Distinct sources of gene flow produce contrasting population genetic dynamics at different range boundaries of a<i>Choristoneura</i>budworm
Bibliographic record
Abstract
Populations are often exposed to multiple sources of gene flow, but accounts are lacking of the population genetic dynamics that result from these interactions or their effects on local evolution. Using a genomic clines framework applied to 1,195 single nucleotide polymorphisms, we documented genomewide, locus-specific patterns of introgression between Choristoneura occidentalis biennis spruce budworms and two ecologically divergent relatives, C. o. occidentalis and Choristoneura fumiferana, that it interacts with at alternate boundaries of its range. We observe contrasting hybrid indexes between the two hybrid zones, no overlap in "gene-flow outliers" (clines showing relatively extreme extents or rates of locus-specific introgression) and variable linkage disequilibrium among those outliers. At the same time, correlated genomewide rates of introgression between zones suggest the presence of processes common to both boundaries. These findings highlight the contrasting population genetic dynamics that can occur at separate frontiers of a single population, while also suggesting that shared patterns may frequently accompany cases of divergence-with-gene-flow that involve a lineage in common. Our results point to potentially complex evolutionary outcomes for populations experiencing multiple sources of gene flow.
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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 | 0.001 | 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) | 0.000 | 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".