Biodiversity Data Use

Models are built using a specific set of occurrence data and environmental data and we do not know how our model will behave in new environments. Transferring a model across space and/or time may lead to extrapolation if the projected environments are novel relative to training environments. Model algorithms have three strategies for dealing with extrapolation of response curves into environmental conditions different than those existing in the region of model calibration, they can:

Truncate - designate all conditions outside of the calibration data range as unsuitable and thus not project beyond the training region Clamp - use the marginal values in the calibration area as the prediction for more extreme conditions in transfer areas thus potentially under predicting the full extent of the projected niche Extrapolate - extend the response curve based on trends obtained from calibration conditions or assumptions about the niche

It is left to the user whether they want their model to clamp or not.