Character displacement of male nuptial colour in threespine sticklebacks (Gasterosteus aculeatus)
Bibliographic record
Abstract
Character displacement in signalling traits occurs when differences between species are greater in sympatry than where either species occurs alone. Finding character displacement in a signalling trait suggests that the trait has diverged as a result of interspecific interactions such as competition, aggression, predation, or reproductive interference. We tested for character displacement of male nuptial coloration between sympatric species of threespine sticklebacks (Gasterosteus aculeatus spp.). The sympatric pairs consist of a large ‘benthic’ species, which feeds on benthic invertebrates, and a smaller planktivorous ‘limnetic’ species. Breeding males of both species develop red throats and blue bodies, although limnetic males appear brighter. To test for character displacement, we compared the nuptial colour of benthics and limnetics from two species-pair lakes (sympatric) with that of males from three similar allopatric lakes (only one species present). We measured the intensity of blue and red coloration using reflectance spectra taken from live fish. We found that allopatric males were intermediate between limnetic and benthic males in the intensity of red colour, indicating character displacement in that trait in sympatry. By contrast, we found no evidence for character displacement in blue intensity, although it differed sharply between the species pairs in one lake (Priest).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".