The impact of a black spruce (<i>Picea mariana</i>) plantation on carbon exchange in a cutover peatland in Western Canada
Bibliographic record
Abstract
Northern peatlands are sinks for atmospheric carbon (C), but peat extraction converts these ecosystems to C sources. Due to a dry regional climate, undisturbed bog peatlands in western Canada often have a tree cover of Picea mariana (Mill.) B.S.P. Thus, a coniferous forest plantation may be an appropriate land use for cutover peatlands. This study determined the effect of a 7-year-old P. mariana plantation on C balance of a cutover peatland. We measured C stored in P. mariana biomass and carbon dioxide (CO 2 ) and methane (CH 4 ) fluxes from bare peat at each of four fertilizer doses. Carbon stored in biomass of Betula papyrifera (Marsh.) that had spontaneously colonized the postfertilized site was also determined. Given that the water table remained very deep and that the sphagnum moss – ericaceous shrub peat-accumulating vegetation was not present, the site remained a source of C when only the planted P. mariana trees were considered, primarily in the form of CO 2 emissions by soil respiration. However, C accumulation in trees, including B. papyrifera biomass, resulted in a net C sink in fertilized plots. Results from this study indicate that tree plantations on cutover peatland may be a suitable land-management strategy on sites difficult to effectively rewet.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".