- Authors: Lauren Hallett [lauren.m.hallett@gmail.com], Meghan Avolio [meghan.avolio@jhu.edu], Ian T. Carroll [carroll.ian@gmail.com], Sydney K. Jones [syd@sevilleta.unm.edu], Andrew A. MacDonald [a.a.m.macdonald@gmail.com], Dan F. B. Flynn [flynn@fas.harvard.edu], Peter Slaughter [slaughter@nceas.ucsb.edu], Julie Ripplinger [julie.ripplinger@asu.edu], Scott L. Collins [scollins@sevilleta.unm.edu], Corinna Gries [cgries@wisc.edu], Matthew B. Jones [jones@nceas.ucsb.edu]
- Version 1.x: doi:10.5063/F1542KJB
- Version 2.x: doi:10.5063/F1N877Z6
- License: Apache 2
- Package source code on Github
- Submit Bugs and feature requests
A package to analyze long-term ecological community datasets.
Univariate and multivariate temporal and spatial diversity indices, rank abundance curves, and community stability metrics. The functions implement metrics that are either explicitly temporal and include the option to calculate them over multiple replicates, or spatial and include the option to calculate them over multiple time points. Functions fall into five categories: static diversity indices, temporal diversity indices, spatial diversity indices, rank abundance curves, and community stability metrics. The diversity indices are temporal and spatial analogs to traditional diversity indices. Specifically, the package includes functions to calculate community richness, evenness and diversity at a given point in space and time. In addition, it contains functions to calculate species turnover, mean rank shifts, and lags in community similarity between two time points.
For an overview of codyn, see:
- Hallett et al. (2016) codyn: An R package of community dynamics metrics. Methods in Ecology and Evolution. http://doi.org/10.1111/2041-210X.12569
From CRAN, the package can be installed using standard tools:
install.packages("codyn")
To simplify the process of running R CMD check
on the package, the source distribution on GitHub includes configuration
files to use Docker to download and build standard Debian-based images for the current release of
R and the current development branch of R. Assuming you already have docker and docker-compose installed, these Docker
configuration files allow a clean environment to be built and tested with a single command. Checks can be run against the
current stable release of R using:
$ docker-compose run --rm r-check-stable
and the checks can be run against the current unstable development version of R using:
$ docker-compose run --rm r-check-devel
Work on this package was supported by NSF-ABI grant #1262458 to C. Gries, M. Jones, and S. Collins. Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California, and a SESYNC Synthesis Postdoctoral Fellowship to MLA.