How to further Interpret Variable Importance?
The documentation offers a couple options. To plot the individual trees in your forest, one can access them like model.estimators_[n].tree_ and then plot them with export_graphviz as explained in the documentation, or you can follow this example that directly prints the structure in text format.

However, I would say this is not the best idea, because a feature can occur in different trees and nodes with different split points. You probably get a better intuition about your features from partial dependence plots that try to isolate the effect of one variable on your response variable.

As a bonus, here is a good article about more alternatives to gain insight into your model (not all applicable to random forests).