Modeling trace element uptake by plants grown in contaminated soil
Bibliographic record
Abstract
Risk assessors are often asked to estimate the concentration of a trace element in the edible part of a plant based on soil properties. More accurate models are needed to better assess the risks associated with the consumption of plants growing in contaminated soils. Although the importance of different soil physico-chemical properties on trace element bioavailability is recognized, the effect of plant physiological processes have received less attention. This thesis reports efforts to integrate soil physico-chemical properties and plant physiological factors in the modeling of trace element uptake by plants and provides a reflection on the assessment of the risks associated with urban gardening on the Island of Montréal. Chapter 2 presents and discusses the results of a field experiment in 19 urban gardens in Montréal. Our results suggest that, although some gardens showed significant contamination, the vegetables grown in all of the gardens we tested were safe for consumption. Our analysis also suggests that the model and methods used by the direction of public health of Montréal in 2007 in their risk assessment greatly overestimated trace element concentrations in vegetables and constituted a weak scientific basis for decision-making. To improve the accuracy of the models used by risk assessors, two approaches were developed. In Chapter 3, the effect of transpiration rate, a process thought to affect trace element uptake and accumulation by plants, was tested in a controlled environment experiment. Our data suggest that, although an effect is observed, its magnitude is not as high as expected, especially when trace element concentrations in the above ground plant parts are concerned. Hence, the integration of transpiration rate into trace element uptake modeling may not constitute a significant improvement. In Chapter 4, data from five experiments are analyzed and models are developed to predict the concentration of 15 trace elements in 13 plant tissues as a function of total trace element concentrations in soil and key soil physico-chemical properties such as pH, soil organic matter (SOM), and cation exchange capacity (CEC). Our results suggest that CEC and pH are the soil properties that best correlate with trace element bioavailability for a wide range of elements and plants.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".