Bioaccumulation of Trace Elements in Fish From Lake Kivu and Its Potential Risk to Consumers in Rwanda
Bibliographic record
Abstract
ABSTRACT Lake Kivu, located between Rwanda and the Democratic Republic of the Congo, is subject to trace element contamination primarily due to the geological composition of its bedrock, watershed soils, and anthropogenic activities. In this study, we investigated the accumulation of trace elements in 13 fish species from Lake Kivu, with samples obtained from fishermen in Rubavu, Karongi, and Rusizi. The fish samples were digested and analyzed for selected trace element concentrations using atomic absorption spectrophotometry (AAS). The concentrations of trace elements in the fish ranged from 0.07 to 2.53 mg/kg for mercury (Hg), 0.69 to 1.16 mg/kg for cadmium (Cd), 0.28 to 0.76 mg/kg for copper (Cu), 2.58 to 3.83 mg/kg for chromium (Cr), and 0.22 to 0.68 mg/kg for manganese (Mn). The highest bio‐concentration factor (BCF) was observed for mercury. Oreochromis niloticus exhibited significantly higher BCFs for mercury compared to other species, with a value of 16,867 L/kg. Haplochromis scheffersi also displayed a high BCF for mercury at 3533 L/kg, followed by Labeo victorianus with a BCF of 2867 L/kg. Mercury (Hg) posed a potential risk for adults in 77% of the fish species analyzed, as indicated by target hazard quotient (THQ) values exceeding 1. Additionally, Cd, Cr, and Hg posed potential risks for children in over 75% of the fish species analyzed. Continuous monitoring of trace element sources and concentrations in the water column and fish of Lake Kivu is urgently needed to assess contamination sources and exposure levels.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".