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Predictive genetic plan for a captive population of the Chinese goral (Naemorhedus griseus) and prescriptive action for ex situ and in situ conservation management in Thailand.

Kornsuang JangtarwanPeerapong KamsongkramNavapong SubpayakomSiwapech SillapaprayoonNarongrit MuangmaiAdisorn KongphoemphApinya WongsodchuenSanya IntapanWiyada ChamchumroonMongkol SafoowongSurin PeyachoknagulPrateep DuengkaeKornsorn Srikulnath
Published in: PloS one (2020)
Captive breeding programs for endangered species can increase population numbers for eventual reintroduction to the wild. Captive populations are typically small and isolated, which results in inbreeding and reduction of genetic variability, and may lead to an increased risk of extinction. The Omkoi Wildlife Breeding Center maintains the only Thai captive Chinese goral (Naemorhedus griseus) population, and has plans to reintroduce individuals into natural isolated populations. Genetic variability was assessed within the captive population using microsatellite data. Although no bottleneck was observed, genetic variability was low (allelic richness = 7.091 ± 0.756, He = 0.455 ± 0.219; He < Ho) and 11 microsatellite loci were informative that likely reflect inbreeding. Estimates of small effective population size and limited numbers of founders, combined with wild-born individuals within subpopulations, tend to cause reduction of genetic variability over time in captive programs. This leads to low reproductive fitness and limited ability to adapt to environmental change, thereby increasing the risk of extinction. Management of captive populations as evolutionarily significant units with diverse genetic backgrounds offers an effective strategy for population recovery. Relocation of individuals among subpopulations, or introduction of newly captured wild individuals into the captive program will help to ensure the future security of Chinese goral. Implications for future conservation actions for the species are discussed herein.
Keyphrases
  • genome wide
  • genetic diversity
  • public health
  • physical activity
  • cell proliferation
  • big data
  • deep learning
  • low birth weight
  • genome wide association study