Concentrations of Ca and Mg in early stages of sapwood decay in red spruce, eastern hemlock, red maple, and paper birch
Bibliographic record
Abstract
The decay of coarse woody debris is a key component in the formation of forest soil and in the biogeochemical cycles of Ca and Mg. We tracked changes in density and concentration of Ca and Mg in sapwood of red maple ( Acer rubrum L.), red spruce ( Picea rubens Sarg.), paper birch ( Betula papyrifera Marsh.), and eastern hemlock ( Tsuga canadensis (L.) Carr.) in Maine and New Hampshire. We repeatedly sampled 10 logs of each combination of tree species and location at the time of felling and at 2-year intervals for 6 years (birch and hemlock) or 8 years (spruce and maple). We found that density loss was essentially linear for the time period investigated, with birch and maple sapwood decaying at faster rates than spruce and hemlock. Repeated-measures analysis and regression modeling of log-transformed concentrations indicated a significant accumulation of Ca for sapwood of all tree species at both locations (30%–90% increase after 6–8 years of ground contact). Regression estimates of Mg concentration in spruce and maple declined about 20% during the 8 years of ground contact. There was no significant trend for Mg concentration in birch and hemlock. Variation in decay rates and trends in Ca and Mg concentration may be due to differences in sapwood quality, the community of wood decay fungi and associated organisms, or to abiotic conditions.
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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 | 0.000 |
| 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) | 0.000 | 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 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".