Geographical surrogates of genetic variation for selecting island populations for conservation
Threatened species often exist in small numbers in isolated populations. Limited financial resources usually constrain conservationists to allocate funds to a subset of these populations. Because obtaining information required to maximize the amount of genetic and phenotypic variation protected can be costly and time-consuming, the utility of surrogates should be explored. This study tests the efficacy of three simple and cost-effective geographical measures in capturing genetic and phenotypic variation in fragmented populations when setting conservation priorities.
We used neutral genetic data (mtDNA and microsatellites) and morphometric data (a proxy for functional variation) for two bird species displaying different patterns of regional population genetic structure: Zosterops flavifrons and Zosterops lateralis. We tested the performance of three geographical surrogates (maximizing: geographical distance between islands; area of islands; geographical representation of islands), in representing divergence between and diversity within populations, constrained to the number of islands being protected.
Maximizing geographical separation of sites provided the best surrogate for a constrained budget (< 50% of the populations) for both species. For a larger protected area system (> 50% of the populations), the spatially most representative sites were often more effective. Selecting islands based on size retained about half of within-population genetic diversity; however, this was not much higher than selecting the islands randomly.
The ability of surrogates to capture genetic or phenotypic variation varied depending on the species, genetic markers and number of islands selected. While imperfect, selection of populations based on simple geographical surrogates for genetic and phenotypic variation will generally be better than random selection for conserving the evolutionary potential of threatened populations when time and money limit a more thorough and direct analyses of genetic and phenotypic variation.