Stress during feather development predicts fitness potential
Notice bibliographique
Résumé
Summary Measures of the quality of an individual are important in the study of proximate and ultimate factors in biology. Records of developmental history are particularly desirable, as many phenotypical traits are influenced by conditions during growth. Conspicuous irregularities in feathers, known as fault bars, result from a variety of stresses that occur during feather growth. The frequency of fault bars was evaluated on primary and tail feathers (grown 1 year previously) of 1919 adult American kestrels from a breeding population in Canada (1990–97). Most (91·5%) birds exhibited some fault‐barring, although females had significantly more feathers with fault bars than males (17% vs. 14%, respectively). Body size, intensity of haematozoan infections and leucocyte differentials were all unrelated to fault bars; however, birds with many fault bars were in poor body condition during prelaying (males) and incubation (males and females). Individual kestrels tended to be consistent in the number of feathers with fault bars from year to year. The percentage of feathers with fault bars was not associated with the timing of arrival in spring or prey abundance per territory; however, birds of both sexes with many bars were less likely to breed. Birds paired non‐randomly, as mates tended to have a similar frequency of fault bars. Males and females with many bars had significantly later clutch initiation dates, but there were no negative consequences regarding clutch size or egg size. Female kestrels with many fault bars had lower survival probabilities. Both sexes were also less likely to be recaptured in years following initial banding if they had many bars, suggesting that they were more likely to emigrate from the study area temporarily. Fault bars on feathers appear to be indicative of an individual’s susceptibility to stress, and are useful in predicting components of fitness. The use of fault bars is a promising tool as they are easy to evaluate and can be assessed on live or dead birds, on moulted feathers and on individuals repeatedly over time.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».