Distinguishing Diffusional and Plant Control of Cd and Ni Uptake by Hyperaccumulator and Nonhyperaccumulator Plants
Bibliographic record
Abstract
This work set out to test the hypothesis that uptake of metals by hyperaccumulator (HA) plants is more likely to be diffusion limited than uptake by nonhyperaccumulator (NHA) plants. Two circumneutral soils, with different contents of organic matter (0.8 and 5.8%), were amended with Cd (0.5 to 5 mg kg(-1)) and Ni (10 to 100 mg kg(-1)). A Cd HA plant, Thlaspi caerulescens, was grown in pots containing the Cd amended soils, and a Ni HA, Thlaspi goesingense, was grown in pots containing the Ni amended soils. A NHA plant of the same family, Thlaspi arvense, was grown in the same soils. Metals were measured in both roots and shoots of all plants. Concentrations of Cd and Ni were measured in soil solution and using the technique of diffusive gradients in thin-films (DGT). The dependencies of metal measured by DGT, [M]DGT, and in soil solution, [M]ss, on the amended metal concentration, [M]add, were consistent with fast supply of Cd but a slower rate of release of Ni from solid phase to solution at lower [Ni]add. Detailed consideration of the dependence of Ni and Cd in shoots and roots on [M]add, [M]ss, and [M]DGT allowed assessment of the supply mechanism. The weight of evidence suggested that diffusion limitation applies for uptake of Cd by both HA and NHA plants and for uptake of Ni by the HA. However, uptake of Ni by the NHA is not limited by diffusion and the biotic ligand model is probably appropriate.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".