Investigation of causes and effects of predation by herring (Larus argentatus) and great black-backed gulls (L. marinus) on black-legged kittiwakes (Rissa tridactyla) on Gull Island, Newfoundland
Notice bibliographique
Résumé
In previous studies it has been observed that herring gulls (Larus argentatus) and great black-backed gulls (L. marinus) depredated breeding black-legged kittiwakes (Rissa tridactyla) that nest along the southeastern coast of Newfoundland, Canada. However, the causes and effects of large gull predation on kittiwakes was never extensively investigated nor quantified. In this study, herring gull and great black-backed gull predation on black-legged kittiwakes at Gull Island, southeastern Newfoundland was quantified at four study plots in relation to the timing of the annual spawning arrival of capelin (Mallotus villosus), the size of kittiwake sub-colonies (number of nests), kittiwake nest-site characteristics, and wind conditions. I also investigated the impact of large gull predation on kittiwake breeding performance during 1998 and 1999. -- I compared large gulls' predation attempt frequency among three periods: before mean gull hatching, between mean gull hatching and the arrival of capelin, and following capelin arrival. In both years, the frequency of gull predation attempts on kittiwakes differed significantly among the three periods, with highest levels of predation occurring after gull chicks hatched but before capelin arrival. Overall gull predation attempt levels were lower in 1999, when capelin spawned earlier, than in 1998. -- Nesting density and the location on the cliff were kittiwake nest-site characteristics that affected significantly the risk of predation. Breeding success (number of successful nests) was influenced by nesting density and ledge width. Additionally, I found that both risk of predation and breeding success varied significantly among plots. Individual kittiwake nests at the smallest plot experienced a higher probability of attack by large gulls than nests at larger plots. Hence, the percentage of failed nests was highest at the smallest plot and decreased as the size of the plots increased. Regardless of wind conditions both gull species attacked nest sites located on upper parts to a higher likelihood than sites located on middle and lower parts of the cliffs. However, during calm conditions, roofs over nest sites reduced the risk of predation by herring gulls, whereas sites located on narrow ledges were less likely to be attacked by great black-backed gulls. During windy conditions, nesting density affected which sites were attacked by great black-backed gulls. -- The level of gull predation behaviour was significantly correlated with the percentage of kittiwake eggs and chicks that disappeared within a week. I estimated that 43% of kittiwake eggs and chicks at Gull Island were taken by gulls in 1998 and 30% in 1999. My results demonstrated that kittiwakes have been indirectly (through increased predation by gulls) affected by the delayed arrival and lower abundance of capelin, and that kittiwake nest-site characteristics, and the size of a sub-colony were significantly correlated with the risk of depredation.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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) | 0,000 | 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 source (Gemma direct ou Codex distillé), 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 ».