Moving towards carbon neutrality: CO<sub>2</sub> exchange of a black spruce forest ecosystem during the first 10 years of recovery after harvest
Bibliographic record
Abstract
Disturbances control the landscape-level C dynamics of boreal forests, but post-disturbance C dynamics are usually poorly quantified. In the current study, we use 10 years of CO2 flux measurements at a boreal black spruce ( Picea mariana (Mill.) B.S.P.) cutover in eastern Canada to estimate time to C neutrality, quantify the relative role of respiration versus photosynthesis during recovery, and determine the agreement between cumulated CO2 fluxes and plot-level changes in C content. The site was a net source of 139 g C·m–2·year–1 2 years post-harvest, dropped further to a source of 173 g C·m–2·year–1 4 years post-harvest, following a scarification treatment, and was nearly C neutral 10 years post-harvest. Gross ecosystem productivity (GEP) increased by 50 g C·m–2·year–1 post-scarification, while ecosystem respiration (ER) increased by only 23 g C·m–2·year–1. The resulting net rate of increase of 27 g C·m–2·year–1 in net ecosystem productivity was driven by changes in increasing leaf area. In fact, vegetation regrowth had a much greater impact on annual fluxes than did interannual variability in climate. Biometric-based measurements of total C losses after harvest were in relatively good agreement with eddy-covariance-based estimates 8 years after the harvest.
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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 | 0.000 | 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) | 0.000 | 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".