IMPACT OF NUTRIENT REMOVAL THROUGH HARVESTING ON THE SUSTAINABILITY OF THE BOREAL FOREST
Bibliographic record
Abstract
The cycling of base cations (K, Ca, Mg, and Na) was investigated in a boreal balsam fir forest (the Lake Laflamme Watershed) between 1999 and 2005. Base cation budgets were calculated for the soil rooting zone that included atmospheric deposition and soil leaching losses, two scenarios of tree uptake (whole-tree and stem-only harvesting), and three scenarios of mineral weathering, leading to six different scenarios. In every scenario there was a net accumulation of Mg within the soil exchangeable reservoir, while Ca accumulated in four scenarios. Potassium was lost in five of the six scenarios. Contrary to Ca and Mg, immobilization of K within tree biomass (69 mol x ha(-1) x yr(-1)) was the main pathway of K losses from the soil exchangeable reservoir, being five times higher than losses via soil leaching (14 mol x ha(-1) x yr(-1)). The amounts of K contained within the aboveground biomass and the exchangeable soil reservoir were 3.3 kmol/ha and 4.2 kmol/ha, respectively. Whole-tree harvesting may thus remove 44% of the K that is readily available for cycling in the short term, making this forest sensitive to commercial forestry operations. Similar values of annual K uptake as well as a similar distribution of K between tree biomass and soil exchangeable reservoirs at 14 other coniferous sites, distributed throughout the boreal forest of Quebec, suggest that the Lake Laflamme Watershed results can be extrapolated to a much larger area. Stem-only harvesting, which would reduce K exports due to biomass removal by 60%, should be used for these types of forest.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".