I'm confused.
It sounds like you saying that you don't want a given predictor to occur at different branching points. For example, you are trying to avoid a model where the first branching point could be a split between x<0 and x>=0, and then a later branching point further splits the x>=0 branch between x<15 and x>=15. Is that right?
I'm not an expert in the fitrensemble function, but I'm pretty sure that that has nothing to do with the resample/replace parameters you are setting. Resampling has to do with whether observations are resampled, not whether predictors are "re-used".
Or maybe I am just totally misunderstanding what you want.
