Anthropogenic nutrients and harmful algae in coastal waters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Harmful algal blooms (HABs) are thought to be increasing in coastal waters worldwide. Anthropogenic nutrient enrichment has been proposed as a principal causative factor of this increase through elevated inorganic and/or organic nutrient concentrations and modified nutrient ratios. We assess: 1) the level of understanding of the link between the amount, form and ratio of anthropogenic nutrients and HABs; 2) the evidence for a link between anthropogenically generated HABs and negative impacts on human health; and 3) the economic implications of anthropogenic nutrient/HAB interactions. We demonstrate that an anthropogenic nutrient-HAB link is far from universal, and where it has been demonstrated, it is most frequently associated with high biomass rather than low biomass (biotoxin producing) HABs. While organic nutrients have been shown to support the growth of a range of HAB species, insufficient evidence exists to clearly establish if these nutrients specifically promote the growth of harmful species in preference to benign ones, or if/how they influence toxicity of harmful species. We conclude that the role of anthropogenic nutrients in promoting HABs is site-specific, with hydrodynamic processes often determining whether blooms occur. We also find a lack of evidence of widespread significant adverse health impacts from anthropogenic nutrient-generated HABs, although this may be partly due to a lack of human/animal health and HAB monitoring. Detailed economic evaluation and cost/benefit analysis of the impact of anthropogenically generated HABs, or nutrient reduction schemes to alleviate them, is also frequently lacking.
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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 | 0.001 | 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) | 0.002 | 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 it