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Integrating population genetics in an adaptive management framework to inform management strategies

Pacioni, C., Trocini, S., Wayne, A.F., Rafferty, C. and Page, M. (2019) Integrating population genetics in an adaptive management framework to inform management strategies. Biodiversity and Conservation, 29 . pp. 947-966.

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Adequate levels of genetic diversity are important for long term persistence of wildlife species, yet genetic principles have only been considered in the last few years when developing management plans for conservation purposes. We present here an example on how genetic management plans can be explicitly integrated into an adaptive management framework. This can be achieved by developing a predictive model to explore population responses to different management options, and by quantifying management targets that should be verified through monitoring programs. We apply this approach to the woylie or brush tailed bettong (Bettongia penicillata); an Australian macropod, listed as Critically Endangered. Results suggest that discrete small populations (e.g. < 1000–3000 individuals) will require active management. Ongoing supplementation programs were the most promising management option. However, the translocation of a 1–4/year woylies would not improve the genetic profile of relatively small populations (< 1000 individuals). Overall, for supplementations to have a significant impact on genetic diversity, translocating > 30 woylies/year over the course of several years is recommended. Formal completion of the adaptive management approach would include, in addition to the stages presented here, a quantitative assessment of the outcome of management and continue refinement of the modelling framework on the basis of new data gained through ongoing monitoring. We encourage the formal inclusion of genetic management within the adaptive management framework as demonstrated in this study.

Item Type: Journal Article
Murdoch Affiliation(s): School of Veterinary and Life Sciences
Publisher: Springer Netherlands
Copyright: © 2019 Springer Nature B.V.
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