Gene Flow and Abundance of a Tropical Fruit Fly in a Horticultural Landscape Mosaic in Eastern Australia Is Limited by Cleared Grazing Land and Area-Wide Management

Abstract

Landscape ecology and genetics provide important analytical frameworks for investigating the effect of environmental features on ecological processes. Few empirical studies, however, have simultaneously tested how landscape characteristics influence spatial patterns of gene flow and abundance of pest insects in heterogeneous environments. To address this, we undertook a combined landscape-ecology/landscape-genetic study of the tephritid fruit fly, Bactrocera tryoni , in the Wide Bay-Burnett region of Southeast Queensland, Australia. This region contains areas of rainforest, Eucalyptus forest, cleared pasture, residential areas, and two areas of intensive horticulture production; one implementing area-wide management practices. We collected B. tryoni samples from 26 sites in 2021 during the months of April, August, October, December and the following year during February and April. We used high-density DArTseq SNP genotyping on samples collected during the 2021 April, August and December sampling periods. We then modelled the contemporary landscape characteristics and management factors influencing gene flow and abundance of this pest species. Genome-wide SNP analysis estimated infinite effective population sizes at all sites and detected limited genetic structure across the landscape. However, fly abundance varied significantly among habitats, with cleared pasture negatively associated with population abundance and acting as a barrier to gene flow. Additionally, highways in composite with cleared pasture exhibited a very strong barrier effect. Abundance was highest in residential areas and rainforest, lowest in Eucalyptus forest, and reduced in the horticultural region with area-wide management implemented. We discuss the benefits of collecting simultaneous genetic and ecological datasets for informing and evaluating area-wide management programmes for insect pests and highlight considerations in the spatial analysis of SNP data when effective population sizes are extremely large.