Inbreeding Depression and Inbreeding Avoidance in a Natural Population of Guppies (<i>Poecilia reticulata</i>)
Bibliographic record
Abstract
Abstract Maintenance of genetic variation in the face of strong natural selection is a long‐standing problem in evolutionary biology. One of the most extreme examples of within‐population variation is the polymorphic, genetically determined color pattern of male Trinidad guppies ( Poecilia reticulata ). Female mating preference for rare or novel patterns has been implicated as a factor in maintaining this variation. The origin of this preference is not understood, although inbreeding avoidance has been proposed as a mechanism. Inbreeding avoidance is advantageous when populations exhibit inbreeding depression and the opportunity for mating between relatives exists. To determine whether these conditions are met in a natural guppy population, we assessed mating and reproductive patterns using polymorphic molecular markers. Females produced more offspring with less‐related males than with more‐related ones. In addition, females were more likely to have mated with less‐related males, but this trend was only marginally significant. Male heterozygosity was positively correlated with mating success and with the number of offspring sired, consistent with strong inbreeding depression for adult male fitness. These results provide substantial insight into mating patterns of a wild guppy population: strong inbreeding depression occurs, and individuals tend to avoid mating with relatives.
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 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 | 0.000 | 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 | 0.000 | 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".