Neutral markers reveal complex population structure across the range of a widespread songbird
Bibliographic record
Abstract
Abstract Understanding how both contemporary and historical physical barriers influence gene flow is key to reconstructing evolutionary histories and can allow us to predict species' resilience to changing environmental conditions. During the last glacial maximum (LGM), many high latitude North American bird species were forced into glacial refugia, including mountain bluebirds (Silia currucoides). Within their current breeding range, mountain bluebirds still experience a wide variety of environmental conditions and barriers that may disrupt gene flow and isolate populations. Using single nucleotide polymorphisms (SNPs) obtained through restriction site‐associated DNA sequencing, we detected at least four genetically distinct mountain bluebird populations. Based on this structure, we determined that isolation‐by‐distance, the northern Rocky Mountains, and discontinuous habitat are responsible for the low connectivity and the overall history of each population going back to the last glacial maximum. Finally, we identified five candidate genes under balancing selection and three loci under diversifying selection. This study provides the first look at connectivity and gene flow across the range of these high‐altitude and high latitude songbirds.
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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) | 0.001 | 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".