A review of mercury concentrations in freshwater fishes of Africa: Patterns and predictors
Bibliographic record
Abstract
The methylated form of mercury (methylmercury) is a potent neurotoxic chemical and a contaminant of concern for fisheries because of its potential effects on ecosystem and human health. In Africa, inland fisheries are a crucial component of food and economic security, yet little information is available on mercury (Hg) contamination trends. The authors compiled published data on Hg contamination in African freshwater fishes, invertebrates, and plankton, as well as on potential drivers of Hg concentrations in these organisms. From 30 identified studies the authors assembled 407 total Hg concentrations from 166 fish species, 10 types of invertebrates, and various plankton, distributed across 31 water bodies in 12 countries. In fishes, total Hg concentrations, expressed as mean (± standard deviation) per location, averaged 156.0 ± 328.0 ng/g wet weight and ranged from 5.5 ng/g wet weight to 1865.0 ng/g wet weight. Only locations with nearby artisanal and small-scale gold mining operations had mean Hg concentrations above the World Health Organization/Food and Agriculture Organization's recommended guideline for fish (500 ng/g wet wt). The authors used mixed models to detect relationships between fish Hg concentrations and trophic level, mass, latitude, and chlorophyll a. Mass, trophic level, and latitude were all positive predictors of Hg concentration, confirming the presence of Hg bioaccumulation and biomagnification in African fishes. Although strong trends in Hg concentrations were evident, the present study also highlights limited availability of Hg data in Africa.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".