I'm using one explanatory variable in a regression tree and in a linear regression. The tree finds a split (with variance reduction splitting rule), though R2 is pretty small (0.2). On the validation data the model is confirmed. On the other hand the linear regression shows no relation (not even with 2nd order polynomial reg): coef and R2 are almost 0s. (Outliers are handled by truncation.) How can you explain this? Can it be that the tree finds/creates a "non existing" pattern only because of the splitting rule?