Influence of Soil Properties and Aging on the Toxicity of Copper on Compost Worm and Barley
Bibliographic record
Abstract
Influence of soil properties and aging on Cu partitioning and toxicity was assessed on 10 artificial soils constituted using a statistical design considering pH (5.5 and 7.5), organic matter (1-30% [w/w]), and clay content (5-35% [w/w]). Total Cu as well as water-, CaCl2-, and diethylene triamine pentaacetic acid (DTPA)-extracted Cu fractions were determined for each soil mixture. Ecotoxic effect was assessed by determining growth inhibition of barley (Hordeum vulgare L.) and compost worm (Eisenia fetida) mortality. Analyses were repeated after a 16-wk aging period of the soils at pH 7.5 (8 x 2-wk wetting and drying cycle). Results indicated that pH was the main factor controlling Cu partitioning, ahead of organic matter and clay content. Calcium chloride (0.5 M)-extracted Cu fractions showed the best correlation with toxic responses (r = 0.55-0.66; p < 0.05), while total and DTPA-extracted Cu concentrations could not explain differences in toxicity. Direct regressions between toxicity and soil properties (pH, organic matter, and clay content) provided better explanation of variance: r2= 0.50 (p = 0.00006) for compost worm mortality, r2= 0.77 (p < 0.00001) for barley shoot inhibition, and r2= 0.92 (p < 0.00001) for barley root inhibition. Copper toxicity was mainly influenced by pH and, to a lesser extent, by organic matter and clay content. Aging in organic soils revealed a slight reduction in ecotoxicity while an increase was observed in soils with low organic matter content. Further investigation using longer aging periods would be necessary to assess the significance of this observation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".