Increasing mercury bioaccumulation and biomagnification rates of Nile perch (Lates niloticus L.) in Winam Gulf, Lake Victoria, Kenya
Bibliographic record
Abstract
The Nile perch (Lates niloticus L.) commercial fishery for Lake Victoria in East Africa is an important source of revenue and employment. We focused on shifts in food web structure and total mercury (THg) bioaccumulation and biomagnification in Nile perch, and lower food web items collected from Winam Gulf (Kenya) sampled 24 years apart (1998 and 2022). Stable isotope carbon (δ13C) values were higher in all species from 2022 compared to 1998. Stable nitrogen isotope (δ15N) values in baseline organisms were lower in 2022 compared to 1998. In Nile perch, δ15N values were correlated with total length, but the δ15N-length regressions were steeper in 1998 compared to 2022 except for one large (158 cm) Nile perch from 1998 with an uncharacteristically low δ15N value. Total Hg concentrations were lower in lower trophic species from 2022 compared to 1998. However, the THg bioaccumulation rate (as a function of fish length) in Nile perch was greater in 2022 compared to 1998 resulting in 24.2 % to 42.4 % higher wet weight dorsal THg concentrations in 2022 Nile perch for market slot size (50 to 85 cm) fish. The contrasting observations of increased THg bioaccumulation with size in 2022 against decreases in the rate of trophic increase with size and lower THg concentrations of lower food web items imply reduced fish growth and potential bioenergetic stressors on Winam Gulf Nile perch. All samples except 1 large Nile perch (139 cm total length collected in 2022) had THg concentrations below the European Union trade limit (500 ng/g wet weight). However, for more vulnerable individuals (women, children and frequent fish eaters), we recommend a decrease in maximum monthly meal consumption for 55–75 cm Nile perch from 16 meals per month calculated for 1998 to a limit of 8 meals per month calculated for 2022.
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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 | 0.001 | 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) | 0.001 | 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".