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Keywords:

  • adaptation;
  • adaptive management;
  • effective population size;
  • experimental evolution;
  • genetic inference;
  • population structure;
  • theoretical modelling

Abstract

Conservation genetics can be seen as the effort to influence the evolutionary process in ways that enhance the persistence of populations. Much published research in the field applies genetic sampling techniques to infer population parameters from the patterns of variation in threatened populations. The limited resolution of these inferences seems to yield limited confidence which results in conservative policy recommendations. As an alternative, I suggest that conservation genetics focus on the relationships between those variables conservationists can control, and the probability of desirable evolutionary outcomes. This research would involve three phases – a greater use of existing evolutionary theory; testing management options using experimental evolution; and ‘field trials’ under an adaptive management framework. It would take a probabilistic approach that recognizes the stochasticity inherent in evolutionary change. This would allow a more nuanced approach to conservation policy than rule of thumb guidelines. Moreover, it would capitalize on the fact that evolution is a unifying theory in biology and draw on the substantial body of evolutionary knowledge that has been built up over the last half a century.