In this study, we wanted to know how geography and ecology predicted population genetic structure among 58 populations of the gall wasp Belonocnema treatae, which exhibits regional specialization on three host plant species across the U.S. Gulf Coast. We combined range-wide sampling with a genotype-by-sequencing approach for 40,699 SNPs across 1,217 individuals. Disentangling the processes underlying geographic and environmental patterns of biodiversity is challenging, as such patterns emerge from eco‐evolutionary processes confounded by spatial autocorrelation among sample units. We evaluated this question using a hierarchical Bayesian model (ENTROPY) to assign individuals to genetic clusters and estimate admixture proportions. Using distance-based Moran’s eigenvector mapping, we generated regression variables that represent varying degrees of spatial autocorrelation in genetic variation among sample sites. These spatial variables, along with host association, were incorporated in distance-based redundancy analysis (dbRDA) to partition the relative contributions of host plant and spatial autocorrelation. This novel approach of combining ENTROPY results with dbRDA to analyze SNP data unveiled a complex mosaic of diversification within and among insect populations forming discrete host associated lineages coupled with geographic variation. This demonstrates that geography and ecology play significant roles in explaining patterns of genomic variation in B. treatae – an emerging model of ecological speciation.
Full article: Driscoe AL, Nice CC, Busbee RW,Hood GR, Egan SP, Ott JR. Host plant associations and geography interact to shape diversification in a specialist insect herbivore. Mol Ecol. 2019;28:4197–4211. https://doi.org/10.1111/mec.15220