Micromorphological and Chemical Approaches to Understand Changes in Ecological Functions of Metal-Impacted Soils under Various Land Uses
Bibliographic record
Abstract
We investigated the changes in faunal activities as measures of the ecological functions of soils impacted by potentially toxic metals (PTMs) under urban, industrial, agricultural, and natural uses. Concentrations and distributions of Zn, Cd, Pb, Cu, Mn, and Fe were estimated by sequential chemical extractions, while relicts and present faunal activities were studied by micromorphological analyses. Urban and natural lands were contaminated with Pb, Cd, and Zn. Microarthropods and fungi are observed to be active in the litter decomposition in natural, agricultural and urban lands which indicates that total concentration of PTMs in soils is not a good indicator to evaluate the limitations of PTMs to fauna activity. Metals immobilization on carbonates and Fe/Mn oxides, and fertilizations reduced the negative effects of metals on faunal activity. Micromorphological analyses showed the impacts of metal on soil ecological functions in industrial site, where the surface soils are devoid of any evidence of faunal activity; likely due to high proportion of Pb and Zn in organic components. Therefore, the impacts of metals in soil fauna activities, hence ecological functions of soils, are best evaluated by the knowledge of metal partitioning on solid phases in combination with observations of fauna activities using micromorphological techniques.
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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 | 0.002 | 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) | 0.001 | 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".