Disproportionate bill length dimorphism and niche differentiation in wintering western sandpipers (Calidris mauri)
Bibliographic record
Abstract
Western sandpipers ( Calidris mauri (Cabanis, 1857)) exhibit slight female-biased sexual size dimorphism (5%) but disproportionate bill length dimorphism (15.9%). We test two predictions of the niche differentiation hypothesis at two wintering sites in Mexico with uniform western sandpiper densities, and use sex ratio as an index of intersexual competition. First, to test whether bill length dimorphism is larger at sites where sex ratios are strongly male-biased, we develop a migrant-based null model to represent dimorphism (12%, based on the average of males and females) in the absence of competition. Relative to the null model, bill length dimorphism was significantly larger at the large site (Santa María: 13.4%) but not at the small site (Punta Banda: 12.7%). Second, we tested whether bill length dimorphism increases as sex ratio approaches 1:1. Although the sex-ratio difference between sites was only 5%, bill length dimorphism increased marginally in the predicted direction. Additional comparisons suggest a cline in bill length dimorphism that mirrors a latitudinal gradient in prey burial depth. While sexual size dimorphism in the western sandpiper likely derived from selection for different body size optima, intersexual competition for food on the wintering grounds appears to have promoted further divergence in bill length.
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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".