Association between heavy metal uptake and growth and reproduction in the anecic earthworm, Alma nilotica
Bibliographic record
Abstract
Abstract Elevated heavy metal concentrations in soils is a cause for concern as they are hazardous to soil organisms including earthworms which are considered as ecosystem engineers. Current ecotoxicity tests predominantly use temperate earthworm species, and thus there is the need to include a broader genera of native species to improve ecological risk assessment. Alma nilotica, is a tropical anecic earthworm species that survives well under laboratory conditions and has potential for use in ecotoxicology testing but lacks published toxicity data for important pollutants. Growth and reproduction bioassays were carried out with Alma nilotica to determine the relationship between the concentrations of Cu, Zn, Pb and Cr in spiked soils and their bioaccumulation and toxic effects. Positive linear relationships were found between soil-metal and internal earthworm-metal concentrations. Cu did not inhibit growth up to 35 days of exposure but became toxic with longer exposure duration. Zn was not regulated by Alma nilotica although it is an essential metal that is well regulated by Eisenia sp. commonly used in standard ecotoxicity tests, showing differences in metal regulation by earthworms of different ecological functional groups. Based on bioaccumulation factors (BAFs), growth inhibition and reproduction effects the metals were ranked in decreasing toxicity as Pb > Cr > Zn > Cu. The mean 20% Internal Effects Concentrations (IEC20s) for reproduction were 1.03. 1.77, 10.2 and 218 mg metal/kg earthworm for Pb, Cr, Zn and Cu respectively. These data can contribute to the improvement of metal risk assessment particularly in tropical contexts.
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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 | 0.001 | 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) | 0.001 | 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".