Reconstructing and modelling 71 years of forest growth in a Canadian boreal landscape: a test of the CBM-CFS3 carbon accounting model
Bibliographic record
Abstract
We carried out a verification exercise of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) carbon accounting model through the use of a reconstructed data set of forest growth and disturbances spanning a 71 year period (1928–1998) and encompassing a 62 km 2 landscape of boreal forest in eastern Canada. Overall, results show that yield curve simulations using CBM-CFS3 underestimate realized net biomass accrual by 10% in undisturbed stands. The bias in disturbed stands may be slightly larger. Errors linked to the estimation of the initial 1928 merchantable volume and biomass through the operational forest photointerpretation and inventory procedure may be the largest single cause of the bias. The local application of regionally parameterized yield curves may also be at fault. It is unlikely that long-term trends in climate or atmospheric composition may have generated such bias. Analyses of changes in specific carbon pools and comparisons made with results from a similar exercise carried out in a Pacific coastal forest show a small relative impact on total carbon from forest management activities in the absence of natural disturbances.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".