resample() vs. aggregate() in function create_species_priority_regions

[Turdus]

Is there a special reason, why we use resample() instead of aggregate() to change the resolution of the resulting raster?

resample() uses bilinear interpolation, which is in my opinion not totally appropriate here. aggregate() offers the possibility to use different functions to calculate the new cell values.

The resulting rasters do not only differ in cell values but also in the number of assigned cells (NA vs. values; visible discrepancy for 7 km resolution).

L. 133 of /R/site_suitability.R:
species_priority <- resample(species_priority, raster(ext=extent(species_priority), resolution=resolution))
why not
species_priority <- aggregate(species_priority, fact=7, fun=mean)?

I produced two example plots (Picea abies).
aggregate:

resample:

[KDolos]

there is no special reason. i used resample, because it worked.