Potential of decaying wood to restore root-available base cations in depleted forest soils
Bibliographic record
Abstract
The depletion of root-available Ca in northern forest soils exposed to decades of increased acid deposition adversely affects forest health and productivity. Laboratory studies indicated the potential of wood-decay fungi to restore lost Ca. This study presents changes in concentration of Ca, Mg, and K in sapwood of red spruce ( Picea rubens Sarg.), red maple ( Acer rubrum L.), eastern hemlock ( Tsuga canadensis (L.) Carrière), and paper birch ( Betula papyrifera Marshall) during the decay process at two experimental forests for 12 years and to compare concentrations of exchangeable Ca, Mg, and Al in decayed wood residues at 10 and 12 years with those in the forest floor. Significant loss of mass indicated by decreasing wood density occurred after 2–8 years in conifers and after only 2 years in hardwoods. A significant gain in wood K was observed at 2 years followed by a significant loss at 8 years. A negligible gain in Ca concentration occurred at 2 years and a substantial gain at 8 years. Observed changes in Mg concentration were variable. No significant difference in exchangeable Ca concentration was observed between decayed wood residue of spruce and maple and the forest floor. However, decayed wood residue had a much lower Al concentration and molar Al/Ca ratio, a condition characteristic of sites with high root-available Ca.
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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".