Replicated hybrid zones reveal genomic patterns of local adaptation and introgression in spruce
Bibliographic record
Abstract
Hybridization between species can occur along repeated zones of contact, providing a natural laboratory for studying the interplay between migration and selection, and identifying loci involved in adaptation and reproductive isolation. However, interpreting how evolutionary processes shape genomic patterns can be challenging: repeatability of genotype-environment association alone is not strong evidence for selection, as hybrid zones derived from the same parental species are not evolutionarily independent. Conversely, processes that operate within the middle of each hybrid zone, such as selection driving directional introgression, may be more evolutionarily independent, and therefore provide stronger evidence of selection. Here we compared hybridization and local adaptation patterns between two replicated regions within the western Canada interior spruce hybrid zone: a broad latitudinal transect with gradual environmental variation and a narrow elevational transect with substantial topographical and environmental variation. We discovered a complex pattern of introgression, with strong differences in ancestry maintained even across small spatial scales at several locations along the elevational transect. Despite differences in their spatial scales, the elevational and latitudinal transects revealed strikingly similar genome-wide patterns of differentiation and adaptation, and consistent patterns of directional introgression. We explore the extent to which the evolutionary non-independence of these hybrid zones allows inferences about the role of natural selection and drift in shaping these patterns. Consistent with theory, we found longer genomic tracts in the elevational transect, likely because the steeper environmental gradients over shorter distances limit the rate of mixing by migration and recombination relative to drift and selection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".