Welcome to the GitHub repository for workshop on community ecology analyses using the vegan package at ESA 2017.
Location and time:
Sunday, August 6, 2017
8:00 AM - 11:30 AM
Location: Room C125-126, Oregon Convention Center
Naupaka Zimmerman and Gavin Simpson.
Naupaka Zimmerman, Andrew Tredennick, Gavin Simpson, Noam Ross.
The R statistical language has enjoyed wide and rapid adoption by many ecologists, and is used across many ecological subdisciplines for statistical analyses and the production of publication-quality figures. For community ecologists using R, one of the most-used, and most-useful, add-on packages is vegan, which provides a wide range of functionality covering inter alia ordination, diversity analysis, and ecological simulation. This workshop will offer participants a practical introduction to some of the most useful functions available within vegan. We will focus in particular on the use of NMDS as an ordination method and on how to visualize the results using related plotting tools. We will also cover between-group tests such as PERMANOVA.
The workshop will assume that participants have a basic level of familiarity with working with data in R, including data import and basic indexing and subsetting. Some familiarity with distance measures is recommended but not required as we will briefly cover data transformation, standardization, and multivariate distance measures. All participants must bring their own laptop with R and RStudio (available free online for all platforms at rstudio.com) pre-installed.
If you don't already have R set up with a suitable code editor, we recommend downloading and installing the most recent versions of R and RStudio Desktop for your platform. Once installed, open RStudio and install the following packages. Simply paste these commands into your prompt.
install.packages("vegan", dependencies = TRUE)
install.packages("permute")The slides, data, and code in this repository may change up until the start of the workshop, so please wait until as late as possible to download these files from GitHub to ensure that you have the most recent copy.
If you're already familiar with Git, then simply clone this repo. If you're not familiar with Git, simply click the green Clone or Download button on the top right side of this page and select Download ZIP. If you're not sure where to save it, just download and unzip to your Desktop.
If you're having any trouble with these steps please drop us an email. We'll also plan to have local copies if you forget to install any of these tools or have trouble downloading the files in this repository.
This work is licensed under a Creative Commons Attribution 4.0 International License.
