Effects of logging on carbon dynamics of a jack pine forest in Saskatchewan, Canada
Bibliographic record
Abstract
Abstract We calculated carbon budgets for a chronosequence of harvested jack pine ( Pinus banksiana Lamb.) stands (0‐, 5‐, 10‐, and∼29‐year‐old) and a∼79‐year‐old stand that originated after wildfire. We measured total ecosystem C content (TEC), above‐, and belowground net primary productivity (NPP) for each stand. All values are reported in order for the 0‐, 5‐, 10‐, 29‐, and 79‐year‐old stands, respectively, for May 1999 through April 2000. Total annual NPP (NPP T ) for the stands (Mg C ha −1 yr −1 ±1 SD) was 0.9±0.3, 1.3±0.1, 2.7±0.6, 3.5±0.3, and 1.7±0.4. We correlated periodic soil surface CO 2 fluxes ( R S ) with soil temperature to model annual R S for the stands (Mg C ha −1 yr −1 ±1 SD) as 4.4±0.1, 2.4±0.0, 3.3±0.1, 5.7±0.3, and 3.2±0.2. We estimated net ecosystem productivity (NEP) as NPP T minus R H (where R H was calculated using a Monte Carlo approach as coarse woody debris respiration plus 30–70% of total annual R S ). Excluding C losses during wood processing, NEP (Mg C ha −1 yr −1 ±1 SD) for the stands was estimated to be −1.9±0.7, −0.4±0.6, 0.4±0.9, 0.4±1.0, and −0.2±0.7 (negative values indicate net sources to the atmosphere.) We also calculated NEP values from the changes in TEC among stands. Only the 0‐year‐old stand showed significantly different NEP between the two methods, suggesting a possible mismatch for the chronosequence. The spatial and methodological uncertainties allow us to say little for certain except that the stand becomes a source of C to the atmosphere following logging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".