Assessment of prey overlap between a native (Polistes humilis) and an introduced (Vespula germanica) social wasp using morphology and phylogenetic analyses of 16S rDNA

In newly invaded communities, interspecific competition is thought to play an important role in determining the success of the invader and its impact on the native community. In southern Australia, the native Polistes humilis was the predominant social wasp prior to the arrival of the exotic Vespula germanica (Hymenoptera: Vespidae). Both species forage for similar resources (water, pulp, carbohydrate and protein prey), and concerns have arisen about potential competition between them. The aim of this study was to identify the protein foods that these wasps feed on. As many prey items are masticated by these wasps to the degree that they cannot be identified using conventional means, morphological identification was complemented by sequencing fragments of the mitochondrial 16S rRNA gene. GenBank searches using blast and phylogenetic analyses were used to identify prey items to at least order level. The results were used to construct complete prey inventories for the two species. These indicate that while P. humilis is restricted to feeding on lepidopteran larvae, V. germanica collects a variety of prey of invertebrate and vertebrate origin. Calculated values of prey overlap between the two species are used to discuss the implications of V. germanica impacting on P. humilis. Results obtained are compared to those gained by solely 'conventional' methods, and the advantages of using DNA-based taxonomy in ecological studies are emphasized.

Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing

This paper describes the development of a model, based on Bayesian networks, to estimate the likelihood that sheep flocks are infested with lice at shearing and to assist farm managers or advisers to assess whether or not to apply a lousicide treatment. The risk of lice comes from three main sources: (i) lice may have been present at the previous shearing and not eradicated; (ii) lice may have been introduced with purchased sheep; and (iii) lice may have entered with strays. A Bayesian network is used to assess the probability of each of these events independently and combine them for an overall assessment. Rubbing is a common indicator of lice but there are other causes too. If rubbing has been observed, an additional Bayesian network is used to assess the probability that lice are the cause. The presence or absence of rubbing and its possible cause are combined with these networks to improve the overall risk assessment.