A population of sexual <i>Daphnia pulex</i> resists invasion by asexual clones
Bibliographic record
Abstract
Asexual reproduction avoids the costs associated with sex, predicting that invading asexual clones can quickly replace sexual populations. Daphnia pulex populations in the Great Lakes area are predominately asexual, but the elimination of sexual populations by invading clones is poorly understood. Asexual clones were detected at low frequency in one rare sexual population in 1995, with some increase in frequency during 2003 and 2004. However, these clones remained at low frequency during further yearly sampling (2005-2013) with no evidence that the resident sexual population was in danger of elimination. There was evidence for hybridization between rare males produced by asexual clones and sexual females with the potential to produce new asexual genotypes and spread the genetic factors for asexuality. In a short-term laboratory competition experiment, the two most common asexual clones did not increase in frequency relative to a genetically diverse sexual population due in part to a greater investment in diapausing eggs that trades-off current population growth for increased contribution to the egg bank. Our results suggest that a successful invasion can be prolonged, requiring a combination of clonal genotypes with high fitness, persistence of clones in the egg bank and negative factors affecting the sexual population such as inbreeding depression resulting from population bottlenecks.
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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 | 0.000 |
| 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 | 0.001 | 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".