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Record W2674492671 · doi:10.15368/theses.2016.152

The Importance of the Multicomponent Display in Sexual Selection of Black Morph Girardinus metallicus (Pisces: Poeciliidae)

2016· dissertation· en· W2674492671 on OpenAlexaff
Erin M. Wojan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton University
Fundersnot available
KeywordsPoeciliidaeSexual selectionBiologyZoologyCourtshipDorsumAnatomyFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Multicomponent displays are composed of traits, such as coloration, structural ornaments, and behavior, that become integrated and signal information to conspecifics. Estimation of multicomponent displays in fishes often involves measurement of color traits. Fish color measurements are often obtained following immobilization via chemical anesthesia; however, the anesthetics may alter the resulting measurements, for example by darkening the skin. Girardinus metallicus, a poeciliid fish endemic to Cuba, has a multicomponent courtship and aggressive display. Black morph males exhibit black ventral coloration including the gonopodium (copulatory organ) and yellow in the non-black areas of their bodies. I investigated the effects of common anesthetics on coloration measurements of G. metallicus. I measured the hue, saturation, and brightness of the anterior dorsal, posterior dorsal, posterior ventral, and caudal body regions, from digital images of the same males obtained without using anesthetic and anesthetized using tricaine methane sulfonate (MS222) and eugenol (clove oil). Because multicomponent displays are intriguing with respect to sexual selection, I investigated the importance of size and coloration traits in sexual selection via female choice and male-male competition in G. metallicus. I found that saturation and hue did not differ significantly across treatments (anesthetization using MS222, anesthetization using clove oil, and without anesthetic in a small glass chamber containing water). However, brightness was greater under the anesthetics, possibly due to photographing the fish behind water and glass in the Non-anesthetic treatment or due to reflectivity differences of the iridophores. The body regions varied in hue, saturation, and brightness. Most importantly, I found differences in the responses of different body regions to the anesthetic treatments, suggesting that anesthetics may affect coloration in unpredictable ways, and that multiple regions of fish should be measured when assessing overall coloration. My results suggest that photographing fish in a glass chamber without anesthetic may be an effective way to obtain digital images for color analysis without using anesthetics that may influence coloration. Having determined a good method for color measurement, I then investigated the role of the multicomponent display in sexual selection. Through direct interaction tests, I found that dominant males had brighter and more saturated yellow coloration than subordinate males, and that dominant males courted more than subordinate males. Within high yellow males, dominant males attempted more copulations than subordinate males. Interestingly, low yellow, subordinate males attempted more copulations than low yellow, dominant males, suggesting that subordinate males invested time into attempting copulations rather than engaging

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.246
Teacher spread0.228 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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