BODY COMPOSITION, MOVEMENT PHENOLOGY AND HABITAT USE OF COMMON EIDER ALONG THE SOUTHERN NEW ENGLAND COAST
Notice bibliographique
Résumé
The nearshore and offshore waters of southern New England provide important winter habitat for many sea duck species including common eiders (Somateria mollissima). Sea ducks that inhabit these waters must contend with global climate change, disease, and anthropogenic disturbance including proposed offshore wind energy development; however, evaluating these potential impacts on sea ducks, in general, and eiders in particular is difficult because knowledge of their ecology during winter is limited. I conducted the first validation of a non-lethal method for estimating body composition (deuterium dilution) of eiders and then applied this method to assess changes in body composition throughout the winter of 2011-12. I constructed models using deuterium-estimated body water, structural measurements, body mass and sex that estimated wet lean mass with 2.0 % relative error, and fat mass with 20.2 % relative error. Both male and female eiders were heavier and had more fat in late winter compared to early winter, whereas wet lean mass remained constant for males and declined over time for females from early to late winter. Based on model accuracy, the deuterium dilution method provided a viable, non-lethal approach for estimating body composition of eider. Biologists interested in assessing the potential impacts of offshore wind energy development and exposure to diseases such as Wellfleet Bay Virus on body composition of eider could use the method to assess changes in body condition. In a complimentary second study, I used satellite telemetry to track the movements of 26 adult female common eiders from November 2011 to July 2013 to delineate the migratory phenology, home ranges, habitat use and site fidelity of eiders that were initially captured during early-winter in southern New England. Eiders exhibited high fidelity to the southern New England wintering area (19 of 23 birds returned to the same area between years), where birds spent approximately 38% of their annual cycle. Birds were relatively sedentary during winter with home ranges that tended to be smaller than other species of seaducks (x -50% kernel core use areas = 38.5 km2 and x -95% kernel utilization distributions = 199.3 km2). Satellite-tagged eiders wintering in southern New England migrated to 4 summer areas in Maine, USA, Nova Scotia, the St. Lawrence Estuary and the Gulf of St. Lawrence, Canada. During winter, eiders preferred shallow waters that were closer to shore, and that had relatively fine-sediment substrate and a higher probability of hard bottom. I used this information to develop a spatially-explicit model that predicted that approximately 13.1% of this 6,212 km2 study area had a medium-high to high relative probability of use by eiders, and identified relatively high-use areas. Managers and policy makers could use this information to evaluate certain siting scenarios for offshore wind energy development so that areas with a high probability of use by eiders are avoided, thus minimizing the chance of negative impacts on the species.
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 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) | 0,001 | 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 ».