Combined Effects of Irradiation, Nutrients, and Cyanobacterial Composition on Microcystin Concentration in Chinese Plateau Lakes
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Microcystins (MCs) are one of the most prevalent cyanotoxins and pose significant risks to aquatic ecosystems and human health, particularly in lakes used as drinking water sources. However, knowledge about the MC concentrations in plateau lakes experiencing high solar radiation is scarce. This study investigated the spatial-temporal distribution of MCs in eight Yunnan Plateau lakes in China, focusing on their relationships with environmental factors. Water samples ( n = 63) were collected during summer and winter seasons and analyzed for MC concentrations along with a suite of environmental variables. Results revealed significant seasonal and spatial variations in MC concentrations, with higher levels in eutrophic lakes Dianchi, Erhai, and Xingyunhu. Notably, mean MC concentrations in Lake Dianchi during summer and Erhai during winter exceeded the World Health Organization’s provisional guideline of 1 μg/L for drinking water. Seasonal analyses revealed distinct regulatory mechanisms: MC concentrations in summer were positively correlated with total phosphorus, total nitrogen, turbidity, and chlorophyll a, reflecting the influence of eutrophication on cyanobacterial growth. While solar radiation intensity (SRI) exhibited a dual role: moderate SRI in winter was associated with higher MC levels, whereas higher SRI in summer suppressed MC production, likely due to photoinhibition or MC degradation. Strikingly, water temperature showed no significant correlation with MC concentrations, suggesting that high solar radiation in the Yunnan Plateau may override temperature-dependent effects on cyanobacterial growth. These findings highlight the importance of nutrient management and the regulatory role of solar radiation in regulating MC production in high-altitude lakes. The study underscores the need for region-specific strategies to mitigate cyanobacterial risks, particularly in drinking water source lakes, by integrating nutrient control and the unique light regime of plateau ecosystems.
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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) | 0.000 | 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".