diff --git a/docs/source/api/demography_api.md b/docs/source/api/demography_api.md
index db14bcbd..1244feff 100644
--- a/docs/source/api/demography_api.md
+++ b/docs/source/api/demography_api.md
@@ -5,7 +5,6 @@ jupytext:
     extension: .md
     format_name: myst
     format_version: 0.13
-    jupytext_version: 1.16.4
 kernelspec:
   display_name: Python 3
   language: python
diff --git a/docs/source/users/tmodel/canopy.md b/docs/source/users/tmodel/canopy.md
index c7887f37..b0911b87 100644
--- a/docs/source/users/tmodel/canopy.md
+++ b/docs/source/users/tmodel/canopy.md
@@ -5,7 +5,6 @@ jupytext:
     extension: .md
     format_name: myst
     format_version: 0.13
-    jupytext_version: 1.16.4
 kernelspec:
   display_name: python3
   language: python
@@ -60,9 +59,13 @@ pft.height
 ```
 
 ```{code-cell}
+:lines_to_next_cell: 2
+
 pft.crown_area
 ```
 
++++ {"lines_to_next_cell": 2}
+
 ### Crown shape
 
 Jaideep's extension of the T Model adds a crown shape model, driven by two parameters
@@ -95,6 +98,8 @@ r_0 &= \frac{1}{q_m}\sqrt{\frac{A_c}{\pi}}
 $$
 
 ```{code-cell}
+:lines_to_next_cell: 2
+
 def calculate_qm(m, n):
 
     # Constant q_m
@@ -128,6 +133,8 @@ print("zm = ", zm)
 print("r0 = ", r0)
 ```
 
++++ {"lines_to_next_cell": 2}
+
 The following functions then provide the value at height $z$ of relative $q(z)$ and
 actual $r(z)$ canopy radius:
 
@@ -275,6 +282,8 @@ The code below calculates the projected crown area for each stem and then plots
 vertical profile for individual stems and across the community.
 
 ```{code-cell}
+:lines_to_next_cell: 2
+
 # Calculate the projected area for each stem
 Ap_z = calculate_projected_area(z=z[:, None], pft=pft, m=m, n=n, qm=qm, zm=zm)
 
@@ -293,6 +302,8 @@ ax2.set_xlabel("Total community $A_p(z)$ (m2)")
 plt.tight_layout()
 ```
 
++++ {"lines_to_next_cell": 2}
+
 ### Canopy closure and canopy gap fraction
 
 The total cumulative projected area shown above is modified by a community-level
@@ -478,12 +489,16 @@ print(Ap_z_star)
 ```
 
 ```{code-cell}
+:lines_to_next_cell: 2
+
 # Calculate the contribution _within_ each layer per stem
 Ap_within_layer = np.diff(Ap_z_star, axis=0, prepend=0)
 
 print(Ap_within_layer)
 ```
 
++++ {"lines_to_next_cell": 2}
+
 ### Leaf area within canopy layers
 
 The projected area occupied by leaves at a given height $\tilde{A}_{cp}(z)$ is