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Reproductive success is predicted by social dynamics and kinship in managed animal populations.
Newman, Saul J; Eyre, Simon; Kimble, Catherine H; Arcos-Burgos, Mauricio; Hogg, Carolyn; Easteal, Simon.
Afiliação
  • Newman SJ; John Curtin School of Medical Research, Australian National University, Acton, Australia.
  • Eyre S; Wellington Zoo, Wellington, New Zealand.
  • Kimble CH; Sedgwick County Zoo, Wichita, USA.
  • Arcos-Burgos M; John Curtin School of Medical Research, Australian National University, Acton, Australia.
  • Hogg C; Zoo and Aquarium Association Australasia, Sydney, Australia.
  • Easteal S; John Curtin School of Medical Research, Australian National University, Acton, Australia.
F1000Res ; 5: 870, 2016.
Article em En | MEDLINE | ID: mdl-27990255
Kin and group interactions are important determinants of reproductive success in many species. Their optimization could, therefore, potentially improve the productivity and breeding success of managed populations used for agricultural and conservation purposes. Here we demonstrate this potential using a novel approach to measure and predict the effect of kin and group dynamics on reproductive output in a well-known species, the meerkat Suricata suricatta. Variation in social dynamics predicts 30% of the individual variation in reproductive success of this species in managed populations, and accurately forecasts reproductive output at least two years into the future. Optimization of social dynamics in captive meerkat populations doubles their projected reproductive output. These results demonstrate the utility of a quantitative approach to breeding programs informed by social and kinship dynamics. They suggest that this approach has great potential for improvements in the management of social endangered and agricultural species.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article