aoa (Area of Applicability) measures whether the values of pixels in a SpatRaster object (x) with environmental layers used to train SDMs are within the range of variables contributed in the modelling.
aoa(x,d,vi=NULL)a SpatRaster object
a SpatRaster object with predictors used to train SDMs
a sdmdata or sdmModels object
optional; a numeric vector of variable importance values of the variables in x; vi should have the same length as the number of variables in x
Babak Naimi naimi.b@gmail.com
The output of this function is a raster with values ranging between 0 and 1 can be infered as the degree of similarity between values of the environmental variables at each pixel and training range. When the values of all variables in x are within the range used to train the models (training range), the output of aoa is 1. Less than 1 refers to degree of dissimilarity to the range (it may be the proportion of variables outside of the training range; smaller value is more dissimilar) .
The aoa function can be used when the predict or ensemble function is used to predict or project distribution in a new area or a new time (e.g., future) where it is likely to have pixels with values outside of the training range.
By using the variable importance, higher weights are given to more important variables to assess similarity.
Naimi, B., Araujo, M.B. (2016) sdm: a reproducible and extensible R platform for species distribution modelling, Ecography, DOI: 10.1111/ecog.01881