Population genetic inference of demographic processes in the African Wild Silk Moth, Gonometa postica (Lasiocampidae)

Abstract

The African Wild Silk moths (Gonometa spp., Lasiocampidae) are species that are presently of particular economic interest in southern Africa. Both Gonometa postica and G. rufobrunnea, two species of African Wild Silk moth native to southern Africa, have been shown to possess a silk fibre of exceptional quality. A small-scale cottage industry utilizing the silk of Gonometa species currently exists in southern Africa, yet a consistent complaint is the lack of supply of cocoons. The Gonometa species in southern Africa have been shown to exhibit large inter-annual population fluctuations. However, it is uncertain whether eruptions are only the result of local populations experiencing ideal conditions or whether current eruptions are initiated by dispersal of individuals from eruptive populations in previous generations. A second observation, regarding eruptions, is that they are patchily distributed at both the local (within outbreaks) and regional scale (across southern Africa). In this thesis I have studied population eruptions through distribution analysis of three years of presence/absence data, and through spatial and temporal population genetic analysis. The analysis of population genetic data allows the inference of population demographic parameters such as population size fluctuations and migrations. In particular, the use of microsatellite markers allows a high-resolution analysis of the connectivity of populations, and provides signal of population size fluctuations. I utilise both mitochondrial DNA control region sequences and polymorphic microsatellite loci to make inferences of population processes in G. postica, using a combination of both analytical and simulation model analysis approaches. The results, in general, indicate that dispersal of moths across South Africa is extensive. These results are further considered in light of the effects of population size fluctuations on spatial genetic pattern, where the potential exists for unstable population demography to influence the inference of dispersal from population genetic data. The population genetic analyses presented here allow the inference of the extent of a local population/outbreak, and the degree of movement between local populations. Given that a large-scale population dynamics project based on G. postica is currently under development, the results determine the geographical extent at which the population dynamics study should be conducted. Furthermore, the population genetics data generated will contribute to the construction of a population dynamics model, including abiotic and biotic variables, which will allow a better understanding of eruptions in this species.