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Record W2809232314

Facteurs environnementaux et sociaux influençant la gestion des réserves énergétiques chez le plectrophane des neiges (Plectrophenax nivalis) en hiver

2018· article· fr· W2809232314 on OpenAlexfundaboutno aff
Marie-Pier Laplante

Bibliographic record

VenueSémaphore (Université du Québec à Rimouski) · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsForestryHumanitiesPolitical scienceGeographyArt
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: Une des stratégies d'acclimatation hivernale adoptée par plusieurs passereaux résidents des régions nordiques est l'augmentation journalière et saisonnière des réserves lipidiques. En puisant dans les réserves accumulées pendant la journée, les oiseaux obtiennent l'énergie nécessaire pour survivre les nuits longues et froides et peuvent aussi subsister quand des tempêtes imprévisibles restreignent l'accès à la nourriture. La taille des réserves accumulées en hiver peut varier au sein d’une même espèce en fonction de plusieurs facteurs, principalement 1) les conditions météorologiques (court-terme), 2) les conditions climatiques (long-terme) et 3) le rang social des individus. Cependant, les connaissances sur comment ces trois facteurs peuvent interagir pour influencer la gestion des réserves énergétiques restent limitées. Nous avons utilisé un jeu de données à long-terme reécoltées dans plusieurs sites d'hivernage de l'est du Canada afin d'examiner la gestion des réserves énergétiques en fonction de l'interaction potentielle de facteurs environnementaux et sociaux chez le plectrophane des neiges. Nos résultats ont montré que les oiseaux font des ajustements précis de leurs réserves en fonction des conditions locales à court-terme, en s'engraissant d'avantage les journées où la météo est plus sévère. De plus, nos résultats montrent que les individus occupant les régions de leur aire d'hivernage présentant un climat (tendances historiques) plus froid et neigeux sont plus gras que ceux hivernant dans des régions plus clémentes. \nDeux mécanismes, mutuellement non-exclusifs, pourraient expliquer ces observations : (1) la présence chez l'espèce de flexibilité phénotypique à court-terme dans l'ajustement des réserves ainsi que (2) la sélection naturelle ayant favorisé l'engraissement chez les populations qui font face à un climat hivernal plus exigeant sur le plan énergétique. Finalement, notre étude a aussi montré que l'environnement social semble avoir un effet régulateur sur les stratégies de gestion des réserves chez l'espèce. Pour un site donneé, les femelles (sexe subordonné) avaient plus de réserves en moyenne que les mâles (sexe dominant) relativement à leur taille structurelle. Notre étude renseigne sur les mécanismes sous-jacents à l'engraissement des passereaux et offre des pistes de réflexion quant aux stratégies d'adaptation qui pourraient permettre au plectrophane des neiges de se maintenir face aux changements climatiques annoncés. -- Mot(s) clé(s) en français : écologie hivernale, écophysiologie des oiseaux, réserves énergétiques, acclimatation hivernale, engraissement hivernal, plectrophane des neiges. -- ABSTRACT: Many small songbirds increase lipid reserves during the wintering period. These reserves are accumulated during the day, acting as the principal source of energy to survive enforced fasting through the night, while also offering a safety margin against starvation in case finding food becomes difficult during the subsequent day(s). Within species, energy reserves are prone to vary with a range of factors, mainly 1) short-term (daily) changes in weather, 2) long-term (historic) climate conditions and 3) social rank of individuals. However, little is known regarding how these factors might interact to influence energy reserve management in passerine birds. Using a long-term (7 year) winter banding dataset from 7 locations across eastern Canada, we examined the relative role of environmental and social factors in influencing winter energy reserve management in the snow bunting (Plectrophenax nivalis). Our results indicate that birds respond to short-term changes in weather by making fine-tuned adjustments of the size of their energy reserves, in that they accumulate more fat on days where the weather is more severe (i.e. heavy snowfall, low temperature). Furthermore, mean energy reserves also increased as long-term trends in climate harshness at a given location increased. Together these results suggest that both short-term phenotypic flexibility in the management of energy reserves as well as selection for phenotypes with differential capacities for fattening across wintering sites are two non- mutually exclusive mechanisms that enable wintering buntings to respond to variation in climatic conditions. \nWe also found that for a given location, females (subordinate sex) consistently exhibited higher fat reserves than males (dominant sex) relative to their body size, potentially suggesting that social dominance may play an additional role in explaining variation in energy reserves in this species. Our findings are also an important first step in determining the adjustments that may allow this species to adapt to future climatic stressors, considering projected climate change in its wintering habitat. Globally, our study expands our knowledge on the winter ecology of the snow bunting and also provides information on the underlying mechanisms regulating fattening in small passerines. -- Mot(s) clé(s) en anglais : winter ecology, avian energetics, energy reserves, winter acclimatization, snow bunting, winter fattening.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.902

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.217
Teacher spread0.204 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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