Moult in the Loggerhead Shrike <i>Lanius ludovicianus</i> is influenced by sex, latitude and migration
Bibliographic record
Abstract
We investigated moult strategies in Loggerhead Shrikes by examining first prebasic or preformative moult patterns and by assessing the general location where individual feathers were grown using stable hydrogen isotope (δ2H) analysis. We tested the relative importance of factors known to impact moult timing and pattern, including age, sex, body size, food availability and migration. Migratory Shrikes showed evidence of suspended moult, in which feathers are moulted on both the breeding and the non‐breeding grounds with a suspension of moult during migration. Extent of moult was best explained by sex, longitude, migratory behaviour and breeding‐ground latitude. Male Hatch Year (HY) Shrikes replaced more feathers on the breeding grounds prior to migration than did HY females and moulted more extensively on the breeding grounds than did females. Non‐migratory HY Shrikes underwent a more extensive preformative moult than migratory HY Shrikes. Individuals in more southerly migratory populations moulted more extensively on the breeding grounds than did those breeding further north. Our data also indicate that individuals in the northeastern populations moulted more extensively on the breeding grounds than did those in the north and southwest. Our study underlines the complex structure and variation in moult possible within species, revealing surprising levels of differentiation between sexes and age cohorts, linked to environmental factors on the breeding grounds. Our study highlights the utility of an intrinsic marker, specifically δ2H analysis, to test hypotheses regarding the evolutionary and ecological forces driving moult. Although the methodology has not commonly been applied to this area of research, our results indicate that it can provide unprecedented insight into inter‐ and intra‐specific adaptive response to constraints, whereby individuals maximize fitness.
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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".