A major limitation for site ranking algorithms in conservation planning is lack of biodiversity data. Measurements such as vegetation communities or occurrences of a single well-inventoried taxon often act as surrogates in those cases.
This study presents a novel ranking alternative based on predicting the rarity-weighted richness using environmental data combined with species occurrences from a subset of sites in a given planning area.
The researchers applied the method to six different areas and tested the ability of the model to prioritize sites for species representation, and with just ten per cent of sites used in the model, the method performed significantly better than a random selection of sites. In one case based on birds in Spain, having just five per cent of sites inventoried, yielded a result 60 per cent as efficient as having all sites inventoried.
The suggested method can be a useful surrogate for prioritizing sites when just a small fraction of the landscape is inventoried.