The effects of seasonal changes, sample site drainage and tree morphology on trace element contents of black spruce ( <b> <i>Picea mariana</i> </b> (Mill.) BSP) crown twigs and outer bark
Bibliographic record
Abstract
A positive correlation between soil metal content and plant metal accumulation has been used by biogeochemists to assist mineral exploration in areas of minimal outcrop. Much-needed study of the impact of vegetation sample collection over an extended time-frame, impact of site drainage, as well as the choice of vegetation sample type are presented. Evaluation of seasonal variability, together with measurements of tree water flow-rate (affected by weather conditions) on tree crown metal uptake was also undertaken to ascertain whether this variability could mask the geochemical signatures or whether normalization to weather conditions is needed. Thirty-three elements, including Au, Ag, Ni, Co, Zn and Cu, were studied. Other factors such as tree crown, outer bark and tree appearance were also studied. Black spruce was selected due to its ubiquitous presence in the boreal forest of central Manitoba. The best agreement between the crown twig metal accumulation and tree water uptake was identified for the rare earth elements (REEs) and the essential elements (Ca, K, Mg, Fe, P, Zn), which also exhibited the highest seasonal variation. The content of pH-sensitive elements (Ag, Co, Ni, Rb, Mn, Cu) in black spruce crowns did not display any direct relationship to the tree water uptake. Elements most affected by site drainage conditions include Ag, Co, Ni, Rb, Mn and Cu. These metals were found in substantially larger quantities in crowns of trees growing on well drained sites. Gold concentrations in outer bark samples growing on well drained sites were 12 times lower than the same samples collected from poorly drained sites. Au, Pb, W, Th, Na, Al were found in substantially larger concentrations in thin (up to 4 mm in diameter) compared to thicker twigs. Ag and Ca accumulated preferentially in thick twigs. K, Mg, P, Mn, Zn, Cu, Au, Ag, Rb and W were present in substantially higher concentrations in the crown twigs compared to outer bark. Pb, B, Hf, Th, V and REEs were present in the outer bark at eight to ten times higher concentrations than in crown twigs, and Hf, Na, Sb, Sc and V five times higher. W was not detectable in the outer bark but its content in the twigs was well above the detection limit. Crown morphology, the outer bark appearance and the number of tree transpiring branches had no measurable effect on metal contents in the assessed tree organs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".