Phytoremediation Efficacy of Salix discolor and S. eriocephela on Adjacent Acidic Clay and Shale Overburden on a Former Mine Site: Growth, Soil, and Foliage Traits
Bibliographic record
Abstract
Plants regularly experience suboptimal environments, but this can be particularly acute on highly-disturbed mine sites. Two North American willows—Salix discolor Muhl. (DIS) and S. eriocephala Michx. (ERI)—were established in common-garden field tests on two adjacent coal mine spoil sites: one with high clay content, the other with shale overburden. The high clay content site had 44% less productivity, a pH of 3.6, 42% clay content, high water holding capacity at saturation (64%), and high soil electrical conductivity (EC) of 3.9 mS cm−1. The adjacent shale overburden site had a pH of 6.8, and after removing 56.5% stone content, a high sand content (67.2%), low water holding capacity at saturation (23%), and an EC of 0.9 mS cm−1. The acidic clay soil had significantly greater Na (20×), Ca (2×), Mg (4.4×), S (10×), C (12×) and N (2×) than the shale overburden. Foliar concentrations from the acidic clay site had significantly greater Mg (1.5×), Mn (3.3×), Fe (5.6×), Al (4.6×), and S (2×) than the shale overburden, indicating that these elements are more soluble under acidic conditions. There was no overall species difference in growth; however, survival was greater for ERI than DIS on both sites, thus overall biomass yield was greater for ERI than DIS. Foliar concentrations of ERI were significantly greater than those of DIS for N (1.3×), Ca (1.5×), Mg (1.2×), Fe (2×), Al (1.5×), and S (1.5×). There were no significant negative relationships between metal concentrations and growth or biomass yield. Both willows showed large variation among genotypes within each species in foliar concentrations, and some clones of DIS and ERI had up to 16× the Fe and Al uptake on the acidic site versus the adjacent overburden. Genetic selection among species and genotypes may be useful for reclamation activities aimed at reducing specific metal concentrations on abandoned mine sites. Results show that, despite having a greater water holding capacity, the greater acidity of the clay site resulted in greater metal mobility—in particular Na—and thus a greater EC. It appears that the decline in productivity was not due to toxicity effects from the increased mobility of metals, but rather to low pH and moisture stress from very high soil Na/EC.
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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 | 0.000 | 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".