MétaCan
Menu
Back to cohort
Record W2173444322 · doi:10.1086/656267

Bighorn Ewes Transfer the Costs of Reproduction to Their Lambs

2010· article· en· W2173444322 on OpenAlexaffabout
Julien G. A. Martin, Marco Festa‐Bianchet

Bibliographic record

VenueThe American Naturalist · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversité LavalUniversité de Sherbrooke
Fundersnot available
KeywordsOvis canadensisReproductionBiologyOffspringAnimal scienceReproductive successPopulationBovidaeGestationFertilityPregnancyEcologyDemography

Abstract

fetched live from OpenAlex

Several studies of large mammals report no direct reproductive costs for females. Individual heterogeneity may hide fitness costs of reproduction, but mothers could also transfer some costs to their offspring. Using data on 442 lambs weaned by 146 bighorn sheep (Ovis canadensis) ewes at Ram Mountain, Alberta, we studied how reproductive effort varied with environmental and maternal conditions. During summer, lactating ewes should gain enough mass to survive the winter and to support their next gestation, while nursing their current lamb. We measured reproductive effort as summer mass gain by lambs corrected for maternal mass in June and maternal mass gain during summer. Females lowered their reproductive effort when population density increased and if they had weaned a lamb the previous year. A reduction in reproductive effort led to lower winter survival by lambs. Bighorn ewes have a conservative reproductive tactic and always favor their own body condition over that of their lambs. When resources are limited, ewes appear to transfer reproductive costs to their lambs, as expected from the much greater relative fitness consequences of a reduction in maternal than in offspring survival.

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)0.000
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 score0.524
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.007
GPT teacher head0.226
Teacher spread0.218 · 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

Citations81
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueThe American NaturalistSame topicWildlife Ecology and ConservationFrench-language works237,207