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Manipulating sex ratio to increase population growth: the example of the Lesser Kestrel

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons56796

Lenz,  T. L.
Department Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Citation

Lenz, T. L., Jacob, A., & Wedekind, C. (2007). Manipulating sex ratio to increase population growth: the example of the Lesser Kestrel. Animal Conservation, 10(2), 236-244. doi:10.1111/j.1469-1795.2007.00099.x.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-D7B9-8
Abstract
Small or decreasing populations call for emergency actions like, for example, captive breeding programs. Such programs aim at rapidly increasing population sizes in order to reduce the loss of genetic variability and to avoid possible Allee effects. The Lesser Kestrel Falco naumanni is one of the species that is currently supported in several captive breeding programs at various locations. Here, we model the demographic and genetic consequences of potential management strategies that are based on offspring sex ratio manipulation. Increased population growth could be achieved by manipulating female conditions and/or male attractiveness in the captive breeders and consequently shifting the offspring sex ratio towards more female offspring, which are then used for reintroduction. Fragmenting populations into wild-breeding and captive-breeding demes and manipulating population sex ratio both immediately increase the inbreeding coefficient in the next generation (i.e. decrease N-e) but may, in the long term, reduce the loss of genetic variability if population growth is restricted by the number of females. We use the Lesser Kestrel and the wealth of information that is available on this species to predict the long-term consequences of various kinds of sex-ratio manipulation. We find that, in our example and possibly in many other cases, a sex-ratio manipulation that seems realistic could have a beneficial effect on the captive breeding program. However, the possible long-term costs and benefits of such measures need to be carefully optimized.