biomod2 requires either presence / absence
data, or presence-only data supplemented with
pseudo-absences that can be generated with the
Pseudo-absences (sometimes also referred as background data) are NOT to be considered as absences, and rather represent the available environment in the studied area. They will be used to compare observed used environment (represented by the presences) against what is available.
Note that it is NOT recommended to mix both absence and pseudo-absences data.
3 different methods are implemented within
select pseudo-absences (PA) :
The selection of one or the other method will depend on a more important and underlying question : how were obtained the dataset presence points ?
The 3 methods proposed within
biomod2 do not depend on
the same assumptions :
|Realized niche fully sampled||no||yes||yes|
The random method is the one with the least assumptions, and should be the default choice when no sufficient information is available about the species ecology and/or the sampling design. The disk and SRE methods assume that the realized niche of the species has been fully sampled, either geographically or environmentally speaking.
Note that it is also possible for the user to select
by himself its own pseudo-absence points, and to give them to the
Barbet-Massin, M., Jiguet, F., Albert, C.H. and Thuiller, W. (2012), Selecting pseudo-absences for species distribution models: how, where and how many?. Methods in Ecology and Evolution, 3: 327-338. https://doi.org/10.1111/j.2041-210X.2011.00172.x
This paper tried to estimate the relative effect of method and number of PA on predictive accuracy of common modelling techniques, using :
Results were varying between modelling techniques :
biomod2 team advices :