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Project

Assessing the role of microbial volatiles in parasitoid-hyperparasitoid interactions and its implications for biological control of insect pests

Biological control exploiting natural enemies of insect pests (e.g. predatory insects and parasitoids) has become increasingly important in insect pest management. However, development and implementation of effective biological control strategies require a thorough understanding of the multi-trophic interactions between the different organisms involved. Since a few decades the study of trophic interactions has evolved from the mere description of the interactions to detailed investigations of the ecological factors that affect these interactions. In this regard, much attention has been given to the role of herbivore-induced plant volatiles (HIPVs) in the communication between plants, herbivores, natural enemies, and enemies of the natural enemies such as hyperparasitoids. In contrast, while microbes are virtually everywhere and have been shown to drive or modify ecological interactions among organisms, little attention has been given to the potential role of microbes and microbial volatile organic compounds (MVOCs) in affecting trophic interactions between insects. The major aim of this project is to test the hypothesis that microbes and MVOCs affect multi-trophic interactions between insect communities, and therefore play an important, but so far unrecognized role in biological control. To test this hypothesis, we will perform a multi-disciplinary project that combines meta-barcoding, microbial ecology, chemical ecology and state-of-the-art laboratory and field experiments.

Date:6 May 2019 →  6 May 2023
Keywords:Plant-insect-bacteria interaction, Chemical ecology, Biological pest control, Parassitoid, Hyperparassitoid, Microbial ecology, Microbial volatiles (mVOC)
Disciplines:Microbiology not elsewhere classified, Animal ecology, Invertebrate biology, Behavioural ecology, Chemical and physical ecology, Bacteriology, Microbiomes, Biological control, Analysis of next-generation sequence data
Project type:PhD project