CatBoost and hyperparameterisation

I'm an ecologist starting my first forays into machine learning. Specifically, I'm using CatBoost to predict presence/absence of a threatened species at discrete wetlands. You guys are the experts in this space, so I'm hoping you can help. Firstly, is hyperparameterisation conserved? So for example, if I'm using a grid search for tree depth using low iterations and higher learning rate, will the best tree depth also hold true at higher iterations and smaller learning rates in all cases? Secondly, …

catboost datascience example experts grid low machine machine learning search space species tree