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Indirect predator effects on clutch size and the cost of egg production

2010· article· en· W2126097787 on OpenAlexaff
Marc Travers, Michael Clinchy, Liana Zanette, Rudy Boonstra, Tony D. Williams

Bibliographic record

VenueEcology Letters · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsThe Scarborough HospitalUniversity of TorontoUniversity of VictoriaSimon Fraser UniversityWestern University
Fundersnot available
KeywordsPredationPredatorBiologyEcologyAvian clutch sizeNest (protein structural motif)InvertebrateZoologyReproduction

Abstract

fetched live from OpenAlex

Predator-induced changes in physiology and behaviour may negatively affect a prey's birth rate. Evidence of such indirect predator effects on prey demography remains scarce in birds and mammals despite invertebrate and aquatic studies that suggest ignoring such effects risks profoundly underestimating the total impact of predators. We report the first experimental demonstration of indirect predator effects on the annual 'birth' rate resulting from negative effects on the size of subsequent clutches laid by birds. We manipulated the probability of nest predation and measured the size of subsequent clutches and multiple indices of the mother's physiological condition, while controlling for food availability, date and stage of breeding. Females subject to frequent experimental nest predation laid smaller subsequent clutches and were in poorer physiological condition, particularly regarding non-resource-based indices (e.g. oxidative stress and glucocorticoid mobilization) consistent with both a response to the threat of predation and an increased cost of egg production.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.000

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 head0.004
GPT teacher head0.204
Teacher spread0.200 · 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".

Quick stats

Citations162
Published2010
Admission routes1
Has abstractyes

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