Widespread gene flow following range expansion in Anna's hummingbird
Bibliographic record
Abstract
Anthropogenic changes have altered the historical distributions of many North American taxa. As environments shift, ecological and evolutionary processes can combine in complex ways to either stimulate or inhibit range expansion. Here we examine the role of evolution in a rapid range expansion whose ecological context has been well-documented, Anna’s Hummingbird ( Calypte anna ). Previous work suggests that the C. anna range expansion is the result of an ecological release facilitated by human-mediated environmental changes, where access to new food sources have allowed further filling of the abiotic niche. We examine the role of gene flow and adaptation during range expansion from their native California north into Canada and east into New Mexico and Texas, USA. Using low coverage whole genome sequencing we found high genetic diversity, low divergence, and little evidence of selection on the northern and eastern expansion fronts. Additionally, there are few (if any) limits to gene flow across the native and expanded range. The lack of selective signals between core and expanded ranges could reflect i) an absence of novel selection pressure in the extended range (supporting the ecological release hypothesis), ii) swamping of adaptive variation due to high gene flow, or iii) limitations of genome scans for detecting small shifts in allele frequencies across many loci. Nevertheless, our results provide an example where strong selection is not apparent during a rapid, contemporary range shift.
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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".