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Record W1861286914

Écologie de la mue chez la Grande Oie des neiges (Chen caerulescens atlantica)

2012· article· fr· W1861286914 on OpenAlexaboutno aff
Émilie Chalifour

Bibliographic record

VenueSémaphore (Université du Québec à Rimouski) · 2012
Typearticle
Languagefr
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
Fundersnot available
KeywordsForestryGeographyHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: Chez la Grande Oie des neiges, la majorité des adultes non-reproducteurs accomplit une migration de mue, au cours de laquelle ils migrent de leur aire de reproduction vers différentes régions de l'Arctique pour y muer. Les objectifs du projet étaient de décrire les patrons de migration de mue ainsi que les aires de mue, jusqu'à maintenant grandement méconnus. Le suivi de femelles adultes munies d'émetteur GPS/Argos nous a permis de localiser pour la première fois les aires de mue de Grandes Oies des neiges nonreproductrices dans l'Arctique canadien. Trente-sept sites de mue utilisés par 30 différentes femelles non-reproductrices ont été délimités. Nous avons observé que la Grande Oie semble accomplir une migration de mue vers le sud, découverte inusitée puisque ce comportement est contraire à celui généralement documenté chez les autres espèces d'oies en Amérique du Nord. Les aires de mue de la Grande Oie semblent chevaucher les aires de reproduction de la Petite Oie des neiges, ce qui était jusqu'à présent insoupçonné. Les zones identifiées pourraient représenter le principal point d'échange entre les deux sousespèces. Les principaux facteurs de sélection d'un habitat de mue sont J'abondance de nourriture et la proximité de plans d'eau. Lors de la mue, la perte simultanée des plumes de vol rend les oies plus vulnérables à la prédation et ces sites seraient de meilleure qualité en termes d'alimentation ou de refuges contre la prédation. Nous avons aussi trouvé des évidences qui indiquent qu'il y a un processus de sélection hiérarchique de l'habitat de mue. De plus amples recherches pourraient permettre de valider les résultats de cette étude et mener à une meilleure compréhension des impacts locaux et des processus de sélection à plus fine échelle.
\nGlobalement, notre étude pourra contribuer à une meilleure gestion et conservation de cette espèce ainsi que des aires qu'elle utilise dans le Grand Nord. --ABSTRACT: Most non-breeding Greater Snow geese (GSG; Chen caerulescens atlantica) undergo a molt migration, in which they migrate from breeding grounds to different regions of the Arctic to molt. This project aimed to describe molt migration patterns and molting sites, yet poorly known. By a deployment of GPS/ Argos transmitters fitted to females, we were able to document for the first time location of non-breeding GSG molting sites in Canadian Arctic. Thirty-seven molting sites used by 30 different non-breeding females were delineated. We also observed that GSG seems to accomplish a southward molt migration, a surprising discovery because a northward molt migration is generally observed in others North American goose species. GSG molting sites also seemed to overlap sorne Lesser Snow geese (Chen caerulescens caerulescens) breeding and molting grounds, which was yet unsuspected. Identified overlapping zones could be the main exchange point between those two sub-species. Main factors of molting habitat selection by GSG were food abundance and proximity of water. During molting period, simultaneous loss of flight feathers renders geese more subject to predation and molting sites should offer high feeding oppOliunities and availability of predator-safe refuges. We also found sorne evidences of the hierarchical nature of the molting habitat selection process. Further investigations could bring support to our results and lead to a better understanding of local impacts and finescale selection process. Globally, our study might contribute to better management and conservation opportunities of this species and its habitat in the high Arctic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.009
GPT teacher head0.198
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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