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Record W1971856119 · doi:10.1093/beheco/arp112

Mate choice based on complex visual signals in the brook stickleback, Culaea inconstans

2009· article· en· W1971856119 on OpenAlexaff
Jessica L. Ward, Deborah A. McLennan

Bibliographic record

VenueBehavioral Ecology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyMate choiceSticklebackMating preferencesCourtshipMatingSexual selectionAssortative matingEvolutionary biologyZoologyEcologyReproductive isolationDemographyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

In species with complex courtship, females often have the opportunity to assess multiple male cues during mate choice. Depending on the strength and form of the coevolutionary relationships between male traits and female preferences, geographic variation in signal complexes can result in a variety of mate choice scenarios ranging from partial to complete positive assortative mating. Using mate choice trials, we investigated the relationship between intrapopulation female biases for complex visual signals and interpopulation mating dynamics in 2 populations of brook stickleback, Culaea inconstans, from distinct mitochondrial DNA genetic lineages. Our results showed that courtship effort is the primary visual criterion of mate assessment in this species; females from both lineages exhibited directional preferences for increased behavioral vigor. In contrast, male nuptial color intensity and body size had little influence on female choice decisions. Interpopulation divergence in male traits was not strongly correlated with divergence in female preferences, producing asymmetric patterns of assortative mate choice across the lineage divide. We compare female preferences for male visual traits in C. inconstans with other members of the Gasterosteidae and suggest that mate assessment differs substantially between stickleback 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

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 head0.056
GPT teacher head0.322
Teacher spread0.266 · 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.

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

Citations16
Published2009
Admission routes1
Has abstractyes

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