In conservation planning, several metrics can be used when seeking to identify how to cover the greatest number of species in the least number of sites. Widely used, species richness, however, appears to be one of the least effective.
This study assesses the performance of three rarity-based indices as new potential surrogates of biodiversity for solving the minimum-set coverage problem: rarity-weighted richness (RWR), index of summed rarity (ISR) and index of relative rarity (IRR). The authors tested the indices in 14 datasets—eight mediated by GBIF—spanning a broad range of taxa, spatial extent and resolution.
In all 14 datasets, rarity indices outperformed species richness and in some cases, also complementarity algorithms. The best performing index was RWR.
With few or no requirements for specialized software, computing power or programming skills, the proposed indices may represent a simple, yet reliable alternative to prohibitively long computation times of integer programming and heuristic algorithms in site prioritization for biodiversity conservation.