise$distance)
>
>
>
>
>
> dev.off()
null device
1
>