Create a binary search tree from a sorted array: Space complexity reasoning
I would say try to think about it more in the terms of data structures used directly in the calculation of the result. Typically you wouldn't consider the call stack because you could in theory rewrite you algorithm to be iterative and have no issues with the call stack. The call stack is only an issue when you reach the max recersion depth. It is also not considered when just analyzing algorithms.

Space complexity is constant or $O(1)$ because you can modify the tree in place.

Your answer about call stacks more so relates to the worst-case time complexity as this is directly related to number of function calls (or call stacks in your case). This is going to be $O(\text{height})$ of the tree which is at most $n$, so $O(n)$ in worst case, but $\Theta(\log(n))$ in average case. The time complexity can be improved to better than $O(n)$ if you keep your tree balanced after each insertion.