Differential Introgression Between the Northern and Southern Extents of the Lodgepole x Jack Pine Hybrid Zone Suggests Environmentally-driven Selection and Local Adaptation.
Bibliographic record
Abstract
Hybrid zones provide a unique opportunity to study evolutionary consequences and selective pressures maintaining species boundaries in the hybridizing species.Lodgepole and jack pine are two native-Canadian species that form a mosaic hybrid zone in western Canada.Introgression occurs between lodgepole and jack pine through this hybrid zone by repeated backcrossing with advanced generation hybrid progeny.Using environmentally associated SNPs identified by redundancy analyses, we examined patterns of introgression between the northern and southern extents of this hybrid zone to identify differential introgression.Through genomic cline analyses, we found significant introgression of these SNPs across the hybrid zone.Twenty-eight SNPs had significantly different patterns of introgression between the northern and southern extents.Fine-scale patterns revealed several SNPs that were introgressing more frequently than expected, suggesting adaptive introgression.We found that patterns of adaptive introgression are occurring more frequently in the northern extent compared to the southern extent, suggesting different environmental pressures.The genetic variation observed between the two hybrid extents has implications in climate change considerations as it may result the two regions responding differently to changing environmental conditions.Using gene annotations and major allele frequency maps, we identified evidence of differing environmental pressures resulting in putative local adaptation within this hybrid zone.Sharing adaptations through this hybrid zone could be an important resource of adaptive potential in these pines species as climate change continues to disrupt forest ecosystems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".