This thesis brings together a series of studies, examining the role of non-native plants in the integration of non-native invertebrates in native food webs. I use data from comprehensive surveys of formally-planted gardens to investigate the efficacy of straightforward measures of non-native plant presence and/or landscape parameters, as reliable predictors of non-native invertebrate presence, finding that non-native invertebrate richness increases with non-native plant species richness, with invertebrates showing a clear preference for woody plants. I then use the context of metapopulation theory to explore the facilitative role of non-native plants in the ability of a non-native invertebrate to persist within a community, finding that where host-plant habitat patches are closer together, the likelihood of a patch being occupied is greater, especially if the patch is occupied but that this effect is not universal, with species-specific effects present also. I then explore the potential for apparent competition, in the form of negative indirect interactions between native and non-native plants mediated by a shared invertebrate enemy, with the indirect interactions biased by plant relatedness, finding that phylogenetically ranked pairwise native/non-native plant interactions are weakly correlated with observed shared invertebrate interactions, while a significant Mantel test result indicates a significant potential for apparent competition. Finally, I test for detectability of apparent competition in a gall wasp community, finding no evidence of apparent competition but potential evidence for the unexpected occurrence of apparent mutualism. Collectively, these findings provide original insight into how non-native plants and non-native invertebrates interact in an ecological community, and how these interactions help to structure the community. Additionally, they have implications for non-native invertebrate species management, from the practical application of ground-level planting decisions to the development of reliable predictive tools
