Year-long monitoring of phytoplankton community, toxigenic cyanobacteria, and total microcystins in a eutrophic tropical dam supplying the Mexico megacity
Bibliographic record
Abstract
The Valle de Bravo dam is an important source of drinking water supply for the Mexico City Conurbation (>26 million inhabitants) and is also a hotspot for nautical sports, recreational fishing, and tourism. However, anthropogenic pressures in the upper reaches of the basin have led to increased eutrophication and numerous harmful cyanobacterial blooms (HCBs). To determine the effect of abiotic variables on the characteristics of the phytoplanktonic community, as well as their influence on the diversity of toxigenic cyanobacteria and related cyanotoxins, we evaluated monthly variations in environmental factors, phytoplankton biovolume and composition and total microcystins in Valle de Bravo dam during the year of 2019. Overall, 75 phytoplanktonic species were identified, mostly belonging to the divisions Cyanobacteria, Chlorophyta, and Bacillariophyta. Cyanobacteria presented the highest biomass throughout the year, with water temperature and rainfall being the best correlated factors. The highest concentrations of total microcystins were recorded from July to September (maximum of 71 μg L−1), associated with the dominance of species such as M. smithii, M. aeruginosa, M. viridis M. flos-aquae, Aphanocapsa planctonica, and Dolichospermum crassum, and environmental factors such as rainfall, total dissolved solids, water temperature, and specific trace metals. In all months except December, the total cyanobacterial biovolume was above the World Health Organization alert level two, indicating potentially high risks to human health. The predominance of cyanobacteria and high biovolumes classified water quality as poor to very poor during most of the year. To avoid the development of HCBs in this dam, the contribution of nutrients by the tributary rivers and sewage must be controlled, since the poor-quality conditions of the water threaten the aquatic biota, the sports and recreation activities and affect the potable water supply.
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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) | 0.000 | 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 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".