Selection analysis on the rapid evolution of a secondary sexual trait
Bibliographic record
Abstract
Evolutionary analyses of population translocations (experimental or accidental) have been important in demonstrating speed of evolution because they subject organisms to abrupt environmental changes that create an episode of selection. However, the strength of selection in such studies is rarely measured, limiting our understanding of the evolutionary process. This contrasts with long-term, mark-recapture studies of unmanipulated populations that measure selection directly, yet rarely reveal evolutionary change. Here, we present a study of experimental evolution of male colour in Trinidadian guppies where we tracked both evolutionary change and individual-based measures of selection. Guppies were translocated from a predator-rich to a low-predation environment within the same stream system. We used a combination of common garden experiments and monthly sampling of individuals to measure the phenotypic and genetic divergence of male coloration between ancestral and derived fish. Results show rapid evolutionary increases in orange coloration in both populations (1 year or three generations), replicating the results of previous studies. Unlike previous studies, we linked this evolution to an individual-based analysis of selection. By quantifying individual reproductive success and survival, we show, for the first time, that males with more orange and black pigment have higher reproductive success, but males with more black pigment also have higher risk of mortality. The net effect of selection is thus an advantage of orange but not black coloration, as reflected in the evolutionary response. This highlights the importance of considering all components of fitness when understanding the evolution of sexually selected traits in the wild.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".