Factors associated with blooms of cyanobacteria in a large shallow lake, China
Bibliographic record
Abstract
BACKGROUND: Eutrophication of freshwater systems can result in blooms of phytoplankton, in many cases cyanobacteria. This can lead to shifts in structure and functions of phytoplankton communities adversely affecting the quality of drinking water sources, which in turn impairs public health. Relationships between structures of phytoplankton communities and concentrations of the toxicant, microcystin-leucine-arginine (MC-LR), have not been well examined in large shallow lakes. The present study investigated phytoplankton communities at seven locations from January to December of 2015 in Tai Lake, and relationships between structures and diversities of phytoplankton communities and water quality parameters, including concentrations of MC-LR and metals, were analyzed. RESULTS: . The greatest diversities of phytoplankton communities, as indicated by species richness, Simpson, Shannon-Wiener, the Berger and Parker, and the Pielou evenness indices, were observed in spring. Furthermore, productivity of phytoplankton was significantly and negatively correlated with diversities. These results demonstrated that Simpson, Shannon-Wiener, the Berger and Parker, and the Pielou evenness indices of phytoplankton communities were significantly related to trophic status and overall primary productivity in Tai Lake. In addition, temperature of surface water, pH, permanganate index, biochemical oxygen demand, total phosphorus, arsenic, total nitrogen/total phosphorous ratio, and MC-LR were the main factors associated with structures of phytoplankton communities in Tai Lake. CONCLUSION: The present study provided helpful information on phytoplankton community structure and diversity in Tai Lake from January to December of 2015. Our findings demonstrated that Simpson, Shannon-Wiener, the Berger and Parker, and the Pielou evenness indices could be used to assess and monitor for status and trends in water quality of Tai Lake. In addition, MC-LR was one of the main factors associated with structures of phytoplankton communities in Tai Lake. The findings may help to address important ecological questions about the impact of a changing environment on biodiversity of lake ecosystems and the control of algae bloom. Further studies are needed to explore the relationship between MC-LR and phytoplankton communities in the laboratory.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".