Classification of samples to species and hybrid categories
The probability of assignment (Z ) of each sample as a pure Bruce spanworm, a pure winter moth, or a hybrid (either F1, F2, Bruce spanworm-backcross, or winter moth-backcross) was estimated using the Bayesian-assignment program NewHybrids v 1.1 b3 (Anderson, 2008; Anderson & Thompson, 2002). We used uniform priors, random starting seeds, burn-in periods of 100,000 generations, and a post-burn-in runtime of 1,000,000 generations. A separate dataset was run for each transect and year combination to reduce assignment errors, given that individuals from one year could be the offspring of individuals from the previous year. Datasets were then filtered so that only individuals with ≥ 10 successfully scored loci were included. Four independent runs were performed for each dataset, and the assignment scores were then averaged across runs. We interpreted samples withZ ≥ 0.75 to any one category as obtaining “strong support”, and samples with 0.5 ≤ Z < 0.75 as obtaining “moderate support”. If a sample was not assigned to any category with Z ≥ 0.5, it was classified as having “weak support” to the category with the highest Z score.
To determine whether there was temporal or spatial variation in hybridization rates across each transect, the mean proportions of hybrids were calculated by dividing the number of genotyped individuals from each trap classified to one of the four hybrid categories by NewHybrids (as described above). Differences between years and between traps were compared using an analysis of variance (ANOVA) as implemented in R v 4.0.2 (R Core Team, 2020).