Phenotypic divergence in two sibling species of shorebird: Common Snipe and Wilson’s Snipe (Charadriiformes: Scolopacidae)
Bibliographic record
Abstract
Natural and social selection are among the main shapers of biological diversity but their relative importance in divergence remains understudied. Additionally, although neutral evolutionary processes may promote phenotypic divergence, their potential contribution in speciation is often overlooked in studies of comparative morphology. In this study, we investigated phenotypic differentiation in two allopatric shorebirds: the Palaearctic Common Snipe Gallinago gallinago and the Nearctic Wilson's Snipe Gallinago delicata. Specimens of Common Snipe (n = 355 skins, n = 163 skeletons) and Wilson's Snipe (n = 403 skins, n = 141 skeletons) in natural history collections were examined to quantify differences in skeletal and external measurements, and measures of wing and tail plumage variables. The species do not differ in skeletal variables except for the relatively larger sternum of the Common Snipe. The two species do not differ in multivariate wing size or shape (pointedness). Previously known plumage differences between these species were confirmed: the Common Snipe has fewer rectrices, longer and wider outermost rectrices, more extensive white on tips of the secondary feathers, and more white in the axillaries. Between‐species variance in skeleton, primary length and plumage variables was greater than expected if drift was mainly responsible for phenotypic divergence, suggesting a role of selective processes. However, drift could not be rejected after adjusting for multiple comparisons. Differences in plumage traits were greater than in skeletal or external measurements. Because snipe use plumage traits in signalling, the results suggest a more rapid divergence in socially selected traits between these species than in traits related to resource use.
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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".