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

Saul J Newman,Mauricio Arcos-Burgos,Catherine H Kimble,Carolyn Hogg,Simon Easteal,Simon Eyre

doi:10.12688/f1000research.8713.1

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.

Highlights

The growing global crisis in biodiversity has caused the survival of endangered species to become increasingly dependent on managed breeding programs
Similar pressures to increase reproductive success in managed social species exist in agriculture, where the maximization of reproductive output is often synonymous with increasing yield
We developed a combined genetic/packing algorithm that optimizes social group structure to increase the reproductive success of the meerkat populations under realistic constraints (Figure S4)

Summary

Introduction

The growing global crisis in biodiversity has caused the survival of endangered species to become increasingly dependent on managed breeding programs. These are generally designed to maximize reproductive success[1,2], but they sometimes fail to increase or even maintain population sizes[1]. It may be possible to improve the success of conservation and agricultural breeding programs involving social species by optimizing kin and group interactions We investigate this possibility using kin and group interactions inferred from detailed longitudinal records of kinship, migration between institutions and reproduction records maintained by zoological institutions. We apply novel methods to predict reproductive success in populations of the highly social meerkat, Suricata suricatta, from observed variation in age, sex, relatedness and social group structure

Methods

Results

Conclusion