THE ECOLOGY AND GENETICS OF FITNESS IN CHLAMYDOMONAS. VIII. THE DYNAMICS OF ADAPTATION TO NOVEL ENVIRONMENTS AFTER A SINGLE EPISODE OF SEX
Bibliographic record
Abstract
According to classical evolutionary theory, sexual recombination can generate the variation necessary to adapt to changing environments and thereby confer an evolutionary advantage of sexual over asexual reproduction. Using the green alga, Chlamydomonas reinhardtii, we investigated the effect of a single sexual episode on adaptation of heterotrophic growth on different carbon sources. In an initial mixture of isolates, sex was induced and the resulting offspring constituted the sexual populations, along with any unmated vegetative cells; the unmated mixture of isolates represented the asexual populations. Mean and variance in division rates (i.e., fitness) were measured four times during approximately 50 generations of vegetative growth in the dark on all possible combinations of four carbon sources. Consistent with effects of recombination of epistatic genes in linkage disequilibrium, sexual populations initially had a higher variance in fitness, but their mean fitness was lower than that of asexual populations, possibly due to recombinational load. Subsequently, fitness of sexual populations exceeded that of asexual ones, but finally they regained parity in both mean and variance of fitness. Although recombination was not more effective on more complex substrates, these results generally support the idea that sex can accelerate adaptation to novel environments.
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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 | 0.001 | 0.000 |
| 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 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".