Well, if by tree you mean datatree, the problem is that they’re not really trees. If I remember correctly, in GH2 they will have another name, and in fact, its origin is GH_Structure< IGH_Goo> and the class DataTree< object> was an attempt to make it easier to operate with them and generally for any type, without restricting it to IGH_Goo which is a wrap of all data in GH1, but if Rutten reads this, please correct me if I am wrong. That said, datatrees can be interpreted as multidimensional arrays, but so can trees. An array does not necessarily have the same number of elements in each dimension. Regardless of interpretations/how they are used, the technical difference is how you jump from one element to another in memory to read or write. In lists/1d arrays, you have to go one by one (and if they are value type data they will be stored one by one in memory), in trees, each node knows the accesses to its parent and descendants (and they can be “randomly” located in memory), and in datatrees, it is like a 2d list, first you go through the paths one by one to the desired one and then one by one each element in the list/branch to the desired memory position/index/element. Maybe it’s not well explained, but this is where the difference really lies, its fundamental dimensions, which can be viewed different depending on the interpretation/use/layers of complexity to operate with.
Grafting, yes and no more dimensions are added. Not because it is still a list of lists and yes because you can interpret your new data organization as another degree of freedom within a given context. For example, a 2d grid of points in a flat list has 1 dimension (you need a list index), if you group them in a datatree between rows and columns you have 2 dimensions (branch index and list index), if each column you divide it in several subgroups, you have 3 dimensions, because to access some element you have to first know the column (first index of the branch), then know the subgroup (second index of the branch) and the position in that subgroup (list index).