Dr Daniel Leybourne BSc, PhD

Barley yellow dwarf virus (BYDV) is a devastating virus of cereal crops, causing barley yellow dwarf disease. This disease, vectored by aphids, can reduce crop yields by 20%. The bird cherry-oat aphid, Rhopalosiphum padi, is the principle UK vector of BYDV-PAV and the grain aphid, Sitobion avenae, is the principle UK vector of BYDV-MAV. Aphids can associate with a wide range of microbial endosymbionts that influence their behaviour and fitness. Despite their importance, little is known about how diversity in aphid populations, including endosymbiont associations, influences disease transmission. This limits the extent to which we can exploit these processes to sustainably manage disease infection. Our preliminary research suggests that diversity within aphid populations can influence disease transmission, but this requires further study and the drivers of this are unknown. Since aphids are clonal, and symbionts can be cured and re-infected, this is an ideal model system to study effects of host genetic and symbiont variation on disease transmission, and to identify the impacts of this on agriculture. Exploring this in more mechanistic detail at the molecular and organismal level is a core research interest of the team and is currently funded by the Royal Commission for the Exhibition of 1851.

Beyond individual interactions, larger scale interactions across landscapes also influence pest and disease dynamics. The landscape surrounding agricultural fields influences pest infestation and disease incidence, with diverse landscapes providing natural pest and disease suppression services. Our preliminary research suggests that the structure of the agricultural landscape also influences symbiont-pest interactions, specifically influencing diversity of endosymbionts (aphids) and microbiome diversity (beetles), but the drivers behind this are unknown. Identifying the causal mechanisms behind these dynamic symbiont-pest-landscape interactions, and determining the impact this has on pest and disease phenotype, will provide insights into the microbial processes that underpin pest and disease infection in agricultural systems and identify processes that could be exploited for sustainable agriculture.

The use of insecticides is unsustainable and increasingly challenging due to insecticide resistance in pest populations, driving the need for more sustainable management options. Pest genotypes that harbour specific phenotypic traits of agricultural importance (e.g., insecticide resistance) can also destabilise pest management plans. We therefore need to develop decision support systems that predict pest and disease outbreaks and the dispersal of important pest genotypes within agricultural fields. Spatial models can be used to support decision-making processes for more effective pest control. We have an increasingly active research interest in this area, and are currently exploring some preliminary vector and virus modelling projects with partners in Scotland.