Effects of Biomass Removals on Site Carbon and Nutrients and Jack Pine Growth in Boreal Forests
Bibliographic record
Abstract
As international demand for renewable energy and forest biomass increases, there is considerable debate about the effect of increased removals on long‐term soil productivity. Carbon and nutrient contents of the aboveground biomass, forest floor, and mineral soil were determined at 14 boreal forest sites in northern Ontario. At each site, three treatments were performed: tree‐length harvesting (OM 0 ), full‐tree harvesting (OM 1 ) and full‐tree harvesting plus forest floor removal (OM 2 ). Theoretical and actual estimates of biomass removal for OM 0 and OM 1 were determined. Jack pine ( Pinus banksiana Lamb.) dominant height increments from Years 10 to 15 ( H D10‐15 ) were determined as a measure of site productivity. A nutrient budget approach was used to estimate C and nutrient removal and retention and to calculate stability ratios (i.e., ratio of nutrient removed during harvest to post‐harvest nutrient reserve) and nutrient replacement times. The OM 1 treatment removed 65% of the potentially available biomass; on average 27 Mg ha −1 of unutilized biomass was burned in slash piles. The OM 1 harvesting residue retention values coincided with guidelines of jurisdictions that recommend retaining one‐third of residues on site after bioenergy harvesting. The OM 0 and OM 1 C and nutrient removals were more similar than estimated in previous studies. Base cation stability ratios and nutrient replacement times gave opposite interpretations in terms of which sites were more sensitive to biomass removal treatments. For sandy sites with thin forest floor horizons H D10–15 responded positively to increased post‐harvest soil C reserves, but for sites with thick forest floors, organic matter accumulation became a detriment to increased growth.
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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 | 0.001 |
| 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 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".