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Record W2100576645 · doi:10.1093/beheco/ars132

The secret sex lives of sage-grouse: multiple paternity and intraspecific nest parasitism revealed through genetic analysis

2012· article· en· W2100576645 on OpenAlexaffabout
Krista L. Bird, Cameron L. Aldridge, Jennifer E. Carpenter, Cynthia A. Paszkowski, Mark S. Boyce, David W. Coltman

Bibliographic record

VenueBehavioral Ecology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyIntraspecific competitionLek matingMatingBrood parasiteNest (protein structural motif)ZoologyEcologyMating systemSeasonal breederPopulationSexual selectionParasitismOffspringMate choiceDemographyGeneticsPregnancyHost (biology)

Abstract

fetched live from OpenAlex

In lek-based mating systems only a few males are expected to obtain the majority of matings in a single breeding season and multiple mating is believed to be rare. We used 13 microsatellites to genotype greater sage-grouse ( Centrocercus urophasianus ) samples from 604 adults and 1206 offspring from 191 clutches (1999–2006) from Alberta, Canada, to determine paternity and polygamy (males and females mating with multiple individuals). We found that most clutches had a single father and mother, but there was evidence of multiple paternity and intraspecific nest parasitism. Annually, most males fathered only one brood, very few males fathered multiple broods, and the proportion of all sampled males in the population fathering offspring averaged 45.9%, suggesting that more males breed in Alberta than previously reported for the species. Twenty-six eggs (2.2%) could be traced to intraspecific nest parasitism and 15 of 191 clutches (7.9%) had multiple fathers. These new insights have important implications on what we know about sexual selection and the mating structure of lekking species.

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 score0.009
Threshold uncertainty score0.615

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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

Citations28
Published2012
Admission routes2
Has abstractyes

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