Aftershocks of the Samarco disaster: diminished growth and increased metal content of Raphanus sativus cultivated in soil with mining tailings
Bibliographic record
Abstract
The collapse of the Fundão tailings dam of the Samarco mining complex in Mariana, Brazil, was the largest mining disaster in the world to date with many socio-economic and environmental impacts. Soil affected by mining tailings was severely altered with negative impacts for agriculture. We tested whether diluting mining tailings with organic soil would eliminate or at least attenuate the ecotoxic effects on plant development and performance. We cultivated radish, Raphanus sativus, in substrates containing different proportions of mining tailings and organic soil: pure tailings (T100%); 2) tailings75% + soil25% (T75%); 3) tailings50% + soil50% (T50%); 4) tailings25% + soil75% (T25%), and 5) pure organic soil (Soil100%, control). There were large differences in soil quality parameters between the 100% tailings treatment (T100%) and the control (Soil100%), as well as for some parameters in the most diluted treatment - T25% (Ca2+, Fe, Mn) in relation to the control treatment. Although dilution of the tailings soil improved radish development, there was lower radish productivity (leaf area, total biomass, and root/tuber biomass) than for pure soil (control). There were also significantly higher amounts of bioaccumulated metals in radish tubers grown with tailings, even when grown in T25% for Fe content and in T75% for Mn content. These results present a worrisome scenario for human communities in the region of the Doce river, as human consumption of crops produced in soil contaminated with tailings is not recommended due to potential toxicological effects from high metal concentrations.
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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 | 0.000 | 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 | 0.000 | 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".