diff --git a/content/applications/user_software/r_packages.md b/content/applications/user_software/r_packages.md
index 56e0623f891e21bd25de986a48f5bd7f0f3bb27a..275dbdb4324d2bb3e583b4a01879f1bc01c1c2e6 100644
--- a/content/applications/user_software/r_packages.md
+++ b/content/applications/user_software/r_packages.md
@@ -3,6 +3,8 @@ title = "Using R Libraries"
 description =  "How to install R packages on HCC resources."
 +++
 
+{{% panel theme="danger" header="**R Package Installation Best Practices**" %}}The preferred way to install R packages is using the [Anaconda Package Manager]({{< relref "using_anaconda_package_manager" >}}), which allows users to create custom software environments.  Unlike the R installer, Anaconda automatically resolves even external compatibility/dependency issues, and is therefore a better choice for many applications.  The instructions are provided here as a reference and for use when a particular R package is not available via conda.  In those cases, we recommend using conda first to install any needed external dependencies or other R packages, then install the desired package within R.{{% /panel %}}
+
 Many commonly used R packages are included in the base R installation available on HCC clusters,
  such as `tidyverse` and `stringr`. However, users are able to install other packages in their 
 user libraries.