Extremely high gain with LightGBM
Its definitely not regularization since default values are 0 (check here)

n_estimators is the number of decision trees you take into bagging. These decision trees take random number of rows AND columns (again depending on the parameters) so it could be that you took some unfortunate combination which should level out with higher number of n_estimators. 

Suggestion: use different criteria for feat.importance for example Permutation importance, and then compare.

Final thought, hyperparams can be irrelevant. Have a look at the effect of parameters on certain tasks, with different algorithms. Conclusion: it can be an overkill (sometimes its important!)