MétaCan
Menu
Back to cohort
Record W2134868343 · doi:10.1098/rsbl.2008.0704

Costs of reproduction in a long-lived bird: large clutch size is associated with low survival in the presence of a highly virulent disease

2009· article· en· W2134868343 on OpenAlexafffund
Sébastien Descamps, H. Grant Gilchrist, Joël Bêty, E. Isabel Buttler, Mark R. Forbes

Bibliographic record

VenueBiology Letters · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsCarleton UniversityUniversité du Québec à RimouskiEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaArcticNet
KeywordsBiologyReproductionAvian clutch sizeVirulenceDiseaseEcologyClutchZoologyGeneticsInternal medicineGene

Abstract

fetched live from OpenAlex

Fitness costs of reproduction are expected to be more pronounced when the environmental conditions deteriorate. We took advantage of a natural experiment to investigate the costs of reproduction among common eiders (Somateria mollissima) nesting at a site in the Arctic, where an avian cholera epizootic appeared at different magnitudes. We tested the predictions that larger reproductive effort (clutch size) is associated with lower survival or breeding probability the following year, and that this relationship was more pronounced under heightened exposure to the disease. Our results indicate that large clutch sizes were associated with lower survival of female eider ducks, but only when there was heightened exposure to avian cholera, as indexed by eider mortality on site. No cost was observed when cholera was absent or when lesser exposure was evident. This supports the hypothesis that fitness costs of high reproductive effort are higher under unfavourable conditions such as a disease epizootic, and further indicates that being a conservative breeder can increase survival probability, given the presence of a highly virulent disease.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.237

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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 teacher head, 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".

Quick stats

Citations82
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueBiology LettersSame topicAnimal Ecology and Behavior StudiesFrench-language works237,207