Genetic variation and seasonal migratory connectivity in Wilson’s warblers (Wilsonia pusilla): species-level differences in nuclear DNA between western and eastern populations
Bibliographic record
Abstract
There is growing interest in understanding patterns of seasonal migratory connectivity between breeding and wintering sites, both because differences in migratory behaviour can be associated with population differentiation and because knowledge of migratory connectivity is essential for understanding the ecology, evolution and conservation of migratory species. We present the first broad survey of geographic variation in the nuclear genome of breeding and wintering Wilson's warblers (Wilsonia pusilla), which have previously served as a research system for the study of whether genetic markers and isotopes can reveal patterns of migratory connectivity. Using 153 samples surveyed at up to 257 variable amplified fragment length polymorphism markers, we show that Wilson's warblers consist of highly distinct western and eastern breeding groups, with all winter samples grouping with the western breeding group. Within the west, there is weak geographic differentiation, at a level insufficient for use in the assignment of wintering samples to specific areas. The distinctiveness of western and eastern genetic groups, with no known intermediates, strongly suggests that these two groups are cryptic species. Analysis of mitochondrial cytochrome b sequence variation shows that the estimated coalescence time between western and eastern clades is approximately 2.3 Ma, a surprisingly old time of divergence that is more typical of distinct species than of subspecies. Given their morphological similarity but strong genetic differences, western and eastern Wilson's warblers present a likely case of association between divergence in migratory behaviour and the process of speciation.
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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 | 0.000 | 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".