diff --git a/README.md b/README.md
index 91d6e2e..dcb099c 100644
--- a/README.md
+++ b/README.md
@@ -102,11 +102,6 @@ But issues can sometimes occur when:
If you run into any of these issues, it is best to consult with your IT department for support.
-## `mvgam` cheatsheet
-
-[![`mvgam` usage
-cheatsheet](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.png)](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.pdf)
-
## WORKSHOP MATERIALS
[Live questions and code sharing](https://docs.google.com/document/d/1xd3icf1wxGxO3SVt2AmKO8CkeKv1QpsxgqK7rR15U08/edit?usp=sharing)
@@ -115,3 +110,34 @@ cheatsheet](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheats
[Live code example 1](https://github.com/nicholasjclark/ESA_2024_timeseries/blob/main/live_code_examples/casestudy1_kestrel.R)
[Live code example 1](https://github.com/nicholasjclark/ESA_2024_timeseries/blob/main/live_code_examples/casestudy2_aphids.R)
+
+## OTHER `mvgam` RESOURCES
+
+A series of vignettes cover data formatting, forecasting and several
+extended case studies of DGAMs. A number of other examples have also
+been compiled:
+
+- Ecological Forecasting with Dynamic Generalized Additive
+ Models
+- Distributed lags (and hierarchical distributed lags)
+ using mgcv
and mvgam
+- State-Space Vector Autoregressions in
+ mvgam
+- Ecological Forecasting with Dynamic GAMs; a tutorial and
+ detailed case study
+- How to interpret and report nonlinear effects from
+ Generalized Additive Models
+- Phylogenetic smoothing using mgcv
+- Incorporating time-varying seasonality in forecast
+ models
+
+[![`mvgam` usage
+cheatsheet](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.png)](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.pdf)