Beneficial soil-borne microbes, such as mycorrhizal fungi or rhizobacteria, can affect the interactions of plants with aboveground insects at several trophic levels. While the mechanisms of interactions with herbivorous insects, that is, the second trophic level, are starting to be understood, it remains unknown how plants mediate the interactions between soil microbes and carnivorous insects, that is, the third trophic level. Using Arabidopsis thaliana Col-0 and the aphid Myzus persicae, we evaluate here the underlying mechanisms involved in the plant-mediated interaction between the non-pathogenic rhizobacterium Pseudomonas fluorescens and the parasitoid Diaeretiella rapae, by combining ecological, chemical and molecular approaches. Rhizobacterial colonization modifies the composition of the blend of herbivore-induced plant volatiles. The volatile blend from rhizobacteria-treated aphid-infested plants is less attractive to an aphid parasitoid, in terms of both olfactory preference behaviour and oviposition, than the volatile blend from aphid-infested plants without rhizobacteria. Importantly, the effect of rhizobacteria on both the emission of herbivore-induced volatiles and parasitoid response to aphid-infested plants is lost in an Arabidopsis mutant (aos/dde2-2) that is impaired in jasmonic acid production. By modifying the blend of herbivore-induced plant volatiles that depend on the jasmonic acid-signalling pathway, rootcolonizing microbes interfere with the attraction of parasitoids of leaf herbivores.

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Banana is an important crop in the Kagera region of Tanzania. Banana xanthomonas wilt (BXW) was first reported in Kagera in 2006, and is now an important limiting factor in banana production, because all cultivars are susceptible and infected plants can fail to produce fruit. BXW is caused by Xanthomonas campestris pv. musacearum (Xcm), which is spread by farm tools, infected planting materials, and pollinating insects. Practices that address Xcm dissemination, such as mat removal, debudding and tool sterilization, have not prevented the spread of BXW in the region. Disease surveys were conducted in Kagera from 2007 to 2011 to assess BXW presence, monitor its intensity and evaluate its socioeconomic impacts. Spatiotemporal clusters of BXW were analysed with ARCGIS and SAS. The relationship between BXW clusters and environmental variables was examined using bivariate correlations in SPSS; two modelling approaches, MaxEnt (maximum entropy) and logistic regression, were used to predict the potential distribution of BXW in Tanzania. Disease progress over time was best described with the Gompertz model. Significant clustering of BXW was observed in all years and hotspots were located in the Muleba, Karagwe, Misenyi and Bukoba rural districts. These findings suggest that BXW spreads rapidly over short distances. BXW clusters were positively correlated with rainfall and negatively with temperature and altitude. According to MaxEnt, precipitation was the main factor associated with BXW development. MaxEnt and logistic regression predicted a wide potential distribution of BXW in Tanzania because the climate in all banana-growing regions is conducive for its establishment.