A probabilistic hazard assessment for cyanobacterial toxins accounting for regional geography and water body trophic status
Bibliographic record
Abstract
Under climate change scenarios freshwater eutrophication is expected to increase, and with it the occurrence of cyanobacterial toxin-producing harmful algal blooms. In the current study, microcystin toxin occurrence data from literature sources and a long-term provincial monitoring program were used to conduct a probabilistic hazard assessment for Alberta, Canada. The large temporal and spatial range of data makes Alberta a model system for identifying regional geography and water body trophic status factors driving toxin concentrations. Environmental exposure distributions of microcystin concentrations were plotted and used to identify the likelihood of a given sample exceeding water guideline values as a function of regional geography, total phosphorus and chlorophyll-a concentration. This process identified regions with intensive cultivation and those most prone to water deficits associated with climate change to be most associated with exceedances of regulatory guideline values. Elevated phosphorus and chlorophyll-a concentrations were also drivers of toxin occurrence. This assessment can be used to identify water bodies of greatest risk to human and animal populations from cyanotoxins and thereby inform regulators as to most effective monitoring strategies. • A probabilistic hazard assessment identified geographic and hydrological factors driving elevated microcystin levels. • Water bodies associated with extensively cultivated lands and prone to water deficits were at high risk of elevated toxin. • Waters high in phosphorus and chlorophyll a also displayed microcystin levels that exceeded regulatory guidelines.
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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".