Data from: Host plant associations and geography interact to shape diversification in a specialist insect herbivore

Disentangling the processes underlying geographic and environmental
patterns of biodiversity challenges biologists as such patterns emerge
from eco-evolutionary processes confounded by spatial autocorrelation
among sample units. The herbivorous insect, Belonocnema treatae
(Hymenoptera: Cynipidae), exhibits regional specialization on three plant
species whose geographic distributions range from sympatry through
allopatry across the southern USA. Using range-wide sampling spanning the
geographic ranges of the three host plants and genotyping-by-sequencing of
1,217 individuals, we tested whether this insect herbivore exhibited
host-plant-associated genomic differentiation while controlling for
spatial autocorrelation among the 58 sample sites. Population genomic
structure based on 40,699 SNPs was evaluated using the hierarchical
Bayesian model ENTROPY to assign individuals to genetic clusters and
estimate admixture proportions. To control for spatial autocorrelation,
distance-based Moran’s eigenvector mapping was used to construct
regression variables summarizing spatial structure inherent among sample
sites. Distance based redundancy analysis (dbRDA) incorporating the
spatial variables was then applied to partition host-plant-associated
differentiation (HAD) from spatial autocorrelation. By combining ENTROPY
and dbRDA to analyze SNP data we unveiled a complex mosaic of highly
structured differentiation within and among gall former populations
finding evidence that geography, HAD and spatial autocorrelation all play
significant roles in explaining patterns of genomic differentiation in B.
treatae. While dbRDA confirmed host association as a significant predictor
of patterns of genomic variation, spatial autocorrelation among sites
explained the largest proportion of variation. Our results demonstrate the
value of combining dbRDA with hierarchical structural analyses to
partition spatial/environmental patterns of genomic variation.