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I'm trying to project an alien species distribution with Biomod2, algorithm GBM, random pseudo-absences in equal number to presences, background restricted to the zoogeographic realms in which the species is present. The species suitability is projected outside the currently known ranges and in climate change scenarios. To account for non-analog climates in the present and future I have built a clamping mask. The problem is: this mask overlaps with the background itself! Where the SDM training set was sampled. Shouldn't this be impossible? What do I miss? I'm sure that all presences are there and pseudo-absences are sufficient to cover the background. This is driving me crazy!

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Which predictors do you use? From what I understand of Biomod2 projections (see below), this mask is based on the future values of your explanatory variables, not on their current values. Therefore it makes sense that this mask can overlap with your study zone.

For instance, if the current average temperature of your study zone is between 10°C and 13°C, and the projected average temperature of your study zone is between 11°C and 14°C, all areas of your study zone with a projected average temperature higher than 13 degrees will be overlapped by the clamping mask.

If build.clamping.mask is set to TRUE a file (same type than new.env arg) will be saved in your projection folder. This mask will identifies locations where predictions are uncertain because the values of the variables are outside the range used for calibrating the models. The ‘build.clamping.mask’ values correspond to the number of variables that are out of their calibrating/training range.

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