Disentangling higher trophic level interactions in the cabbage aphid food web using high-throughput DNA sequencing
The lack of understanding of complex food-web interactions has been a major gap in the history of biological control. In particular, a better understanding of the functioning of pest food-webs and how they vary between native and invaded geographical ranges is of prime interest for biological control research and associated integrated pest management. Technical limitations associated with the deciphering of complex food-webs can now be largely overcome by the use of high throughput DNA sequencing techniques such as Illumina MiSeq. We tested the efficiency of this next generation sequencing technology in a metabarcoding approach, to study aphid food-webs using the cabbage aphid as model. We compared the variations in structure and composition of aphid food-webs in the species’ native range (United Kingdom, UK) and in an invaded range (New Zealand, NZ). We showed that Illumina MiSeq is a well suited technology to study complex aphid food-webs from aphid mummies. We found an unexpectedly high top down pressure in the NZ cabbage aphid food-web, which coupled to a large ratio of consumer species / prey species and a lack of potential inter-specific competition between primary parasitoids, could cause the NZ food-web to be more vulnerable than the UK one. This study also reports for the first time the occurrence of a new hyperparasitoid species in NZ, as well as new associations between hyperparasitoids parasitoids and the cabbage aphid in this country. We conclude that the complexity of aphid food-webs in agricultural systems could often be underestimated, particularly at higher trophic levels; and that the use of high throughput DNA sequencing tools, could largely help to overcome this impediment.... [Show full abstract]
Keywordsmetabarcoding; biological control; enemy release hypothesis; hyperparasitism; parasitoids; hyperparasitoids; competition
Fields of Research100202 Biological Control; 070708 Veterinary Parasitology; 060307 Host-Parasite Interactions; 070301 Agro-ecosystem Function and Prediction
© Lefort M et al.