Applying genomics to metapopulation management in North American insurance populations of southern sable antelope (Hippotragus niger niger) and addra gazelle (Nanger dama ruficollis)

Abstract

Insurance populations can provide a short-term safeguard for at-risk species. The goal for all insurance populations should be to maintain a high welfare, genetically diverse, self-sustaining population that is available for eventual reintroduction of animals back into the wild when it is safe to do so. However, many insurance populations in zoos are not meeting sustainability goals, and there is a need for larger conservation centers and sanctuaries, a greater focus on threatened species, and metapopulation management between independently managed populations. Within North America, privately-owned ranches frequently maintain large populations of threatened ungulates that are presently managed independently from AZA-accredited zoos. Using a large set of single nucleotide polymorphisms, we generated empirical kinship and genetic distance estimates for AZA and private ranch populations of southern sable antelope (Hippotragus niger niger) and critically endangered addra gazelle (Nanger dama ruficollis). We used stochastic population models to project population mean kinship (mk) and founder genome equivalents (FGE) over time with and without genetic metapopulation management, using empirical kinships and genetic distances to guide transfers. Mean kinship-guided transfers were consistently beneficial for all study populations, for both species. Genetic distance-guided transfers, however, resulted in modest population mk increases for AZA populations, but predicted remarkable decreases in population mk for ranch populations. Although predicted benefits varied depending on management approach, our results show that a metapopulation management plan, whether mutually beneficial or altruistic, best supports species conservation by mitigating the loss of genetic diversity, minimizing the possibility of inbreeding, and yielding genetically diverse animals.

Keywords

• Metapopulation management
• Kinship
• Genetic distance
• Conservation genetics
• Population modelling
• Insurance populations