Prealternate molt intensity and timing in six Nearctic-Neotropical migratory warblers
Bibliographic record
Abstract
Molt is vital for maintaining year-round feather function yet is one of the least understood events in the annual cycle of migratory birds. In Nearctic-Neotropical migratory songbirds, prealternate molt has received far less study than prebasic molt because it typically occurs during the least studied period of the annual cycle: the stationary nonbreeding period. Improving our basic understanding of prealternate molt is fundamental for identifying how it interacts with other life history stages across the annual cycle. Here, we provide a detailed quantification of the timing and intensity of prealternate molt for six species of parulid warblers on their stationary nonbreeding grounds in Jamaica. We demonstrate that head and body feather molt is common for Northern Waterthrush (Parkesia noveboracensis), Black-and-white Warbler (Mniotilta varia), American Redstart (Setophaga ruticilla), Northern Parula (Setophaga americana), and Prairie Warbler (Setophaga discolor), and for most species increases in frequency and intensity later in the nonbreeding period. Black-and-white Warbler and American Redstart demonstrated age-specific differences in molt intensity, with greater molt intensity exhibited by first-cycle than definitive-cycle birds. In addition, we provide support for the occurrence of a prealternate molt in Ovenbirds (Seiurus aurocapilla). These findings advance our understanding of prealternate molt in the study species and can serve as a foundation for investigating the mechanisms that regulate prealternate molt and potential carry-over effects from the nonbreeding grounds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".