Mutation in algae – the increasing role of anthropogenic environmental stress
Bibliographic record
Abstract
Algae are globally important primary producers and when faced with anthropogenic pollutant stress (APS; e.g. heavy metals, herbicides) or naturally occurring stress (NOS; e.g. naturally acidic conditions, high sulphide concentrations), physiological processes may be disrupted. This might lead to abnormal growth and, potentially, individual mortality, or, in extreme cases, extirpation. However, algal populations could persist, in the face of such stressors, if they were able to evolve rapidly based on genetic variation generated through induced mutation and/or recombination. We searched the literature for studies which assessed rates of recombination and mutation under a diversity of environmental conditions. Unfortunately, we did not encounter studies which provided estimates of recombination rates in algae, thus identifying a major gap in the literature. Our meta-analysis of published mutation rates raised the intriguing hypothesis that algae may have higher mutation rates when exposed to APS vs NOS. We conclude that more studies examining algae from diverse habitats are needed to bolster our understanding of the mechanisms behind this increased discrepency in DNA replication, and that elevated mutation rates may contribute to evolutionary rescue in algal populations experiencing declines in water quality on both local and global scales.
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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 | 0.000 |
| 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) | 0.002 | 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".