Rdistance: Density and Abundance from Distance-Sampling Surveys

Distance-sampling (<doi:10.1007/978-3-319-19219-2>) estimates density and abundance of survey targets (e.g., animals) when detection probability declines with distance. Distance-sampling is popular in ecology, especially when survey targets are observed from aerial platforms (e.g., airplane or drone), surface vessels (e.g., boat or truck), or along walking transects. Distance-sampling includes line-transect studies that measure observation distances as the closest approach of the sample route (transect) to the target (i.e., perpendicular off-transect distance), and point-transect studies that measure observation distances from stationary observers to the target (i.e., radial distance). The routines included here fit smooth (parametric) curves to histograms of observation distances and use those functions to compute effective sampling distances, density of targets in the surveyed area, and abundance of targets in a surrounding study area. Curve shapes include the half-normal, hazard rate, and negative exponential functions. Physical measurement units are required and used throughout to ensure density is reported correctly. The help files are extensive and have been vetted by multiple authors.

Package details

AuthorTrent McDonald [cre, aut], Jason Carlisle [aut], Aidan McDonald [aut] (point transect methods), Ryan Nielson [ctb] (smoothed likelihood), Ben Augustine [ctb] (maximization method), James Griswald [ctb] (maximization method), Patrick McKann [ctb] (maximization method), Lacey Jeroue [ctb] (vignettes), Hoffman Abigail [ctb] (vignettes), Kleinsausser Michael [ctb] (vignettes), Joel Reynolds [ctb] (Gamma likelihood), Pham Quang [ctb] (Gamma likelihood), Earl Becker [ctb] (Gamma likelihood), Aaron Christ [ctb] (Gamma likelihood), Brook Russelland [ctb] (Gamma likelihood), Stefan Emmons [ctb] (Automated tests), Will McDonald [ctb] (Automated tests), Reid Olson [ctb] (Automated tests and bug fixes)
MaintainerTrent McDonald <trent@mcdonalddatasciences.com>
LicenseGNU General Public License
Version4.0.5
URL https://github.com/tmcd82070/Rdistance/wiki
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("Rdistance")

Try the Rdistance package in your browser

Any scripts or data that you put into this service are public.

Rdistance documentation built on April 12, 2025, 1:12 a.m.