Migratory shorebird adheres to Bergmann's Rule by responding to environmental conditions through the annual lifecycle
Bibliographic record
Abstract
The inverse relationship between body size and environmental temperature is a widespread ecogeographic pattern. However, the underlying forces that produce this pattern are unclear in many taxa. Expectations are particularly unclear for migratory species, as individuals may escape environmental extremes and reorient themselves along the environmental gradient. In addition, some aspects of body size are largely fixed while others are environmentally flexible and may vary seasonally. Here, we used a long‐term dataset that tracked multiple populations of the migratory piping plover Charadrius melodus across their breeding and non‐breeding ranges to investigate ecogeographic patterns of phenotypically flexible (body mass) and fixed (wing length) size traits in relation to latitude (Bergmann's Rule), environmental temperature (heat conservation hypothesis), and migratory distance. We found that body mass was correlated with both latitude and temperature across the breeding and non‐breeding ranges, which is consistent with predictions of Bergmann's Rule and heat conservation. However, wing length was correlated with latitude and temperature only on the breeding range. This discrepancy resulted from low migratory connectivity across seasons and the tendency for individuals with longer wings to migrate farther than those with shorter wings. Ultimately, these results suggest that wing length may be driven more by conditions experienced during the breeding season or tradeoffs related to migration, whereas body mass is modified by environmental conditions experienced throughout the annual lifecycle.
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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 | 0.002 |
| 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 | 0.001 | 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".