When using GridSearchCV with regression tree how to interpret mean_test_score?
By default, GridSearchCV uses the score method of its estimator; see the last paragraph of the scoring parameter on the docs:

If None, the estimator’s score method is used.

And DecisionTreeRegressor.score (indeed, all/most regressors) uses R^2.

In response to your edit: you can specify scoring='neg_mean_squared_error'.  But note too that there's a linear relationship between MSE and R^2, so optimizing either of these are equivalent.