Print PageEvolutionary theory indicates that population genetic diversity is an important predictor of extinction risk, especially when environments change rapidly. Data from laboratory studies have revealed a strong, negative effect of modest losses of genetic diversity on long-term population survival in degraded environments. However these minor losses of genetic diversity may have little detectable effect on extinction risk in more benign environments. It is important to understand the power of measurable genetic diversity and genome x environment interactions when managing at-risk species. This is especially true when translocations are required to supplement small populations or to restore species to historical habitats from which they have been lost. The western pond turtle (Emys marmorata) is one example of a species which has been lost from much of its range, especially in heavily urbanized Southern California. Genetic analyses may provide a powerful set of tools for designing an evolutionarily informed restoration strategy in this and other at-risk species.
Results/Conclusions
Management strategies using genetic data may be key to the successful restoration of Emys marmorata and other at-risk species with four important caveats. First, laboratory studies suggest that existing molecular tools may lack the power to detect ecologically important losses of genetic diversity – however detectable losses of genetic diversity are likely to be ecologically important. Second, evaluations of genetic health based on data from populations in ideal environments may underestimate extinction risk in even slightly degraded environments. Third, genetic rescue programs may be able to increase population fitness in ideal environments but may not raise levels of genetic diversity to levels necessary for long-term population (or species) survival where degrading environments present new evolutionary challenges. Fourth, local adaptation may complicate restoration efforts and lead to outbreeding depression when incompatible populations are combined. Genome scans and landscape genomics methods may overcome this last challenge
