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Detecting host–parasitoid interactions in an invasive Lepidopteran using nested tagging DNA metabarcoding
Author(s) -
Kitson James J. N.,
Hahn Christoph,
Sands Richard J.,
Straw Nigel A.,
Evans Darren M.,
Lunt David H.
Publication year - 2019
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.14518
Subject(s) - biology , parasitoid , dna barcoding , parasitism , biological pest control , ecology , host (biology) , larva , lepidoptera genitalia , zoology , evolutionary biology
Abstract Determining the host–parasitoid interactions and parasitism rates for invasive species entering novel environments is an important first step in assessing potential routes for biocontrol and integrated pest management. Conventional insect rearing techniques followed by taxonomic identification are widely used to obtain such data, but this can be time‐consuming and prone to biases. Here, we present a next‐generation sequencing approach for use in ecological studies which allows for individual‐level metadata tracking of large numbers of invertebrate samples through the use of hierarchically organised molecular identification tags. We demonstrate its utility using a sample data set examining both species identity and levels of parasitism in late larval stages of the oak processionary moth ( Thaumetopoea processionea— Linn. 1758), an invasive species recently established in the United Kingdom. Overall, we find that there are two main species exploiting the late larval stages of oak processionary moth in the United Kingdom with the main parasitoid ( Carcelia iliaca— Ratzeburg, 1840) parasitising 45.7% of caterpillars, while a rare secondary parasitoid ( Compsilura concinnata— Meigen, 1824) was also detected in 0.4% of caterpillars. Using this approach on all life stages of the oak processionary moth may demonstrate additional parasitoid diversity. We discuss the wider potential of nested tagging DNA metabarcoding for constructing large, highly resolved species interaction networks.