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Breeding Bonobos for Diversity

With the continuous pressure on endangered mammal species, ex-situ breeding programmes are more often implemented as a last resort for conservation. Conservation programmes have to avoid inbreeding depression and irreversible adaptation to captivity that would hinder reintroduction of endangered species. Maintaining sufficient initial genetic diversity of the captive population can avoid these complications. Since the capacity to accommodate specimens is limited, maximising genetic diversity within small populations is thus essential. In this project we aim to compare the efficacy of a breeding strategy based on Optimal Contribution Breeding with the Mean Kinship Breeding strategy using computer modelling based on real captive populations. The merit of each strategy will be exemplified using the global bonobo (Pan paniscus) zoo population as a model for the simulation. The main goal of this project is to study whether using Optimal Contribution Breeding can maximise the capacity to maintain genetic diversity of endangered mammal species in captivity by using the bonobo captive population as a model species in these simulations. To achieve this we aim to: 1) Determine which diversity measures/scales are most informative in endangered animal populations in captivity; 2) Develop an algorithm to apply Optimal Contributions in practice that incorporates current progeny into the overall optimal contribution vector; 3) Compare current practices based on Mean Kinship breeding with the optimal contribution selection (OCS) algorithm developed by the diversity measures determined.
Date:1 Jan 2014  →  Today