Compensating for the meltdown: The critical effective size of a population with deleterious and compensatory mutations
Bibliographic record
Abstract
In the short term, the persistence of species depends on the continued existence of suitable habitat and protection from extraordinary causes of mortality, essentially ecological and socioeconomic problems. On a longer time-scale, however, genetic problems could become paramount. Populations that have only deleterious mutations eventually decline in fitness to extinction, because of the fixation by genetic drift of a small fraction of these mutations. This proceeds fastest in small populations, because genetic drift is a more powerful factor in these circumstances. If, as is biologically reasonable, some mutations are beneficial to the population, there will exist a critical effective size above which the population can persist indefinitely, because fixation of beneficial alleles can balance the effects of deleterious mutations. This critical effective size is likely to be in the hundreds, meaning a census population size in the thousands. If some mutations act to compensate for the detrimental effects of others, then the rate of beneficial mutations will increase as fitness declines; this causes the critical effective size to be even lower. In this paper, we review the theoretical impact of beneficial and compensatory mutations on the probability of extinction, as well as the substantial theoretical and empirical literature on compensation. There are many possible mechanisms for compensatory mutations. There are insufficient data to make quantitative predictions, but it is clear that there is more hope for preserving the genetic integrity of threatened species than previously thought.
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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 | 0.000 | 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) | 0.000 | 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".