Trace metals as indicators of tree rooting in bituminous soils
Bibliographic record
Abstract
Abstract In some reclamation practices, following bitumen mining in the Canadian Boreal forest, overburden containing low concentrations of hydrocarbons (<8% of bulk soil volume) is buried under suitable soils. Residual hydrocarbons may influence the growth of trees used in afforestation of reclaimed sites, thus determining whether roots interact with buried bitumen is a key to predicting reclamation success. As the organic fraction of bitumen is enriched in vanadium, nickel, molybdenum, and rhenium, dendrochemistry may be a method to determine whether tree roots are interacting with bitumen without disturbing soils. We analyzed trace concentrations of these metals in soil, soil pore water, and tree cores of Pinus banksiana growing on natural bitumen deposits and sites free of bitumen. If roots are present within bitumen and passively uptake trace metals during water transport and wood growth, metals enriched in bitumen should be present in higher concentrations in the woody tissue of trees growing in bituminous soils compared to trees growing in bitumen‐free soils. Concentrations of nickel in trees growing on shallow bitumen deposits were approximately 3× higher than those growing in bitumen‐free soils. The concentration of vanadium (1.33 μg kg−1 in younger wood and 3.21 μg kg−1 in older wood) was also elevated in trees on bituminous sites, though not significantly. Molybdenum concentrations decreased by ~25% in trees growing on bituminous sites, likely an outcome of soil pH. This research supports the use of dendrochemistry to investigate, and potentially monitor, tree rooting at depth in substrates with signature metals.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".