Mahalanobis scores for training data

Hi all. I have a series of distribution models with the mahalanobis 
distance implementation of dismo. I used the data.frame method because 
of the nature of data. However in order to run the proper diagnostic 
tests (not the traditional AUC) I need to calculate the distances of the 
training data. To date I've done this using the predict function as:

predict(model, data)

Bus this only gives scores of 1, which is incorrect given that all 
scores should normally go from 0 to -inf. I suppose that what the 
function is doing is identifying training data and returning 1 as 
closest to training data. But is there a way to compute the raw distances?

Regards

Gerardo