Competition between microcystin‐ and non‐microcystin‐producing <i>Planktothrix agardhii</i> (cyanobacteria) strains under different environmental conditions
Bibliographic record
Abstract
The factors that control the production of microcystins (hepatotoxins) during cyanobacterial blooms, and the function of these metabolites remain largely unknown. In an attempt to provide answers to these questions, we compared the fitness of microcystin (MC)-producing and non-MC-producing Planktothrix agardhii strains under various experimental conditions. More specifically, we investigated the effects of temperature, light intensity and nitrate concentrations on several MC-producing and non-MC-producing strains in monoculture and competition experiments. In the monoculture experiments, no significant difference in cell growth rates was found for any of the environmental conditions tested. On the other hand, at the end of the competition experiments, we found that when the environmental conditions limited cell growth, MC-producing strains were clearly winning out over the non-MC-producing ones. This suggested that, under growth-limiting conditions, the benefits of producing MC outweigh the cost. Moreover, the reverse was found under non-growth-limiting conditions, suggesting that under environmental conditions that favour cyanobacterial growth, the cost of MC production must outweigh its benefits. These findings suggest that environmental factors may have an indirect effect on the MC production rate, and on the selection of MC-producing and non-MC-producing strains, via their direct impact on both the cell growth rate and the cell densities in the cultures. Several hypotheses have been advanced concerning the possible function of MCs, but none of them seems to be supported by our data.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".