In niche models, overfitting has been traditionally assessed by large difference between training and test AUC or other model performance metrics. Are there other methods to assess model overfitting than this? MORE IMPORTANTLY, how do you assess model overfitting if you do not partition data into independent training and test data? Recommendations and their implementation (preferably R scripts, compatible with BIOMOD2) would be greatly appreciated.

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