Educational demonstration of the burnr R package
This demo includes 5 short modules that extend basic burnr functionality into advanced graphics, analyses, and forest demography. Emphasis is on graphical visualization for its importance in seeing ecological pattern and process.
All necessary datasets are provided. Users may have to install some R libraries (packages) on their machines to enable some scripts to run. New libraries can be downloaded within RStudio, or with install.packages("PackageName"). This only needs to be done once to download the library.
To obtain a copy of this R project and run the code on your machine, you will need to copy the repository. There are two ways to do this:
- In RStudio, go to File > New Project, and choose “Version Control”, select “Git”, and paste the repository url: https://github.com/chguiterman/burnr_demo.git
- In GitHub, click the green "Code" button at top-right, then select "Download ZIP".
Select where you want the project to live on your machine. The project includes the set of folders containing data and scripts that you see on this github page.
After a moment, you should see the folders in the "Files" tab of your Rstudio console.
You can now open and run the code. The datasets are housed within the project, so R will know where to find them.
If you'd like to contribute to this demo page, please fork the repository and submit pull requests. See here for more info: http://r-bio.github.io/intro-git-rstudio/
A copy of the article (Malevich et al. 2018) describing burnr is provided for additional help.
The burnr website also has some additional help files: https://ltrr-arizona-edu.github.io/burnr/