Soil Texture Explains Soil Sensitivity to C and N Losses from Whole-Tree Harvesting in the Boreal Forest
Bibliographic record
Abstract
The use of forest biomass to produce energy is increasingly viewed as a means to reduce fossil fuel consumption and mitigate global warming. However, the impact of such practices on soils in the long term is not well known. We revisited forest plots that were subjected to either whole-tree (WTH, n = 86) or stem-only (SOH, n = 110) harvesting 30 years ago in the boreal forest in Quebec, Canada. The objective of the present study was to find soil properties that could explain the lower soil C and N stocks at the sites subjected to WTH compared to SOH after 30 years. Compared to SOH, lower soil C and N stocks attributable to WTH occurred when soil particle content <20 µm was below 30%. The theoretical separation of soil organic matter into two fractions according to soil particle content <20 µm—a recalcitrant and a labile fraction—could explain the observed pattern of soil C and N differences between WTH and SOH. Imperfect or poor soil drainage conditions were also associated with lower soil C and N in WTH compared to SOH. Limiting additional biomass harvesting from these sites would help to preserve soil C and N from potential losses.
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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 | 0.001 | 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".