Identifying Key Biodiversity Areas Based on Distinct Genetic Diversity

Key Biodiversity Areas (KBAs) are sites that contribute significantly to the global persistence of biodiversity. Distinct genetic diversity has been introduced as one of the metrics to estimate whether a site holds a threshold proportion of a species' global genetic diversity during the KBA identification process. However, genetic data has so far not been applied in KBA identification due to the lack of thoroughly tested methods and guidance. We tested the suitability of six analytical methods for identification of KBAs based upon genetic data: allelic overlap, Analyses of Molecular Variance (AMOVA), average taxonomic distinctness (AvTD, Δ⁺), effective population size (N_e), the genetic differentiation index (D_est), and the diversity index Simpson's λ. We conclude that Δ⁺, a measure that was developed to measure taxonomic distinctness of biotic communities, performs best in the context of KBA identification as it reflects the unique nature of a species' genetic diversity, is based on simple allele frequencies, and can be easily applied and calculated. AMOVA, N_e, allelic overlap, and our modified version of λ were difficult to apply, interpret, or both. D_est is easily applied for measuring genetic distinctiveness but not genetic diversity. For this reason, it may not be suitable for prioritising areas for the long-term protection of the species.