Artificial selection for nonreproductive host killing in a native parasitoid on the invasive pest, Drosophila suzukii

Establishment and spread of invasive species can be facilitated by lack of natural enemies in the invaded area. Host-range evolution of natural enemies augments their ability to reduce the impact of the invader and could enhance their value for biological control. We assessed the potential of the Drosophila parasitoid, Leptopilina heterotoma (Hymenoptera: Figitidae), to exploit the invasive pest Drosophila suzukii by focusing on three performance indices: (i) attack rate; (ii) host killing, consisting of killing rate and lethal attack rate (killing efficiency); and (iii) successful offspring development (reproductive success). We found significant intraspecific variation in attack rate and killing rate and lethal attack rate among seven European populations, but offspring generally failed to successfully develop from the D. suzukii host. We crossed these European lines to create a genetically variable source population and performed a half-sib analysis to quantify genetic variation. Using a Bayesian animal model, we found that attack rate and killing rate had a heritability of $$ , lethal attack rate $$ , and offspring development $$ . We then artificially selected wasps with the highest killing rate of D. suzukii for seven generations to test whether host-killing could be improved. There was a small and inconsistent response to selection in the three selection lines. Realized heritability ( $$ ) after four generations of selection was 0.17 but near zero after seven generations of selection. The genetic response might have been masked by an increased D. suzukii fitness resulting from adaptation to laboratory conditions. Our study reveals that native, European, L. heterotoma can attack the invasive pest, D. suzukii and significantly reduce fly survival and that different steps of the parasitization process need to be considered in the evolution of host-range. It highlights how evolutionary principles can be applied to optimize performance of native species for biological control.