Interspecific interactions modulate atrazine and S-metolachlor toxicity on aquatic microbial autotrophs
Bibliographic record
Abstract
Atrazine and S-metolachlor are frequently detected herbicides in streams in agricultural areas, sometimes at concentrations of concern that may affect photosynthetic organisms. In the present study, we exposed a coculture of the green alga Enallax costatus, the diatom Gomphonema parvulum and the cyanobacteria Phormidium sp. and Microcystis aeruginosa to a gradient of atrazine and S-metolachlor (0, 10, 100 and 1000 µg·L-1) for 7 days. The results showed that species interactions in a coculture can modulate herbicide toxicity compared to responses observed in monocultures. Green algae and cyanobacteria were more sensitive to atrazine in coculture than in monoculture, while diatoms showed better tolerance in coculture. S-metolachlor affected the chlorophyll fluorescence of organisms in coculture to a greater extent than atrazine, particularly for the green alga and the diatom. Despite its mode of action as an inhibitor of the synthesis of very long chain fatty acids (VLCFAs), S-metolachlor did not result in a significant reduction in these fatty acids. In general, the two herbicides had a more pronounced effect on fluorescence than on lipids in coculture. The modification in photosynthetic organisms composing the coculture was accompanied by a change in fatty acid profiles, reflecting the specific fatty acid profiles of each group of organisms. In addition, herbicide exposure may have caused lipid peroxidation, leading to a decrease in the relative abundance of polyunsaturated fatty acids (PUFAs) in the coculture. This study highlights the importance of considering interspecific interactions in ecotoxicology, as they can modulate herbicide toxicity on aquatic photosynthetic communities. In addition, lipid and fatty acid profiles provide sensitive information that complements ‘traditional’ descriptors such as cell density and photosynthesis parameters. Lipidomics can be used to study changes in coculture composition (community composition) as well as to assess the potential of herbicides to affect organisms at the cellular level.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".