Altitudinal migration in American Dippers (Cinclus mexicanus): Do migrants produce higher quality offspring?
Bibliographic record
Abstract
Breeding at high elevations can favour life-history strategies in which parents shift to investing in higher quality rather than higher numbers of offspring. In American Dippers ( Cinclus mexicanus Swainson, 1827), altitudinal migrants produce fewer fledglings than sedentary individuals (residents) that breed at lower elevations. We examined whether migrants compensate for their lower fecundity by providing their offspring with a higher quality diet and (or) more food, and producing higher quality offspring. Nestling diet was assessed using observations and stable isotope analysis of feathers grown during the nestling period. Nestling quality was assessed using a condition index (residuals from a mass–tarsus regression) and postfledging survival. We found that migrants fed their offspring less fish, and despite having higher feeding rates, had lower energetic provisioning rates than residents. Migrants also produced offspring that were in worse condition and had lower postfledging survival. This study found no evidence that altitudinal migration is associated with a trade-off favouring the production of smaller numbers of higher quality young. Instead our data provide support for the hypothesis that altitudinal migration in American Dippers is an outcome of competition for limited nest sites at lower elevations that forces some individuals to move to higher elevations to breed.
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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".