Genetic control of invasive plants species using selfish genetic elements
Bibliographic record
Abstract
Invasive plants cause substantial environmental damage and economic loss. Here, we explore the possibility that a selfish genetic element found in plants called cytoplasmic male sterility (CMS) could be exploited for weed control. CMS is caused by mutations in the mitochondrial genome that sterilize male reproductive organs. We developed an analytical model and a spatial simulation to assess the use of CMS alleles to manage weed populations. Specifically, we examined how fertility, selfing, pollen limitation and dispersal influenced extinction rate and time until extinction in populations where CMS arises. We found that the introduction of a CMS allele can cause rapid population extinction, but only under a restricted set of conditions. Both models suggest that the CMS strategy will be appropriate for species where pollen limitation is negligible, inbreeding depression is high and the fertility advantage of females over hermaphrodites is substantial. In general, spatial structure did not have a strong influence on the simulation outcome, although low pollen dispersal and intermediate levels of seed dispersal tended to reduce population extinction rates. Given these results, the introduction of CMS alleles into a population of invasive plants probably represents an effective control method for only a select number of species.
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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 | 0.000 | 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) | 0.001 | 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".