Base cation distribution and requirement of three common forest ecosystems in eastern Canada based on site-specific and general allometric equations
Bibliographic record
Abstract
Base cations (Ca, Mg, and K) are essential nutrients for forest growth. Many studies have reported important decreases in the soils of several forests in eastern North America, partly because of atmospheric acid deposition and forest harvesting. To quantify the impacts of these perturbations on forest base cations, accurate estimation of tree biomass and nutrient content is needed. However, most of tree nutrient contents are calculated with general allometric equations, leading to inaccurate estimates. We thus calculated tree biomass and base cation content for three common forest types in eastern Canada using site-specific allometric equations and compared them with those calculated with general allometric equations and nutrient concentrations of tree compartments taken from the literature. General allometric equations resulted in above-ground tree biomass estimates in the same range as ours (±15%), but the use of nutrient concentrations taken from the literature resulted mainly in overestimation of above-ground tree nutrient content (–13% to +81%), leading to inaccurate wood requirement estimates (–63% to +86%). Therefore, the development of site-specific equations to estimate above-ground tree base cation content is recommended.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".