Annual carbon balance of Canada's forests during 1895–1996
Bibliographic record
Abstract
This paper reports annual carbon (C) balance of Canada's forests during 1895–1996 estimated using the Integrated Terrestrial Ecosystem C‐budget model (InTEC) [Chen et al. this issue]. During 1895–1910, Canada's forests were small sources of 30±15 Tg C yr−1 due to large disturbances (forest fire, insect‐induced mortality, and harvest) in late nineteenth century. The forests became large sinks of 170±85 Tg C yr−1 during 1930–1970, owing to forest regrowth in previously disturbed areas and growth stimulation by nondisturbance factors such as climate, atmospheric CO2 concentration, and N deposition. In recent decades (1980–1996), Canada's forests have been moderate sinks of 50±25 Tg C yr−1, as a result of a tradeoff between the negative effects of increased disturbances and positive effects of nondisturbance factors. The nondisturbance factors, in order of importance, are (1) atmospheric N deposition (measured by a national monitoring network), (2) net N mineralization and fixation (estimated from temperature and precipitation records), (3) growing season length increase (estimated from spring air temperature records), and (4) CO2 fertilization (estimated from CO2 records using a leaf‐level photosynthesis model). The magnitudes of modeled nondisturbance effects are consistent with simulation results by the Carnegie‐Ames‐Stanford Approach (CASA) and are also in broad agreement with flux measurements above mature forest stands at several locations in Canada. Results for the disturbance effects agree with a previous study [Kurz and Apps, 1996]. The overall C balance from InTEC generally agrees with that derived from tree ring data [Auclair and Bedford, 1997] and from forest inventories. The combination of our result and that of Houghton et al. [1999] for the United States suggests that North America (> 15°N) was probably a C sink of 0.2‐0.5 Pg C yr±−1 during 1980s, much less than that of 1.7 Pg C yr±−1 estimated by Fan et al. [1998] using an atmospheric inversion method.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".