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Reproductive success is predicted by social dynamics and kinship in managed animal populations.

ABSTRACT: 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.

SUBMITTER: Newman SJ

PROVIDER: S-EPMC5155502 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Reproductive success is predicted by social dynamics and kinship in managed animal populations.

Newman Saul J SJ Eyre Simon S Kimble Catherine H CH Arcos-Burgos Mauricio M Hogg Carolyn C Easteal Simon S

F1000Research 20160511

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 <i>Suricata suricatta</i>. Variation in social dynamics pred ...[more]

PMID: 27990255

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Project description:BackgroundStudies of natural animal populations reveal widespread evidence for the diffusion of novel behaviour patterns, and for intra- and inter-population variation in behaviour. However, claims that these are manifestations of animal 'culture' remain controversial because alternative explanations to social learning remain difficult to refute. This inability to identify social learning in social settings has also contributed to the failure to test evolutionary hypotheses concerning the social learning strategies that animals deploy.Methodology/principal findingsWe present a solution to this problem, in the form of a new means of identifying social learning in animal populations. The method is based on the well-established premise of social learning research, that--when ecological and genetic differences are accounted for--social learning will generate greater homogeneity in behaviour between animals than expected in its absence. Our procedure compares the observed level of homogeneity to a sampling distribution generated utilizing randomization and other procedures, allowing claims of social learning to be evaluated according to consensual standards. We illustrate the method on data from groups of monkeys provided with novel two-option extractive foraging tasks, demonstrating that social learning can indeed be distinguished from unlearned processes and a social learning, and revealing that the monkeys only employed social learning for the more difficult tasks. The method is further validated against published datasets and through simulation, and exhibits higher statistical power than conventional inferential statistics.Conclusions/significanceThe method is potentially a significant technological development, which could prove of considerable value in assessing the validity of claims for culturally transmitted behaviour in animal groups. It will also be of value in enabling investigation of the social learning strategies deployed in captive and natural animal populations.

Dataset Information

Reproductive success is predicted by social dynamics and kinship in managed animal populations.

Publications

Reproductive success is predicted by social dynamics and kinship in managed animal populations.

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