Dam Adult Branch Occupancy Model
Description
DABOM is an R package for estimating abundance of anadromous fishes using fish tagged at a primary sampling facility (e.g., dam) and later detected in upstream tributaries. It incorporates the branching structure of a stream network, and simultaneously estimates imperfect detection probabilities at all detection locations and movement probabilities past detection locations. The movement probabilities, when multiplied correctly and combined with an estimate of total abundance at the tagging site, can be used to estimate abundance at a variety of spatial scales. Further mathematical details of the model can be found in Waterhouse, 2020.
The user can find more information related to installation and use of this package on the package website.
Installation instructions
The DABOM compendium can be downloaded as a zip from from this URL: https://github.com/BiomarkABS/DABOM/archive/master.zip
Or the user can install the compendium as an R package from GitHub by using Hadley Wickham’s devtools package:
# install and load remotes, if necessary
install.packages("devtools")
devtools::install_github("KevinSee/DABOM",
build_vignettes = TRUE)devtools may require the downloading and installation of Rtools. The latest version of Rtools can be found here.
For the latest development version:
devtools::install_github("KevinSee/DABOM@develop")JAGS Software
The user will also need the JAGS software to run DABOM. They can download that from SourceForge. JAGS (Just Another Gibbs Sampler) software is used by DABOM for Bayesian inference. Please download version >= 4.0.0.
Other R Packages
The user will also need to install tidyverse, a series of R packages that work together for data science (i.e. data cleaning and manipulation), as well as the rjags package to interface with JAGS. The tidyverse and rjags packages are all available from the R community and can be installed by typing the following into your R console:
install.packages("tidyverse")
install.packages("rjags")Authors
DABOM is a collaborative project, with the primary contributors being:
- Kevin See (WDFW)
- Ryan N. Kinzer (Nez Perce Tribe)
Licenses
Text and figures : CC-BY-4.0
Code : See the DESCRIPTION file
Data : CC-0 attribution requested in reuse
Contributions
We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.