Mixed-species effect on tree aboveground carbon pools in the east-central boreal forests
Bibliographic record
Abstract
This study investigates the potential of mixed forest stands as better aboveground carbon sinks than pure stands. According to the facilitation and niche complementarity hypotheses, we predict higher carbon sequestration in mature boreal mixedwoods. Aboveground carbon contents of black spruce ( Picea mariana (Mill.) Britton, Sterns, Poggenb.) and trembling aspen ( Populus tremuloides Michx.) mixtures were investigated in the eastern boreal forest, whereas jack pine ( Pinus banksiana Lamb.) and trembling aspen were used in the central boreal forest. No carbon gain was found in species mixtures; nearly pure trembling aspen stands contained the greatest amount of aboveground carbon, black spruce stands had the least, and mixtures were intermediate with amounts that could generally be predicted by linear interpolation with stem proportions. These results suggest that for aspen, the potentially detrimental effect of spruce on soils observed in other studies may be offset by greater light availability in mixtures. On the other hand, for black spruce, the potentially beneficial effects of aspen on soils could be offset by greater competition by aspen for nutrients and light. The mixture of jack pine and trembling aspen did not benefit any of these species while inducing a loss in trembling aspen carbon at the stand level.
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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 | 0.001 | 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".