Cyanobacterial effects on an aquatic keystone grazer are reshaped by presence of the herbicide atrazine
Bibliographic record
Abstract
Abstract As cyanobacterial blooms and herbicide pollution, which are often detected in eutrophic waters, can separately jeopardise zooplankton populations, there is an urgent and on‐going need to understand the strength and direction of their interactive effects. This is a crucial step toward realistic risk‐evaluation of agricultural pollution in eutrophic waterbodies. In this study, we evaluated how the herbicide, atrazine (ATZ), alters the effects of cyanobacterial food on the zooplankter, Daphnia magna. We found survival time of Daphnia decreased with increasing amounts of Microcystis in their diets, and the magnitude of this cyanobacterial effect was independent of ATZ. In contrast, ATZ exposure triggered faster growth and larger body size in Daphnia fed diets containing Microcystis compared to those fed the good‐food diet. Although toxic Microcystis reduced the overall reproductive output of Daphnia, the presence of ATZ, regardless of the type of food treatment, exhibited a masking effect by further significantly decreasing Daphnia's overall reproductive output, resulting in a low level of reproduction. Finally, we found an expression trade‐off at the molecular scale between growth and reproduction genes on one side, and antioxidation gene on the other, which could account in part for ATZ's influence on Microcystis toxicity to Daphnia at maturation stage. These results demonstrated that ATZ can reshape Daphnia's responses to Microcystis, predominantly with effects on growth and reproductive traits. These trait‐dependent responses were found to be closely linked to the regulation of key metabolic pathways. Collectively, our study enhances current knowledge regarding the potential interaction between fundamental trophic levels in cyanobacteria‐dominated lakes around farmlands, and is helpful to achieve more realistic environmental risk management of agricultural pollution in eutrophic waterbodies.
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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 | 0.000 |
| 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) | 0.001 | 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".